MLOps.community
En podkast av Demetrios Brinkmann
Kategorier:
379 Episoder
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Red Teaming LLMs // Ron Heichman // #252
Publisert: 6.8.2024 -
Balancing Speed and Safety // Panel // AIQCON
Publisert: 2.8.2024 -
Reliable LLM Products, Fueled by Feedback // Chinar Movsisyan // #251
Publisert: 30.7.2024 -
A Blueprint for Scalable & Reliable Enterprise AI/ML Systems // Panel // AIQCON
Publisert: 26.7.2024 -
AI Operations Without Fundamental Engineering Discipline // Nikhil Suresh // #250
Publisert: 23.7.2024 -
AI in Healthcare // Eric Landry // #249
Publisert: 19.7.2024 -
Evaluating the Effectiveness of Large Language Models: Challenges and Insights // Aniket Singh // #248
Publisert: 16.7.2024 -
Extending AI: From Industry to Innovation // Sophia Rowland & David Weik // #246
Publisert: 12.7.2024 -
Detecting Harmful Content at Scale // Matar Haller // #245
Publisert: 9.7.2024 -
All Data Scientists Should Learn Software Engineering Principles // Catherine Nelson // #245
Publisert: 5.7.2024 -
Meta GenAI Infra Blog Review // Special MLOps Podcast
Publisert: 3.7.2024 -
AI Agents for Consumers // Shaun Wei // #244
Publisert: 28.6.2024 -
ML and AI as Distinct Control Systems in Heavy Industrial Settings // Richard Howes // #243
Publisert: 25.6.2024 -
Accelerating Multimodal AI // Ethan Rosenthal // #242
Publisert: 21.6.2024 -
Navigating the AI Frontier: The Power of Synthetic Data and Agent Evaluations in LLM Development // Boris Selitser // #241
Publisert: 18.6.2024 -
How to Build Production-Ready AI Models for Manufacturing // [Exclusive] LatticeFlow Roundtable
Publisert: 14.6.2024 -
From Robotics to Recommender Systems // Miguel Fierro // #240
Publisert: 11.6.2024 -
Uber's Michelangelo: Strategic AI Overhaul and Impact // #239
Publisert: 7.6.2024 -
AWS Tranium and Inferentia // Kamran Khan and Matthew McClean // #238
Publisert: 4.6.2024 -
Build Reliable Systems with Chaos Engineering // Benjamin Wilms // #237
Publisert: 31.5.2024
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.
