In this talk, Wanchao Liang, Software Engineer at Meta Pytorch Team, explores the technology advancements of PyTorch Distributed, and dives into the details of … Continued
On-Demand Videos
Machine learning models power Uber’s everyday business. However, developing and deploying a model is not a one-time event but a continuous process that requires … Continued
In this session, Adit Madan, Director of Product Management at Alluxio, presents an overview of using distributed caching to accelerate model training and serving. … Continued
As the AI landscape rapidly evolves, the advancements in generative AI technologies, such as ChatGPT, are driving a need for a robust AI infra … Continued
As enterprises race to roll out artificial intelligence, often overlookModel training requires extensive computational and GPU resources. When training models on AWS, loading data … Continued
As enterprises race to roll out artificial intelligence, often overlooked are the infrastructure needs to support scalable ML model development and deployment. Efforts to … Continued
Organizations are retooling their enterprise data infrastructure in the race for AI/ML. However, growing datasets, extensive data engineering overhead, high GPU costs, and expensive … Continued
Join us with David Loshin, President of Knowledge Integrity, and Sridhar Venkatesh, SVP of Product at Alluxio, to learn more about the infrastructure hurdles … Continued
When training models on ultra-large datasets, one of the biggest challenges is low GPU utilization. These powerful processors are often underutilized due to inefficient … Continued