Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...

Is distributed training the future of AI? As the shock of the DeepSeek release fades, its legacy may be an awareness that alternative approaches to model training are worth exploring, and DeepMind ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

In a new paper, researchers from Tencent AI Lab Seattle and the University of Maryland, College Park, present a reinforcement learning technique that enables large language models (LLMs) to utilize ...

What if you could train massive machine learning models in half the time without compromising performance? For researchers and developers tackling the ever-growing complexity of AI, this isn’t just a ...

Poor utilization is not the single domain of on-prem datacenters. Despite packing instances full of users, the largest cloud providers have similar problems. However, just as the world learned by ...