NAVIAI 2.0, independently developed by the Zhejiang Humanoid Robot Innovation Center, is a humanoid robot that stands 1.65 meters tall, weighs 60 kilograms, boasts 41 degrees of freedom, and has an AI computing power of 275 Tops. It showcases exceptional performance and a highly anthropomorphic design, with the ability to execute smooth and natural movements. It can perform complex tasks such as giving speeches, making tea, and playing chess, demonstrating a very high level of anthropomorphic motion mapping execution ability. At the exhibition, it not only served as the host but also displayed its ability to quickly learn new movements and perform high-precision tasks in industrial settings.

Reddit user @zefman designed an experiment where different language models competed in chess in real-time to interestingly evaluate their performance. GPT-4o stood out in the experiment as the strongest contender, outperforming models like Claude and Gemini. By comparing each model's decision-making process, it was found that they each have unique ways of analyzing the game. The experiment used a uniform prompt to ensure a fair comparison, allowing models 5 chances to re-select when choosing a wrong move. The conclusion is that GPT-4o performs exceptionally well in chess.

OpenAI is considering self-developed AI chips to reduce hardware investment costs and overcome GPU shortages. The self-developed chips are seen as a signal of further independence from Microsoft. OpenAI is exploring the manufacture of consumer-level AI products in collaboration with Jony Ive to develop an 'AI iPhone.' The self-developed chips will help OpenAI achieve control similar to that of the Wintel alliance in the PC era. The ambition behind OpenAI's self-developed chips signifies the start of a new chess game.

Google DeepMind has developed an integrated system AZdb that combines multiple AlphaZero agents into a 'coalition' to enhance AI chess capabilities and improve generalization. The AZdb agents utilize behavioral diversity and response diversity to create unique playing styles, better adapting to different opponents and new situations. Tests show that AZdb solves problems twice as hard, with an ELO rating improvement of 50 points, outperforming the old AlphaZero.