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#6015: How Banks Move a Million vs a Billion Dollars
A million and a billion are the same number to a computer. The difference is liquidity, netting, and where the payment actually settles.
#6014: Why Every AI Model Is Secretly a Decoder
Encoder, decoder, or both? The three transformer shapes, why one won, and why BERT still refuses to die.
#6013: What Happens Inside One LLM Forward Pass
One trip through the network, layer by layer — and why a classifier needs one pass while an LLM needs hundreds.
#6012: Inside the Decode Loop: How LLMs Generate One Token at a Time
The model doesn't choose tokens or decide when to stop — the engine does. A step-by-step tour of one decode iteration.
#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.