[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"portal-settings:figure:de":3,"public-menus:all":45,"post:pubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning:de":531,"related:post:pubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning:de:1":2153},{"statusCode":4,"data":5,"message":44},200,{"tenantId":6,"lang":7,"defaultLang":8,"siteUrl":9,"contactEmail":10,"brandName":11,"logoUrl":12,"siteName":11,"siteDescription":13,"ogImage":14,"robotsIndex":15,"socialLinks":14,"reservedSlugs":14,"seoPolicy":16},"figure","de","en","https:\u002F\u002Ffigure.rocks","info@stajic.de","Figure Rocks","\u002Ffavicon-32x32.png","",null,true,{"branding":17,"relatedContent":18,"crossDomainLinks":19},{"logoUrl":12},{"enabled":15},[20,23,26,29,32,35,38,41],{"url":21,"label":22,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Floving.rocks","loving.rocks",{"url":24,"label":25,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fstajic.de","stajic.de",{"url":27,"label":28,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fbazify.com","bazify.com",{"url":30,"label":31,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fbazify.de","bazify.de",{"url":33,"label":34,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002F2mesta.com","2mesta.com",{"url":36,"label":37,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002F2mesta.de","2mesta.de",{"url":39,"label":40,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fbazify.at","bazify.at",{"url":42,"label":43,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fweb-hoch3.de","web-hoch3.de","Portal settings resolved",[46],{"id":47,"name":48,"location":49,"isActive":15,"isDefault":15,"items":50},2,"Main Menu","sidebar",[51,65,176,298,391,467],{"id":52,"title":53,"url":61,"target":62,"icon":63,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":64},"1",{"de":54,"en":55,"es":56,"fr":57,"it":55,"ru":58,"sr":59,"zh":60},"Startseite","Home","Inicio","Accueil","Главная","Početna","首页","\u002F","_self","i-lucide-home",[],{"id":66,"title":67,"url":69,"target":62,"icon":70,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":72},"2",{"de":68,"en":68,"es":68,"fr":68,"it":68,"ru":68,"sr":68,"zh":68},"amiibo","\u002Famiibo","i-lucide-scan-line","custom",[73,85,92,106,120,134,148,162],{"id":74,"title":75,"url":69,"target":62,"icon":83,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":84},"2-1",{"de":76,"en":77,"es":78,"fr":79,"it":79,"ru":80,"sr":81,"zh":82},"amiibo-Hub","amiibo Hub","Centro amiibo","Hub amiibo","Хаб amiibo","amiibo centar","amiibo 中心","i-lucide-layout-grid",[],{"id":86,"title":87,"url":89,"target":62,"icon":90,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":91},"1772724791061",{"de":88,"en":88},"Franchise","\u002Famiibo\u002Ffranchise","i-lucide-star",[],{"id":93,"title":94,"url":103,"target":62,"icon":104,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":105},"2-3",{"de":95,"en":96,"es":97,"fr":98,"it":99,"ru":100,"sr":101,"zh":102},"Region & Verpackung (EU\u002FUS\u002FJP)","Region & Packaging (EU\u002FUS\u002FJP)","Región y embalaje (UE\u002FEE. UU.\u002FJP)","Région & Emballage (UE\u002FUS\u002FJP)","Regione & Confezione (EU\u002FUS\u002FJP)","Регион & упаковка (EU\u002FUS\u002FJP)","Region & pakovanje (EU\u002FUS\u002FJP)","地区 & 包装 (EU\u002FUS\u002FJP)","\u002Famiibo-library\u002Famiibo-editions-and-regions","i-lucide-globe",[],{"id":107,"title":108,"url":117,"target":62,"icon":118,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":119},"2-4",{"de":109,"en":110,"es":111,"fr":112,"it":113,"ru":114,"sr":115,"zh":116},"Schnellidentifikations-Checkliste","Fast Identification Checklist","Lista de identificación rápida","Liste d'identification rapide","Checklist identificazione rapida","Чек-лист быстрой идентификации","Kontrolna lista za brzu identifikaciju","快速识别清单","\u002Famiibo\u002Fidentify-checklist","i-lucide-list-checks",[],{"id":121,"title":122,"url":131,"target":62,"icon":132,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":133},"2-6",{"de":123,"en":124,"es":125,"fr":126,"it":127,"ru":128,"sr":129,"zh":130},"Tipps für Sealed-Sammlungen","Sealed Collection Tips","Consejos de colección sellada","Conseils collection scellée","Consigli collezione sigillata","Советы по коллекции Sealed","Saveti za zapečaćene kolekcije","密封收藏贴士","\u002Famiibo\u002Fsealed-tips","i-lucide-shield-check",[],{"id":135,"title":136,"url":145,"target":62,"icon":146,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":147},"2-5",{"de":137,"en":138,"es":139,"fr":140,"it":141,"ru":142,"sr":143,"zh":144},"Zustand & Bewertung","Condition & Grading","Estado & Graduación","État & Évaluation","Condizioni & Valutazione","Состояние & Оценка","Stanje & ocenjivanje","品相与分级","\u002Famiibo-library\u002Famiibo-condition-and-grading","i-lucide-badge-check",[],{"id":149,"title":150,"url":159,"target":62,"icon":160,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":161},"2-2",{"de":151,"en":152,"es":153,"fr":154,"it":155,"ru":156,"sr":157,"zh":158},"Ausgaben & Nachdrucke","Editions & Reprints","Ediciones & Reimpresiones","Éditions & Réimpressions","Edizioni & ristampe","Издания & переиздания","Izdanja & reizdanja","版本 & 重印","\u002Famiibo\u002Fcollecting\u002F","i-lucide-layers",[],{"id":163,"title":164,"url":173,"target":62,"icon":174,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":175},"2-7",{"de":165,"en":166,"es":167,"fr":168,"it":169,"ru":170,"sr":171,"zh":172},"Nachdruck-Timeline","Reprint Timeline","Cronología de reimpresión","Chronologie des réimpressions","Cronologia ristampe","Хронология переизданий","Hronologija reprinta","重印时间轴","\u002Freference\u002Ftimelines\u002Famiibo-reprint-timeline","i-lucide-timer",[],{"id":177,"title":178,"url":187,"target":62,"icon":188,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":189},"3",{"de":179,"en":180,"es":181,"fr":182,"it":183,"ru":184,"sr":185,"zh":186},"Spiele","Games","Juegos","Jeux","Giochi","Игры","Igre","游戏","\u002Fgames","i-lucide-gamepad-2",[190,202,216,230,244,257,271,285],{"id":191,"title":192,"url":187,"target":62,"icon":83,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":201},"3-1",{"de":193,"en":194,"es":195,"fr":196,"it":197,"ru":198,"sr":199,"zh":200},"Spiele-Hub","Games Hub","Centro de juegos","Hub de jeux","Hub Giochi","Игровой центр","Centar za igre","游戏中心",[],{"id":203,"title":204,"url":213,"target":62,"icon":214,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":215},"1-1",{"de":205,"en":206,"es":207,"fr":208,"it":209,"ru":210,"sr":211,"zh":212},"Neu & Angesagt","New & Trending","Novedades & Tendencias","Nouveautés & Tendances","Novità & Tendenze","Новинки & тренды","Novo & Popularno","新品 & 热门","\u002Fnews\u002Fgaming-news","i-lucide-sparkles",[],{"id":217,"title":218,"url":227,"target":62,"icon":228,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":229},"1-2",{"de":219,"en":220,"es":221,"fr":222,"it":223,"ru":224,"sr":225,"zh":226},"Angebote","Deals","Ofertas","Offres","Offerte","Акции","Ponude","优惠","\u002Fdeals","i-lucide-badge-percent",[],{"id":231,"title":232,"url":241,"target":62,"icon":242,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":243},"1-3",{"de":233,"en":234,"es":235,"fr":236,"it":237,"ru":238,"sr":239,"zh":240},"Release-Kalender","Release Calendar","Calendario de lanzamientos","Calendrier des sorties","Calendario delle uscite","Календарь релизов","Kalendar izdanja","发布日历","\u002Freleases","i-lucide-calendar-days",[],{"id":245,"title":246,"url":254,"target":62,"icon":255,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":256},"3-2",{"de":247,"en":248,"es":249,"fr":250,"it":251,"sr":252,"zh":253},"amiibo-kompatible Spiele","amiibo-Compatible Games","Juegos compatibles con Amiibo","Jeux compatibles Amiibo","Giochi compatibili con amiibo","Amiibo kompatibilne igre","Amiibo 兼容游戏","\u002Freference\u002Fcompatibility","i-lucide-check-circle-2",[],{"id":258,"title":259,"url":268,"target":62,"icon":269,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":270},"3-3",{"de":260,"en":261,"es":262,"fr":263,"it":264,"ru":265,"sr":266,"zh":267},"Wie amiibo funktionieren","How amiibo work","Cómo funcionan los Amiibo","Comment fonctionnent les Amiibo","Come funzionano gli Amiibo","Как работают Amiibo","Kako Amiibo rade","Amiibo 如何运作","\u002Fgames\u002Fhow-amiibo-unlocks-work","i-lucide-puzzle",[],{"id":272,"title":273,"url":282,"target":62,"icon":283,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":284},"3-4",{"de":274,"en":275,"es":276,"fr":277,"it":278,"ru":279,"sr":280,"zh":281},"Beste Amiibo pro Spiel","Best amiibo per Game","Mejores Amiibo por juego","Meilleurs Amiibo par jeu","Migliori Amiibo per gioco","Лучшие Amiibo по играм","Najbolji Amiibo po igri","各游戏最佳 Amiibo","\u002Fgames\u002Fbest-amiibo-per-game","i-lucide-award",[],{"id":286,"title":287,"url":295,"target":62,"icon":296,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":297},"3-5",{"de":288,"en":289,"es":290,"fr":291,"it":292,"ru":293,"sr":294},"Freischaltbares & Belohnungen","Unlockables & Rewards","Desbloqueables & Recompensas","Déblocables & Récompenses","Sbloccabili & Ricompense","Разблокировки & награды","Otključavanja & nagrade","\u002Fgames\u002Funlocks-and-benefits","i-lucide-gift",[],{"id":299,"title":300,"url":308,"target":62,"icon":309,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":310},"4",{"de":301,"en":302,"es":303,"it":304,"ru":305,"sr":306,"zh":307},"Sammeln","Collecting","Coleccionismo","Collezionismo","Коллекционирование","Kolekcionarstvo","收藏","\u002Fcollecting","i-lucide-gem",[311,322,336,349,363,377],{"id":312,"title":313,"url":320,"target":62,"icon":83,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":321},"4-1",{"de":314,"en":315,"fr":316,"it":317,"ru":318,"zh":319},"Sammel-Hub","Collecting Hub","Hub de collecte","Hub di raccolta","Центр сбора","收藏中心","\u002Famiibo\u002Fcollecting",[],{"id":323,"title":324,"url":333,"target":62,"icon":334,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":335},"4-2",{"de":325,"en":326,"es":327,"fr":328,"it":329,"ru":330,"sr":331,"zh":332},"Kaufberatung","Buying Guide","Guía de compra","Guide d'achat","Guida all'acquisto","Гид покупателя","Vodič za kupovinu","购买指南","\u002Famiibo-library\u002Famiibo-buying-smart","i-lucide-shopping-bag",[],{"id":337,"title":338,"url":346,"target":62,"icon":347,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":348},"4-3",{"de":339,"en":339,"es":340,"fr":341,"it":342,"ru":343,"sr":344,"zh":345},"Fake vs Real","Falso vs. Real","Faux vs Vrai","Falso vs Vero","Фейк vs Оригинал","Lažno vs Pravo","真假对比","\u002Famiibo-library\u002Famiibo-buying-smart\u002Favoid-fake-listings","i-lucide-scan",[],{"id":350,"title":351,"url":360,"target":62,"icon":361,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":362},"4-4",{"de":352,"en":353,"es":354,"fr":355,"it":356,"ru":357,"sr":358,"zh":359},"Aufbewahrung & Präsentation","Storage & Display","Almacenamiento & exhibición","Rangement & Présentation","Contenitori & Esposizione","Хранение & витрины","Odlaganje & izlaganje","存储 & 展示","\u002Famiibo-library\u002Famiibo-care-and-storage","i-lucide-box",[],{"id":364,"title":365,"url":374,"target":62,"icon":375,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":376},"4-5",{"de":366,"en":367,"es":368,"fr":369,"it":370,"ru":371,"sr":372,"zh":373},"Preisübersicht","Price Guide","Guía de precios","Guide des prix","Guida ai prezzi","Гид по ценам","Cenovnik","价格指南","\u002Fcollections\u002Fprice-guide","i-lucide-bar-chart-3",[],{"id":378,"title":379,"url":388,"target":62,"icon":389,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":390},"4-6",{"de":380,"en":381,"es":382,"fr":383,"it":384,"ru":385,"sr":386,"zh":387},"Raritäten","Rare Finds","Hallazgos únicos","Trouvailles rares","Pezzi rari","Редкие находки","Retki nalazi","稀有发现","\u002Fcollections\u002Frare-and-notable","i-lucide-trophy",[],{"id":392,"title":393,"url":401,"target":62,"icon":402,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":403},"5",{"de":394,"en":395,"es":396,"fr":395,"it":397,"ru":398,"sr":399,"zh":400},"Technik","Tech","Tecnología","Tecnologia","Технологии","Tehnologija","科技","\u002Ftech","i-lucide-cpu",[404,415,427,440,453],{"id":405,"title":406,"url":401,"target":62,"icon":83,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":414},"5-1",{"de":407,"en":407,"es":408,"fr":409,"it":410,"ru":411,"sr":412,"zh":413},"Tech Hub","Centro tecnológico","Hub Tech","Hub Tecnologico","Технохаб","Tehnološki centar","科技中心",[],{"id":416,"title":417,"url":424,"target":62,"icon":425,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":426},"5-2",{"de":418,"en":419,"fr":420,"it":421,"ru":422,"zh":423},"Audio- & Mikrofonqualität","Audio & Mic Quality","Qualité audio & micro","Qualità audio & mic","Качество звука & микрофона","音频 & 麦克风质量","\u002Fgear\u002Faudio","i-lucide-mic",[],{"id":428,"title":429,"url":437,"target":62,"icon":438,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":439},"5-3",{"de":430,"en":431,"es":432,"fr":433,"it":434,"sr":435,"zh":436},"Controller & Zubehör","Controllers & Accessories","Mandos & accesorios","Manettes & accessoires","Controller & Accessori","Kontroleri & dodatna oprema","控制器 & 配件","\u002Fgear\u002Fcontrols","i-lucide-joystick",[],{"id":441,"title":442,"url":450,"target":62,"icon":451,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":452},"5-4",{"de":443,"en":444,"es":445,"fr":446,"it":447,"ru":448,"sr":449},"Displays & Aufnahme","Displays & Capture","Pantallas & Captura","Écrans & Capture","Display & Acquisizione","Дисплеи & Захват","Ekrani & snimanje","\u002Fgear\u002Fdisplays","i-lucide-monitor",[],{"id":454,"title":455,"url":464,"target":62,"icon":465,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":466},"5-5",{"de":456,"en":457,"es":458,"fr":459,"it":460,"ru":461,"sr":462,"zh":463},"Netzwerkstabilität","Network Stability","Estabilidad de la red","Stabilité du réseau","Stabilità della rete","Стабильность сети","Stabilnost mreže","网络稳定性","\u002Fplaybooks\u002Fnetwork-stability","i-lucide-wifi",[],{"id":468,"title":469,"url":477,"target":62,"icon":478,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":479},"6",{"de":470,"en":470,"es":471,"fr":472,"it":473,"ru":474,"sr":475,"zh":476},"Shop","Tienda","Boutique","Negozio","Магазин","Prodavnica","商店","\u002Fshop","i-lucide-shopping-cart",[480,492,498,506,519],{"id":481,"title":482,"url":477,"target":62,"icon":490,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":491},"6-1",{"de":483,"en":484,"es":485,"fr":486,"ru":487,"sr":488,"zh":489},"Shop-Hub","Shop Hub","Centro de compras","Espace Boutique","Центр магазина","Centar za kupovinu","购物中心","i-lucide-store",[],{"id":493,"title":494,"url":496,"target":62,"icon":70,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":497},"6-2",{"de":68,"en":68,"es":495,"fr":495,"it":495,"sr":495,"zh":495},"Amiibo","\u002Famiibo-shop",[],{"id":499,"title":500,"url":503,"target":62,"icon":504,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":505},"6-3",{"de":501,"en":501,"es":501,"fr":501,"it":501,"ru":501,"sr":501,"zh":502},"LEGO","乐高","\u002Flego-shop","i-lucide-blocks",[],{"id":507,"title":508,"url":516,"target":62,"icon":517,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":518},"6-4",{"de":509,"en":510,"es":511,"fr":512,"it":513,"sr":514,"zh":515},"Figuren & Sammlerstücke","Figures & Collectibles","Figuras & Coleccionables","Figurines & Objets de collection","Figure & Collezionismo","Figure & kolekcionarstvo","手办 & 收藏品","\u002Fshop\u002Ffigures","i-lucide-package",[],{"id":520,"title":521,"url":528,"target":62,"icon":529,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":530},"6-5",{"de":522,"en":522,"fr":523,"it":524,"ru":525,"sr":526,"zh":527},"Gaming Gear","Équipement gaming","Accessori gaming","Игровое снаряжение","Gejming oprema","游戏装备","\u002Fgaming-gear-shop","i-lucide-headphones",[],{"statusCode":4,"data":532,"message":2152},{"id":533,"title":534,"slug":535,"content":536,"contentJson":537,"excerpt":1217,"featuredImage":1218,"featuredImageAlt":1219,"featuredImageCaption":14,"featuredImageTitle":14,"featuredImageCopyright":14,"featuredImageAuthor":14,"featuredImageSourceUrl":14,"featuredImageLicense":14,"featuredImageIsAiGenerated":870,"status":1220,"publishedAt":1221,"createdAt":1222,"updatedAt":1223,"seoLocalePaths":1224,"categories":1233,"author":1258,"translations":1262},"444","PUBG Ally zeigt, warum KI-Teamkollegen zwei Gehirne brauchen: schnelle Reflexe und langsames Denken","pubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","\u003Cp>Ein Sprachmodell kann über ein Feuergefecht sprechen, aber es sollte nicht für jede Bewegung, Zielanpassung und Sekundenbruchteil-Reaktion darin verantwortlich sein. NVIDIA ACE und KRAFTONs PUBG Ally zeigen, warum nützliche KI-Teammitglieder mehr als ein einzelnes Modell brauchen: schnelle Gameplay-Steuerung und langsamere Sprachschlussfolgerung sind unterschiedliche Aufgaben.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--info my-6 rounded-xl border p-5 border-blue-300 bg-blue-50 dark:border-blue-900 dark:bg-blue-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Direkte Antwort\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>Die stärkste Architektur für ein KI-Teammitglied ist nicht „LLM steuert alles“.\u003C\u002Fstrong> PUBG Ally trennt schnelles reaktives Gameplay von bewusstem Schlussfolgern. Eine Verhaltensbaum-Ebene übernimmt reflexartige Bewegung und Kampf, während ein kleines Sprachmodell die Spielerabsicht, den Live-Spielzustand und die übergeordnete Koordination interpretiert.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Caside class=\"editorjs-callout editorjs-callout--note my-6 rounded-xl border p-5 border-gray-300 bg-gray-50 dark:border-gray-700 dark:bg-gray-900\u002F40\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Das in diesem Artikel verwendete Modell\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Das Modell des Zwei-Geschwindigkeiten-Spielagenten und die Aktionsautoritätsgrenze unten sind praktische Figure-Rocks-Frameworks, inspiriert von der öffentlich beschriebenen Architektur für NVIDIA ACE und PUBG Ally. Sie sind keine offizielle NVIDIA- oder KRAFTON-Terminologie.