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Abhishek Jambla
Abhishek Jambla

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How Google DeepMind Uses Games to Build Smarter AI Agents

Google DeepMind’s Alexandre Moufarek (Director, Inception team) says games are still the best training ground for AI. The simple version:

What is SIMA 2?

An agent that looks at the screen and uses a normal keyboard and mouse, like a player
Needs no game code or special APIs
Powered by Gemini, so it can reason, explain its plan and chat

How it learns

Starts from human gameplay videos
Then practises alone, with Gemini giving feedback
Understands sketches, emojis and other languages

Why it matters

Task success rose from 31% to 65%
It handled worlds generated by Genie 3 that it had never seen
Game uses: smarter NPCs, AI companions, automated QA testing
Next: an offline EVE Online sandbox to study memory and long-term planning

Limits: still research. It struggles with long multi-step tasks and has short memory.

Media

🖼️ Chart comparing SIMA 1, SIMA 2 and humans on task success: https://lh3.googleusercontent.com/KwuGClFlsydWIS2azo2WjBWkMY-Hm3geOZAad00wP-CMtmWQa8DlpmqOMvXC6QKiPnEUBgtToVWnJ9rzz0O7dTcaVFhYOSggEugNVJBWVgc1hegDfg=w1440 (Image: Google DeepMind)
🎥 Official intro video: https://www.youtube.com/watch?v=Zphax4f6Rls

References & Credits

Google DeepMind – SIMA 2 (SIMA Team)
Google DeepMind – From Atari to EVE Online (Alexandre Moufarek & Adrian Bolton)
AI Magazine – reference article
Decrypt – SIMA 2 coverage (31% vs 65% figures)
MIT Technology Review – SIMA 2 and Gemini
Image and video: Google DeepMind

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