machine learning - Distributed Thoughts

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machine learning

A collection of 3 posts

The Loop Is Only as Good as the Metric

The Loop Is Only as Good as the Metric

On Thursday I wrote about Karpathy's autoresearch, the 630-line training loop that runs 100 ML experiments overnight on a single GPU while you sleep. The post generated a lot of conversation, and most of it centered on the automation: agents doing research, models training themselves, the future of

The Model Is the Byproduct

The Model Is the Byproduct

Last Friday, Andrej Karpathy open-sourced a 630-line Python script and went to bed. By morning, an AI agent running on a single GPU had completed roughly 100 complete LLM training runs, each lasting exactly five minutes, autonomously modifying the neural network architecture, the optimizer, the hyperparameters, evaluating the results, keeping

From Kubeflow to Real-World ML: Why Data Locality Matters Just as Much as Compute

From Kubeflow to Real-World ML: Why Data Locality Matters More Than Compute When my co-founders, Jeremy Lewi, Vishnu Kannan, and I started Kubeflow back in 2017, we were trying to solve what felt like the biggest problem in machine learning. Brilliant data scientists would craft elegant models on their laptops,