HeyJaredThe Practical AI Digest
Distilling AI/ML theory into practical insights. One concept at a time. No jargon.
- Indexed episodes, last 90 days
- 5
- Latest publication
- Sep 10, 2026
- Audience
- Checking…
- Earliest in this view
- Jul 16, 2026
Latest episodes
Retrieval-Augmented Generation Is Broken: How to Fix It (opens the original)
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RAG pipelines fail in production for structural reasons. We break down the five failure modes and what Agentic RAG, Self-RAG, and GraphRAG actually fix.
Distillation: How Small Models Eat Big Models for Lunch (opens the original)
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Training a frontier model costs millions. Distilling a capable student from it costs thousands. Knowledge distillation is quietly reorganizing the economics of the entire AI industry.
World Models: When AI Learns Physics Instead of Memorizing Data (opens the original)
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A language model can describe a falling glass. It cannot predict where the water goes. World models close the gap between AI that talks about reality and AI that can act in it.
The Evaluation Crisis: We Do Not Know How Good Our Models Actually Are (opens the original)
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MMLU is saturated. Chatbot Arena is gameable. Public benchmarks leak into training data. The only eval that matters is the one you build yourself, on your data, for your task.
Mixture of Experts at the Edge: Running 30B Parameter Models on Your Laptop (opens the original)
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A 30B parameter model runs on a MacBook because only 3B parameters fire per token. Mixture of Experts splits memory cost from compute cost, and that changes everything about where AI can run.
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