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 ...
The internet is saying Google Research developed Pied Piper. Anyone familiar with the popular HBO series, Silicon Valley, will know the fictional company in the show develops an industry-leading ...
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Compression technique makes AI models leaner and faster while they're still learning
Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...
The big picture: Google has developed three AI compression algorithms – TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss – designed to significantly reduce the memory footprint of large ...
Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches ...
Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising ...
Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...
New Google technology reduces the memory requirements of AI models. Investors were worried about slowing memory demand, but it's too early to make that call. That sparked fears among Sandisk investors ...
Neural Texture Compression (NTC) optimized memory usage for either neural rendering or high-resolution texture and game data.
Intel and Nvidia showed off their respective AI-powered texture-compression technologies over the weekend, demonstrating impressive reductions in VRAM use while maintaining texture quality, or even ...
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