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ML Infrastructure Without The Ops: Simplifying The ML Developer Experience With Runhouse

AI Engineering Podcast

CHAPTER

Navigating the ML Hype Cycle

This chapter explores the challenges enterprises face in adapting to the rapidly evolving landscape of Machine Learning technologies, particularly the focus on large language models. It discusses the importance of first-party data and a democratized approach to ML infrastructure, while also analyzing how platforms like Runhouse may fit into various organizational needs. The conversation highlights the necessity for integration with existing DevOps practices to optimize ML workflows and promote collaboration across teams.

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