On this episode of the ML Platform Podcast, Mike Del Balso is our guest. Mike shares insights on his journey from Google to Tecton, building the ML platform (Michelangelo) at Uber, feature platforms, vector databases, and the future of the MLOps space in the world of foundational models.
Chapters:
01:37 Michael’s time at Google
10:00 Building the ML platform at Uber
18:24 What does not fit within an ML platform?
27:09 Feature platforms
34:39 Point solutions vs. end-to-end platforms
38:29 Vector databases and feature platforms
50:38 Real-time machine learning
01:00:42 The biggest challenges when building the real-time feature platform
01:09:13 The future of the MLOps space with LLMs
01:14:12 Closing remarks
Resources:
Machine Learning: The High Interest Credit Card of Technical Debt: research.google/pubs/machine-learning-the-high-interest-credit-card-of-technical-debt/
Meet Michelangelo: Uber’s Machine Learning Platform: www.uber.com/en-PT/blog/michelangelo-machine-learning-platform/
Feature Stores and LLMs: blog.langchain.dev/feature-stores-and-llms/
Building a Machine Learning Platform [Definitive Guide]: neptune.ai/blog/ml-platform-guide?
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Connect with Piotr on Linkedin: www.linkedin.com/in/piotrniedzwiedz
Connect with Aurimas on Linkedin: www.linkedin.com/in/aurimas-griciunas
Connect with Mike on Linkedin: www.linkedin.com/in/michaeldelbalso
#mlplatform #michelangelo #ml #machinelearning
Негізгі бет Ғылым және технология Learnings From Building the ML Platform at Uber (Michelangelo)
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