Physicists at CU Boulder have, for the first time, used liquid crystals to create a new kind of time crystal, a curious phase of matter in which particles are in constant motion.
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Upgrading an RTX 4090 to 48 GB of VRAM is (slightly) easier than I thought, thanks to a custom PCB, some second-hand GDDR6X, and a leaked Nvidia BIOS
Yet another episode of: “Andy learns things with you.”
A Systems View of LLMs on TPUs
Training LLMs often feels like alchemy, but understanding and optimizing the performance of your models doesn’t have to. This book aims to demystify the science of scaling language models: how TPUs (and GPUs) work and how they communicate with each other, how LLMs run on real hardware, and how to parallelize your models during training and inference so they run efficiently at massive scale. If you’ve ever wondered “how expensive should this LLM be to train” or “how much memory do I need to serve this model myself” or “what’s an AllGather”, we hope this will be useful to you.
Mathematical model of memory suggests seven senses are optimal
Skoltech scientists have devised a mathematical model of memory. By analyzing its new model, the team came to surprising conclusions that could prove useful for robot design, artificial intelligence, and for better understanding of human memory. Published in Scientific Reports, the study suggests there may be an optimal number of senses—if so, those of us with five senses could use a couple more.
“Our conclusion is, of course, highly speculative in application to human senses, although you never know: It could be that humans of the future would evolve a sense of radiation or magnetic field. But in any case, our findings may be of practical importance for robotics and the theory of artificial intelligence,” said study co-author Professor Nikolay Brilliantov of Skoltech AI.
“It appears that when each concept retained in memory is characterized in terms of seven features—as opposed to, say, five or eight—the number of distinct objects held in memory is maximized.”