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Rahul Agarwal

Founder | Agentic AI... • 1m

What if your AI could run experiments while you sleep? Andrej Karpathy released a project that feels like a peek into the future of ML research. It lets an agent manage model experiments autonomously. Here’s the flow: The agent edits train.py. It trains for a fixed five-minute window. Checks if validation improves. Keeps or discards changes. Repeats hundreds of times overnight. The twist? You don’t write most of the Python. You define program.md, instructions and goals. The agent handles the execution. Why it matters: Experiment iteration speeds up dramatically. Logs are cleaner and more organized. Overnight compute is fully utilized. Your role shifts from coder to research orchestrator. It’s practical. Not just theoretical. A tangible step toward autonomous ML workflows. Still early days. But already useful for anyone tweaking models or tuning parameters. You can jump in, test features, and contribute PRs. This approach shows how AI can amplify human research. Less repetitive coding. More creative orchestration. It’s an exciting glimpse of how ML loops might operate in the near future. Check it out: https://github.com/karpathy/autoresearch

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