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 ...
The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...
Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 ...
Memory stocks fell Wednesday despite broader technology sector strength, with shares dropping after Google unveiled ...
Kioxia Corporation today announced the successful demonstration of achieving high-dimensional vector search scaling to 4.8 billion vectors on a single server with its open-source KIOXIA AiSAQ(TM) ...
When designing search systems, the decision to use keyword-based search, vector-based search, or a hybrid approach can significantly impact performance, relevance, and user satisfaction. Each method ...
News flash: Vector databases and vector searches are no longer a differentiation. Yes, how fast times change as what was cool just six months ago is suddenly table stakes! What is cool is a unified ...
Nvidia has a structured data enablement strategy. Nvidia provides libaries, software and hardware to index and search data ...
A new technical paper titled “Cross-Layer Design of Vector-Symbolic Computing: Bridging Cognition and Brain-Inspired Hardware Acceleration” was published by researchers at Purdue University and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results