MLOps.community
Un podcast de Demetrios
430 Épisodes
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PyTorch for Control Systems and Decision Making // Vincent Moens // #276
Publié: 04/12/2024 -
AI-Driven Code: Navigating Due Diligence & Transparency in MLOps // Matt van Itallie // #275
Publié: 29/11/2024 -
PyTorch's Combined Effort in Large Model Optimization // Michael Gschwind // #274
Publié: 26/11/2024 -
LLMs to agents: The Beauty & Perils of Investing in GenAI // VC Panel // Agents in Production
Publié: 22/11/2024 -
We Can All Be AI Engineers and We Can Do It with Open Source Models // Luke Marsden // #273
Publié: 20/11/2024 -
Exploring AI Agents: Voice, Visuals, and Versatility // Panel // Agents in Production
Publié: 15/11/2024 -
The Impact of UX Research in the AI Space // Lauren Kaplan // #272
Publié: 13/11/2024 -
EU AI Act - Navigating New Legislation // Petar Tsankov // MLOps Podcast #271
Publié: 01/11/2024 -
Boosting LLM/RAG Workflows & Scheduling w/ Composable Memory and Checkpointing // Bernie Wu // #270
Publié: 22/10/2024 -
How to Systematically Test and Evaluate Your LLMs Apps // Gideon Mendels // #269
Publié: 18/10/2024 -
Exploring the Impact of Agentic Workflows // Raj Rikhy // #268
Publié: 15/10/2024 -
The Only Constant is (Data) Change // Panel // DE4AI
Publié: 11/10/2024 -
The AI Dream Team: Strategies for ML Recruitment and Growth // Jelmer Borst and Daniela Solis // #267
Publié: 09/10/2024 -
Making Your Company LLM-native // Francisco Ingham // #266
Publié: 06/10/2024 -
Unpacking 3 Types of Feature Stores // Simba Khadder // #265
Publié: 01/10/2024 -
Reinvent Yourself and Be Curious // Stefano Bosisio // MLOps Podcast #264
Publié: 27/09/2024 -
Global Feature Store // Gottam Sai Bharath & Cole Bailey // #263
Publié: 24/09/2024 -
RAG Quality Starts with Data Quality // Adam Kamor // #262
Publié: 20/09/2024 -
Who's MLOps for Anyway? // Jonathan Rioux // #261
Publié: 17/09/2024 -
Alignment is Real // Shiva Bhattacharjee // #260
Publié: 13/09/2024
Relaxed Conversations around getting AI into production, whatever shape that may come in (agentic, traditional ML, LLMs, Vibes, etc)