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Cnav class=\"editorjs-toc\" data-editorjs-toc=\"true\" aria-label=\"Inhalt\">\u003Cstrong class=\"editorjs-toc__title\">Inhalt\u003C\u002Fstrong>\u003Col class=\"editorjs-toc__list editorjs-toc__list--depth-0\">\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-5\" class=\"editorjs-toc__link\">Warum ein KI-Modell nicht die ganze Figur steuern sollte\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-9\" class=\"editorjs-toc__link\">PUBG Ally verwendet eine Zwei-Geschwindigkeiten-Architektur\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-13\" class=\"editorjs-toc__link\">Das Modell des Zwei-Geschwindigkeiten-Spielagenten\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-16\" class=\"editorjs-toc__link\">Der Live-Spielzustand macht das Modell nützlich\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-21\" class=\"editorjs-toc__link\">Die Grenze der Handlungsbefugnis\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-26\" class=\"editorjs-toc__link\">Warum ereignisgesteuertes Denken besser ist als ständiges Abfragen des Sprachmodells\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-30\" class=\"editorjs-toc__link\">Der Entscheidungsauslösefilter\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-32\" class=\"editorjs-toc__link\">Inferenz auf dem Gerät verändert den Designraum\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-36\" class=\"editorjs-toc__link\">KI-Inferenz konkurriert jetzt mit dem Rendering\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-40\" class=\"editorjs-toc__link\">Das KI-Ressourcenbudget im Spiel\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-42\" class=\"editorjs-toc__link\">Warum kleine Modelle in Spielen sinnvoll sind\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-46\" class=\"editorjs-toc__link\">RAG und Tools lösen unterschiedliche Probleme\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-50\" class=\"editorjs-toc__link\">Was traditionelle NPCs immer noch besser machen\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-55\" class=\"editorjs-toc__link\">Die Zuverlässigkeitsschleife des Agenten\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-58\" class=\"editorjs-toc__link\">Warum natürliche Sprache Fehler überzeugender macht\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-62\" class=\"editorjs-toc__link\">Mehrsprachige Spiel-Agenten werden praktikabel\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-66\" class=\"editorjs-toc__link\">Was würde diese Antwort ändern?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-69\" class=\"editorjs-toc__link\">Einschränkungen\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-72\" class=\"editorjs-toc__link\">Fazit\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-76\" class=\"editorjs-toc__link\">FAQ\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-78\" class=\"editorjs-toc__link\">Glossar\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-80\" class=\"editorjs-toc__link\">Primärquellen\u003C\u002Fa>\u003C\u002Fli>\u003C\u002Fol>\u003C\u002Fnav>\n\u003Ch2 id=\"section-5\">Warum ein KI-Modell nicht die ganze Figur steuern sollte\u003C\u002Fh2>\n\u003Cp>Eine moderne Spielfigur muss mehrere Probleme auf radikal unterschiedlichen Zeitskalen lösen.\u003C\u002Fp>\n\u003Cp>Sie muss möglicherweise in Millisekunden ein Hindernis vermeiden, auf nahes Schussfeuer reagieren, einem Spielerbefehl folgen, entscheiden, ob sie plündern soll, einen Plan in natürlicher Sprache erklären und sich merken, was der Spieler zuvor gefragt hat.\u003C\u002Fp>\n\u003Cp>Der Versuch, all das durch eine einzige Sprachmodell-Schleife zu zwingen, erzeugt eine zeitliche Diskrepanz. Das Modell ist gut in semantischem Schlussfolgern und Planen, aber Echtzeitsteuerung benötigt oft deterministische Logik, die bei jedem Spiel-Tick reagieren kann.\u003C\u002Fp>\n\u003Ch2 id=\"section-9\">PUBG Ally verwendet eine Zwei-Geschwindigkeiten-Architektur\u003C\u002Fh2>\n\u003Cp>KRAFTON beschreibt PUBG Ally als einen mitspielbaren KI-Teammitglied, das von NVIDIA ACE angetrieben wird. Das System kombiniert Spielerstimme, Live-Match-Zustand, ein kleines Sprachmodell und spielseitige Steuerungslogik.\u003C\u002Fp>\n\u003Cp>Laut NVIDIAs technischem Deep Dive trennt die Architektur einen System-1-Verhaltensbaum von einem System-2-Sprachmodell. Der Verhaltensbaum übernimmt schnelles reaktives Gameplay wie Bewegung und Kampf, während das Sprachmodell bewusstes Schlussfolgern, Kommunikation und Koordination übernimmt.\u003C\u002Fp>\n\u003Cp>Diese Aufteilung ist eines der wichtigsten Designmuster in Echtzeit-Spiel-KI, weil sie jedem Subsystem die Autorität über die Arbeit gibt, für die es tatsächlich geeignet ist.\u003C\u002Fp>\n\u003Ch2 id=\"section-13\">Das Modell des Zwei-Geschwindigkeiten-Spielagenten\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Wie ein praktisches KI-Teammitglied die Arbeit aufteilen kann\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">1. Wahrnehmung und Beobachtung\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Das Spiel legt relevanten Live-Zustand offen, wie Position, Inventar, Bedrohungen, nahe Objekte und Spieleranfragen.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">2. Bewusstes Schlussfolgern\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Das Sprachmodell interpretiert die Absicht, wählt ein Ziel, plant und entscheidet, welches Werkzeug oder welche Aktionsklasse aufgerufen wird.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">3. Aktionsübergabe\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Die übergeordnete Entscheidung wird in strukturierte spielseitige Befehle umgewandelt.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">4. Reaktive Ausführung\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Verhaltensbäume oder andere deterministische Controller übernehmen Bewegung, Kampf, Navigation und reflexartige Reaktionen.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">5. Erneute Beobachtung\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Der Agent liest den geänderten Spielzustand und aktualisiert seinen Plan, wenn die Welt nicht mehr den vorherigen Annahmen entspricht.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">System 1 vs. System 2 in einem Spielagenten\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Schnelle reaktive Ebene\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Bewusste Schlussfolgerungsebene\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Zeitskala\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Typische Aufgaben\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Wenn es zu langsam ist\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Bester Steuerungsstil\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-16\">Der Live-Spielzustand macht das Modell nützlich\u003C\u002Fh2>\n\u003Cp>Das PUBG-Ally-Modell schlussfolgert nicht allein aus dem Dialog. NVIDIA sagt, dass die Spiel-Engine den Live-Match-Zustand für den Agenten durch Beobachtungswerkzeuge offenlegt, die als textuelle Beschreibungen dargestellt werden.\u003C\u002Fp>\n\u003Cp>Das ist wichtig, weil ein Teammitglied wissen muss, was gerade passiert: was der Spieler gesagt hat, welche Gegenstände in der Nähe sind, woher die Gefahr kommt und ob der vorherige Plan noch gültig ist.\u003C\u002Fp>\n\u003Cp>Dies ist dasselbe Zuverlässigkeitsprinzip, das für jeden Spielassistenten gilt: Allgemeines Spielwissen reicht nicht aus, wenn die korrekte Aktion vom aktuellen Sitzungszustand abhängt.\u003C\u002Fp>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Fde\u002Fblog\u002Fyour-game-assistant-knows-the-game-but-does-it-know-your-game-state\" class=\"flex flex-col sm:flex-row gap-4 rounded-xl border border-gray-200 dark:border-gray-700 p-4 transition hover:border-primary-500\">\u003Cdiv class=\"min-w-0 flex-1\">\u003Cstrong class=\"block text-lg text-gray-900 dark:text-gray-100\">Dein Spielassistent kennt das Spiel – aber kennt er deinen Spielzustand?\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Warum aktuelle Gesundheit, Inventar, Quest-Flags, Abklingzeiten und andere Live-Zustände bestimmen, ob KI-Spielratschläge tatsächlich gültig sind.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Lies den Leitfaden zum Spielzustand →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-21\">Die Grenze der Handlungsbefugnis\u003C\u002Fh2>\n\u003Cp>Ein nützlicher Echtzeit-Spielagent braucht eine klare Grenze zwischen dem, was das Modell entscheiden darf, und dem, was die Spiel-Engine tatsächlich ausführen darf.\u003C\u002Fp>\n\u003Cp>Das Modell kann ein Ziel wählen wie „in Deckung gehen“, „Munition plündern“, „dem Spieler folgen“ oder „diesen Feind angreifen“. Der spielseitige Controller sollte diese Absicht dann in legale, begrenzte Aktionen übersetzen, die Navigation, Animation, Abklingzeiten, Physik und Spielregeln befolgen.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--success my-6 rounded-xl border p-5 border-emerald-300 bg-emerald-50 dark:border-emerald-900 dark:bg-emerald-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Das Sicherheitsmuster\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Lass das Modell unter \u003Cstrong>autorisierten Absichten\u003C\u002Fstrong> wählen. Lass die Engine nur \u003Cstrong>validierte Spielaktionen\u003C\u002Fstrong> ausführen.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Gute vs. gefährliche Agentensteuerung\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Begrenzte Architektur\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Unbegrenzte Architektur\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Bewegung\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Kampf\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Inventar\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Sprache\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-26\">Warum ereignisgesteuertes Denken besser ist als ständiges Abfragen des Sprachmodells\u003C\u002Fh2>\n\u003Cp>Die Modellschleife von PUBG Ally wird als ereignisgesteuert beschrieben. Sie kann ausgelöst werden, wenn der Spieler spricht oder durch relevante Ereignisse im Spiel.\u003C\u002Fp>\n\u003Cp>Das ist effizienter, als das Modell in jedem Frame die gesamte Welt neu überdenken zu lassen. Die meisten Frames erfordern keine strategische Entscheidung.\u003C\u002Fp>\n\u003Cp>Ein gutes Auslösesystem ruft das Sprachmodell auf, wenn Semantik wichtig ist: ein neuer Befehl eintrifft, eine Bedrohung den Plan ändert, ein Ziel abgeschlossen wird, ein Gegenstand relevant wird oder der aktuelle Plan fehlschlägt.\u003C\u002Fp>\n\u003Ch2 id=\"section-30\">Der Entscheidungsauslösefilter\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Wann sollte das Sprachmodell aufwachen?\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Spielerabsicht geändert\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Eine neue gesprochene oder textliche Anfrage erfordert Interpretation.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Plan ungültig geworden\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Das Ziel verschwand, der Pfad schlug fehl, der Gegenstand ist weg oder der Kampf hat die Situation verändert.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Übergeordneter Meilenstein erreicht\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Die Figur ist angekommen, hat geplündert, geheilt oder ein geplantes Teilziel abgeschlossen.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Wichtige neue Beobachtung\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Eine neue Bedrohung, Ressource oder strategische Gelegenheit erscheint.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Konversation erforderlich\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Der Agent sollte bestätigen, erklären oder um Klärung bitten.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">6\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Andernfalls reaktiv bleiben\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Lass die untergeordneten Controller ohne unnötige Modellinferenz weiterlaufen.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-32\">Inferenz auf dem Gerät verändert den Designraum\u003C\u002Fh2>\n\u003Cp>NVIDIA ACE ist sowohl um Inferenz auf dem Gerät als auch um Cloud-Optionen herum konzipiert. Für PUBG Ally sagt NVIDIA, dass das kleine Sprachmodell lokal auf der GPU des Spielers läuft.\u003C\u002Fp>\n\u003Cp>Die veröffentlichte Architektur verwendet ein Mistral-NeMo-Minitron-Modell mit 2B Parametern, das so konzipiert ist, dass es in den VRAM-Spielraum passt, der nach dem Betrieb von PUBG selbst noch übrig bleibt.\u003C\u002Fp>\n\u003Cp>Das ist eine nicht triviale Einschränkung. Spiel-KI kann nicht einfach den gesamten verfügbaren GPU-Speicher oder die Rechenleistung beanspruchen, weil die Grafiklast weiterhin Priorität hat.\u003C\u002Fp>\n\u003Ch2 id=\"section-36\">KI-Inferenz konkurriert jetzt mit dem Rendering\u003C\u002Fh2>\n\u003Cp>Dies schafft ein neues Ressourcenproblem für Spiele: Grafik und KI-Inferenz könnten dieselbe GPU gemeinsam nutzen.\u003C\u002Fp>\n\u003Cp>NVIDIAs In-Game Inferencing SDK wurde entwickelt, um lokale KI-Modelle neben Grafik-Workloads zu planen. Sein Zweck ist nicht nur, Modelle auszuführen, sondern dies zu tun, ohne das Frame-Zeit-Budget des Spiels zu zerstören.\u003C\u002Fp>\n\u003Cp>Das bedeutet, dass zukünftige Leistungsbewertungen möglicherweise nicht nur DLSS, Raytracing und VRAM-Nutzung messen müssen, sondern auch die Kosten der lokalen NPC-Inferenz.\u003C\u002Fp>\n\u003Ch2 id=\"section-40\">Das KI-Ressourcenbudget im Spiel\u003C\u002Fh2>\n\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">Ressource\u003C\u002Fth>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">Grafik benötigt sie für\u003C\u002Fth>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">KI-Agent benötigt sie für\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">VRAM\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Texturen, Puffer, Geometrie, Raytracing, Frame-Generierung\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Modellgewichte, KV-Cache, Embeddings und Inferenzpuffer\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">GPU-Compute\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Rasterisierung, RT, neuronale Grafik\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">SLM\u002FASR\u002FTTS-Inferenz\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">CPU-Zeit\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Simulation, Draw-Submission, Spielsysteme\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Agent-Orchestrierung, Tools, Textverarbeitung\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Speicherbandbreite\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Asset- und Render-Workloads\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Modellausführung und Datenbewegung\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Frame-Zeit-Reserve\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Flüssige Darstellung\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Inferenz mit niedriger Latenz ohne sichtbares Ruckeln\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\n\u003Ch2 id=\"section-42\">Warum kleine Modelle in Spielen sinnvoll sind\u003C\u002Fh2>\n\u003Cp>Ein Spielagent muss nicht alles im Internet wissen. Er muss das Vokabular des Spiels, den aktuellen Zustand, Aktionswerkzeuge und eine begrenzte Menge relevanten Wissens verstehen.\u003C\u002Fp>\n\u003Cp>Deshalb betont NVIDIA ACE kleine Modelle, die für Gaming-Hardware optimiert sind. KRAFTON beschreibt auch die Domänenanpassung für PUBG Ally: Das Modell wurde auf die Sanhok-Karte und den AI-Duo-Kontext beschränkt und um PUBG-spezifische Konzepte und Tool-Nutzung herum trainiert.\u003C\u002Fp>\n\u003Cp>Ein kleineres spezialisiertes Modell kann nützlicher sein als ein viel größeres allgemeines Modell, wenn seine Welt, seine Werkzeuge und seine Handlungsgrenzen gut definiert sind.\u003C\u002Fp>\n\u003Ch2 id=\"section-46\">RAG und Tools lösen unterschiedliche Probleme\u003C\u002Fh2>\n\u003Cp>NVIDIAs ACE Game Agent SDK stellt Agent-, Chat- und RAG-APIs bereit. Das sind separate Fähigkeiten, weil Wissensabruf und Aktionsausführung nicht dasselbe sind.\u003C\u002Fp>\n\u003Cp>RAG kann fundiertes Spielwissen liefern, wie Gegenstandsregeln, Fraktionsdaten oder Mechaniken. Tools legen offen, was der Agent im laufenden Spiel beobachten oder tun kann.\u003C\u002Fp>\n\u003Cp>Ein Agent kann die richtige Tatsache abrufen und trotzdem scheitern, wenn er den falschen Live-Zustand hat oder die falsche Aktion aufruft. Wissen, Zustand und Handlungsbefugnis müssen alle separat validiert werden.\u003C\u002Fp>\n\u003Ch2 id=\"section-50\">Was traditionelle NPCs immer noch besser machen\u003C\u002Fh2>\n\u003Cp>Sprachmodell-Agenten sind nicht automatisch bei jeder NPC-Aufgabe besser.\u003C\u002Fp>\n\u003Cp>Skriptbasierte Logik ist billiger, einfacher zu testen und vorhersehbarer, wenn das gewünschte Verhalten bereits bekannt ist. Ein Türwächter mit drei festen Zuständen braucht keine agentische Reasoning-Schleife.\u003C\u002Fp>\n\u003Cp>Die stärksten Anwendungsfälle sind Situationen, in denen natürliche Sprache, breite Planung, kontextuelle Anpassung oder spielerspezifische Koordination einen Wert schaffen, den statische Logik nur schwer bieten kann.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Wann man skriptbasierte KI vs. agentische KI einsetzt\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Traditionelle\u002Fskriptbasierte KI\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Agentische KI\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Vorhersehbarkeit\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Offene Sprache\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Unerwartete Spielerabsicht\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Reflexaktionen\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Deterministische QA\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-55\">Die Zuverlässigkeitsschleife des Agenten\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Was vor und nach jeder bedeutsamen Agentenaktion geschehen sollte\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Beobachten\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Nur den aktuellen Zustand lesen, der für die Entscheidung relevant ist.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Schlussfolgern\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Ein Ziel oder eine Aktionsklasse aus dem beobachteten Zustand und der Spielerabsicht wählen.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Validieren\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Prüfen, ob die Aktion zulässig, verfügbar und autorisiert ist.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Ausführen\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Die Absicht an die deterministische spielseitige Steuerung übergeben.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Bestätigen\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Den resultierenden Spielzustand lesen, anstatt Erfolg anzunehmen.