Model Flexibility Matters
MLOps has evolved significantly, especially with the rise of large language models, which come with unique challenges in management and deployment. Observing customer needs is crucial; if a model works well, customers should not be forced to upgrade prematurely. Flexibility in switching models when desired, rather than being compelled, is key to maintaining customer satisfaction and operational efficiency.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Cohere's SVP Technology - Saurabh Baji
Related Questions