Navigating LLM Challenges
The discussion highlights the complexities of building products with large language models, emphasizing the distinctions between ML engineers and MLOps roles. Insights into the importance of a robust platform for transitioning ideas into production are shared, along with a look at tools like Llamaindex and Olama that can enhance the LLM development process.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
787: MLOps: The Job and The Key Tools — with Demetrios Brinkmann
Related Questions
How will large language models (LLMs) and AI change software engineering and the software development lifecycle (SDLC) as discussed in the episode 787: MLOps: The Job and The Key Tools — with Demetrios Brinkmann and the clip LLM Tools Explained?
How will large language models (LLMs) and AI change software engineering and the software development lifecycle (SDLC) as discussed in the episode 787: MLOps: The Job and The Key Tools — with Demetrios Brinkmann and the clip LLMOps Revolution?
What is the power of building a machine learning platform as discussed in the episode Vector Similarity Search at Scale // Dave Bergstein // MLOps Coffee Sessions #52 and the clip Building ML Platforms?