In the AI industry, Together AI recently announced the completion of a $305 million Series B funding round, which has garnered widespread attention. The company's rise is closely related to its newly launched deep reasoning model, DeepSeek-R1. Contrary to initial concerns, many industry experts believe that advancements in deep reasoning have not diminished the demand for infrastructure; rather, they are continuously enhancing this demand. Image source note: Image generated by AI, image licensed from service provider Midjourney since its establishment in 2023.

Today, xAI, led by Elon Musk, officially launched its latest model Grok3, which Musk described as currently the 'smartest AI on Earth.' It will compete with ChatGPT, Gemini, DeepSeek, and Claude. During the launch event, xAI showcased many benchmark tests, revealing that Grok3 outperformed Gemini2Pro, Claude3.5Sonnet, GPT4o, and Dee in mathematical, scientific, and coding benchmarks.

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

Today, the Alibaba Cloud Tongyi team officially released the new mathematical reasoning process reward model Qwen2.5-Math-PRM. This model offers two sizes, 72B and 7B, with performance significantly outperforming similar open-source process reward models, especially excelling in identifying reasoning errors. The 7B version of Qwen2.5-Math-PRM astonishingly surpasses the widely popular GPT-4o, marking an important step in Alibaba Cloud's research and development of reasoning models.

The Alibaba Qwen team recently published a paper titled 'Lessons Learned from the Development of Process Reward Models in Mathematical Reasoning' and introduced two new models in the Qwen2.5-Math-PRM series, featuring 7B and 72B parameters respectively. These models break through the limitations of the existing PRM framework in mathematical reasoning, significantly improving the accuracy and generalization ability of reasoning models through innovative techniques. Mathematical reasoning has long been a major challenge for large language models (LLMs), especially regarding errors in intermediate reasoning steps.

Today, iFlytek officially launched its first deep reasoning large model, the Xunfei Spark Deep Reasoning Model X1, trained on a fully domestic computing power platform. This innovative achievement marks another significant advancement for iFlytek in the field of artificial intelligence. The Xunfei Spark Deep Reasoning Model X1 demonstrates characteristics similar to human 'slow thinking' during problem-solving, while achieving industry-leading results with relatively low computing power, with several key metrics ranking first in the country. Particularly in Chinese mathematical capabilities, this model performs exceptionally well, showcasing strong technical prowess.

At the smart office product upgrade launch conference held on January 7, iFLYTEK announced the upcoming launch of its latest 'iFLYTEK Spark Deep Reasoning Model X1' on January 15. This release is set to infuse more powerful artificial intelligence capabilities into iFLYTEK's smart office products, expected to further expand the application boundaries of smart office solutions. As a leading artificial intelligence company in China, iFLYTEK has been committed to deeply integrating AI technology with office environments. The newly released X1 model aims to enhance the deep reasoning capabilities of intelligent products, enabling them to handle complex tasks.

The Qwen team recently announced the open-source release of their latest multimodal reasoning model, QVQ, marking an important step forward in the capabilities of artificial intelligence in visual understanding and complex problem-solving. This model is based on Qwen2-VL-72B and aims to enhance AI reasoning capabilities by combining language and visual information. In the MMMU evaluation, QVQ achieved a high score of 70.3, demonstrating significant performance improvements over Qwen2-VL-72B-Instruct in several math-related benchmark tests.

On December 18th, at the Volcano Engine FORCE Power Conference, Volcano Engine President Tan Dai unveiled the new Doubao Visual Understanding Model. This model processes both text and image-related information simultaneously, providing more accurate answers. The new model excels in content recognition, understanding, and reasoning capabilities, featuring more nuanced visual description abilities, which brings stronger intelligent processing capabilities to enterprise users. Tan Dai revealed at the conference that the Doubao Visual Understanding Model has achieved significant technological breakthroughs and has also seen a dramatic reduction in pricing.

The Alibaba International AI team has recently released a new reasoning model called Marco-o1, which focuses on solving open-ended questions, extending beyond traditional subjects with standard answers such as programming and mathematics. The research team is dedicated to exploring whether such models can be effectively adapted to fields that are difficult to quantify and lack clear rewards.

The Dark Side of the Moon Kimi Smart Assistant has announced the launch of its next-generation mathematical reasoning model, k0-math. The k0-math model has shown outstanding performance in multiple mathematical benchmark tests, surpassing OpenAI's o1 series models, o1-mini and o1-preview, in four mathematical benchmark assessments including middle school entrance exams, college entrance exams, graduate school entrance exams, and MATH competitions that include introductory problems.