The search giant had previously created a machine learning data set out of food scraps from its kitchens. Now it’s partnering ...

A decade ago, Hassabis's lifelong enduring love of play and AI led to AlphaGo beating the world's deepest board game. The ...

Alphabet's recently announced memory compression technology has spooked investors in Micron, Sandisk, and Seagate, but they are missing the bigger picture. In fact, lower memory prices and more ...

Google’s TurboQuant is making waves in the AI hardware sector by addressing long-standing challenges in memory usage and processing efficiency. Developed with components like the Quantized ...

Google's TurboQuant algorithm significantly reduces memory usage for large language models. Memory chipmakers could face pressure, but investors may be worrying too much. This industry, and one ...

Google published a paper on March 31 that states that Bitcoin's cryptography could be impacted by quantum computing sooner than previously stated.

Micron Technology (MU) shares fell to $339 Monday as fears over Alphabet’s (GOOGL) TurboQuant AI memory-compression algorithm raised concerns about long-term demand for high-bandwidth memory across ...

Google says a new compression algorithm, called TurboQuant, can compress and search massive AI data sets with near-zero indexing time, potentially removing one of the biggest speed limits in modern ...

Google has introduced TurboQuant, a compression algorithm that reduces large language model (LLM) memory usage by at least 6x while boosting performance, targeting one of AI's most persistent ...

Google has unveiled TurboQuant, a new AI compression algorithm that can reduce the RAM requirements for large language models by 6x. By optimizing how AI stores data through a method called ...

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...

Google says its new TurboQuant method could improve how efficiently AI models run by compressing the key-value cache used in LLM inference and supporting more efficient vector search. In tests on ...