What’s so hard about training and deploying LLMs?

What happens when you scale up machine learning workloads to build more powerful models? What happens when you try to train bigger models, use more hardware, wrangle more data?
In this talk, Davis Blalock will walk through the hurdles of memory limitations, hardware failures, compute management, experimentation, evaluation, and how they all contribute to the escalating time and cost of training LLMs. He will also discuss the reliable and efficient systems his team has built to address these challenges – enabling better, cheaper, faster workflows for organizations of all sizes to train and deploy generative AI models.

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