Showing: 1 - 10 of 29 RESULTS
On‑Device Generative Agents for Lifelike NPCs
About the talk
Developers are starting embrace generative AI to elevate NPC believability, but current cloud‑based agent frameworks are far too costly and slow for real‑time integration. In this session, you’ll learn how Atelico’s Generative Agents Realtime Playground (GARP) leverages proprietary small LLMs, cognitive memory architecture, and hot‑swappable adapters to run lifelike, emergent NPC behavior directly on consumer hardware with zero inference cost and no rate‑limits. We’ll walk through our end‑to‑end pipeline:
– Game‑object serialization & prompt templating
– Memory DB design (working vs. long‑term memory, retrieval, reflection)
– Adapter‑based fine‑tuning for character, planning & chat
– Performance optimizations (quantized models, parallel LM calls, caching, guardrails)
You’ll come away with actionable guidelines for implementing LLMs in your game, architecting cognitive agents, and designing player interactions that nudge emergent narratives, all without breaking the bank.
Takeaway
– AI Engine Architecture: How to orchestrate LLMs, memory and adapters for real‑time agents
– Implementation Patterns: Prompt templating, JSON serialization, parallel calls & safety guardrails
– Performance Strategies: Quantized small models, LoRA swapping, prefix caching, batching
– Design Best‑Practices: Balancing autonomy vs. authorial control, chat‑driven nudging, emergent behavior design
– Integration Guidelines: Godot plugin workflows, data pipelines & dev tooling All these are lessons learned implementing GARP and our first, yet unannounced, game.
Experience level needed: Intermediate
Use Cases and Practical Methodologies for Reinforcement Learning for Learning at Agents at Scale
About the talk
As games continue to build diverse and dynamic gaming experiences there is constant pressure to be able to iterate quickly, adjust NPC behavior and create more and more dynamic content. Within this context, in this session, we will:
– Explore Use Cases: The wide variety of ways that these reinforcement learning techniques can be applied in games of all kinds
– Discuss: Telemetry and player data collection methodologies as input to some of these models
– Demo: See how Databricks can help you scale: Experience data generation, efficient training on CPU and GPU, experimentation with managed MLFlow, deployment of models and governance of assets, usage and monitoring of training workflows
– Explain How: To enable this dynamism for your future titles
You will leave this session with new ideas on how this might apply: ones that are feasible today and aspirational, more challenging, use cases for the future.
How to bully AI into delivering meaningful gameplay
About the talk
Generative AI has the potential to deliver radical new gameplay experiences – featuring emergent stories, unshackled characters, and unprecedented player agency.
But it won’t do it without a fight.
Left to its own devices, Generative AI will happily churn out incoherent, soulless slop. A million miles from game-ready quality. And no – contrary to popular belief – you cannot fine-tune and prompt your way out of the problem. So stop trusting the model, and start bullying it.
This talk draws on seven years of R&D in the AI gameplay space – culminating in the development of our game Dead Meat. It argues that developers are not going far enough in their efforts to wrangle AI – and advocates for the adoption of an additional “bully layer” that forces AI to deliver to a human authorial vision.
We’ll give a behind the scenes peek at what “bullying” AI means in practice – combining real-time “direction”, dynamic context control, and intelligent quest systems to generate meaningful AI-powered gameplay. This will include real-world examples from our own game Dead Meat, as well as a number of our other key demos.
Because, as we know from experience, GenAI is not magic: it is a deeply flawed technology. But, if you get it its face and bully the hell out of it to do what you want, when you want, it CAN create experiences that feel magic.
Takeaway
– Stop putting your faith in AI’s ability to semi – autonomously – create good gameplay experiences. Left to its own devices, AI WILL create slop.
– Stop believing that prompting and fine – tuning can save you from AI slop. Despite the near – universal emphasis of these methods, they cannot deliver game – ready quality.
– Start BULLYING AI into doing what you want. Additional technologies are needed to force AI to create something good, because it sure as hell won’t do it on its own accord.
– Start adopting a “bully” layer that intelligently manages character direction and conversational quests in real – time – based on game consciousness, player desires, and authorial intention.
– GenAI is not magic: it is a deeply flawed technology. But, if you get it its face and bully the hell out of it to do what you want, when you want, it CAN create experiences that feel magic.
Experience level needed: Beginner, Intermediate, Advanced
Good Enough AI: Pragmatic Approaches for Crafting Compelling Player Experiences in Games
About the talk
“Good Enough” AI: Pragmatic Approaches for Crafting Compelling Player Experiences in AAA Games, will cover the practicalities of building effective AI within the demands of large-scale game development. Drawing on my time as a Senior AI Programmer on Cyberpunk 2077’s vehicle AI, I’ll explain how we developed systems from scratch using Behavior Trees and implemented editor tools to support content creators. I’ll illustrate how these sensible strategies enabled a variety of engaging vehicle interactions across numerous quests and open-world scenarios, including the Delamain questline. The aim is to show that truly effective game AI often comes down to prioritizing player experience and efficient development over sheer algorithmic complexity.
Takeaway
– Empowering Content Creators Through Tooling
– Connecting AI to Creative Vision
– Lessons from the AAA Trenches
– Practical Strategies for Impactful AI in games
Experience level needed: Beginner, Intermediate
The Living World AI Recipe Book: Practical Insights for Ambient Character Simulation
About the talk
Ambient characters breathe life into open world games, enhancing immersion and forging emotional connections with players through subtle environmental storytelling. Yet, the systems driving these characters often receive less attention than core gameplay mechanics like combat or stealth. This talk tackles the challenge of creating believable and engaging ambient character simulations without reinventing the wheel.
We’ll delve into a practical toolkit of proven, scalable, and maintainable techniques that prioritize performance and minimize production risks. Whether you’re approaching ambient character simulation for the first time, or an experienced developer seeking to broaden their knowledge and adopt industry best practices, this session provides effective solutions and actionable insights you can implement immediately.
Takeaway
– Learn to effectively advocate for strategic investment in living world AI by understanding its impact on player engagement, environmental storytelling, and overall business value.
– Know how to implement an ambient character simulation in a way that is scalable, maintainable and minimizes production risks through a collection of tried and tested techniques and best practices.
– Understand what problem each of the presented techniques is trying to solve, and how to critically evaluate when it makes sense for your game project.
Experience level needed: Beginner
Elevating Mobile Game Experiences With On-Device ML Inference
About the talk
In this talk, we’ll explore how mobile developers can harness on-device ML for a variety of use cases. We’ll discuss practical approaches to running language models and other inference workloads locally to power features like dynamic dialogue, NPC behaviors, and adaptive systems. We’ll also show how neural graphics can enhance rendering and visual fidelity while reducing performance costs.