Today I’d like to share an article from DeepSeek, titled DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models. This article introduces DeepSeekMath 7B, which is pre-trained on DeepSeek-Coder-Base-v1.5 7B based on a collection of 120B math-related tokens, natural language and code data. The model achieved an astonishing score of 51.7% in competitive-level…
Today we will share DeepSeek R1, Title: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning: Incentivizing the reasoning capability of LLM via reinforcement learning. This paper introduces DeepSeek’s first generation of reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. The DeepSeek-R1-Zero model was trained through large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as an initial step,…
1 Background During the Spring Festival, DeepSeek R1 once again attracted widespread attention, and even the DeepSeek V3 interpretation article we previously wrote was also re-transmitted and discussed a lot. Although there have been many analyses and reproductions of DeepSeek R1, here we have decided to compile some corresponding reading notes. We will use three…
The high cost of using large AI models is a major reason why many AI applications have not yet been implemented and promoted. Choosing extreme performance means huge computing power costs, which leads to high usage costs that ordinary users cannot accept. The competition for large AI models is like a war without smoke. After…
The Google Gemini 2.0 family is finally complete! It dominates the charts as soon as it is released. Amidst the pursuit and blockades of Deepseek, Qwen and o3, Google released three models in one go early this morning: Gemini 2.0 Pro, Gemini 2.0 Flash and Gemini 2.0 Flash-Lite. On the large model LMSYS rankings, Gemini…
Highlights AI Agent reshapes the customer experience Jesse Zhang: How is an Agent actually constructed? Our view is that over time, it will become more and more like a natural language-based Agent because that is how the large language models (LLMs) are trained. In the long term, if you have a super intelligent agent that…
Highlights Competition with DeepSeek is good for the US Cathie Wood: I think it shows that the cost of innovation is falling dramatically, and that this trend has already started. For example, before DeepSeek, the cost of training artificial intelligence fell by 75% per year, and the cost of inference even fell by 85% to…
The story of Gemini 2.0 is accelerating. The Flash Thinking Experimental version in December brought developers a working model with low latency and high performance. Earlier this year, 2.0 Flash Thinking Experimental was updated in the Google AI Studio to further improve performance by combining the speed of Flash with enhanced inference capabilities. Last week,…
Introduction In the rapidly evolving landscape of artificial intelligence, DeepSeek has emerged as a powerful language model. This comprehensive analysis explores the top 17 alternatives to DeepSeek, examining their unique features, capabilities, and use cases. Our research focuses on both international and Chinese platforms that offer DeepSeek integration or similar capabilities. Top Alternatives Analysis 1….
Just now, another domestic model was added to the Big Model Arena list from Ali, Qwen2.5-Max, which surpassed DeepSeek-V3 and ranked seventh in the overall rankings with a total score of 1332. It also surpassed models such as Claude 3.5 Sonnet and Llama 3.1 405B in one fell swoop. In particular, it excels in programming…