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">6\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Neu planen\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Wenn das Ergebnis von der Erwartung abweicht, den Plan aktualisieren, anstatt Kontinuität zu halluzinieren.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Caside class=\"editorjs-callout editorjs-callout--warning my-6 rounded-xl border p-5 border-amber-300 bg-amber-50 dark:border-amber-900 dark:bg-amber-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Die gefährlichste Halluzination eines Spiel-Agenten\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Es ist nicht nur, eine falsche Tatsache zu sagen. Es ist \u003Cstrong>zu glauben, eine Aktion sei erfolgreich gewesen, obwohl die Engine sagt, dass sie es nicht war\u003C\u002Fstrong>. Jede bedeutsame Aktion sollte mit einer Zustandsbestätigung abschließen.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-58\">Warum natürliche Sprache Fehler überzeugender macht\u003C\u002Fh2>\n\u003Cp>ACE kann automatische Spracherkennung, Sprachschlussfolgerung und Text-zu-Sprache kombinieren, sodass ein Teamkollege natürlich hören, handeln und sprechen kann.\u003C\u002Fp>\n\u003Cp>Das verbessert die Immersion, erhöht aber auch die Notwendigkeit der Verankerung. Ein selbstbewusster gesprochener Satz wie „Ich habe das Medikit aufgehoben“ klingt autoritativ, selbst wenn die Item-Interaktion fehlgeschlagen ist.\u003C\u002Fp>\n\u003Cp>Sprache sollte daher nach Möglichkeit bestätigten Zustand melden, nicht bloß die beabsichtigte Aktion des Modells.\u003C\u002Fp>\n\u003Ch2 id=\"section-62\">Mehrsprachige Spiel-Agenten werden praktikabel\u003C\u002Fh2>\n\u003Cp>NVIDIA erweiterte ACE im Jahr 2026 um mehrsprachige On-Device-Modelle für Sprache, Spracherkennung und Sprachsynthese.\u003C\u002Fp>\n\u003Cp>NVIDIAs Entwickler-Update vom Mai 2026 beschreibt Qwen 3.5 4B-Unterstützung über 201 Sprachen und Dialekte, Riva Parakeet TDT 600M-Spracherkennung für 25 Sprachen und Chatterbox Multilingual 500M-Stimmen über 24 Sprachen.\u003C\u002Fp>\n\u003Cp>Das erweitert den Designraum für KI-Begleiter über rein englischsprachige Demos hinaus und macht lokale Sprachinteraktion zu einem realistischen Produktmerkmal.\u003C\u002Fp>\n\u003Ch2 id=\"section-66\">Was würde diese Antwort ändern?\u003C\u002Fh2>\n\u003Cp>Die Architektur könnte einheitlicher werden, wenn zukünftige Modelle deterministische Sub-Frame-Aktionslatenz erreichen und gleichzeitig klein genug bleiben, um kontinuierlich neben Grafik-Workloads zu laufen. Heute bleibt die Trennung von Reflexsteuerung und semantischem Schlussfolgern das praktischere Design.\u003C\u002Fp>\n\u003Cp>Spezialisierte neuronale Steuerungsrichtlinien könnten auch einige traditionelle Verhaltensbaum-Funktionen ersetzen, aber die Notwendigkeit expliziter Aktionsautorität, Zustandsvalidierung und schneller Ausführung wird bestehen bleiben.\u003C\u002Fp>\n\u003Ch2 id=\"section-69\">Einschränkungen\u003C\u002Fh2>\n\u003Cp>PUBG Ally ist eine Implementierung, kein Beweis dafür, dass jedes Spiel dieselbe Architektur übernehmen sollte. Unterschiedliche Genres haben unterschiedliche Anforderungen an Latenz, Determinismus, Hardware und Gameplay.\u003C\u002Fp>\n\u003Cp>Die öffentlichen Architekturdetails werden zudem primär von NVIDIA und KRAFTON bereitgestellt. Sie sind nützlich, um das implementierte System zu verstehen, sollten aber nicht als unabhängiges Performance-Benchmarking behandelt werden.\u003C\u002Fp>\n\u003Ch2 id=\"section-72\">Fazit\u003C\u002Fh2>\n\u003Cp>Die Zukunft von Spielagenten wird wahrscheinlich nicht darin bestehen, dass ein einziges riesiges Modell den gesamten KI-Stack des Spiels ersetzt.\u003C\u002Fp>\n\u003Cp>PUBG Ally deutet stattdessen auf eine hybride Architektur hin: Sprachmodelle interpretieren Absichten und treffen Entscheidungen auf hoher Ebene; deterministische Controller führen schnelles Gameplay aus; der Live-Zustand hält das Modell geerdet; und die Spiel-Engine behält die Kontrolle darüber, was tatsächlich passieren kann.\u003C\u002Fp>\n\u003Cp>Das siegreiche Design ist nicht der Agent, der über alles nachdenkt. Es ist der Agent, der weiß, worüber er nachdenken sollte – und was in der Spielschleife bleiben sollte.\u003C\u002Fp>\n\u003Ch2 id=\"section-76\">FAQ\u003C\u002Fh2>\n\u003Csection class=\"editorjs-faq my-6 rounded-xl border border-gray-200 p-5 dark:border-gray-700\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">KI-Teamkollegen, NVIDIA ACE und Spielagenten\u003C\u002Fh3>\u003Cdiv id=\"faq1\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Verwendet PUBG Ally ein einziges KI-Modell, um alles zu steuern?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Nein. Die von KRAFTON veröffentlichte Architektur trennt die Reasoning-Fähigkeiten des Sprachmodells von der schnellen Verhaltensbaum-Steuerung für Bewegung und Kampf.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq2\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Warum lässt man ein LLM nicht die Bewegung direkt steuern?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Die Inferenz von Sprachmodellen ist für semantisches Reasoning ausgelegt, nicht für deterministische Motorsteuerung pro Tick. Schnelle Gameplay-Aktionen profitieren von begrenzten spielseitigen Controllern.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq3\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Läuft PUBG Ally in der Cloud?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">NVIDIA zufolge laufen die von PUBG Ally verwendeten ACE-Kernmodelle lokal auf der GPU des Spielers, einschließlich des kleinen Sprachmodells.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq4\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Woher weiß die KI, was im Match passiert?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Das Spiel stellt den Live-Zustand über Beobachtungswerkzeuge bereit, während die Spielerstimme transkribiert und mit diesem Zustand für das Reasoning des Modells kombiniert wird.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq5\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Was ist das ACE Game Agent SDK?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Es ist NVIDIAs leichtgewichtiges C\u002FC++-Framework für native In-Game-Agenten, das Agent-, Chat- und RAG-APIs bereitstellt und für die Integration auf dem Gerät entwickelt wurde.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq6\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Werden KI-Agenten geskriptete NPCs ersetzen?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Nicht überall. Geskriptete KI bleibt günstiger, deterministisch und effektiv für begrenzte Verhaltensweisen. Agentische KI ist am nützlichsten, wo Sprache, Anpassung und offene Koordination wichtig sind.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-78\">Glossar\u003C\u002Fh2>\n\u003Csection class=\"editorjs-glossary my-6 rounded-xl border border-gray-200 dark:border-gray-700 p-5\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Wichtige Begriffe zu Spielagenten\u003C\u002Fh3>\u003Cdl>\u003Cdiv id=\"system-1-control\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">System-1-Steuerung\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Schnelle reaktive spielseitige Logik für unmittelbare Aktionen wie Bewegung, Kampf und Navigation.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"system-2-reasoning\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">System-2-Reasoning\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Langsameres, bewusstes Reasoning für Planung, Interpretation der Spielerabsicht, Koordination und Konversation.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"two-speed-game-agent\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Two-Speed Game Agent\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Ein Modell von Figure Rocks, das Reflexebene-Spielsteuerung von Reasoning auf höherer Ebene trennt.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"action-authority-boundary\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Action Authority Boundary\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Ein Konzept von Figure Rocks, das definiert, welche Absichten ein Modell wählen darf und welche legalen Aktionen die Spiel-Engine ausführen darf.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"observation-tool\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Beobachtungswerkzeug\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Eine spielseitige Schnittstelle, die ausgewählte aktuelle Zustände in strukturierter oder textueller Form für einen KI-Agenten bereitstellt.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"agent-harness\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Agent Harness\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Die Orchestrierungsschicht, die Modellinferenz, Beobachtungen, Werkzeuge, Speicher, Retrieval und spielseitige Ausführung verbindet.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"nvigi\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">NVIGI\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">NVIDIAs In-Game-Inferenz-Framework zum Ausführen und Planen lokaler KI-Modelle parallel zu Grafik-Workloads des Spiels.\u003C\u002Fdd>\u003C\u002Fdiv>\u003C\u002Fdl>\u003C\u002Fsection>\n\u003Ch2 id=\"section-80\">Primärquellen\u003C\u002Fh2>\n\u003Ca href=\"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fhow-krafton-built-pubg-ally-a-co-playable-character-powered-by-nvidia-ace\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA Developer – Wie KRAFTON PUBG Ally entwickelt hat\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizieller technischer Deep Dive über die System-1-Verhaltensbaum-\u002FSystem-2-SLM-Architektur, Live-Spielzustandsbeobachtungen, On-Device-Inferenz und Domänenanpassung.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fdeveloper.nvidia.com\u002Face-for-games\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA Developer – ACE für Spiele\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizielle ACE-Übersicht über das Game Agent SDK, Agent-\u002FChat-\u002FRAG-APIs, On-Device-Modelle und Anwendungsfälle für autonome Spielcharaktere.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fbuild-on-device-ai-companions-with-the-nvidia-ace-game-agent-sdk-and-unreal-engine-5-plugins\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA Developer – On-Device-KI-Begleiter entwickeln\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizieller Artikel von Juni 2026, der das Game Agent SDK, Unreal-Engine-Plugins und die Architektur für On-Device-KI-Begleiter vorstellt.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fgeforce\u002Fnews\u002Fpubg-ally-ai-teammate-beta-available-now\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA GeForce – PUBG Ally Duo-Modus-Beta\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizieller Artikel, der PUBG Ally als kollaborativen autonomen KI-Teamkollegen und die Entwicklung von ACE über konversationelle NPCs hinaus beschreibt.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fwhats-new-for-game-developers-in-nvidia-rtx-dlss-4-5-for-ue5-and-multilingual-ai-characters\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">NVIDIA Developer – Mehrsprachige KI-Charaktere\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizielles Update von Mai 2026, das mehrsprachige On-Device-ACE-Modelle für Sprache, ASR und TTS beschreibt.\u003C\u002Fp>\u003C\u002Fa>",{"time":538,"blocks":539,"version":1216},1790376796486,[540,546,554,561,568,574,579,584,589,594,599,604,609,614,637,668,673,678,683,688,697,702,707,712,719,748,753,758,763,768,773,797,802,807,812,817,822,827,832,837,842,872,877,882,887,892,897,902,907,912,917,922,927,932,965,970,994,1001,1006,1011,1016,1021,1026,1031,1036,1041,1046,1051,1056,1061,1066,1071,1076,1081,1086,1091,1096,1126,1131,1165,1170,1180,1189,1198,1207],{"id":541,"data":542,"type":544,"tunes":545},"intro",{"text":543},"Ein Sprachmodell kann über ein Feuergefecht sprechen, aber es sollte nicht für jede Bewegung, Zielanpassung und Sekundenbruchteil-Reaktion darin verantwortlich sein. NVIDIA ACE und KRAFTONs PUBG Ally zeigen, warum nützliche KI-Teammitglieder mehr als ein einzelnes Modell brauchen: schnelle Gameplay-Steuerung und langsamere Sprachschlussfolgerung sind unterschiedliche Aufgaben.","paragraph",{},{"id":547,"data":548,"type":552,"tunes":553},"direct",{"body":549,"title":550,"variant":551},"\u003Cstrong>Die stärkste Architektur für ein KI-Teammitglied ist nicht „LLM steuert alles“.\u003C\u002Fstrong> PUBG Ally trennt schnelles reaktives Gameplay von bewusstem Schlussfolgern. Eine Verhaltensbaum-Ebene übernimmt reflexartige Bewegung und Kampf, während ein kleines Sprachmodell die Spielerabsicht, den Live-Spielzustand und die übergeordnete Koordination interpretiert.","Direkte Antwort","info","callout",{},{"id":555,"data":556,"type":552,"tunes":560},"model-note",{"body":557,"title":558,"variant":559},"Das Modell des Zwei-Geschwindigkeiten-Spielagenten und die Aktionsautoritätsgrenze unten sind praktische Figure-Rocks-Frameworks, inspiriert von der öffentlich beschriebenen Architektur für NVIDIA ACE und PUBG Ally. Sie sind keine offizielle NVIDIA- oder KRAFTON-Terminologie.","Das in diesem Artikel verwendete Modell","note",{},{"id":562,"data":563,"type":566,"tunes":567},"toc",{"title":564,"maxLevel":565,"minLevel":47},"Inhalt",3,"tableOfContents",{},{"id":569,"data":570,"type":572,"tunes":573},"h-one-model",{"text":571,"level":47},"Warum ein KI-Modell nicht die ganze Figur steuern sollte","header",{},{"id":575,"data":576,"type":544,"tunes":578},"p-one-1",{"text":577},"Eine moderne Spielfigur muss mehrere Probleme auf radikal unterschiedlichen Zeitskalen lösen.",{},{"id":580,"data":581,"type":544,"tunes":583},"p-one-2",{"text":582},"Sie muss möglicherweise in Millisekunden ein Hindernis vermeiden, auf nahes Schussfeuer reagieren, einem Spielerbefehl folgen, entscheiden, ob sie plündern soll, einen Plan in natürlicher Sprache erklären und sich merken, was der Spieler zuvor gefragt hat.",{},{"id":585,"data":586,"type":544,"tunes":588},"p-one-3",{"text":587},"Der Versuch, all das durch eine einzige Sprachmodell-Schleife zu zwingen, erzeugt eine zeitliche Diskrepanz. Das Modell ist gut in semantischem Schlussfolgern und Planen, aber Echtzeitsteuerung benötigt oft deterministische Logik, die bei jedem Spiel-Tick reagieren kann.",{},{"id":590,"data":591,"type":572,"tunes":593},"h-two-speed",{"text":592,"level":47},"PUBG Ally verwendet eine Zwei-Geschwindigkeiten-Architektur",{},{"id":595,"data":596,"type":544,"tunes":598},"p-two-1",{"text":597},"KRAFTON beschreibt PUBG Ally als einen mitspielbaren KI-Teammitglied, das von NVIDIA ACE angetrieben wird. Das System kombiniert Spielerstimme, Live-Match-Zustand, ein kleines Sprachmodell und spielseitige Steuerungslogik.",{},{"id":600,"data":601,"type":544,"tunes":603},"p-two-2",{"text":602},"Laut NVIDIAs technischem Deep Dive trennt die Architektur einen System-1-Verhaltensbaum von einem System-2-Sprachmodell. Der Verhaltensbaum übernimmt schnelles reaktives Gameplay wie Bewegung und Kampf, während das Sprachmodell bewusstes Schlussfolgern, Kommunikation und Koordination übernimmt.",{},{"id":605,"data":606,"type":544,"tunes":608},"p-two-3",{"text":607},"Diese Aufteilung ist eines der wichtigsten Designmuster in Echtzeit-Spiel-KI, weil sie jedem Subsystem die Autorität über die Arbeit gibt, für die es tatsächlich geeignet ist.",{},{"id":610,"data":611,"type":572,"tunes":613},"h-model",{"text":612,"level":47},"Das Modell des Zwei-Geschwindigkeiten-Spielagenten",{},{"id":615,"data":616,"type":635,"tunes":636},"two-speed-flow",{"steps":617,"title":633,"orientation":634},[618,621,624,627,630],{"label":619,"description":620},"1. Wahrnehmung und Beobachtung","Das Spiel legt relevanten Live-Zustand offen, wie Position, Inventar, Bedrohungen, nahe Objekte und Spieleranfragen.",{"label":622,"description":623},"2. Bewusstes Schlussfolgern","Das Sprachmodell interpretiert die Absicht, wählt ein Ziel, plant und entscheidet, welches Werkzeug oder welche Aktionsklasse aufgerufen wird.",{"label":625,"description":626},"3. Aktionsübergabe","Die übergeordnete Entscheidung wird in strukturierte spielseitige Befehle umgewandelt.",{"label":628,"description":629},"4. Reaktive Ausführung","Verhaltensbäume oder andere deterministische Controller übernehmen Bewegung, Kampf, Navigation und reflexartige Reaktionen.",{"label":631,"description":632},"5. Erneute Beobachtung","Der Agent liest den geänderten Spielzustand und aktualisiert seinen Plan, wenn die Welt nicht mehr den vorherigen Annahmen entspricht.","Wie ein praktisches KI-Teammitglied die Arbeit aufteilen kann","auto","processFlow",{},{"id":638,"data":639,"type":666,"tunes":667},"system-table",{"rows":640,"title":657,"layout":658,"columns":659},[641,645,649,653],{"id":642,"label":643,"values":644},"timescale","Zeitskala",[13,13],{"id":646,"label":647,"values":648},"tasks","Typische Aufgaben",[13,13],{"id":650,"label":651,"values":652},"failure","Wenn es zu langsam ist",[13,13],{"id":654,"label":655,"values":656},"control","Bester Steuerungsstil",[13,13],"System 1 vs. System 2 in einem Spielagenten","table",[660,663],{"id":661,"label":662},"system1","Schnelle reaktive Ebene",{"id":664,"label":665},"system2","Bewusste Schlussfolgerungsebene","comparison",{},{"id":669,"data":670,"type":572,"tunes":672},"h-state",{"text":671,"level":47},"Der Live-Spielzustand macht das Modell nützlich",{},{"id":674,"data":675,"type":544,"tunes":677},"p-state-1",{"text":676},"Das PUBG-Ally-Modell schlussfolgert nicht allein aus dem Dialog. NVIDIA sagt, dass die Spiel-Engine den Live-Match-Zustand für den Agenten durch Beobachtungswerkzeuge offenlegt, die als textuelle Beschreibungen dargestellt werden.",{},{"id":679,"data":680,"type":544,"tunes":682},"p-state-2",{"text":681},"Das ist wichtig, weil ein Teammitglied wissen muss, was gerade passiert: was der Spieler gesagt hat, welche Gegenstände in der Nähe sind, woher die Gefahr kommt und ob der vorherige Plan noch gültig ist.",{},{"id":684,"data":685,"type":544,"tunes":687},"p-state-3",{"text":686},"Dies ist dasselbe Zuverlässigkeitsprinzip, das für jeden Spielassistenten gilt: Allgemeines Spielwissen reicht nicht aus, wenn die korrekte Aktion vom aktuellen Sitzungszustand abhängt.",{},{"id":689,"data":690,"type":695,"tunes":696},"ref-state",{"url":691,"title":692,"excerpt":693,"ctaLabel":694},"https:\u002F\u002Ffigure.rocks\u002Fde\u002Fblog\u002Fyour-game-assistant-knows-the-game-but-does-it-know-your-game-state","Dein Spielassistent kennt das Spiel – aber kennt er