
Scaling Up Test-Time Compute with Latent Reasoning with Jonas Geiping - #723
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Scaling Challenges in AI Model Development
This chapter explores the hurdles encountered while scaling a model from millions to billions of parameters, focusing on supercomputer constraints and outdated hardware. It highlights innovative solutions for optimizing resource use and addresses the importance of reproducibility in machine learning experiments, concluding with a commitment to open-source contributions.
00:00
Transcript
Play full episode
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.