AI Efficiency

Micron just lost over $100 per share. Samsung shed 5%. DDR5 prices dropped 30%. The culprit? A compression algorithm from Google Research that makes AI models need dramatically less memory. And it hasn’t even shipped as a product yet. The DeepSeek Sequel Nobody Expected TurboQuant does something deceptively simple: it compresses the key-value cache — the short-term memory AI models use during inference — by 6x while making inference 8x faster. Zero accuracy loss. No retraining. No fine-tuning. Just plug it into your existing pipeline. ...

A single research paper from Google just wiped billions off memory chip stocks across three continents. No earnings miss. No supply chain disruption. Just math. The algorithm is called TurboQuant. If it delivers on its promises, it rewrites the economics of running every major AI model on the planet. We’re talking 6x less memory, 8x faster inference, and zero accuracy loss. The Bottleneck Everyone Ignored Every AI conversation eats memory. When you chat with an AI, the model stores your context in a key-value (KV) cache — its working memory. Longer conversations mean bigger caches, which means more expensive GPU memory consumed. ...