deinen Spielzustand?","Warum aktuelle Gesundheit, Inventar, Quest-Flags, Abklingzeiten und andere Live-Zustände bestimmen, ob KI-Spielratschläge tatsächlich gültig sind.","Lies den Leitfaden zum Spielzustand","referralArticle",{},{"id":698,"data":699,"type":572,"tunes":701},"h-authority",{"text":700,"level":47},"Die Grenze der Handlungsbefugnis",{},{"id":703,"data":704,"type":544,"tunes":706},"p-auth-1",{"text":705},"Ein nützlicher Echtzeit-Spielagent braucht eine klare Grenze zwischen dem, was das Modell entscheiden darf, und dem, was die Spiel-Engine tatsächlich ausführen darf.",{},{"id":708,"data":709,"type":544,"tunes":711},"p-auth-2",{"text":710},"Das Modell kann ein Ziel wählen wie „in Deckung gehen“, „Munition plündern“, „dem Spieler folgen“ oder „diesen Feind angreifen“. Der spielseitige Controller sollte diese Absicht dann in legale, begrenzte Aktionen übersetzen, die Navigation, Animation, Abklingzeiten, Physik und Spielregeln befolgen.",{},{"id":713,"data":714,"type":552,"tunes":718},"auth-rule",{"body":715,"title":716,"variant":717},"Lass das Modell unter \u003Cstrong>autorisierten Absichten\u003C\u002Fstrong> wählen. Lass die Engine nur \u003Cstrong>validierte Spielaktionen\u003C\u002Fstrong> ausführen.","Das Sicherheitsmuster","success",{},{"id":720,"data":721,"type":666,"tunes":747},"authority-table",{"rows":722,"title":739,"layout":658,"columns":740},[723,727,731,735],{"id":724,"label":725,"values":726},"movement","Bewegung",[13,13],{"id":728,"label":729,"values":730},"combat","Kampf",[13,13],{"id":732,"label":733,"values":734},"inventory","Inventar",[13,13],{"id":736,"label":737,"values":738},"speech","Sprache",[13,13],"Gute vs. gefährliche Agentensteuerung",[741,744],{"id":742,"label":743},"good","Begrenzte Architektur",{"id":745,"label":746},"bad","Unbegrenzte Architektur",{},{"id":749,"data":750,"type":572,"tunes":752},"h-event",{"text":751,"level":47},"Warum ereignisgesteuertes Denken besser ist als ständiges Abfragen des Sprachmodells",{},{"id":754,"data":755,"type":544,"tunes":757},"p-event-1",{"text":756},"Die Modellschleife von PUBG Ally wird als ereignisgesteuert beschrieben. Sie kann ausgelöst werden, wenn der Spieler spricht oder durch relevante Ereignisse im Spiel.",{},{"id":759,"data":760,"type":544,"tunes":762},"p-event-2",{"text":761},"Das ist effizienter, als das Modell in jedem Frame die gesamte Welt neu überdenken zu lassen. Die meisten Frames erfordern keine strategische Entscheidung.",{},{"id":764,"data":765,"type":544,"tunes":767},"p-event-3",{"text":766},"Ein gutes Auslösesystem ruft das Sprachmodell auf, wenn Semantik wichtig ist: ein neuer Befehl eintrifft, eine Bedrohung den Plan ändert, ein Ziel abgeschlossen wird, ein Gegenstand relevant wird oder der aktuelle Plan fehlschlägt.",{},{"id":769,"data":770,"type":572,"tunes":772},"h-trigger",{"text":771,"level":47},"Der Entscheidungsauslösefilter",{},{"id":774,"data":775,"type":635,"tunes":796},"trigger-flow",{"steps":776,"title":795,"orientation":634},[777,780,783,786,789,792],{"label":778,"description":779},"Spielerabsicht geändert","Eine neue gesprochene oder textliche Anfrage erfordert Interpretation.",{"label":781,"description":782},"Plan ungültig geworden","Das Ziel verschwand, der Pfad schlug fehl, der Gegenstand ist weg oder der Kampf hat die Situation verändert.",{"label":784,"description":785},"Übergeordneter Meilenstein erreicht","Die Figur ist angekommen, hat geplündert, geheilt oder ein geplantes Teilziel abgeschlossen.",{"label":787,"description":788},"Wichtige neue Beobachtung","Eine neue Bedrohung, Ressource oder strategische Gelegenheit erscheint.",{"label":790,"description":791},"Konversation erforderlich","Der Agent sollte bestätigen, erklären oder um Klärung bitten.",{"label":793,"description":794},"Andernfalls reaktiv bleiben","Lass die untergeordneten Controller ohne unnötige Modellinferenz weiterlaufen.","Wann sollte das Sprachmodell aufwachen?",{},{"id":798,"data":799,"type":572,"tunes":801},"h-local",{"text":800,"level":47},"Inferenz auf dem Gerät verändert den Designraum",{},{"id":803,"data":804,"type":544,"tunes":806},"p-local-1",{"text":805},"NVIDIA ACE ist sowohl um Inferenz auf dem Gerät als auch um Cloud-Optionen herum konzipiert. Für PUBG Ally sagt NVIDIA, dass das kleine Sprachmodell lokal auf der GPU des Spielers läuft.",{},{"id":808,"data":809,"type":544,"tunes":811},"p-local-2",{"text":810},"Die veröffentlichte Architektur verwendet ein Mistral-NeMo-Minitron-Modell mit 2B Parametern, das so konzipiert ist, dass es in den VRAM-Spielraum passt, der nach dem Betrieb von PUBG selbst noch übrig bleibt.",{},{"id":813,"data":814,"type":544,"tunes":816},"p-local-3",{"text":815},"Das ist eine nicht triviale Einschränkung. Spiel-KI kann nicht einfach den gesamten verfügbaren GPU-Speicher oder die Rechenleistung beanspruchen, weil die Grafiklast weiterhin Priorität hat.",{},{"id":818,"data":819,"type":572,"tunes":821},"h-contention",{"text":820,"level":47},"KI-Inferenz konkurriert jetzt mit dem Rendering",{},{"id":823,"data":824,"type":544,"tunes":826},"p-contention-1",{"text":825},"Dies schafft ein neues Ressourcenproblem für Spiele: Grafik und KI-Inferenz könnten dieselbe GPU gemeinsam nutzen.",{},{"id":828,"data":829,"type":544,"tunes":831},"p-contention-2",{"text":830},"NVIDIAs In-Game Inferencing SDK wurde entwickelt, um lokale KI-Modelle neben Grafik-Workloads zu planen. Sein Zweck ist nicht nur, Modelle auszuführen, sondern dies zu tun, ohne das Frame-Zeit-Budget des Spiels zu zerstören.",{},{"id":833,"data":834,"type":544,"tunes":836},"p-contention-3",{"text":835},"Das bedeutet, dass zukünftige Leistungsbewertungen möglicherweise nicht nur DLSS, Raytracing und VRAM-Nutzung messen müssen, sondern auch die Kosten der lokalen NPC-Inferenz.",{},{"id":838,"data":839,"type":572,"tunes":841},"h-budget",{"text":840,"level":47},"Das KI-Ressourcenbudget im Spiel",{},{"id":843,"data":844,"type":658,"tunes":871},"resource-table",{"content":845,"stretched":870,"withHeadings":15},[846,850,854,858,862,866],[847,848,849],"Ressource","Grafik benötigt sie für","KI-Agent benötigt sie für",[851,852,853],"VRAM","Texturen, Puffer, Geometrie, Raytracing, Frame-Generierung","Modellgewichte, KV-Cache, Embeddings und Inferenzpuffer",[855,856,857],"GPU-Compute","Rasterisierung, RT, neuronale Grafik","SLM\u002FASR\u002FTTS-Inferenz",[859,860,861],"CPU-Zeit","Simulation, Draw-Submission, Spielsysteme","Agent-Orchestrierung, Tools, Textverarbeitung",[863,864,865],"Speicherbandbreite","Asset- und Render-Workloads","Modellausführung und Datenbewegung",[867,868,869],"Frame-Zeit-Reserve","Flüssige Darstellung","Inferenz mit niedriger Latenz ohne sichtbares Ruckeln",false,{},{"id":873,"data":874,"type":572,"tunes":876},"h-small",{"text":875,"level":47},"Warum kleine Modelle in Spielen sinnvoll sind",{},{"id":878,"data":879,"type":544,"tunes":881},"p-small-1",{"text":880},"Ein Spielagent muss nicht alles im Internet wissen. Er muss das Vokabular des Spiels, den aktuellen Zustand, Aktionswerkzeuge und eine begrenzte Menge relevanten Wissens verstehen.",{},{"id":883,"data":884,"type":544,"tunes":886},"p-small-2",{"text":885},"Deshalb betont NVIDIA ACE kleine Modelle, die für Gaming-Hardware optimiert sind. KRAFTON beschreibt auch die Domänenanpassung für PUBG Ally: Das Modell wurde auf die Sanhok-Karte und den AI-Duo-Kontext beschränkt und um PUBG-spezifische Konzepte und Tool-Nutzung herum trainiert.",{},{"id":888,"data":889,"type":544,"tunes":891},"p-small-3",{"text":890},"Ein kleineres spezialisiertes Modell kann nützlicher sein als ein viel größeres allgemeines Modell, wenn seine Welt, seine Werkzeuge und seine Handlungsgrenzen gut definiert sind.",{},{"id":893,"data":894,"type":572,"tunes":896},"h-rag-tools",{"text":895,"level":47},"RAG und Tools lösen unterschiedliche Probleme",{},{"id":898,"data":899,"type":544,"tunes":901},"p-rag-1",{"text":900},"NVIDIAs ACE Game Agent SDK stellt Agent-, Chat- und RAG-APIs bereit. Das sind separate Fähigkeiten, weil Wissensabruf und Aktionsausführung nicht dasselbe sind.",{},{"id":903,"data":904,"type":544,"tunes":906},"p-rag-2",{"text":905},"RAG kann fundiertes Spielwissen liefern, wie Gegenstandsregeln, Fraktionsdaten oder Mechaniken. Tools legen offen, was der Agent im laufenden Spiel beobachten oder tun kann.",{},{"id":908,"data":909,"type":544,"tunes":911},"p-rag-3",{"text":910},"Ein Agent kann die richtige Tatsache abrufen und trotzdem scheitern, wenn er den falschen Live-Zustand hat oder die falsche Aktion aufruft. Wissen, Zustand und Handlungsbefugnis müssen alle separat validiert werden.",{},{"id":913,"data":914,"type":572,"tunes":916},"h-traditional",{"text":915,"level":47},"Was traditionelle NPCs immer noch besser machen",{},{"id":918,"data":919,"type":544,"tunes":921},"p-trad-1",{"text":920},"Sprachmodell-Agenten sind nicht automatisch bei jeder NPC-Aufgabe besser.",{},{"id":923,"data":924,"type":544,"tunes":926},"p-trad-2",{"text":925},"Skriptbasierte Logik ist billiger, einfacher zu testen und vorhersehbarer, wenn das gewünschte Verhalten bereits bekannt ist. Ein Türwächter mit drei festen Zuständen braucht keine agentische Reasoning-Schleife.",{},{"id":928,"data":929,"type":544,"tunes":931},"p-trad-3",{"text":930},"Die stärksten Anwendungsfälle sind Situationen, in denen natürliche Sprache, breite Planung, kontextuelle Anpassung oder spielerspezifische Koordination einen Wert schaffen, den statische Logik nur schwer bieten kann.",{},{"id":933,"data":934,"type":666,"tunes":964},"scripted-agentic",{"rows":935,"title":956,"layout":658,"columns":957},[936,940,944,948,952],{"id":937,"label":938,"values":939},"predictability","Vorhersehbarkeit",[13,13],{"id":941,"label":942,"values":943},"language","Offene Sprache",[13,13],{"id":945,"label":946,"values":947},"adaptation","Unerwartete Spielerabsicht",[13,13],{"id":949,"label":950,"values":951},"latency","Reflexaktionen",[13,13],{"id":953,"label":954,"values":955},"testing","Deterministische QA",[13,13],"Wann man skriptbasierte KI vs. agentische KI einsetzt",[958,961],{"id":959,"label":960},"scripted","Traditionelle\u002Fskriptbasierte KI",{"id":962,"label":963},"agentic","Agentische KI",{},{"id":966,"data":967,"type":572,"tunes":969},"h-reliability",{"text":968,"level":47},"Die Zuverlässigkeitsschleife des Agenten",{},{"id":971,"data":972,"type":635,"tunes":993},"reliability-flow",{"steps":973,"title":992,"orientation":634},[974,977,980,983,986,989],{"label":975,"description":976},"Beobachten","Nur den aktuellen Zustand lesen, der für die Entscheidung relevant ist.",{"label":978,"description":979},"Schlussfolgern","Ein Ziel oder eine Aktionsklasse aus dem beobachteten Zustand und der Spielerabsicht wählen.",{"label":981,"description":982},"Validieren","Prüfen, ob die Aktion zulässig, verfügbar und autorisiert ist.",{"label":984,"description":985},"Ausführen","Die Absicht an die deterministische spielseitige Steuerung übergeben.",{"label":987,"description":988},"Bestätigen","Den resultierenden Spielzustand lesen, anstatt Erfolg anzunehmen.",{"label":990,"description":991},"Neu planen","Wenn das Ergebnis von der Erwartung abweicht, den Plan aktualisieren, anstatt Kontinuität zu halluzinieren.","Was vor und nach jeder bedeutsamen Agentenaktion geschehen sollte",{},{"id":995,"data":996,"type":552,"tunes":1000},"action-warning",{"body":997,"title":998,"variant":999},"Es ist nicht nur, eine falsche Tatsache zu sagen. Es ist \u003Cstrong>zu glauben, eine Aktion sei erfolgreich gewesen, obwohl die Engine sagt, dass sie es nicht war\u003C\u002Fstrong>. Jede bedeutsame Aktion sollte mit einer Zustandsbestätigung abschließen.","Die gefährlichste Halluzination eines Spiel-Agenten","warning",{},{"id":1002,"data":1003,"type":572,"tunes":1005},"h-speech",{"text":1004,"level":47},"Warum natürliche Sprache Fehler überzeugender macht",{},{"id":1007,"data":1008,"type":544,"tunes":1010},"p-speech-1",{"text":1009},"ACE kann automatische Spracherkennung, Sprachschlussfolgerung und Text-zu-Sprache kombinieren, sodass ein Teamkollege natürlich hören, handeln und sprechen kann.",{},{"id":1012,"data":1013,"type":544,"tunes":1015},"p-speech-2",{"text":1014},"Das verbessert die Immersion, erhöht aber auch die Notwendigkeit der Verankerung. Ein selbstbewusster gesprochener Satz wie „Ich habe das Medikit aufgehoben“ klingt autoritativ, selbst wenn die Item-Interaktion fehlgeschlagen ist.",{},{"id":1017,"data":1018,"type":544,"tunes":1020},"p-speech-3",{"text":1019},"Sprache sollte daher nach Möglichkeit bestätigten Zustand melden, nicht bloß die beabsichtigte Aktion des Modells.",{},{"id":1022,"data":1023,"type":572,"tunes":1025},"h-multilingual",{"text":1024,"level":47},"Mehrsprachige Spiel-Agenten werden praktikabel",{},{"id":1027,"data":1028,"type":544,"tunes":1030},"p-multi-1",{"text":1029},"NVIDIA erweiterte ACE im Jahr 2026 um mehrsprachige On-Device-Modelle für Sprache, Spracherkennung und Sprachsynthese.",{},{"id":1032,"data":1033,"type":544,"tunes":1035},"p-multi-2",{"text":1034},"NVIDIAs Entwickler-Update vom Mai 2026 beschreibt Qwen 3.5 4B-Unterstützung über 201 Sprachen und Dialekte, Riva Parakeet TDT 600M-Spracherkennung für 25 Sprachen und Chatterbox Multilingual 500M-Stimmen über 24 Sprachen.",{},{"id":1037,"data":1038,"type":544,"tunes":1040},"p-multi-3",{"text":1039},"Das erweitert den Designraum für KI-Begleiter über rein englischsprachige Demos hinaus und macht lokale Sprachinteraktion zu einem realistischen Produktmerkmal.",{},{"id":1042,"data":1043,"type":572,"tunes":1045},"h-change",{"text":1044,"level":47},"Was würde diese Antwort ändern?",{},{"id":1047,"data":1048,"type":544,"tunes":1050},"p-change-1",{"text":1049},"Die Architektur könnte einheitlicher werden, wenn zukünftige Modelle deterministische Sub-Frame-Aktionslatenz erreichen und gleichzeitig klein genug bleiben, um kontinuierlich neben Grafik-Workloads zu laufen. Heute bleibt die Trennung von Reflexsteuerung und semantischem Schlussfolgern das praktischere Design.",{},{"id":1052,"data":1053,"type":544,"tunes":1055},"p-change-2",{"text":1054},"Spezialisierte neuronale Steuerungsrichtlinien könnten auch einige traditionelle Verhaltensbaum-Funktionen ersetzen, aber die Notwendigkeit expliziter Aktionsautorität, Zustandsvalidierung und schneller Ausführung wird bestehen bleiben.",{},{"id":1057,"data":1058,"type":572,"tunes":1060},"h-limit",{"text":1059,"level":47},"Einschränkungen",{},{"id":1062,"data":1063,"type":544,"tunes":1065},"p-limit-1",{"text":1064},"PUBG Ally ist eine Implementierung, kein Beweis dafür, dass jedes Spiel dieselbe Architektur übernehmen sollte. Unterschiedliche Genres haben unterschiedliche Anforderungen an Latenz, Determinismus, Hardware und Gameplay.",{},{"id":1067,"data":1068,"type":544,"tunes":1070},"p-limit-2",{"text":1069},"Die öffentlichen Architekturdetails werden zudem primär von NVIDIA und KRAFTON bereitgestellt. Sie sind nützlich, um das implementierte System zu verstehen, sollten aber nicht als unabhängiges Performance-Benchmarking behandelt werden.",{},{"id":1072,"data":1073,"type":572,"tunes":1075},"h-conclusion",{"text":1074,"level":47},"Fazit",{},{"id":1077,"data":1078,"type":544,"tunes":1080},"p-conc-1",{"text":1079},"Die Zukunft von Spielagenten wird wahrscheinlich nicht darin bestehen, dass ein einziges riesiges Modell den gesamten KI-Stack des Spiels ersetzt.",{},{"id":1082,"data":1083,"type":544,"tunes":1085},"p-conc-2",{"text":1084},"PUBG Ally deutet stattdessen auf eine hybride Architektur hin: Sprachmodelle interpretieren Absichten und treffen Entscheidungen auf hoher Ebene; deterministische Controller führen schnelles Gameplay aus; der Live-Zustand hält das Modell geerdet; und die Spiel-Engine behält die Kontrolle darüber, was tatsächlich passieren kann.",{},{"id":1087,"data":1088,"type":544,"tunes":1090},"p-conc-3",{"text":1089},"Das siegreiche Design ist nicht der Agent, der über alles nachdenkt. Es ist der Agent, der weiß, worüber er nachdenken sollte – und was in der Spielschleife bleiben sollte.",{},{"id":1092,"data":1093,"type":572,"tunes":1095},"h-faq",{"text":1094,"level":47},"FAQ",{},{"id":1097,"data":1098,"type":1097,"tunes":1125},"faq",{"items":1099,"title":1124},[1100,1104,1108,1112,1116,1120],{"id":1101,"answer":1102,"question":1103},"faq1","Nein. Die von KRAFTON veröffentlichte Architektur trennt die Reasoning-Fähigkeiten des Sprachmodells von der schnellen Verhaltensbaum-Steuerung für Bewegung und Kampf.","Verwendet PUBG Ally ein einziges KI-Modell, um alles zu steuern?",{"id":1105,"answer":1106,"question":1107},"faq2","Die Inferenz von Sprachmodellen ist für semantisches Reasoning ausgelegt, nicht für deterministische Motorsteuerung pro Tick. Schnelle Gameplay-Aktionen profitieren von begrenzten spielseitigen Controllern.","Warum lässt man ein LLM nicht die Bewegung direkt steuern?",{"id":1109,"answer":1110,"question":1111},"faq3","NVIDIA zufolge laufen die von PUBG Ally verwendeten ACE-Kernmodelle lokal auf der GPU des Spielers, einschließlich des kleinen Sprachmodells.","Läuft PUBG Ally in der Cloud?",{"id":1113,"answer":1114,"question":1115},"faq4","Das Spiel stellt den Live-Zustand über Beobachtungswerkzeuge bereit, während die Spielerstimme transkribiert und mit diesem Zustand für das Reasoning des Modells kombiniert wird.","Woher weiß die KI, was im Match passiert?",{"id":1117,"answer":1118,"question":1119},"faq5","Es ist NVIDIAs leichtgewichtiges C\u002FC++-Framework für native In-Game-Agenten, das Agent-, Chat- und RAG-APIs bereitstellt und für die Integration auf dem Gerät entwickelt wurde.","Was ist das ACE Game Agent SDK?",{"id":1121,"answer":1122,"question":1123},"faq6","Nicht überall. Geskriptete KI bleibt günstiger, deterministisch und effektiv für begrenzte Verhaltensweisen. Agentische KI ist am nützlichsten, wo Sprache, Anpassung und offene Koordination wichtig sind.","Werden KI-Agenten geskriptete NPCs ersetzen?","KI-Teamkollegen, NVIDIA ACE und Spielagenten",{},{"id":1127,"data":1128,"type":572,"tunes":1130},"h-glossary",{"text":1129,"level":47},"Glossar",{},{"id":1132,"data":1133,"type":1132,"tunes":1164},"glossary",{"title":1134,"entries":1135},"Wichtige Begriffe zu Spielagenten",[1136,1140,1144,1148,1152,1156,1160],{"term":1137,"anchor":1138,"definition":1139},"System-1-Steuerung","system-1-control","Schnelle reaktive spielseitige Logik für unmittelbare Aktionen wie Bewegung, Kampf und Navigation.",{"term":1141,"anchor":1142,"definition":1143},"System-2-Reasoning","system-2-reasoning","Langsameres, bewusstes Reasoning für Planung, Interpretation der Spielerabsicht, Koordination und Konversation.",{"term":1145,"anchor":1146,"definition":1147},"Two-Speed Game Agent","two-speed-game-agent","Ein Modell von Figure Rocks, das