Noam Brown, Head of AI Reasoning Research at OpenAI, recently stated in a panel discussion at NVIDIA's GTC conference that certain forms of reasoning AI models "could have existed 20 years earlier if researchers had known the right approach and algorithms." He pointed out several reasons why this research direction was overlooked. Brown recounted his experience in game AI research at Carnegie Mellon University, including Pluribus, which defeated top human professional poker players. He stated that he helped create...

Tencent Yuanbao is an AI assistant tool supporting Tencent HunYuan (Turbo/T1) and DeepSeek (V3/R1) large language models. Users can utilize its unlimited online search and file parsing capabilities to enhance work and learning efficiency. This update allows users to choose between sharing 'short images' (showing only the answer) or 'long images' (including the detailed reasoning process) when sharing, offering personalized and diverse sharing options.

Recently, AI researchers from Stanford University and the University of Washington successfully trained an AI reasoning model named S1, with a training cost of less than $50 and very low cloud computing credits required. This research was published last Friday, indicating that S1 performs comparably to OpenAI's O1 model and DeepSeek's R1 model in mathematical and programming ability tests. The code and data for S1 have been made publicly available on GitHub for other researchers to use. The research team reported that they drew from a

In today's rapidly advancing era of artificial intelligence (AI), major enterprises are working tirelessly to apply AI technology in production environments in hopes of achieving higher returns on investment. However, despite the availability of various advanced AI models in the market, teams still face numerous challenges during deployment. According to Peter Bendor-Samuel, the CEO of Everest Group, 90% of generative AI pilot projects will struggle to enter the production phase. Additionally, Gartner predicts that by 20

In the field of artificial intelligence, an innovative research from China is gaining widespread attention. Scientists from Tsinghua University and the Shanghai Artificial Intelligence Laboratory have proposed a novel framework called 'Diagram of Thought' (DoT), which is expected to revolutionize our understanding of AI thinking patterns. The core idea of the DoT framework is to mimic the human thought process in solving complex problems. Just like how we continually hypothesize, critique, and revise when tackling difficult problems, ultimately arriving at a conclusion, DoT...

The Google DeepMind team, in collaboration with academic institutions, has developed an innovative method called Generative Reward Model (GenRM) aimed at improving the accuracy and reliability of generative AI in reasoning tasks. GenRM incorporates a validation process into text generation tasks, allowing the model to simultaneously generate and evaluate potential solutions while supporting Chain of Thought (CoT), enhancing the comprehensiveness of the validation process. Compared to traditional methods, GenRM has shown significant advantages in multiple tests, with accuracy improvements ranging from 16% to 64%, particularly in...