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Large language model (LLM) training has become increasingly popular over the last year with the release of several publicly available models such as Llama2, Falcon, and StarCoder. Customers are now training LLMs of unprecedented size ranging from 1 billion to over 175 billion parameters. Training these LLMs requires significant compute resources and time as hundreds …

Read more “Enable faster training with Amazon SageMaker data parallel library”

Businesses are under increased pressure to do more with less, while customer expectations and demands have never been higher. Today’s enterprises need a way to be more productive, effective, and responsive while still addressing the operational challenges of cost containment, risk reduction, security, and compliance. Google Cloud partner of 15 years, EPAM Systems, a leading …

Read more “Built-with Google AI: Meet Vivien, EPAM’s digital assistant with the power of Google Cloud gen AI”

GPUs have been called the rare Earth metals — even the gold — of artificial intelligence, because they’re foundational for today’s generative AI era. Three technical reasons, and many stories, explain why that’s so. Each reason has multiple facets well worth exploring, but at a high level: GPUs employ parallel processing. GPU systems scale up …

Read more “Why GPUs Are Great for AI”

Posted by Robin Kothari and Rolando Somma, Research Scientists, Google Research, Quantum AI Team Quantum computers promise to solve some problems exponentially faster than classical computers, but there are only a handful of examples with such a dramatic speedup, such as Shor’s factoring algorithm and quantum simulation. Of those few examples, the majority of them …

Read more “A new quantum algorithm for classical mechanics with an exponential speedup”