Reflexebene-Spielsteuerung von Reasoning auf höherer Ebene trennt.",{"term":1149,"anchor":1150,"definition":1151},"Action Authority Boundary","action-authority-boundary","Ein Konzept von Figure Rocks, das definiert, welche Absichten ein Modell wählen darf und welche legalen Aktionen die Spiel-Engine ausführen darf.",{"term":1153,"anchor":1154,"definition":1155},"Beobachtungswerkzeug","observation-tool","Eine spielseitige Schnittstelle, die ausgewählte aktuelle Zustände in strukturierter oder textueller Form für einen KI-Agenten bereitstellt.",{"term":1157,"anchor":1158,"definition":1159},"Agent Harness","agent-harness","Die Orchestrierungsschicht, die Modellinferenz, Beobachtungen, Werkzeuge, Speicher, Retrieval und spielseitige Ausführung verbindet.",{"term":1161,"anchor":1162,"definition":1163},"NVIGI","nvigi","NVIDIAs In-Game-Inferenz-Framework zum Ausführen und Planen lokaler KI-Modelle parallel zu Grafik-Workloads des Spiels.",{},{"id":1166,"data":1167,"type":572,"tunes":1169},"h-sources",{"text":1168,"level":47},"Primärquellen",{},{"id":1171,"data":1172,"type":1178,"tunes":1179},"src-pubg-deep-dive",{"link":1173,"meta":1174},"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fhow-krafton-built-pubg-ally-a-co-playable-character-powered-by-nvidia-ace\u002F",{"image":1175,"title":1176,"description":1177},{"url":13},"NVIDIA Developer – Wie KRAFTON PUBG Ally entwickelt hat","Offizieller technischer Deep Dive über die System-1-Verhaltensbaum-\u002FSystem-2-SLM-Architektur, Live-Spielzustandsbeobachtungen, On-Device-Inferenz und Domänenanpassung.","linkTool",{},{"id":1181,"data":1182,"type":1178,"tunes":1188},"src-ace-sdk",{"link":1183,"meta":1184},"https:\u002F\u002Fdeveloper.nvidia.com\u002Face-for-games",{"image":1185,"title":1186,"description":1187},{"url":13},"NVIDIA Developer – ACE für Spiele","Offizielle ACE-Übersicht über das Game Agent SDK, Agent-\u002FChat-\u002FRAG-APIs, On-Device-Modelle und Anwendungsfälle für autonome Spielcharaktere.",{},{"id":1190,"data":1191,"type":1178,"tunes":1197},"src-ace-companions",{"link":1192,"meta":1193},"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fbuild-on-device-ai-companions-with-the-nvidia-ace-game-agent-sdk-and-unreal-engine-5-plugins\u002F",{"image":1194,"title":1195,"description":1196},{"url":13},"NVIDIA Developer – On-Device-KI-Begleiter entwickeln","Offizieller Artikel von Juni 2026, der das Game Agent SDK, Unreal-Engine-Plugins und die Architektur für On-Device-KI-Begleiter vorstellt.",{},{"id":1199,"data":1200,"type":1178,"tunes":1206},"src-pubg-beta",{"link":1201,"meta":1202},"https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fgeforce\u002Fnews\u002Fpubg-ally-ai-teammate-beta-available-now\u002F",{"image":1203,"title":1204,"description":1205},{"url":13},"NVIDIA GeForce – PUBG Ally Duo-Modus-Beta","Offizieller Artikel, der PUBG Ally als kollaborativen autonomen KI-Teamkollegen und die Entwicklung von ACE über konversationelle NPCs hinaus beschreibt.",{},{"id":1208,"data":1209,"type":1178,"tunes":1215},"src-multilingual",{"link":1210,"meta":1211},"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fwhats-new-for-game-developers-in-nvidia-rtx-dlss-4-5-for-ue5-and-multilingual-ai-characters\u002F",{"image":1212,"title":1213,"description":1214},{"url":13},"NVIDIA Developer – Mehrsprachige KI-Charaktere","Offizielles Update von Mai 2026, das mehrsprachige On-Device-ACE-Modelle für Sprache, ASR und TTS beschreibt.",{},"2.31","Ein Sprachmodell kann Taktiken und Spielerabsichten verstehen, aber es sollte nicht jede Bewegung und Kampfreaktion direkt steuern. PUBG Ally zeigt eine praktischere Architektur: schnelle Verhaltensbaum-Steuerung für Reflexaktionen, kombiniert mit einem kleinen Sprachmodell für Planung, Koordination und natürliche Konversation.","\u002Fuploads\u002F2026\u002F09\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning-1790376777825-bi2zzb.webp","pubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning-1790376777825-bi2zzb","PUBLISHED","2026-09-25T18:51:00.000Z","2026-09-25T22:51:40.254Z","2026-09-25T22:56:33.518Z",{"en":1225,"de":1226,"sr":1227,"es":1228,"fr":1229,"it":1230,"ru":1231,"zh":1232},"\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","\u002Fde\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","\u002Fsr\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","\u002Fes\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","\u002Ffr\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","\u002Fit\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","\u002Fru\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning","\u002Fzh\u002Fblog\u002Fpubg-ally-shows-why-ai-teammates-need-two-brains-fast-reflexes-and-slow-reasoning",[1234,1238,1242,1246,1250,1254],{"id":1235,"name":1236,"slug":1237},262,"Super Smash Bros.","super-smash-bros",{"id":1239,"name":1240,"slug":1241},251,"Unschärfe und Persistenz","blur-and-persistence",{"id":1243,"name":1244,"slug":1245},252,"Overdrive und Smearing","overdrive-and-smearing",{"id":1247,"name":1248,"slug":1249},253,"Bildwiederholrate und Klarheit","refresh-and-clarity",{"id":1251,"name":1252,"slug":1253},430,"Animal Crossing","animal-crossing",{"id":1255,"name":1256,"slug":1257},337,"Korrekte Frame-Cap-Regeln","correct-frame-cap-rules",{"id":392,"login":1259,"email":1260,"displayName":1261},"aleksandar","aleksandar@stajic.de","Aleksandar Stajic",[1263,1804],{"lang":8,"title":1264,"content":1265,"contentJson":1266,"excerpt":1803},"PUBG Ally Shows Why AI Teammates Need Two Brains: Fast Reflexes and Slow Reasoning","{\"time\":1790376779898,\"blocks\":[{\"id\":\"intro\",\"type\":\"paragraph\",\"data\":{\"text\":\"A language model can talk about a firefight, but it should not be responsible for every movement, aim adjustment and split-second reaction inside one. NVIDIA ACE and KRAFTON's PUBG Ally show why useful AI teammates need more than a single model: fast gameplay control and slower language reasoning are different jobs.\"},\"tunes\":{}},{\"id\":\"direct\",\"type\":\"callout\",\"data\":{\"variant\":\"info\",\"title\":\"Direct answer\",\"body\":\"\u003Cstrong>The strongest architecture for an AI teammate is not “LLM controls everything.”\u003C\u002Fstrong> PUBG Ally separates fast reactive gameplay from deliberate reasoning. A behavior-tree layer handles reflex-level movement and combat, while a small language model interprets player intent, live game state and higher-level coordination.\"},\"tunes\":{}},{\"id\":\"model-note\",\"type\":\"callout\",\"data\":{\"variant\":\"note\",\"title\":\"The model used in this article\",\"body\":\"The Two-Speed Game Agent model and Action Authority Boundary below are practical Figure Rocks frameworks inspired by the architecture publicly described for NVIDIA ACE and PUBG Ally. They are not official NVIDIA or KRAFTON terminology.\"},\"tunes\":{}},{\"id\":\"toc\",\"type\":\"tableOfContents\",\"data\":{\"title\":\"Contents\",\"minLevel\":2,\"maxLevel\":3},\"tunes\":{}},{\"id\":\"h-one-model\",\"type\":\"header\",\"data\":{\"text\":\"Why one AI model should not run the whole character\",\"level\":2},\"tunes\":{}},{\"id\":\"p-one-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"A modern game character has to solve several problems at radically different timescales.\"},\"tunes\":{}},{\"id\":\"p-one-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"It may need to avoid an obstacle in milliseconds, react to nearby gunfire, follow a player command, decide whether to loot, explain a plan in natural language and remember what the player asked earlier.\"},\"tunes\":{}},{\"id\":\"p-one-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"Trying to force all of that through one language-model loop creates a timing mismatch. The model is good at semantic reasoning and planning, but real-time control often needs deterministic logic that can react every game tick.\"},\"tunes\":{}},{\"id\":\"h-two-speed\",\"type\":\"header\",\"data\":{\"text\":\"PUBG Ally uses a two-speed architecture\",\"level\":2},\"tunes\":{}},{\"id\":\"p-two-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"KRAFTON describes PUBG Ally as a co-playable AI teammate powered by NVIDIA ACE. The system combines player voice, live match state, a small language model and game-side control logic.\"},\"tunes\":{}},{\"id\":\"p-two-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"According to NVIDIA's technical deep dive, the architecture separates a System 1 behavior tree from a System 2 language model. The behavior tree handles fast reactive gameplay such as movement and combat, while the language model handles deliberate reasoning, communication and coordination.\"},\"tunes\":{}},{\"id\":\"p-two-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"That split is one of the most important design patterns in real-time game AI because it gives each subsystem authority over the work it is actually suited to perform.\"},\"tunes\":{}},{\"id\":\"h-model\",\"type\":\"header\",\"data\":{\"text\":\"The Two-Speed Game Agent model\",\"level\":2},\"tunes\":{}},{\"id\":\"two-speed-flow\",\"type\":\"processFlow\",\"data\":{\"title\":\"How a practical AI teammate can divide the work\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. Perception and observation\",\"description\":\"The game exposes relevant live state such as position, inventory, threats, nearby objects and player requests.\"},{\"label\":\"2. Deliberate reasoning\",\"description\":\"The language model interprets intent, chooses a goal, plans and decides which tool or action class to invoke.\"},{\"label\":\"3. Action handoff\",\"description\":\"The high-level decision is converted into structured game-side commands.\"},{\"label\":\"4. Reactive execution\",\"description\":\"Behavior trees or other deterministic controllers handle movement, combat, navigation and reflex-level reactions.\"},{\"label\":\"5. Re-observation\",\"description\":\"The agent reads the changed game state and updates its plan when the world no longer matches the previous assumptions.\"}]},\"tunes\":{}},{\"id\":\"system-table\",\"type\":\"comparison\",\"data\":{\"title\":\"System 1 vs System 2 in a game agent\",\"layout\":\"table\",\"columns\":[{\"id\":\"system1\",\"label\":\"Fast reactive layer\"},{\"id\":\"system2\",\"label\":\"Deliberate reasoning layer\"}],\"rows\":[{\"id\":\"timescale\",\"label\":\"Timescale\",\"values\":[\"\",\"\"]},{\"id\":\"tasks\",\"label\":\"Typical tasks\",\"values\":[\"\",\"\"]},{\"id\":\"failure\",\"label\":\"If it is too slow\",\"values\":[\"\",\"\"]},{\"id\":\"control\",\"label\":\"Best control style\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"h-state\",\"type\":\"header\",\"data\":{\"text\":\"Live game state is what makes the model useful\",\"level\":2},\"tunes\":{}},{\"id\":\"p-state-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"The PUBG Ally model does not reason from dialogue alone. NVIDIA says the game engine exposes live match state to the agent through observation tools represented as textual descriptions.\"},\"tunes\":{}},{\"id\":\"p-state-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"That matters because a teammate needs to know what is happening now: what the player said, what items exist nearby, where danger is coming from and whether the previous plan is still valid.\"},\"tunes\":{}},{\"id\":\"p-state-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"This is the same reliability principle that applies to any game assistant: general game knowledge is not enough when the correct action depends on current session state.\"},\"tunes\":{}},{\"id\":\"ref-state\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fyour-game-assistant-knows-the-game-but-does-it-know-your-game-state\",\"title\":\"Your Game Assistant Knows the Game — But Does It Know Your Game State?\",\"excerpt\":\"Why current health, inventory, quest flags, cooldowns and other live state determine whether AI game advice is actually valid.\",\"ctaLabel\":\"Read the game-state guide\"},\"tunes\":{}},{\"id\":\"h-authority\",\"type\":\"header\",\"data\":{\"text\":\"The Action Authority Boundary\",\"level\":2},\"tunes\":{}},{\"id\":\"p-auth-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"A useful real-time game agent needs a clear boundary between what the model may decide and what the game engine may actually execute.\"},\"tunes\":{}},{\"id\":\"p-auth-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"The model can choose a goal such as “move to cover,” “loot ammunition,” “follow the player” or “engage that enemy.” The game-side controller should then translate that intent into legal, bounded actions that obey navigation, animation, cooldowns, physics and game rules.\"},\"tunes\":{}},{\"id\":\"auth-rule\",\"type\":\"callout\",\"data\":{\"variant\":\"success\",\"title\":\"The safety pattern\",\"body\":\"Let the model choose among \u003Cstrong>authorized intentions\u003C\u002Fstrong>. Let the engine execute only \u003Cstrong>validated game actions\u003C\u002Fstrong>.\"},\"tunes\":{}},{\"id\":\"authority-table\",\"type\":\"comparison\",\"data\":{\"title\":\"Good vs dangerous agent control\",\"layout\":\"table\",\"columns\":[{\"id\":\"good\",\"label\":\"Bounded architecture\"},{\"id\":\"bad\",\"label\":\"Unbounded architecture\"}],\"rows\":[{\"id\":\"movement\",\"label\":\"Movement\",\"values\":[\"\",\"\"]},{\"id\":\"combat\",\"label\":\"Combat\",\"values\":[\"\",\"\"]},{\"id\":\"inventory\",\"label\":\"Inventory\",\"values\":[\"\",\"\"]},{\"id\":\"speech\",\"label\":\"Speech\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"h-event\",\"type\":\"header\",\"data\":{\"text\":\"Why event-driven reasoning beats constant language-model polling\",\"level\":2},\"tunes\":{}},{\"id\":\"p-event-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"PUBG Ally's model loop is described as event-driven. It can be triggered by the player speaking or by relevant in-game events.\"},\"tunes\":{}},{\"id\":\"p-event-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"That is more efficient than asking the model to rethink the entire world on every frame. Most frames do not require a strategic decision.\"},\"tunes\":{}},{\"id\":\"p-event-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"A good trigger system calls the language model when semantics matter: a new order arrives, a threat changes the plan, an objective is completed, an item becomes relevant or the current plan fails.\"},\"tunes\":{}},{\"id\":\"h-trigger\",\"type\":\"header\",\"data\":{\"text\":\"The Decision Trigger Filter\",\"level\":2},\"tunes\":{}},{\"id\":\"trigger-flow\",\"type\":\"processFlow\",\"data\":{\"title\":\"When should the language model wake up?\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"Player intent changed\",\"description\":\"A new spoken or textual request requires interpretation.\"},{\"label\":\"Plan invalidated\",\"description\":\"The target disappeared, path failed, item is gone or combat changed the situation.\"},{\"label\":\"High-level milestone reached\",\"description\":\"The character arrived, looted, healed or completed a planned subgoal.\"},{\"label\":\"Important new observation\",\"description\":\"A new threat, resource or strategic opportunity appears.\"},{\"label\":\"Conversation needed\",\"description\":\"The agent should confirm, explain or ask for clarification.\"},{\"label\":\"Otherwise stay reactive\",\"description\":\"Let low-level controllers continue without unnecessary model inference.\"}]},\"tunes\":{}},{\"id\":\"h-local\",\"type\":\"header\",\"data\":{\"text\":\"On-device inference changes the design space\",\"level\":2},\"tunes\":{}},{\"id\":\"p-local-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA ACE is designed around on-device inference as well as cloud options. For PUBG Ally, NVIDIA says the small language model runs locally on the player's GPU.\"},\"tunes\":{}},{\"id\":\"p-local-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"The published architecture uses a 2B-parameter Mistral-NeMo-Minitron model designed to fit into the VRAM headroom remaining after PUBG itself is running.\"},\"tunes\":{}},{\"id\":\"p-local-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"That is a non-trivial constraint. Game AI cannot simply consume all available GPU memory or compute because the graphics workload still has priority.\"},\"tunes\":{}},{\"id\":\"h-contention\",\"type\":\"header\",\"data\":{\"text\":\"AI inference now competes with rendering\",\"level\":2},\"tunes\":{}},{\"id\":\"p-contention-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"This creates a new resource problem for games: graphics and AI inference may share the same GPU.\"},\"tunes\":{}},{\"id\":\"p-contention-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's In-Game Inferencing SDK is designed to schedule local AI models alongside graphics workloads. Its purpose is not only to run models, but to do so without destroying the game's frame-time budget.\"},\"tunes\":{}},{\"id\":\"p-contention-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"That means future performance reviews may need to measure not only DLSS, ray tracing and VRAM use, but also the cost of local NPC inference.\"},\"tunes\":{}},{\"id\":\"h-budget\",\"type\":\"header\",\"data\":{\"text\":\"The Game AI Resource Budget\",\"level\":2},\"tunes\":{}},{\"id\":\"resource-table\",\"type\":\"table\",\"data\":{\"withHeadings\":true,\"stretched\":false,\"content\":[[\"Resource\",\"Graphics needs it for\",\"AI agent needs it for\"],[\"VRAM\",\"Textures, buffers, geometry, ray tracing, frame generation\",\"Model weights, KV cache, embeddings and inference buffers\"],[\"GPU compute\",\"Rasterization, RT, neural graphics\",\"SLM\u002FASR\u002FTTS inference\"],[\"CPU time\",\"Simulation, draw submission, game systems\",\"Agent orchestration, tools, text processing\"],[\"Memory bandwidth\",\"Asset and render workloads\",\"Model execution and data movement\"],[\"Frame-time headroom\",\"Smooth presentation\",\"Low-latency inference without visible stutter\"]]},\"tunes\":{}},{\"id\":\"h-small\",\"type\":\"header\",\"data\":{\"text\":\"Why small models make sense inside games\",\"level\":2},\"tunes\":{}},{\"id\":\"p-small-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"A game agent does not need to know everything on the internet. It needs to understand the game's vocabulary, current state, action tools and a limited set of relevant knowledge.\"},\"tunes\":{}},{\"id\":\"p-small-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"That is why NVIDIA ACE emphasizes small models optimized for gaming hardware. KRAFTON also describes domain adaptation for PUBG Ally: the model was constrained to the Sanhok map and AI Duo context and trained around PUBG-specific concepts and tool use.