Skip to content
Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning episode artwork

Mar 14, 2025 11 min

Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

from Best AI papers explained Hosted by Enoch H. Kang

Longer version

Episode details come from the podcast's RSS feed.

Embed this episode

Ready to play

Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

0:00 11:35

No transcript yet.

Requests help us decide what to transcribe next.

Share this episode

Similar podcasts

CISO Perspectives (public) N2K Networks This season on CISO Perspectives, host Kim Jones explores some of the challenges of leading through uncertainty. We explore the complexity of the changing nature of regulation and working with the federal government, the evolution of privacy and fraud, and how emerging technologies like AI and quantum computing are changing cyber. When you don’t know what questions to ask, you’re afraid to ask, or don’t know who to ask, CISO Perspectives provides the foundation for learning in this brave new world.

Frequently asked questions

How long is this episode of Best AI papers explained?

This episode is 11 minutes long.

When was this Best AI papers explained episode published?

This episode was published on March 14, 2025.

Can I download this Best AI papers explained episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.