Minimax-M1 World’s First Large-Scale Reasoning Model - Thorough Testing
AI Summary
This video reviews the Miniax M1 model, the world’s longest context window AI with a 1 million token input and 80,000 token output capability. The host tests the model by prompting it to generate code for a dynamic tower defense game simulator and strategy optimizer with various gameplay features. Miniax M1 is described as a hybrid attention reasoning model with 456 billion parameters, operating efficiently with only 25% of flops compared to similar models. The video showcases the AI generating the game code, running the game, and demonstrates its reinforcement learning capabilities by solving a complex conditional probability problem. The host discusses the significance of long thinking models for real-world challenges, emphasizing the computational demands and global AI development landscape. The video is sponsored by Camel AI, an open-source multi-agent infrastructure community.