\"},\"tunes\":{}},{\"id\":\"p-small-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"A smaller specialized model can be more useful than a much larger general model if its world, tools and action boundaries are well defined.\"},\"tunes\":{}},{\"id\":\"h-rag-tools\",\"type\":\"header\",\"data\":{\"text\":\"RAG and tools solve different problems\",\"level\":2},\"tunes\":{}},{\"id\":\"p-rag-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's ACE Game Agent SDK exposes Agent, Chat and RAG APIs. Those are separate capabilities because knowledge retrieval and action execution are not the same thing.\"},\"tunes\":{}},{\"id\":\"p-rag-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"RAG can provide grounded game knowledge such as item rules, faction data or mechanics. Tools expose what the agent can observe or do in the live game.\"},\"tunes\":{}},{\"id\":\"p-rag-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"An agent can retrieve the correct fact and still fail if it has the wrong live state or invokes the wrong action. Knowledge, state and action authority all need separate validation.\"},\"tunes\":{}},{\"id\":\"h-traditional\",\"type\":\"header\",\"data\":{\"text\":\"What traditional NPCs still do better\",\"level\":2},\"tunes\":{}},{\"id\":\"p-trad-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"Language-model agents are not automatically better at every NPC task.\"},\"tunes\":{}},{\"id\":\"p-trad-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Scripted logic is cheaper, easier to test and more predictable when the desired behavior is already known. A door guard who has three fixed states does not need an agentic reasoning loop.\"},\"tunes\":{}},{\"id\":\"p-trad-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"The strongest use cases are situations where natural language, broad planning, contextual adaptation or player-specific coordination create value that static logic struggles to provide.\"},\"tunes\":{}},{\"id\":\"scripted-agentic\",\"type\":\"comparison\",\"data\":{\"title\":\"When to use scripted AI vs agentic AI\",\"layout\":\"table\",\"columns\":[{\"id\":\"scripted\",\"label\":\"Traditional\u002Fscripted AI\"},{\"id\":\"agentic\",\"label\":\"Agentic AI\"}],\"rows\":[{\"id\":\"predictability\",\"label\":\"Predictability\",\"values\":[\"\",\"\"]},{\"id\":\"language\",\"label\":\"Open-ended language\",\"values\":[\"\",\"\"]},{\"id\":\"adaptation\",\"label\":\"Unexpected player intent\",\"values\":[\"\",\"\"]},{\"id\":\"latency\",\"label\":\"Reflex actions\",\"values\":[\"\",\"\"]},{\"id\":\"testing\",\"label\":\"Deterministic QA\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"h-reliability\",\"type\":\"header\",\"data\":{\"text\":\"The Agent Reliability Loop\",\"level\":2},\"tunes\":{}},{\"id\":\"reliability-flow\",\"type\":\"processFlow\",\"data\":{\"title\":\"What should happen before and after every meaningful agent action\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"Observe\",\"description\":\"Read only the current state relevant to the decision.\"},{\"label\":\"Reason\",\"description\":\"Choose a goal or action class from the observed state and player intent.\"},{\"label\":\"Validate\",\"description\":\"Check that the action is legal, available and authorized.\"},{\"label\":\"Execute\",\"description\":\"Hand the intent to deterministic game-side control.\"},{\"label\":\"Confirm\",\"description\":\"Read the resulting game state rather than assuming success.\"},{\"label\":\"Replan\",\"description\":\"If the result differs from expectation, update the plan instead of hallucinating continuity.\"}]},\"tunes\":{}},{\"id\":\"action-warning\",\"type\":\"callout\",\"data\":{\"variant\":\"warning\",\"title\":\"The most dangerous game-agent hallucination\",\"body\":\"It is not only saying a wrong fact. It is \u003Cstrong>believing an action succeeded when the engine says it did not\u003C\u002Fstrong>. Every meaningful action should close with state confirmation.\"},\"tunes\":{}},{\"id\":\"h-speech\",\"type\":\"header\",\"data\":{\"text\":\"Why natural speech makes errors more convincing\",\"level\":2},\"tunes\":{}},{\"id\":\"p-speech-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"ACE can combine automatic speech recognition, language reasoning and text-to-speech so a teammate can hear, act and speak naturally.\"},\"tunes\":{}},{\"id\":\"p-speech-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"That improves immersion, but it also increases the need for grounding. A confident spoken sentence such as “I picked up the med kit” sounds authoritative even if the item interaction failed.\"},\"tunes\":{}},{\"id\":\"p-speech-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"Speech should therefore report confirmed state wherever possible, not merely the model's intended action.\"},\"tunes\":{}},{\"id\":\"h-multilingual\",\"type\":\"header\",\"data\":{\"text\":\"Multilingual game agents are becoming practical\",\"level\":2},\"tunes\":{}},{\"id\":\"p-multi-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA expanded ACE in 2026 with multilingual on-device models for language, speech recognition and speech synthesis.\"},\"tunes\":{}},{\"id\":\"p-multi-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"NVIDIA's May 2026 developer update describes Qwen 3.5 4B support across 201 languages and dialects, Riva Parakeet TDT 600M speech recognition for 25 languages and Chatterbox Multilingual 500M voices across 24 languages.\"},\"tunes\":{}},{\"id\":\"p-multi-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"That broadens the design space for AI companions beyond English-only demos and makes local language interaction a realistic product feature.\"},\"tunes\":{}},{\"id\":\"h-change\",\"type\":\"header\",\"data\":{\"text\":\"What would change this answer?\",\"level\":2},\"tunes\":{}},{\"id\":\"p-change-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"The architecture could become more unified if future models achieve deterministic sub-frame action latency while remaining small enough to run continuously beside graphics workloads. Today, separating reflex control from semantic reasoning remains the more practical design.\"},\"tunes\":{}},{\"id\":\"p-change-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Specialized neural control policies may also replace some traditional behavior-tree functions, but the need for explicit action authority, state validation and fast execution will remain.\"},\"tunes\":{}},{\"id\":\"h-limit\",\"type\":\"header\",\"data\":{\"text\":\"Limitations\",\"level\":2},\"tunes\":{}},{\"id\":\"p-limit-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"PUBG Ally is one implementation, not proof that every game should adopt the same architecture. Different genres have different latency, determinism, hardware and gameplay requirements.\"},\"tunes\":{}},{\"id\":\"p-limit-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"The public architecture details are also primarily provided by NVIDIA and KRAFTON. They are useful for understanding the implemented system but should not be treated as independent performance benchmarking.\"},\"tunes\":{}},{\"id\":\"h-conclusion\",\"type\":\"header\",\"data\":{\"text\":\"Conclusion\",\"level\":2},\"tunes\":{}},{\"id\":\"p-conc-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"The future of game agents is unlikely to be one giant model replacing the game AI stack.\"},\"tunes\":{}},{\"id\":\"p-conc-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"PUBG Ally points toward a hybrid architecture instead: language models interpret intent and make high-level decisions; deterministic controllers execute fast gameplay; live state keeps the model grounded; and the game engine retains authority over what can actually happen.\"},\"tunes\":{}},{\"id\":\"p-conc-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"The winning design is not the agent that thinks about everything. It is the agent that knows what it should think about—and what should stay in the game loop.\"},\"tunes\":{}},{\"id\":\"h-faq\",\"type\":\"header\",\"data\":{\"text\":\"FAQ\",\"level\":2},\"tunes\":{}},{\"id\":\"faq\",\"type\":\"faq\",\"data\":{\"title\":\"AI teammates, NVIDIA ACE and game agents\",\"items\":[{\"id\":\"faq1\",\"question\":\"Does PUBG Ally use one AI model to control everything?\",\"answer\":\"No. KRAFTON's published architecture separates language-model reasoning from fast behavior-tree control for movement and combat.\"},{\"id\":\"faq2\",\"question\":\"Why not let an LLM control movement directly?\",\"answer\":\"Language-model inference is designed for semantic reasoning, not deterministic per-tick motor control. Fast gameplay actions benefit from bounded game-side controllers.\"},{\"id\":\"faq3\",\"question\":\"Does PUBG Ally run in the cloud?\",\"answer\":\"NVIDIA says the core ACE models used by PUBG Ally run locally on the player's GPU, including the small language model.\"},{\"id\":\"faq4\",\"question\":\"How does the AI know what is happening in the match?\",\"answer\":\"The game exposes live state through observation tools, while player voice is transcribed and combined with that state for model reasoning.\"},{\"id\":\"faq5\",\"question\":\"What is the ACE Game Agent SDK?\",\"answer\":\"It is NVIDIA's lightweight C\u002FC++ framework for native in-game agents, exposing Agent, Chat and RAG APIs and designed for on-device integration.\"},{\"id\":\"faq6\",\"question\":\"Will AI agents replace scripted NPCs?\",\"answer\":\"Not everywhere. Scripted AI remains cheaper, deterministic and effective for bounded behaviors. Agentic AI is most useful where language, adaptation and open-ended coordination matter.\"}]},\"tunes\":{}},{\"id\":\"h-glossary\",\"type\":\"header\",\"data\":{\"text\":\"Glossary\",\"level\":2},\"tunes\":{}},{\"id\":\"glossary\",\"type\":\"glossary\",\"data\":{\"title\":\"Key game-agent terms\",\"entries\":[{\"term\":\"System 1 control\",\"definition\":\"Fast reactive game-side logic used for immediate actions such as movement, combat and navigation.\",\"anchor\":\"system-1-control\"},{\"term\":\"System 2 reasoning\",\"definition\":\"Slower deliberate reasoning used for planning, player intent interpretation, coordination and conversation.\",\"anchor\":\"system-2-reasoning\"},{\"term\":\"Two-Speed Game Agent\",\"definition\":\"A Figure Rocks model that separates reflex-level game control from higher-level model reasoning.\",\"anchor\":\"two-speed-game-agent\"},{\"term\":\"Action Authority Boundary\",\"definition\":\"A Figure Rocks concept defining which intentions a model may choose and which legal actions the game engine is allowed to execute.\",\"anchor\":\"action-authority-boundary\"},{\"term\":\"Observation tool\",\"definition\":\"A game-side interface that exposes selected current state to an AI agent in a structured or textual form.\",\"anchor\":\"observation-tool\"},{\"term\":\"Agent harness\",\"definition\":\"The orchestration layer connecting model inference, observations, tools, memory, retrieval and game-side execution.\",\"anchor\":\"agent-harness\"},{\"term\":\"NVIGI\",\"definition\":\"NVIDIA's in-game inferencing framework for running and scheduling local AI models alongside game graphics workloads.\",\"anchor\":\"nvigi\"}]},\"tunes\":{}},{\"id\":\"h-sources\",\"type\":\"header\",\"data\":{\"text\":\"Primary sources\",\"level\":2},\"tunes\":{}},{\"id\":\"src-pubg-deep-dive\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fhow-krafton-built-pubg-ally-a-co-playable-character-powered-by-nvidia-ace\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA Developer — How KRAFTON Built PUBG Ally\",\"description\":\"Official technical deep dive covering the System 1 behavior-tree \u002F System 2 SLM architecture, live game-state observations, on-device inference and domain adaptation.\"}},\"tunes\":{}},{\"id\":\"src-ace-sdk\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdeveloper.nvidia.com\u002Face-for-games\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA Developer — ACE for Games\",\"description\":\"Official ACE overview covering the Game Agent SDK, Agent\u002FChat\u002FRAG APIs, on-device models and autonomous game-character use cases.\"}},\"tunes\":{}},{\"id\":\"src-ace-companions\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fbuild-on-device-ai-companions-with-the-nvidia-ace-game-agent-sdk-and-unreal-engine-5-plugins\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA Developer — Build On-Device AI Companions\",\"description\":\"Official June 2026 article introducing the Game Agent SDK, Unreal Engine plugins and on-device AI companion architecture.\"}},\"tunes\":{}},{\"id\":\"src-pubg-beta\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fwww.nvidia.com\u002Fen-us\u002Fgeforce\u002Fnews\u002Fpubg-ally-ai-teammate-beta-available-now\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA GeForce — PUBG Ally Duo Mode Beta\",\"description\":\"Official article describing PUBG Ally as a collaborative autonomous AI teammate and the evolution of ACE beyond conversational NPCs.\"}},\"tunes\":{}},{\"id\":\"src-multilingual\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdeveloper.nvidia.com\u002Fblog\u002Fwhats-new-for-game-developers-in-nvidia-rtx-dlss-4-5-for-ue5-and-multilingual-ai-characters\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"NVIDIA Developer — Multilingual AI Characters\",\"description\":\"Official May 2026 update describing multilingual on-device ACE models for language, ASR and TTS.\"}},\"tunes\":{}}],\"version\":\"2.31.6\"}",{"time":1267,"blocks":1268,"version":1802},1790376779898,[1269,1273,1278,1283,1287,1291,1295,1299,1303,1307,1311,1315,1319,1323,1343,1365,1369,1373,1377,1381,1388,1392,1396,1400,1405,1427,1431,1435,1439,1443,1447,1470,1474,1478,1482,1486,1490,1494,1498,1502,1506,1533,1537,1541,1545,1549,1553,1557,1561,1565,1569,1573,1577,1581,1606,1610,1633,1638,1642,1646,1650,1654,1658,1662,1666,1670,1674,1678,1682,1686,1690,1694,1698,1702,1706,1710,1713,1736,1740,1763,1767,1774,1781,1788,1795],{"id":541,"data":1270,"type":544,"tunes":1272},{"text":1271},"A language model can talk about a firefight, but it should not be responsible for every movement, aim adjustment and split-second reaction inside one. NVIDIA ACE and KRAFTON's PUBG Ally show why useful AI teammates need more than a single model: fast gameplay control and slower language reasoning are different jobs.",{},{"id":547,"data":1274,"type":552,"tunes":1277},{"body":1275,"title":1276,"variant":551},"\u003Cstrong>The strongest architecture for an AI teammate is not “LLM controls everything.”\u003C\u002Fstrong> PUBG Ally separates fast reactive gameplay from deliberate reasoning. A behavior-tree layer handles reflex-level movement and combat, while a small language model interprets player intent, live game state and higher-level coordination.","Direct answer",{},{"id":555,"data":1279,"type":552,"tunes":1282},{"body":1280,"title":1281,"variant":559},"The Two-Speed Game Agent model and Action Authority Boundary below are practical Figure Rocks frameworks inspired by the architecture publicly described for NVIDIA ACE and PUBG Ally. They are not official NVIDIA or KRAFTON terminology.","The model used in this article",{},{"id":562,"data":1284,"type":566,"tunes":1286},{"title":1285,"maxLevel":565,"minLevel":47},"Contents",{},{"id":569,"data":1288,"type":572,"tunes":1290},{"text":1289,"level":47},"Why one AI model should not run the whole character",{},{"id":575,"data":1292,"type":544,"tunes":1294},{"text":1293},"A modern game character has to solve several problems at radically different timescales.",{},{"id":580,"data":1296,"type":544,"tunes":1298},{"text":1297},"It may need to avoid an obstacle in milliseconds, react to nearby gunfire, follow a player command, decide whether to loot, explain a plan in natural language and remember what the player asked earlier.",{},{"id":585,"data":1300,"type":544,"tunes":1302},{"text":1301},"Trying to force all of that through one language-model loop creates a timing mismatch. The model is good at semantic reasoning and planning, but real-time control often needs deterministic logic that can react every game tick.",{},{"id":590,"data":1304,"type":572,"tunes":1306},{"text":1305,"level":47},"PUBG Ally uses a two-speed architecture",{},{"id":595,"data":1308,"type":544,"tunes":1310},{"text":1309},"KRAFTON describes PUBG Ally as a co-playable AI teammate powered by NVIDIA ACE. The system combines player voice, live match state, a small language model and game-side control logic.",{},{"id":600,"data":1312,"type":544,"tunes":1314},{"text":1313},"According to NVIDIA's technical deep dive, the architecture separates a System 1 behavior tree from a System 2 language model. The behavior tree handles fast reactive gameplay such as movement and combat, while the language model handles deliberate reasoning, communication and coordination.",{},{"id":605,"data":1316,"type":544,"tunes":1318},{"text":1317},"That split is one of the most important design patterns in real-time game AI because it gives each subsystem authority over the work it is actually suited to perform.",{},{"id":610,"data":1320,"type":572,"tunes":1322},{"text":1321,"level":47},"The Two-Speed Game Agent model",{},{"id":615,"data":1324,"type":635,"tunes":1342},{"steps":1325,"title":1341,"orientation":634},[1326,1329,1332,1335,1338],{"label":1327,"description":1328},"1. Perception and observation","The game exposes relevant live state such as position, inventory, threats, nearby objects and player requests.",{"label":1330,"description":1331},"2. Deliberate reasoning","The language model interprets intent, chooses a goal, plans and decides which tool or action class to invoke.",{"label":1333,"description":1334},"3. Action handoff","The high-level decision is converted into structured game-side commands.",{"label":1336,"description":1337},"4. Reactive execution","Behavior trees or other deterministic controllers handle movement, combat, navigation and reflex-level reactions.",{"label":1339,"description":1340},"5. Re-observation","The agent reads the changed game state and updates its plan when the world no longer matches the previous assumptions.","How a practical AI teammate can divide the work",{},{"id":638,"data":1344,"type":666,"tunes":1364},{"rows":1345,"title":1358,"layout":658,"columns":1359},[1346,1349,1352,1355],{"id":642,"label":1347,"values":1348},"Timescale",[13,13],{"id":646,"label":1350,"values":1351},"Typical tasks",[13,13],{"id":650,"label":1353,"values":1354},"If it is too slow",[13,13],{"id":654,"label":1356,"values":1357},"Best