Google LLC has unveiled a technology called TurboQuant that can speed up artificial intelligence models and lower their memory requirements. Amir Zandieh and Vahab Mirrokni, two of the researchers who ...
Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...
If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...
Google's TurboQuant can dramatically reduce AI memory usage. TurboQuant is a response to the spiraling cost of AI. A positive outcome is making AI more accessible by lowering inference costs. With the ...
When Google unveiled TurboQuant on March 24, headlines declared the algorithm could slash AI memory use sixfold with zero accuracy loss and deliver eight times faster processing. Within days, Samsung ...
Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...
At its core, TurboQuant compresses the key-value (KV) cache -- the short-term working memory AI models use during inference -- by converting data vectors into polar coordinates and subsequently ...
TurboQuant compresses AI’s KV cache by 6x – but cheaper inference historically expands total demand, not shrinks it, a dynamic known as the Jevons Paradox. The selloff in SanDisk and Seagate is ...
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