MLOps.community
A podcast by Demetrios Brinkmann
Categories:
391 Episodes
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AI's Next Frontier // Aditya Naganath // #277
Published: 11/12/2024 -
PyTorch for Control Systems and Decision Making // Vincent Moens // #276
Published: 4/12/2024 -
AI-Driven Code: Navigating Due Diligence & Transparency in MLOps // Matt van Itallie // #275
Published: 29/11/2024 -
PyTorch's Combined Effort in Large Model Optimization // Michael Gschwind // #274
Published: 26/11/2024 -
LLMs to agents: The Beauty & Perils of Investing in GenAI // VC Panel // Agents in Production
Published: 22/11/2024 -
We Can All Be AI Engineers and We Can Do It with Open Source Models // Luke Marsden // #273
Published: 20/11/2024 -
Exploring AI Agents: Voice, Visuals, and Versatility // Panel // Agents in Production
Published: 15/11/2024 -
The Impact of UX Research in the AI Space // Lauren Kaplan // #272
Published: 13/11/2024 -
EU AI Act - Navigating New Legislation // Petar Tsankov // MLOps Podcast #271
Published: 1/11/2024 -
Boosting LLM/RAG Workflows & Scheduling w/ Composable Memory and Checkpointing // Bernie Wu // #270
Published: 22/10/2024 -
How to Systematically Test and Evaluate Your LLMs Apps // Gideon Mendels // #269
Published: 18/10/2024 -
Exploring the Impact of Agentic Workflows // Raj Rikhy // #268
Published: 15/10/2024 -
The Only Constant is (Data) Change // Panel // DE4AI
Published: 11/10/2024 -
The AI Dream Team: Strategies for ML Recruitment and Growth // Jelmer Borst and Daniela Solis // #267
Published: 9/10/2024 -
Making Your Company LLM-native // Francisco Ingham // #266
Published: 6/10/2024 -
Unpacking 3 Types of Feature Stores // Simba Khadder // #265
Published: 1/10/2024 -
Reinvent Yourself and Be Curious // Stefano Bosisio // MLOps Podcast #264
Published: 27/09/2024 -
Global Feature Store // Gottam Sai Bharath & Cole Bailey // #263
Published: 24/09/2024 -
RAG Quality Starts with Data Quality // Adam Kamor // #262
Published: 20/09/2024 -
Who's MLOps for Anyway? // Jonathan Rioux // #261
Published: 17/09/2024
Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.