control style",[13,13],"System 1 vs System 2 in a game agent",[1360,1362],{"id":661,"label":1361},"Fast reactive layer",{"id":664,"label":1363},"Deliberate reasoning layer",{},{"id":669,"data":1366,"type":572,"tunes":1368},{"text":1367,"level":47},"Live game state is what makes the model useful",{},{"id":674,"data":1370,"type":544,"tunes":1372},{"text":1371},"The PUBG Ally model does not reason from dialogue alone. NVIDIA says the game engine exposes live match state to the agent through observation tools represented as textual descriptions.",{},{"id":679,"data":1374,"type":544,"tunes":1376},{"text":1375},"That matters because a teammate needs to know what is happening now: what the player said, what items exist nearby, where danger is coming from and whether the previous plan is still valid.",{},{"id":684,"data":1378,"type":544,"tunes":1380},{"text":1379},"This is the same reliability principle that applies to any game assistant: general game knowledge is not enough when the correct action depends on current session state.",{},{"id":689,"data":1382,"type":695,"tunes":1387},{"url":1383,"title":1384,"excerpt":1385,"ctaLabel":1386},"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fyour-game-assistant-knows-the-game-but-does-it-know-your-game-state","Your Game Assistant Knows the Game — But Does It Know Your Game State?","Why current health, inventory, quest flags, cooldowns and other live state determine whether AI game advice is actually valid.","Read the game-state guide",{},{"id":698,"data":1389,"type":572,"tunes":1391},{"text":1390,"level":47},"The Action Authority Boundary",{},{"id":703,"data":1393,"type":544,"tunes":1395},{"text":1394},"A useful real-time game agent needs a clear boundary between what the model may decide and what the game engine may actually execute.",{},{"id":708,"data":1397,"type":544,"tunes":1399},{"text":1398},"The model can choose a goal such as “move to cover,” “loot ammunition,” “follow the player” or “engage that enemy.” The game-side controller should then translate that intent into legal, bounded actions that obey navigation, animation, cooldowns, physics and game rules.",{},{"id":713,"data":1401,"type":552,"tunes":1404},{"body":1402,"title":1403,"variant":717},"Let the model choose among \u003Cstrong>authorized intentions\u003C\u002Fstrong>. Let the engine execute only \u003Cstrong>validated game actions\u003C\u002Fstrong>.","The safety pattern",{},{"id":720,"data":1406,"type":666,"tunes":1426},{"rows":1407,"title":1420,"layout":658,"columns":1421},[1408,1411,1414,1417],{"id":724,"label":1409,"values":1410},"Movement",[13,13],{"id":728,"label":1412,"values":1413},"Combat",[13,13],{"id":732,"label":1415,"values":1416},"Inventory",[13,13],{"id":736,"label":1418,"values":1419},"Speech",[13,13],"Good vs dangerous agent control",[1422,1424],{"id":742,"label":1423},"Bounded architecture",{"id":745,"label":1425},"Unbounded architecture",{},{"id":749,"data":1428,"type":572,"tunes":1430},{"text":1429,"level":47},"Why event-driven reasoning beats constant language-model polling",{},{"id":754,"data":1432,"type":544,"tunes":1434},{"text":1433},"PUBG Ally's model loop is described as event-driven. It can be triggered by the player speaking or by relevant in-game events.",{},{"id":759,"data":1436,"type":544,"tunes":1438},{"text":1437},"That is more efficient than asking the model to rethink the entire world on every frame. Most frames do not require a strategic decision.",{},{"id":764,"data":1440,"type":544,"tunes":1442},{"text":1441},"A good trigger system calls the language model when semantics matter: a new order arrives, a threat changes the plan, an objective is completed, an item becomes relevant or the current plan fails.",{},{"id":769,"data":1444,"type":572,"tunes":1446},{"text":1445,"level":47},"The Decision Trigger Filter",{},{"id":774,"data":1448,"type":635,"tunes":1469},{"steps":1449,"title":1468,"orientation":634},[1450,1453,1456,1459,1462,1465],{"label":1451,"description":1452},"Player intent changed","A new spoken or textual request requires interpretation.",{"label":1454,"description":1455},"Plan invalidated","The target disappeared, path failed, item is gone or combat changed the situation.",{"label":1457,"description":1458},"High-level milestone reached","The character arrived, looted, healed or completed a planned subgoal.",{"label":1460,"description":1461},"Important new observation","A new threat, resource or strategic opportunity appears.",{"label":1463,"description":1464},"Conversation needed","The agent should confirm, explain or ask for clarification.",{"label":1466,"description":1467},"Otherwise stay reactive","Let low-level controllers continue without unnecessary model inference.","When should the language model wake up?",{},{"id":798,"data":1471,"type":572,"tunes":1473},{"text":1472,"level":47},"On-device inference changes the design space",{},{"id":803,"data":1475,"type":544,"tunes":1477},{"text":1476},"NVIDIA ACE is designed around on-device inference as well as cloud options. For PUBG Ally, NVIDIA says the small language model runs locally on the player's GPU.",{},{"id":808,"data":1479,"type":544,"tunes":1481},{"text":1480},"The published architecture uses a 2B-parameter Mistral-NeMo-Minitron model designed to fit into the VRAM headroom remaining after PUBG itself is running.",{},{"id":813,"data":1483,"type":544,"tunes":1485},{"text":1484},"That is a non-trivial constraint. Game AI cannot simply consume all available GPU memory or compute because the graphics workload still has priority.",{},{"id":818,"data":1487,"type":572,"tunes":1489},{"text":1488,"level":47},"AI inference now competes with rendering",{},{"id":823,"data":1491,"type":544,"tunes":1493},{"text":1492},"This creates a new resource problem for games: graphics and AI inference may share the same GPU.",{},{"id":828,"data":1495,"type":544,"tunes":1497},{"text":1496},"NVIDIA's In-Game Inferencing SDK is designed to schedule local AI models alongside graphics workloads. Its purpose is not only to run models, but to do so without destroying the game's frame-time budget.",{},{"id":833,"data":1499,"type":544,"tunes":1501},{"text":1500},"That means future performance reviews may need to measure not only DLSS, ray tracing and VRAM use, but also the cost of local NPC inference.",{},{"id":838,"data":1503,"type":572,"tunes":1505},{"text":1504,"level":47},"The Game AI Resource Budget",{},{"id":843,"data":1507,"type":658,"tunes":1532},{"content":1508,"stretched":870,"withHeadings":15},[1509,1513,1516,1520,1524,1528],[1510,1511,1512],"Resource","Graphics needs it for","AI agent needs it for",[851,1514,1515],"Textures, buffers, geometry, ray tracing, frame generation","Model weights, KV cache, embeddings and inference buffers",[1517,1518,1519],"GPU compute","Rasterization, RT, neural graphics","SLM\u002FASR\u002FTTS inference",[1521,1522,1523],"CPU time","Simulation, draw submission, game systems","Agent orchestration, tools, text processing",[1525,1526,1527],"Memory bandwidth","Asset and render workloads","Model execution and data movement",[1529,1530,1531],"Frame-time headroom","Smooth presentation","Low-latency inference without visible stutter",{},{"id":873,"data":1534,"type":572,"tunes":1536},{"text":1535,"level":47},"Why small models make sense inside games",{},{"id":878,"data":1538,"type":544,"tunes":1540},{"text":1539},"A game agent does not need to know everything on the internet. It needs to understand the game's vocabulary, current state, action tools and a limited set of relevant knowledge.",{},{"id":883,"data":1542,"type":544,"tunes":1544},{"text":1543},"That is why NVIDIA ACE emphasizes small models optimized for gaming hardware. KRAFTON also describes domain adaptation for PUBG Ally: the model was constrained to the Sanhok map and AI Duo context and trained around PUBG-specific concepts and tool use.",{},{"id":888,"data":1546,"type":544,"tunes":1548},{"text":1547},"A smaller specialized model can be more useful than a much larger general model if its world, tools and action boundaries are well defined.",{},{"id":893,"data":1550,"type":572,"tunes":1552},{"text":1551,"level":47},"RAG and tools solve different problems",{},{"id":898,"data":1554,"type":544,"tunes":1556},{"text":1555},"NVIDIA's ACE Game Agent SDK exposes Agent, Chat and RAG APIs. Those are separate capabilities because knowledge retrieval and action execution are not the same thing.",{},{"id":903,"data":1558,"type":544,"tunes":1560},{"text":1559},"RAG can provide grounded game knowledge such as item rules, faction data or mechanics. Tools expose what the agent can observe or do in the live game.",{},{"id":908,"data":1562,"type":544,"tunes":1564},{"text":1563},"An agent can retrieve the correct fact and still fail if it has the wrong live state or invokes the wrong action. Knowledge, state and action authority all need separate validation.",{},{"id":913,"data":1566,"type":572,"tunes":1568},{"text":1567,"level":47},"What traditional NPCs still do better",{},{"id":918,"data":1570,"type":544,"tunes":1572},{"text":1571},"Language-model agents are not automatically better at every NPC task.",{},{"id":923,"data":1574,"type":544,"tunes":1576},{"text":1575},"Scripted logic is cheaper, easier to test and more predictable when the desired behavior is already known. A door guard who has three fixed states does not need an agentic reasoning loop.",{},{"id":928,"data":1578,"type":544,"tunes":1580},{"text":1579},"The strongest use cases are situations where natural language, broad planning, contextual adaptation or player-specific coordination create value that static logic struggles to provide.",{},{"id":933,"data":1582,"type":666,"tunes":1605},{"rows":1583,"title":1599,"layout":658,"columns":1600},[1584,1587,1590,1593,1596],{"id":937,"label":1585,"values":1586},"Predictability",[13,13],{"id":941,"label":1588,"values":1589},"Open-ended language",[13,13],{"id":945,"label":1591,"values":1592},"Unexpected player intent",[13,13],{"id":949,"label":1594,"values":1595},"Reflex actions",[13,13],{"id":953,"label":1597,"values":1598},"Deterministic QA",[13,13],"When to use scripted AI vs agentic AI",[1601,1603],{"id":959,"label":1602},"Traditional\u002Fscripted AI",{"id":962,"label":1604},"Agentic AI",{},{"id":966,"data":1607,"type":572,"tunes":1609},{"text":1608,"level":47},"The Agent Reliability Loop",{},{"id":971,"data":1611,"type":635,"tunes":1632},{"steps":1612,"title":1631,"orientation":634},[1613,1616,1619,1622,1625,1628],{"label":1614,"description":1615},"Observe","Read only the current state relevant to the decision.",{"label":1617,"description":1618},"Reason","Choose a goal or action class from the observed state and player intent.",{"label":1620,"description":1621},"Validate","Check that the action is legal, available and authorized.",{"label":1623,"description":1624},"Execute","Hand the intent to deterministic game-side control.",{"label":1626,"description":1627},"Confirm","Read the resulting game state rather than assuming success.",{"label":1629,"description":1630},"Replan","If the result differs from expectation, update the plan instead of hallucinating continuity.","What should happen before and after every meaningful agent action",{},{"id":995,"data":1634,"type":552,"tunes":1637},{"body":1635,"title":1636,"variant":999},"It is not only saying a wrong fact. It is \u003Cstrong>believing an action succeeded when the engine says it did not\u003C\u002Fstrong>. Every meaningful action should close with state confirmation.","The most dangerous game-agent hallucination",{},{"id":1002,"data":1639,"type":572,"tunes":1641},{"text":1640,"level":47},"Why natural speech makes errors more convincing",{},{"id":1007,"data":1643,"type":544,"tunes":1645},{"text":1644},"ACE can combine automatic speech recognition, language reasoning and text-to-speech so a teammate can hear, act and speak naturally.",{},{"id":1012,"data":1647,"type":544,"tunes":1649},{"text":1648},"That improves immersion, but it also increases the need for grounding. A confident spoken sentence such as “I picked up the med kit” sounds authoritative even if the item interaction failed.",{},{"id":1017,"data":1651,"type":544,"tunes":1653},{"text":1652},"Speech should therefore report confirmed state wherever possible, not merely the model's intended action.",{},{"id":1022,"data":1655,"type":572,"tunes":1657},{"text":1656,"level":47},"Multilingual game agents are becoming practical",{},{"id":1027,"data":1659,"type":544,"tunes":1661},{"text":1660},"NVIDIA expanded ACE in 2026 with multilingual on-device models for language, speech recognition and speech synthesis.",{},{"id":1032,"data":1663,"type":544,"tunes":1665},{"text":1664},"NVIDIA's May 2026 developer update describes Qwen 3.5 4B support across 201 languages and dialects, Riva Parakeet TDT 600M speech recognition for 25 languages and Chatterbox Multilingual 500M voices across 24 languages.",{},{"id":1037,"data":1667,"type":544,"tunes":1669},{"text":1668},"That broadens the design space for AI companions beyond English-only demos and makes local language interaction a realistic product feature.",{},{"id":1042,"data":1671,"type":572,"tunes":1673},{"text":1672,"level":47},"What would change this answer?",{},{"id":1047,"data":1675,"type":544,"tunes":1677},{"text":1676},"The architecture could become more unified if future models achieve deterministic sub-frame action latency while remaining small enough to run continuously beside graphics workloads. Today, separating reflex control from semantic reasoning remains the more practical design.",{},{"id":1052,"data":1679,"type":544,"tunes":1681},{"text":1680},"Specialized neural control policies may also replace some traditional behavior-tree functions, but the need for explicit action authority, state validation and fast execution will remain.",{},{"id":1057,"data":1683,"type":572,"tunes":1685},{"text":1684,"level":47},"Limitations",{},{"id":1062,"data":1687,"type":544,"tunes":1689},{"text":1688},"PUBG Ally is one implementation, not proof that every game should adopt the same architecture. Different genres have different latency, determinism, hardware and gameplay requirements.",{},{"id":1067,"data":1691,"type":544,"tunes":1693},{"text":1692},"The public architecture details are also primarily provided by NVIDIA and KRAFTON. They are useful for understanding the implemented system but should not be treated as independent performance benchmarking.",{},{"id":1072,"data":1695,"type":572,"tunes":1697},{"text":1696,"level":47},"Conclusion",{},{"id":1077,"data":1699,"type":544,"tunes":1701},{"text":1700},"The future of game agents is unlikely to be one giant model replacing the game AI stack.",{},{"id":1082,"data":1703,"type":544,"tunes":1705},{"text":1704},"PUBG Ally points toward a hybrid architecture instead: language models interpret intent and make high-level decisions; deterministic controllers execute fast gameplay; live state keeps the model grounded; and the game engine retains authority over what can actually happen.",{},{"id":1087,"data":1707,"type":544,"tunes":1709},{"text":1708},"The winning design is not the agent that thinks about everything. It is the agent that knows what it should think about—and what should stay in the game loop.",{},{"id":1092,"data":1711,"type":572,"tunes":1712},{"text":1094,"level":47},{},{"id":1097,"data":1714,"type":1097,"tunes":1735},{"items":1715,"title":1734},[1716,1719,1722,1725,1728,1731],{"id":1101,"answer":1717,"question":1718},"No. KRAFTON's published architecture separates language-model reasoning from fast behavior-tree control for movement and combat.","Does PUBG Ally use one AI model to control everything?",{"id":1105,"answer":1720,"question":1721},"Language-model inference is designed for semantic reasoning, not deterministic per-tick motor control. Fast gameplay actions benefit from bounded game-side controllers.","Why not let an LLM control movement directly?",{"id":1109,"answer":1723,"question":1724},"NVIDIA says the core ACE models used by PUBG Ally run locally on the player's GPU, including the small language model.","Does PUBG Ally run in the cloud?",{"id":1113,"answer":1726,"question":1727},"The game exposes live state through observation tools, while player voice is transcribed and combined with that state for model reasoning.","How does the AI know what is happening in the match?",{"id":1117,"answer":1729,"question":1730},"It is NVIDIA's lightweight C\u002FC++ framework for native in-game agents, exposing Agent, Chat and RAG APIs and designed for on-device integration.","What is the ACE Game Agent SDK?",{"id":1121,"answer":1732,"question":1733},"Not everywhere. Scripted AI remains cheaper, deterministic and effective for bounded behaviors. Agentic AI is most useful where language, adaptation and open-ended coordination matter.","Will AI agents replace scripted NPCs?","AI teammates, NVIDIA ACE and game agents",{},{"id":1127,"data":1737,"type":572,"tunes":1739},{"text":1738,"level":47},"Glossary",{},{"id":1132,"data":1741,"type":1132,"tunes":1762},{"title":1742,"entries":1743},"Key game-agent terms",[1744,1747,1750,1752,1754,1757,1760],{"term":1745,"anchor":1138,"definition":1746},"System 1 control","Fast reactive game-side logic used for immediate actions such as movement, combat and navigation.",{"term":1748,"anchor":1142,"definition":1749},"System 2 reasoning","Slower deliberate reasoning used for planning, player intent interpretation, coordination and conversation.",{"term":1145,"anchor":1146,"definition":1751},"A Figure Rocks model that separates reflex-level game control from higher-level model reasoning.",{"term":1149,"anchor":1150,"definition":1753},"A Figure Rocks concept defining which intentions a model may choose and which legal actions the game engine is allowed to execute.",{"term":1755,"anchor":1154,"definition":1756},"Observation tool","A game-side interface that exposes selected current state to an AI agent in a structured or textual form.",{"term":1758,"anchor":1158,"definition":1759},"Agent harness","The orchestration layer connecting model inference, observations, tools, memory, retrieval and game-side execution.",{"term":1161,"anchor":1162,"definition":1761},"NVIDIA's in-game inferencing framework for running and scheduling local AI models alongside game graphics workloads.",{},{"id":1166,"data":1764,"type":572,"tunes":1766},{"text":1765,"level":47},"Primary sources",{},{"id":1171,"data":1768,"type":1178,"tunes":1773},{"link":1173,"meta":1769},{"image":1770,"title":1771,"description":1772},{"url":13},"NVIDIA Developer — How KRAFTON Built PUBG Ally","Official technical deep dive covering the System 1 behavior-tree \u002F System 2 SLM