Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in which the probabilities of tokens occurring in a specific order is ...
TurboQuant vector quantization targets KV cache bloat, aiming to cut LLM memory use by 6x while preserving benchmark accuracy ...
Memory prices are plunging and stocks in memory companies are collapsing following news from Google Research of a ...
When Aquant Inc. was looking to build its platform — an artificial intelligence service that supports field technicians and agents teams with an AI-powered copilot to provide personalized ...
Google senior AI product manager Shubham Saboo has turned one of the thorniest problems in agent design into an open-source engineering exercise: persistent memory. This week, he published an ...
The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...
Google (GOOG)(GOOGL) revealed a set of new algorithms today designed to reduce the amount of memory needed to run large language models and vector search engines. Shares of major memory and storage ...
Chocolate Factory boffins have found a way to reduce AI’s memory use, but don’t assume that means less demand for DRAM ...
The rapid evolution of semiconductor devices has amplified the demand for advanced automated test equipment (ATE) that can handle increasingly complex test scenarios for logic devices. ATE vector ...
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