Artificial Intelligence
Episodes whose main subject is AI itself: building with, training, evaluating, or debating AI systems. AI used only as a tool for another topic goes to that topic.
#6011: Inside LLM Inference: Prefill, Decode, and the KV Cache
One 8K-token sequence on a 13B model eats 6.7GB of KV cache—while the weights are only 26GB. Here's what actually happens per request.
#6010: Ten Ridiculous Wearables, Ranked by Sincerity
Brainwave cat ears, a tomato-dispensing shoulder robot, and a $3,000 sock tracker — all built with total sincerity.
#6009: Vertex AI Is Now the Gemini Agent Platform
Vertex AI just became the Gemini Enterprise Agent Platform. Here's the family tree, the five products, and when to actually move.
#6008: Why Codex Writes Code for a Dead API
Models don't hallucinate your API — they quote real docs from the wrong year. Here's why, and what actually fixes it.
#6007: What a $1M AI Inference Contract Actually Contains
The sticker price isn't the deal. Inside the commit floors, discount curves, and overage traps of enterprise AI contracts.
#6006: Data Residency vs. Inference Residency: What the Law Actually Says
GDPR doesn't require local GPUs. Here's what actually drives geographically restricted AI inference — and the three layers everyone conflates.
#6005: What's Actually Behind a Government AI Chatbot
Singapore runs open-weight models on commercial cloud. The UK built its own chatbot, then shut it down for Copilot. What's really behind civil-serv...
#6004: Nobody Can Buy Unlimited AI Inference
Every published tier, every reserved deal, every prepaid reservation — all bounded. Even Azure says it out loud: quota isn't capacity.
#6003: What Enterprises Actually Pay for AI Inference
Twelve and a half billion dollars in enterprise API spend — and nobody can tell you who spent it. Inside AI's most undocumented market.
#6002: Claude on AWS: Three Doors, One Rate Card
Same per-token price everywhere — so why buy Claude through AWS instead of Anthropic? The answer is commitments, compliance, and silicon.
#6001: What Do Inference Providers Actually Sell?
Same open weights, 20x cost gap. What Fireworks, Together, and Groq actually sell — and when to just rent a GPU.
#6000: 6,000 Episodes and a GPU Bill: Inside My Weird Prompts
Six thousand episodes, one human in the loop, and a Modal bill that keeps growing. A behind-the-scenes update on the podcast.
#5997: Counting Our Listeners, Then Planning a Cave
What Podtrac actually measures, why downloads jumped 79% while listeners stayed flat, and how long you'd need in a cave to hear it all.
#5996: Turning 3,000 Episodes Into a Video Channel
We already own the transcripts. The missing piece is the review queue — and that's where the money actually goes.
#5994: Hebrew in Latin Letters: A TTS Pipeline Fix
A token classifier that finds Hebrew words written in Latin letters so TTS stops mangling them — built for under $3.
#5995: NVIDIA ASR: Parakeet, Canary, and Nemotron Explained
Whisper gives you one dial. NVIDIA gives you five. A practical map of the Parakeet, Canary, and Nemotron speech models.
#5993: Why Every Renovation Show Looks the Same
Shiplap, white quartz, open plan — why does every renovation show produce the identical room, and who's really choosing it?
#5992: Ridiculous But Legal Ways to Get RAM for AI
Memory prices are up 485% on some kits. Here are ten ridiculous — but completely legal — ways to get RAM for AI without the markup.
#5991: Batch Inference on Your Own GPU: vLLM, SGLang, Ollama, llama.cpp
Hosted batch APIs sell you half-price tokens. Here's how to get the same file-in, file-out workflow on your own Linux box.
#5989: Twenty Tiny Beats That Make a Podcast Stick
Twenty novel recurring segment pitches — and the test each one has to pass: does it add context, or just noise?