Researchers from Koç University, in collaboration with institutions in Turkey and Japan, have developed an AI model that predicts viewer attention in 360-degree videos by combining visual and auditory ...
Developed by Professor Sanjay Mehrotra, the Sliding Scale AdaptiVe Expedited (SAVE) algorithm could improve organ allocation ...
Google’s TurboQuant Compression May Support Faster Inference, Same Accuracy on Less Capable Hardware
Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches ...
Abstract: Large multimodal models (LMMs) have advanced significantly by integrating visual encoders with extensive language models, enabling robust reasoning capabilities. However, compressing LMMs ...
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 ...
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 ...
Paying for 4k and tools for Netflix doesn't guarantee a great stream, unfortunately, thanks to some behind-the-scenes ways the company saves money.
Hybrid architectures (mixing full attention with linear/SSM layers) tolerate aggressive KV quantization because the non-attention layers absorb and correct quantization errors. b_h = b_avg + 0.25 * (H ...
Memory prices are falling, and stock prices of memory companies took a hit, following news from Google Research of a breakthrough that will greatly reduce the amount of memory needed for AI processing ...
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