Practical AI: Machine Learning, Data Science
Technology:Software How-To
Worlds are colliding! This week we join forces with the hosts of the MLOps.Community podcast to discuss all things machine learning operations. We talk about how the recent explosion of foundation models and generative models is influencing the world of MLOps, and we discuss related tooling, workflows, perceptions, etc.
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Show Notes:
MLOps.Community
Something missing or broken? PRs welcome!
Timestamps:
(00:07) - Welcome to Practical AI
(00:43) - Demetrios and Mihail
(01:54) - What is the MLOps Community?
(05:14) - Chris throws a hand grenade into the convo
(09:44) - MLOps vs DevOps when deploying
(15:30) - Ops vs experiment tracking
(16:43) - Where is MLOps going?
(25:57) - Is this even legal??
(32:22) - Sponsor: Changelog++
(33:21) - Is generative model bloat an issue?
(36:35) - MLOps' diverse uses
(42:52) - You are not Google
(54:07) - Wrap up
(56:07) - Outro
AI in the U.S. Congress
First impressions of GPT-4o
Full-stack approach for effective AI agents
Autonomous fighter jets?!
Private, open source chat UIs
Mamba & Jamba
Udio & the age of multi-modal AI
RAG continues to rise
Should kids still learn to code?
AI vs software devs
Prompting the future
Generating the future of art & entertainment
YOLOv9: Computer vision is alive and well
Representation Engineering (Activation Hacking)
Leading the charge on AI in National Security
Gemini vs OpenAI
Data synthesis for SOTA LLMs
Large Action Models (LAMs) & Rabbits 🐇
Collaboration & evaluation for LLM apps
Advent of GenAI Hackathon recap
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