World Models: When AI Learns Physics Instead of Memorizing Data
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.
13 Aug 19min
The Evaluation Crisis: We Do Not Know How Good Our Models Actually Are
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.
30 Juli 20min
Mixture of Experts at the Edge: Running 30B Parameter Models on Your Laptop
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.
16 Juli 20min
The Agent Interoperability Problem: Why Your AI Agents Can Not Talk to Each Other
90% of enterprises deploy AI agents. Only 23% scale them. The gap is interoperability. Three protocols, MCP, A2A, and ACP, are racing to build the connective tissue before the ecosystem fragments.
2 Juli 21min
KV Cache Compression: The Memory Wall Nobody Talks About
Your GPU is not compute-bound. It is memory-bound. The KV cache is eating half your inference budget, and two ICLR 2026 breakthroughs KVTC and TurboQuant are about to change the math entirely.
18 Juni 21min
Context Rot: Why Million-Token Windows Quietly Fail
Models advertise million-token windows but accuracy degrades well before the limit. Three recent studies, the mechanisms behind the rot, and a practitioner playbook for what to do Monday.
4 Juni 21min
LLMOps: Operating Large Language Models in Production
Building an AI model is one thing: keeping a large language model running reliably in the real world is another. In this episode, we discuss LLMOps, the emerging set of practices and tools for deployi...
26 Maj 28min
