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THE DAILY INDEX

Technology, AI, software, security, crypto and business

HEADLINES & LAUNCHES

TLDR AI

THE NVIDIA AI GPU BLACK MARKET (3.5 HOUR VIDEO)

This documentary features direct interviews with smugglers, dealers, and manufacturers across Hong Kong and Shenzhen, documenting how export-controlled chips flow from US Facebook Marketplace sales to Chinese warehouses. Reporters filmed transactions with smugglers buying RTX 4090s for $2,000 and buying modified cards from underground shops to turbocharge GPUs beyond what Nvidia offers. NVIDIA dismissed the smuggling evidence as "tall tales."

APIS DON'T MAKE GOOD MCP TOOLS

MCP has become the de facto standard for giving large language models access to tools that someone else wrote. However, writing tools for a new MCP server is hard, so people often propose auto-converting existing APIs into MCP tools. This doesn't work well because agents don't do well with large numbers of tools, APIs can blow through context windows quickly, and APIs don't make the most of agents' unique capabilities. Agents can just call APIs if they need to do that. They do best when given tools that are designed for their unique capabilities and limitations.

HOW TO THINK ABOUT GPUS

This article looks at how Nvidia GPUs work, how they're networked together, and what that means for large language models, especially compared to TPUs. A modern machine learning GPU is basically a bunch of compute cores that specialize in matrix multiplication connected to a stick of fast memory. TPUs are dedicated matrix multiplication machines that are cheap, predictable, and great if used as intended. Networking is one of the areas where GPUs and TPUs differ the most - TPUs are connected in 2D or 3D tori, where each TPU is only connected to its neighbors, while GPUs use a more tree-based switching network.

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