Live from TWIMLcon! You're not Facebook. Architecting MLOps for B2B Use Cases with Jacopo Tagliabue - #596
Published:Oct 24, 2022 17:37
•1 min read
•Practical AI
Analysis
This article highlights a crucial distinction in the field of MLOps: the difference between approaches suitable for large consumer internet companies (like Facebook and Google) and those that are more appropriate for smaller, B2B businesses. The interview with Jacopo Tagliabue focuses on adapting MLOps principles to make them more accessible and relevant for a broader range of practitioners. The core issue is that MLOps strategies developed for FAANG companies may not translate well to the resource constraints and different operational needs of B2B companies. The article suggests a need for tailored MLOps solutions.
Key Takeaways
- •MLOps strategies developed for large consumer internet companies may not be suitable for B2B companies.
- •The article emphasizes the need for adapting MLOps to fit the specific needs of B2B businesses.
- •The interview with Jacopo Tagliabue provides insights into scaling down MLOps for wider applicability.
Reference
“How should you be thinking about MLOps and the ML lifecycle in that case?”