Oxen.ai Blog
Welcome to the Oxen.ai blog 🐂
The team at Oxen.ai is dedicated to helping AI practictioners go from research to production. To help enable this, we host a research paper club on Fridays called ArXiv Dives, where we go over state of the art research and how you can apply it to your own work.
Take a look at our Arxiv Dives, Practical ML Dives as well as a treasure trove of content on how to go from raw datasets to production ready AI/ML systems. We cover everything from prompt engineering, fine-tuning, computer vision, natural language understanding, generative ai, data engineering, to best practices when versioning your data. So, dive in and explore – we're excited to share our journey and learnings with you 🚀
Last week on Arxiv Dives we dug into research behind DeepSeek-R1, and uncovered that one of the techniques they use in the their training pipeline is called Group Relative Policy O...
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Since the release of DeepSeek-R1, Group Relative Policy Optimization (GRPO) has become the talk of the town for Reinforcement Learning in Large Language Models due to its effective...
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In January 2025, DeepSeek took a shot directly at OpenAI by releasing a suite of models that “Rival OpenAI’s o1.” From their website: In the spirit of Arxiv Dives we are going to...
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DeepSeek-R1 is a big step forward in the open model ecosystem for AI with their latest model competing with OpenAI's o1 on a variety of metrics. There is a lot of hype, and a lot o...
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Today we released oxen v0.25.0 🎉 which comes with a few performance optimizations, including how we traverse the Merkle Tree to find files and folders. The main improvement is how...
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In this post we peel back some of the layers of Oxen.ai’s Merkle Tree and show how we make it suitable for projects with large directories. If you are unfamiliar with Merkle Trees ...
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Intro Merkle Trees are important data structures for ensuring integrity, deduplication, and verification of data at scale. They are used heavily in tools such as Git, Bitcoin, IPF...
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RAGAS is an evaluation framework for Retrieval Augmented Generation (RAG). A paper released by Exploding Gradients, AMPLYFI, and CardiffNLP. RAGAS gives us a suite of metrics that ...
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Data is often seen as static. It's common to just dump your data into S3 buckets in tarballs or upload to Hugging Face and leave it at that. Yet nowadays, data needs to evolve and ...
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Welcome to the last arXiv Dive of 2024! Every other week we have been diving into interesting research papers in AI/ML. In this blog we’ll be diving into Open Coder, a paper and co...
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