architecture, live game-state observations, on-device inference and domain adaptation.",{},{"id":1181,"data":1775,"type":1178,"tunes":1780},{"link":1183,"meta":1776},{"image":1777,"title":1778,"description":1779},{"url":13},"NVIDIA Developer — ACE for Games","Official ACE overview covering the Game Agent SDK, Agent\u002FChat\u002FRAG APIs, on-device models and autonomous game-character use cases.",{},{"id":1190,"data":1782,"type":1178,"tunes":1787},{"link":1192,"meta":1783},{"image":1784,"title":1785,"description":1786},{"url":13},"NVIDIA Developer — Build On-Device AI Companions","Official June 2026 article introducing the Game Agent SDK, Unreal Engine plugins and on-device AI companion architecture.",{},{"id":1199,"data":1789,"type":1178,"tunes":1794},{"link":1201,"meta":1790},{"image":1791,"title":1792,"description":1793},{"url":13},"NVIDIA GeForce — PUBG Ally Duo Mode Beta","Official article describing PUBG Ally as a collaborative autonomous AI teammate and the evolution of ACE beyond conversational NPCs.",{},{"id":1208,"data":1796,"type":1178,"tunes":1801},{"link":1210,"meta":1797},{"image":1798,"title":1799,"description":1800},{"url":13},"NVIDIA Developer — Multilingual AI Characters","Official May 2026 update describing multilingual on-device ACE models for language, ASR and TTS.",{},"2.31.6","A language model can understand tactics and player intent, but it should not control every movement and combat reaction directly. PUBG Ally shows a more practical architecture: fast behavior-tree control for reflex actions, combined with a small language model for planning, coordination and natural conversation.",{"lang":7,"title":534,"content":536,"contentJson":1805,"excerpt":1217},{"time":538,"blocks":1806,"version":1216},[1807,1810,1813,1816,1819,1822,1825,1828,1831,1834,1837,1840,1843,1846,1855,1870,1873,1876,1879,1882,1885,1888,1891,1894,1897,1912,1915,1918,1921,1924,1927,1937,1940,1943,1946,1949,1952,1955,1958,1961,1964,1974,1977,1980,1983,1986,1989,1992,1995,1998,2001,2004,2007,2010,2027,2030,2040,2043,2046,2049,2052,2055,2058,2061,2064,2067,2070,2073,2076,2079,2082,2085,2088,2091,2094,2097,2100,2110,2113,2124,2127,2132,2137,2142,2147],{"id":541,"data":1808,"type":544,"tunes":1809},{"text":543},{},{"id":547,"data":1811,"type":552,"tunes":1812},{"body":549,"title":550,"variant":551},{},{"id":555,"data":1814,"type":552,"tunes":1815},{"body":557,"title":558,"variant":559},{},{"id":562,"data":1817,"type":566,"tunes":1818},{"title":564,"maxLevel":565,"minLevel":47},{},{"id":569,"data":1820,"type":572,"tunes":1821},{"text":571,"level":47},{},{"id":575,"data":1823,"type":544,"tunes":1824},{"text":577},{},{"id":580,"data":1826,"type":544,"tunes":1827},{"text":582},{},{"id":585,"data":1829,"type":544,"tunes":1830},{"text":587},{},{"id":590,"data":1832,"type":572,"tunes":1833},{"text":592,"level":47},{},{"id":595,"data":1835,"type":544,"tunes":1836},{"text":597},{},{"id":600,"data":1838,"type":544,"tunes":1839},{"text":602},{},{"id":605,"data":1841,"type":544,"tunes":1842},{"text":607},{},{"id":610,"data":1844,"type":572,"tunes":1845},{"text":612,"level":47},{},{"id":615,"data":1847,"type":635,"tunes":1854},{"steps":1848,"title":633,"orientation":634},[1849,1850,1851,1852,1853],{"label":619,"description":620},{"label":622,"description":623},{"label":625,"description":626},{"label":628,"description":629},{"label":631,"description":632},{},{"id":638,"data":1856,"type":666,"tunes":1869},{"rows":1857,"title":657,"layout":658,"columns":1866},[1858,1860,1862,1864],{"id":642,"label":643,"values":1859},[13,13],{"id":646,"label":647,"values":1861},[13,13],{"id":650,"label":651,"values":1863},[13,13],{"id":654,"label":655,"values":1865},[13,13],[1867,1868],{"id":661,"label":662},{"id":664,"label":665},{},{"id":669,"data":1871,"type":572,"tunes":1872},{"text":671,"level":47},{},{"id":674,"data":1874,"type":544,"tunes":1875},{"text":676},{},{"id":679,"data":1877,"type":544,"tunes":1878},{"text":681},{},{"id":684,"data":1880,"type":544,"tunes":1881},{"text":686},{},{"id":689,"data":1883,"type":695,"tunes":1884},{"url":691,"title":692,"excerpt":693,"ctaLabel":694},{},{"id":698,"data":1886,"type":572,"tunes":1887},{"text":700,"level":47},{},{"id":703,"data":1889,"type":544,"tunes":1890},{"text":705},{},{"id":708,"data":1892,"type":544,"tunes":1893},{"text":710},{},{"id":713,"data":1895,"type":552,"tunes":1896},{"body":715,"title":716,"variant":717},{},{"id":720,"data":1898,"type":666,"tunes":1911},{"rows":1899,"title":739,"layout":658,"columns":1908},[1900,1902,1904,1906],{"id":724,"label":725,"values":1901},[13,13],{"id":728,"label":729,"values":1903},[13,13],{"id":732,"label":733,"values":1905},[13,13],{"id":736,"label":737,"values":1907},[13,13],[1909,1910],{"id":742,"label":743},{"id":745,"label":746},{},{"id":749,"data":1913,"type":572,"tunes":1914},{"text":751,"level":47},{},{"id":754,"data":1916,"type":544,"tunes":1917},{"text":756},{},{"id":759,"data":1919,"type":544,"tunes":1920},{"text":761},{},{"id":764,"data":1922,"type":544,"tunes":1923},{"text":766},{},{"id":769,"data":1925,"type":572,"tunes":1926},{"text":771,"level":47},{},{"id":774,"data":1928,"type":635,"tunes":1936},{"steps":1929,"title":795,"orientation":634},[1930,1931,1932,1933,1934,1935],{"label":778,"description":779},{"label":781,"description":782},{"label":784,"description":785},{"label":787,"description":788},{"label":790,"description":791},{"label":793,"description":794},{},{"id":798,"data":1938,"type":572,"tunes":1939},{"text":800,"level":47},{},{"id":803,"data":1941,"type":544,"tunes":1942},{"text":805},{},{"id":808,"data":1944,"type":544,"tunes":1945},{"text":810},{},{"id":813,"data":1947,"type":544,"tunes":1948},{"text":815},{},{"id":818,"data":1950,"type":572,"tunes":1951},{"text":820,"level":47},{},{"id":823,"data":1953,"type":544,"tunes":1954},{"text":825},{},{"id":828,"data":1956,"type":544,"tunes":1957},{"text":830},{},{"id":833,"data":1959,"type":544,"tunes":1960},{"text":835},{},{"id":838,"data":1962,"type":572,"tunes":1963},{"text":840,"level":47},{},{"id":843,"data":1965,"type":658,"tunes":1973},{"content":1966,"stretched":870,"withHeadings":15},[1967,1968,1969,1970,1971,1972],[847,848,849],[851,852,853],[855,856,857],[859,860,861],[863,864,865],[867,868,869],{},{"id":873,"data":1975,"type":572,"tunes":1976},{"text":875,"level":47},{},{"id":878,"data":1978,"type":544,"tunes":1979},{"text":880},{},{"id":883,"data":1981,"type":544,"tunes":1982},{"text":885},{},{"id":888,"data":1984,"type":544,"tunes":1985},{"text":890},{},{"id":893,"data":1987,"type":572,"tunes":1988},{"text":895,"level":47},{},{"id":898,"data":1990,"type":544,"tunes":1991},{"text":900},{},{"id":903,"data":1993,"type":544,"tunes":1994},{"text":905},{},{"id":908,"data":1996,"type":544,"tunes":1997},{"text":910},{},{"id":913,"data":1999,"type":572,"tunes":2000},{"text":915,"level":47},{},{"id":918,"data":2002,"type":544,"tunes":2003},{"text":920},{},{"id":923,"data":2005,"type":544,"tunes":2006},{"text":925},{},{"id":928,"data":2008,"type":544,"tunes":2009},{"text":930},{},{"id":933,"data":2011,"type":666,"tunes":2026},{"rows":2012,"title":956,"layout":658,"columns":2023},[2013,2015,2017,2019,2021],{"id":937,"label":938,"values":2014},[13,13],{"id":941,"label":942,"values":2016},[13,13],{"id":945,"label":946,"values":2018},[13,13],{"id":949,"label":950,"values":2020},[13,13],{"id":953,"label":954,"values":2022},[13,13],[2024,2025],{"id":959,"label":960},{"id":962,"label":963},{},{"id":966,"data":2028,"type":572,"tunes":2029},{"text":968,"level":47},{},{"id":971,"data":2031,"type":635,"tunes":2039},{"steps":2032,"title":992,"orientation":634},[2033,2034,2035,2036,2037,2038],{"label":975,"description":976},{"label":978,"description":979},{"label":981,"description":982},{"label":984,"description":985},{"label":987,"description":988},{"label":990,"description":991},{},{"id":995,"data":2041,"type":552,"tunes":2042},{"body":997,"title":998,"variant":999},{},{"id":1002,"data":2044,"type":572,"tunes":2045},{"text":1004,"level":47},{},{"id":1007,"data":2047,"type":544,"tunes":2048},{"text":1009},{},{"id":1012,"data":2050,"type":544,"tunes":2051},{"text":1014},{},{"id":1017,"data":2053,"type":544,"tunes":2054},{"text":1019},{},{"id":1022,"data":2056,"type":572,"tunes":2057},{"text":1024,"level":47},{},{"id":1027,"data":2059,"type":544,"tunes":2060},{"text":1029},{},{"id":1032,"data":2062,"type":544,"tunes":2063},{"text":1034},{},{"id":1037,"data":2065,"type":544,"tunes":2066},{"text":1039},{},{"id":1042,"data":2068,"type":572,"tunes":2069},{"text":1044,"level":47},{},{"id":1047,"data":2071,"type":544,"tunes":2072},{"text":1049},{},{"id":1052,"data":2074,"type":544,"tunes":2075},{"text":1054},{},{"id":1057,"data":2077,"type":572,"tunes":2078},{"text":1059,"level":47},{},{"id":1062,"data":2080,"type":544,"tunes":2081},{"text":1064},{},{"id":1067,"data":2083,"type":544,"tunes":2084},{"text":1069},{},{"id":1072,"data":2086,"type":572,"tunes":2087},{"text":1074,"level":47},{},{"id":1077,"data":2089,"type":544,"tunes":2090},{"text":1079},{},{"id":1082,"data":2092,"type":544,"tunes":2093},{"text":1084},{},{"id":1087,"data":2095,"type":544,"tunes":2096},{"text":1089},{},{"id":1092,"data":2098,"type":572,"tunes":2099},{"text":1094,"level":47},{},{"id":1097,"data":2101,"type":1097,"tunes":2109},{"items":2102,"title":1124},[2103,2104,2105,2106,2107,2108],{"id":1101,"answer":1102,"question":1103},{"id":1105,"answer":1106,"question":1107},{"id":1109,"answer":1110,"question":1111},{"id":1113,"answer":1114,"question":1115},{"id":1117,"answer":1118,"question":1119},{"id":1121,"answer":1122,"question":1123},{},{"id":1127,"data":2111,"type":572,"tunes":2112},{"text":1129,"level":47},{},{"id":1132,"data":2114,"type":1132,"tunes":2123},{"title":1134,"entries":2115},[2116,2117,2118,2119,2120,2121,2122],{"term":1137,"anchor":1138,"definition":1139},{"term":1141,"anchor":1142,"definition":1143},{"term":1145,"anchor":1146,"definition":1147},{"term":1149,"anchor":1150,"definition":1151},{"term":1153,"anchor":1154,"definition":1155},{"term":1157,"anchor":1158,"definition":1159},{"term":1161,"anchor":1162,"definition":1163},{},{"id":1166,"data":2125,"type":572,"tunes":2126},{"text":1168,"level":47},{},{"id":1171,"data":2128,"type":1178,"tunes":2131},{"link":1173,"meta":2129},{"image":2130,"title":1176,"description":1177},{"url":13},{},{"id":1181,"data":2133,"type":1178,"tunes":2136},{"link":1183,"meta":2134},{"image":2135,"title":1186,"description":1187},{"url":13},{},{"id":1190,"data":2138,"type":1178,"tunes":2141},{"link":1192,"meta":2139},{"image":2140,"title":1195,"description":1196},{"url":13},{},{"id":1199,"data":2143,"type":1178,"tunes":2146},{"link":1201,"meta":2144},{"image":2145,"title":1204,"description":1205},{"url":13},{},{"id":1208,"data":2148,"type":1178,"tunes":2151},{"link":1210,"meta":2149},{"image":2150,"title":1213,"description":1214},{"url":13},{},"Post erfolgreich abgerufen",{"items":2154,"source":2228,"manualIds":2229,"manualMatchedIds":2230},[2155,2161,2167,2173,2179,2185,2192,2198,2204,2210,2216,2222],{"id":2156,"slug":2157,"title":2158,"excerpt":2159,"featuredImage":14,"publishedAt":2160},"421","kicks","Kicks","Das Schubert-amiibo gehört zur Animal Crossing amiibo-Figurenserie, die während des frühen Ausbaus von Nintendos NFC-Figuren-Ökosystem veröffentlicht wurde. Wie die anderen Charaktere in dieser Serie fungiert die Figur als physischer Schlüssel, der sich über NFC mit kompatiblen Nintendo-Spielen verbindet. Beim Scannen verknüpft das amiibo den Charakter Schubert mit verschiedenen In-Game-Systemen. Der praktische Nutzen ist einfach: Er ermöglicht Spielern den Zugriff auf charakterspezifische Interaktionen, kleine Freischaltungen oder thematische Inhalte, abhängig vom unterstützten Titel.","2026-03-06T15:31:00.000Z",{"id":2162,"slug":2163,"title":2164,"excerpt":2165,"featuredImage":14,"publishedAt":2166},"376","incineroar-79","Incineroar - Nummer 79","Das Incineroar-Amiibo aus der Super Smash Bros.-Serie stellt das von Wrestling inspirierte Feuer-Pokémon so dar, wie es in Super Smash Bros. Ultimate erscheint. Es fungiert als physische NFC-Figur, die Charakterdaten speichern und mit kompatiblen Nintendo-Systemen interagieren kann. Der Mehrwert liegt vor allem in seiner Nutzung als trainierbarer Figure Player (FP) in Super Smash Bros. Ultimate, wo es Verhaltensmuster basierend auf der Interaktion mit dem Spieler entwickelt.","2026-02-22T13:02:00.000Z",{"id":2168,"slug":2169,"title":2170,"excerpt":2171,"featuredImage":14,"publishedAt":2172},"351","r-o-b-famicom-54","R.O.B. (Famicom) - Nummer 54","Das R.O.B. (Famicom-Farben) amiibo ist eine Charakterfigur aus der Super Smash Bros. Serie, die Kämpferdaten speichert und mit kompatiblen Nintendo-Spielen interagiert. Es stellt die rot-weiße Version des Roboters dar, wie er für den japanischen Family Computer veröffentlicht wurde. Dieses amiibo bietet funktionale Vorteile im Spiel und dauerhafte Charakterdaten.","2026-02-20T23:06:00.000Z",{"id":2174,"slug":2175,"title":2176,"excerpt":2177,"featuredImage":14,"publishedAt":2178},"352","roy-55","Roy - Nummer 55","Die Roy-amiibo aus der Super Smash Bros. Serie repräsentiert den Fire Emblem-Charakter Roy in seiner Smash Bros.-Interpretation. Es ist eine NFC-fähige Figur, die Charakterdaten speichert und mit kompatiblen Nintendo-Spielen interagiert. Der Mehrwert liegt in ihrer Doppelrolle: ein physisches Sammlerstück mit detaillierten plastischen Details und ein funktionaler Kämpfer im Spiel, der trainiert, gespeichert und wiederverwendet werden kann.","2026-02-20T22:12:00.000Z",{"id":2180,"slug":2181,"title":2182,"excerpt":2183,"featuredImage":14,"publishedAt":2184},"378","dark-samus-81","Dark Samus - Nummer 81","Das Dark-Samus-amiibo aus der Super-Smash-Bros.-Serie erweitert den spielbaren Kämpfer zu einer physischen Trainings-Einheit. Es ist nicht nur ein Dekorationsobjekt. Es speichert Daten, entwickelt Verhaltensmuster in kompatiblen Titeln und spiegelt die Match-Historie zurück ins Spiel. Sein Mehrwert liegt in dieser Persistenz. Die Figur wird zu einem anpassungsfähigen Gegner statt zu einem statischen Unlock.","2026-02-22T16:16:00.000Z",{"id":2186,"slug":2187,"title":2188,"excerpt":2189,"featuredImage":2190,"publishedAt":2191},"446","directx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","DirectX wird zu einer ML-Plattform: Was lineare Algebra und neuronale Shader für zukünftige Spiele bedeuten","DirectX geht über traditionelle Grafik-Shader hinaus. Microsoft fügt hardwarebeschleunigte lineare Algebra direkt zu HLSL hinzu sowie einen separaten Pfad für größere ML-Modelle, wodurch das Fundament für neuronale Texturen, erlernte Materialien, neuronale Beleuchtung und andere KI-gesteuerte Rendering-Techniken gelegt wird.","\u002Fuploads\u002F2026\u002F09\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games-1790378019857-utigyk.webp","2026-09-25T19:12:00.000Z",{"id":2193,"slug":2194,"title":2195,"excerpt":2196,"featuredImage":14,"publishedAt":2197},"387","alex-89","Alex - Nummer 89","Die Alex-amiibo aus der Super Smash Bros. Collection stellt den Minecraft-Charakter dar, wie er in Super Smash Bros. Ultimate verwendet wird. Es handelt sich um eine NFC-Figur, die mit unterstützten Nintendo-Systemen interagiert. Ihr Mehrwert zeigt sich am deutlichsten dort, wo gespeicherte Daten wiederverwendet werden können.","2026-02-22T17:32:00.000Z",{"id":2199,"slug":2200,"title":2201,"excerpt":2202,"featuredImage":14,"publishedAt":2203},"420","resetti","Resetti","Die Resetti-amiibo gehört zur Animal Crossing-amiibo-Figurenreihe, die während der frühen Expansion von Nintendos NFC-basierten Charakterfiguren veröffentlicht wurde. Wie andere in dieser Serie fungiert die Figur als physische Darstellung eines Charakters, kombiniert mit einem kleinen NFC-Chip, der mit kompatiblen Nintendo-Systemen kommuniziert. Wenn sie gescannt wird, verknüpft die Figur den Charakter Mr. Resetti mit unterstützten Spielen und schaltet kleine Interaktionen oder Charakterauftritte frei, die mit seiner Rolle im Animal Crossing-Universum verbunden sind.","2026-03-06T13:59:00.000Z",{"id":2205,"slug":2206,"title":2207,"excerpt":2208,"featuredImage":14,"publishedAt":2209},"359","bayonetta-player-2-62","Bayonetta – Player 2 – Nummer 62","Die Bayonetta – Player 2 amiibo aus der Super Smash Bros. Serie stellt das alternative Kostüm des Charakters dar, wie es in Super Smash Bros. für Nintendo 3DS und Wii U und später in Super Smash Bros. Ultimate zu sehen ist. Es handelt sich um eine Standard-NFC-Figur mit integriertem Speicher, der von kompatiblen Systemen beschrieben und gelesen werden kann. In der Praxis bedeutet dies, dass die Figur Kämpferdaten und Trainingsfortschritte speichern kann, wenn sie in unterstützten Titeln verwendet wird.","2026-02-20T21:48:00.000Z",{"id":2211,"slug":2212,"title":2213,"excerpt":2214,"featuredImage":14,"publishedAt":2215},"379","richter-82","Richter - Nummer 82","Das Richter-amiibo aus der Super Smash Bros.-Serie repräsentiert den Belmont-Erben, wie er in Super Smash Bros. Ultimate erscheint. Es ist eine funktionale NFC-Figur, die Charakterdaten speichern und mit kompatibler Nintendo-Software interagieren kann. Abseits seiner physischen Präsenz liegt sein praktischer Nutzen in der Fähigkeit, in unterstützten Titeln einen amiibo-Kämpfer (FP) zu erstellen und zu trainieren. Die Figur wurde im Januar 2019 veröffentlicht.","2026-02-22T11:21:00.000Z",{"id":2217,"slug":2218,"title":2219,"excerpt":2220,"featuredImage":14,"publishedAt":2221},"419","celeste","Celeste","Das Celeste-amiibo gehört zur Animal Crossing-amiibo-Figurenreihe, die während der ersten Welle von Figuren veröffentlicht wurde, die dem Animal Crossing-Universum gewidmet sind. Wie andere Figuren in dieser Kollektion fungiert es als kleiner NFC-Träger, der mit Nintendos amiibo-Ökosystem verbunden ist. Beim Scannen verknüpft die Figur den Charakter Celeste mit kompatiblen Spielen. Der Wert des amiibo liegt hauptsächlich darin, Charakterauftritte und kleine Gameplay-Interaktionen zu ermöglichen, die ansonsten nur unter bestimmten Umständen auftreten.","2026-03-06T14:42:00.000Z",{"id":2223,"slug":2224,"title":2225,"excerpt":2226,"featuredImage":14,"publishedAt":2227},"389","kazuya-91","Kazuya - Nummer 91","Der Kazuya-amiibo aus der Super Smash Bros. Collection erweitert die Funktion des Charakters über den Bildschirm hinaus. Er ist kein isoliertes dekoratives Extra. Er speichert Daten, passt sich dem Spielerverhalten an und kehrt mit erlernten Mustern in kompatible Spiele zurück. Im praktischen Einsatz wird er zu einem beständigen Trainingspartner. Der Mehrwert liegt in der Kontinuität. Matches enden nicht einfach; sie summieren sich.","2026-02-22T14:17:00.000Z","fallback",[],[]]