Google DeepMind teams up with EVE Online maker to test AI that plays like a person
The lab behind AlphaGo wants game characters that actually understand what's happening on screen. Its new partner? The studio running a 22-year-old space universe.
Key points
- Google DeepMind announced a new research partnership with Fenris Creations, the independent studio behind space game EVE Online, which launched in 2003.
- The lab's game-playing agent SIMA 2, built on its Gemini AI models, can follow spoken instructions and play titles like No Man's Sky and Valheim using only a keyboard and mouse.
- DeepMind's 2015 Deep Q-Network learned 49 Atari games from raw pixels, and AlphaGo beat world champion Lee Sedol in 2016.
- The same game-research foundations later fed into AlphaFold, which won the 2024 Nobel Prize in Chemistry for predicting protein structures.
- EVE Online's continuously running universe is being used to test AI skills like long-term memory and planning across weeks or months.
Google DeepMind, the AI lab inside Google that built AlphaGo, has announced a new research partnership with Fenris Creations, the studio behind the long-running space game EVE Online.
The pitch is simple. DeepMind wants to build AI characters that behave less like scripted robots and more like curious players. Fenris has a 22-year-old online universe full of real humans doing real strategy. Put them together, and you get a giant sandbox for testing smarter AI.
What is DeepMind actually building?
The headline project is called SIMA 2, short for Scalable Instructable Multiworld Agent. It is a generalist gaming agent, meaning one piece of software that can play many different games without being retrained for each one.
Here is the clever part. SIMA 2 does not plug into a game's code. It looks at the screen the way you do, listens to instructions in plain English, and clicks the mouse and taps the keyboard. No special access required.
It runs on Gemini, Google's family of large AI models (the same technology that powers its chatbot). DeepMind says SIMA 2 can already hold a conversation while playing titles including No Man's Sky, Valheim and Hydroneer.
Why partner with a 22-year-old space game?
Because EVE Online is genuinely weird, in a useful way. Launched in 2003, it puts thousands of players into a single shared galaxy that never resets. Alliances form. Wars happen. A player-run economy trades goods across thousands of star systems.
That is exactly the kind of messy, long-running environment where today's AI tends to fall over. DeepMind lists four skills it wants to test there:
| Capability | What it means in plain English |
|---|---|
| Continual learning | Picking up new skills without forgetting old ones |
| Memory | Remembering things for weeks, not just one chat |
| Long-horizon planning | Thinking months ahead, not just the next move |
| Multi-agent dynamics | Cooperating, competing and negotiating with others |
The partnership also covers EVE Vanguard, a first-person shooter set in the same universe, and EVE Frontier, an experimental version where players can reprogram the rules of the world itself.
How did we get here?
Games have been DeepMind's testing ground since day one. A quick tour:
In 2015, the lab's Deep Q-Network learned to play 49 Atari 2600 games, from Pong to Space Invaders, just by staring at the pixels. In 2016, AlphaGo beat world champion Lee Sedol at Go, a game experts thought was a decade away from being cracked. AlphaZero later mastered chess, shogi and Go with a single algorithm. AlphaStar reached Grandmaster level at StarCraft II in 2019.
Those same techniques then jumped out of games entirely. AlphaFold used them to predict the shapes of proteins, work that won the 2024 Nobel Prize in Chemistry.
What does this mean for players?
Nothing tomorrow. This is research, not a product launch, and DeepMind has not promised any of it will ship inside EVE Online.
But the direction of travel is clear. If a generalist agent can drop into an existing game without touching its code, studios could use it two ways. During development, AI testers could hammer a game after every update, catching bugs a human QA team would miss. After launch, non-player characters, the shopkeepers and sidekicks you meet in games, could actually respond to what you do instead of repeating the same three lines.
One practical note on privacy. SIMA agents work by watching the screen, so any future rollout inside a live game would need clear rules about what an AI companion sees and stores about your play. That is worth asking about before you invite one into your save file.
