TurboQuant and the Memory Stock Sell-Off: Why the Panic Outpaced the Paper

Why this efficiency gain is ultimately bullish for the memory chokepoint and the entire inference economy.

Photo by Alexander Mils via Unsplash

A Google blog post about compressing AI memory went viral. Within 48 hours, the market capitalization of memory semiconductors evaporated by over $100 billion. TurboQuant helps solve a core problem of the Agentic era: making long-context LLM inference efficient. But the algorithm compresses only the inference-time cache, not the model weights, training data, or storage.