OpenAI’s o3 Pro: AI That Crushes Games! 🎮

The video starts with a discussion on putting major AIs to the test in gaming rather than traditional benchmarks like tetris, super mario, and sokoban. It explores the challenges and findings of evaluating AI performance in gaming.

The segment discusses previous AI models struggling with Tetris gameplay, leaving gaps and forming lines poorly. It introduces the DeepSeek R1 model and its impact on Tetris gameplay improvements.

This part looks at AIs competing in various games, emphasizing the point system in Claude 4 Opus where each piece put down earns a point before losing the game.

The AI's performance in Super Mario is reviewed, highlighting moments of intelligent gameplay like finding hidden blocks but also instances of reckless actions leading to failure. The superiority of the o3 AI model in defeating Super Mario is mentioned.

The video showcases the OpenAI o3 AI model's capabilities in solving game levels, including planning and strategic thinking. It also mentions the slow movement speed due to the textual representation of games.

The significance of games as benchmarks for AI evaluation is discussed, emphasizing the emergence of planning and strategic thinking in AI models through game training, with specific reference to Sokoban.