Inside AI: machine learning and deep learning
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.
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AI Foundations
Posts on AI engineering, LLM systems, and software development.
What makes a model: data and algorithm
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.
How a model learns: training and inference
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.
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.