From models to LLMs
An LLM is one kind of ML model — trained on text, predicts the next token. That single trick at scale gets you ChatGPT, and also explains where it breaks.
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Posts on AI engineering, LLM systems, and software development.
An LLM is one kind of ML model — trained on text, predicts the next token. That single trick at scale gets you ChatGPT, and also explains where it breaks.
Training is the expensive one-time event where a model's numbers get tuned. Inference is the cheap repeated use afterwards. The gap in cost is enormous, and it shapes the whole industry.
A model is a file of learned numbers, produced by running an algorithm over data. Both ingredients matter, but bad data beats a good algorithm every time.
Open the AI umbrella. Machine learning is the part that learns from data. Deep learning is ML done with neural networks — and that's where today's models live.