open-r1 VS DeepSeek-R1

https://github.com/huggingface/open-r1

DeepSeek, known for its high-performance AI models like R1 and V3, has been a game-changer in the AI landscape. However, recent reports have highlighted issues with API instability, affecting developers and users who rely on these services. Understanding the root causes of this instability is essential for addressing and mitigating these issues.

We kind-of have that in DeepSeek-R1-zero [1], but it has problem. From the original authors:

> With RL, DeepSeek-R1-Zero naturally emerged with numerous powerful and interesting reasoning behaviors. However, DeepSeek-R1-Zero encounters challenges such as endless repetition, poor readability, and language mixing.

A lot of these we can probably solve, but as other have pointed out we want a model that humans can converse with, not an AI for the purpose of other AI.

That said, it seems like a promising area of research:

> DeepSeek-R1-Zero demonstrates capabilities such as self-verification, reflection, and generating long CoTs, marking a significant milestone for the research community.

[1] https://github.com/deepseek-ai/DeepSeek-R1

Thank you for reading the blog. Here is the DeepSeek R1's Research Paper in case you want to check it out.

deepseek-ai/DeepSeek-R1

Benchmarks of reasoning models. Source

For R1-Zero, the RL process focused on accuracy and making sure that thinking was inside the correct tags, but it did not enforce any particular structure on the thinking itself. [1]

The pure RL approach improved reasoning, but had readability issues that led to using SFT thinking data in the final version of R1:

> DeepSeek-R1-Zero struggles with challenges like poor readability, and language mixing. To make reasoning processes more readable and share them with the open community, we explore DeepSeek-R1, a method that utilizes RL with human-friendly cold-start data.

[1] https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSee...

If that weren't enough, they've published the code as Open Source. Transparent. Ready to be studied, modified, and improved by anyone (Including competitors).

Access the Repository: Visit the DeepSeek R1 GitHub repository to explore the model's codebase.

In recent years, artificial intelligence and machine learning have revolutionized how we approach complex problems across various domains, from natural language processing to computer vision. In this context, tools like DeepSeek R1 have stood out for their ability to deliver efficient and high-performance solutions to challenging tasks that other models struggle with.