
I'm using AI to learn AI, and I'm publishing the journey as I go. Each episode is a NotebookLM-generated audio overview of a study brief I wrote — Chip Huyen chapters, LeetCode problem walkthroughs, AI Engineering interview topics. Built for myself, useful for anyone studying AI engineering for Google Cloud, Anthropic, OpenAI, or similar roles. Made transparently with NotebookLM (audio) and Claude... more
| Publishes | Daily | Episodes | 45 | Founded | 3 months ago |
|---|---|---|---|---|---|
| Number of Listeners | Categories | TechnologyEducationHow To | |||

Running one token through a language model isn't one big GPU operation. It's hundreds to thousands of tiny ones, and each of those has to be launched by the CPU first. During decode, those little operations finish so fast the GPU starves waiting for ... more
The single idea the entire craft rests on is this: the model is a commodity, and the system around it is the job. A raw frontier model is a brilliant intern with amnesia, no hands, and no way to check its own work. The AI engineer gives it hands thro... more
Scaled dot-product attention is not a mysterious black box. It's four elementary operations — matrix multiplication, transpose, scaling by a constant, and softmax — plus three learned projections that produce queries, keys, and values. You can write ... more
An LLM engine like vLLM exists because serving a model well is its own systems problem, distinct from training it. Text generation is autoregressive and memory-bound, and the key-value cache is the real capacity limit on how many users fit on a GPU. ... more
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Apple Podcasts | #230 |
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This tech-focused show delivers deep-dive explorations into AI engineering topics, with a strong emphasis on practical how-tos, coding interview prep, and real-world system design considerations. Across recent episodes, listeners get rigorous breakdowns of AI concepts (from attention mechanisms to large-model serving), hands-on problem-solving (LeetCode discussions and algorithmic thinking framed for practical engineering), and production-level perspectives on building and deploying AI systems. The format blends dense technical analysis with approachable explanations, often anchored by interview-style prompts and roadmaps that help engineers prepare for roles at leading tech companies. A standout trait is the tight connection between theory... more
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Code With Wilson launched 3 months ago and published 45 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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