Hacking Diffusion into Qwen3 for the ARC Challenge
Exploring the fundamental tradeoffs between autoregressive and diffusion approaches for ARC solving - an empirical analysis of speed, accuracy, and architectural constraints.
Read more →Startup CTO who scaled ML from prototype to production, with hands-on expertise in federated learning (Google), AutoML (Meta), and generative AI (Comfy Org).
Exploring the fundamental tradeoffs between autoregressive and diffusion approaches for ARC solving - an empirical analysis of speed, accuracy, and architectural constraints.
Read more →We built a life insurance classification bot that matches clients with carriers based on medical conditions. Our initial implementation used what we thought was a temporary solution—letting the LLM pick and read files directly. After implementing a 'proper' RAG system, we discovered our simple approach wasn't just easier to maintain—it performed better. Here's what we learned about the tradeoffs.
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