Recently, I noticed that Google DeepMind has developed something quite interesting called SIMA 2. This AI agent's performance in virtual environments truly stands out.

Simply put, SIMA 2's task completion ability has improved significantly from the previous generation, jumping from 31% directly to 65%, which is a very clear progress. What is supporting this improvement? Mainly, it can now understand more complex high-level goals, no longer just executing simple commands, but truly able to collaborate within game environments and apply learned concepts to different scenarios.

Even more impressive, SIMA 2 is powered by Gemini technology, capable of processing text, speech, and image inputs simultaneously, and can even generate tasks to iterate its learning. This means its learning approach has become more proactive and flexible.

Of course, even the most advanced systems have their limits. SIMA 2 still struggles with complex tasks that require multi-step reasoning, and there is room for improvement in visual understanding within 3D environments. But from the perspective of AGI development, this ability to learn and adapt within virtual environments indeed marks an important milestone toward general artificial intelligence.