Here it is! We review the year where scaling large AI models hit its ceiling, Google reclaimed momentum with efficient vertical integration, and the market shifted from hype to viability. Join us as we talk about why human-in-the-loop is failing, why generative AI agents validating other agents compounds errors, and how small expert data quietly beat the big models. • Google’s resurgence with Gemini 3.0 and TPU-driven efficiency • Monetization pressures and ads in co-pilot assistants •...
All content for The AI Fundamentalists is the property of Dr. Andrew Clark & Sid Mangalik and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Here it is! We review the year where scaling large AI models hit its ceiling, Google reclaimed momentum with efficient vertical integration, and the market shifted from hype to viability. Join us as we talk about why human-in-the-loop is failing, why generative AI agents validating other agents compounds errors, and how small expert data quietly beat the big models. • Google’s resurgence with Gemini 3.0 and TPU-driven efficiency • Monetization pressures and ads in co-pilot assistants •...
Supervised machine learning for science with Christoph Molnar and Timo Freiesleben, Part 2
The AI Fundamentalists
41 minutes
9 months ago
Supervised machine learning for science with Christoph Molnar and Timo Freiesleben, Part 2
Part 2 of this series could have easily been renamed "AI for science: The expert’s guide to practical machine learning.” We continue our discussion with Christoph Molnar and Timo Freiesleben to look at how scientists can apply supervised machine learning techniques from the previous episode into their research. Introduction to supervised ML for science (0:00) Welcome back to Christoph Molnar and Timo Freiesleben, co-authors of “Supervised Machine Learning for Science: How to Stop Worryi...
The AI Fundamentalists
Here it is! We review the year where scaling large AI models hit its ceiling, Google reclaimed momentum with efficient vertical integration, and the market shifted from hype to viability. Join us as we talk about why human-in-the-loop is failing, why generative AI agents validating other agents compounds errors, and how small expert data quietly beat the big models. • Google’s resurgence with Gemini 3.0 and TPU-driven efficiency • Monetization pressures and ads in co-pilot assistants •...
