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ML Platform Podcast neptune.ai
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- Technologie
Get behind-the-scenes insights into the world of internal ML platforms and MLOps stack components with Piotr Niedźwiedź and Aurimas Griciūnas in their show, where together with ML platform professionals, they discuss design choices, best practices, and real-world solutions to MLOps challenges.
Brought to you by neptune.ai.
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Going Deep On Model Serving, Deploying LLMs and Anything Production-Deployment
On this episode of the ML Platform Podcast, Chaoyu Yang discusses the MLOps stack's model serving, model registry and feature store components, online model training, large language model deployment, LLM agents, and more.
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Building Internal ML Platform at Scout24: How to Ship Features that People Actually Need
On this episode of the ML Platform Podcast, we have Olalekan Elesin as our guest. Olalekan shares insights on building the ML Platform at Scout24, including problems to be solved, reasons for going multi-cloud, point solutions vs. end-to-end platforms, data platforms vs. ML platforms, iterative product development approach, and more.
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Building ML Platform at Uber, Feature Stores, Vector Databases, and Real-time Feature Management
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.
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Year in Review: LLMs & LLMOps, State of MLOps, and What's Next in 2024
On this special, end-of-the-year episode of the ML Platform Podcast, Piotr Niedzwiedzi and Aurimas Griciūnas discuss the state of MLOps and LLMOps, the impact of LLMs on layoffs and ML team composition, unsolved LLM challenges, use cases that don’t align with LLMs, MLOps and LLMOps predictions for 2024, and more.
With LLMs and AI being the center of discussion we also decided to experiment with generative AI for this video. Hope you don’t mind the experimentation. -
Building MLOps Capabilities at GitLab As a One-Person ML Platform Team With Eduardo Bonet
On this episode of the ML Platform Podcast, we have Eduardo Bonet as our guest. Eduardo shares insights on the Staff Incubation Engineer’s work at GitLab, the relationship between MLOps and DevOps, the future of metadata tracking, CI/CD and ML model training pipelines, foundational (LLM) model metadata management, and more.
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Learnings From Building the ML Platform at Mailchimp With Mikiko Bazeley
On this episode of the ML Platform Podcast, we have Mikiko Bazeley as our guest. Mikiko shares insights on the ML Platform at Mailchimp, including success stories and golden paths, team structures, templating, generative AI use cases, feedback monitoring, and more.
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