Model Releases
Self-improving AI is a big deal! As a first step, I've been exploring how much of the post-training can be automated. Here is a first post o…
Self-improving AI is a big deal! As a first step, I've been exploring how much of the post-training can be automated. Here is a first post on how I am using @FireworksAI_HQ Agent to automate LLM fine-
Self-improving AI is a big deal! As a first step, I've been exploring how much of the post-training can be automated. Here is a first post on how I am using @FireworksAI_HQ Agent to automate LLM fine-tuning itself. Dataset + Skill file included. For the use case, I took inspiration from @karpathy's tweet on LLM Knowledge Bases. I asked Claude Code to interact with Fireworks Agent to fine-tune a small Qwen model to get the right output style to efficiently keep growing my PaperWiki (https://x.com/omarsar0/status/2042286186920550498?s=20). All done via natural language. This is obviously the future of improving AI systems. The next step with the PaperWiki project is how to tune a model to better "know" the data. Harder to do, but if possible, then we have an incredibly powerful system that can recursively self-improve and can be extremely useful for things like knowledge discovery and automating all kinds of research end-to-end. More on this soon. Thanks to the Fireworks team for allowing me to test this early. Super excited about this.
Source: DAIR.AI (X) | 2026-05-20