• LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
• LoRA — A cheap way to fine-tune a model by training a small add-on layer instead of changing all of the model's weights.
• fine-tuning — Taking a trained model and training it a bit more on your own examples so it gets better at one specific job.
• open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.

Fine-tuned open-weight models reached GPT-4-level accuracy on Uber's item tagging and search tasks while serving far more traffic, and the post shows the training stack that made that repeatable at scale.

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