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The 5090 graphics card uses NVIDIA’s new Blackwell architecture and the GB202 chip, packing 32GB of GDDR7 memory for serious ...
TL;DR: Google developed three AI compression algorithms-TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss-that reduce large language models' KV cache memory by at least six times without ...
Investigators have discovered how brain cells responsible for working memory -- the type required to remember a phone number long enough to dial it -- coordinate intentional focus and short-term ...
This Animation Startup Wants to Make It Easier to Tell Open-Ended Stories ...
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 ...
As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...
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 ...
Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in large language models to 3.5 bits per channel, cutting memory consumption ...
Working memory is the active and robust retention of multiple bits of information over the time-scale of a few seconds. It is distinguished from short-term memory by the involvement of executive or ...
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Google's TurboQuant reduces AI LLM cache memory capacity requirements by at least six times
Google Research published TurboQuant on Tuesday, a training-free compression algorithm that quantizes LLM KV caches down to 3 bits without any loss in model accuracy. In benchmarks on Nvidia H100 GPUs ...
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