RL
Reinforcement Learning Rl
Indexing
Sifting through hundreds of thousands of hours of indexed videos
Reinforcement Learning Rl
Sifting through hundreds of thousands of hours of indexed videos
Reinforcement Learning Rl
Arcmira media summary
Explore podcasts, interviews & explainers on Reinforcement Learning (RL) — 27 indexed from Sourcery with Molly O'Shea & Dwarkesh Patel, updated May 2026.
The methodology used to train Figure's robots for stability and recovery from physical disturbances.
Discussion on how RL generation and training affects the total compute budget and model efficiency.
Technical discussion of value vs. policy networks and how they represent positive and negative rewards.
Discussion on the shift from scaling laws to RL and test-time compute.
Deep discussion on RL paradigms, hill climbing, and verification functions.
Arcmira tracks 27 indexed media appearances or mentions for Reinforcement Learning (RL), tied to source videos, channels, and transcript-derived context.
Arcmira uses indexed YouTube videos and transcripts. Representative source evidence on this page includes "Figure's First Full HQ Tour: From the Lab to the Factory Floor" with transcript-derived context and links when available.
Reinforcement Learning (RL) is connected to Dwarkesh Patel, Alex Volkov from ThursdAI, Cognitive Revolution "How AI Changes Everything" in Arcmira's media graph.
27
Mentions
2.6M
Views
The trendline is visible, but the dated evidence behind Reinforcement Learning (RL) is in the premium layer.
“The methodology used to train Figure's robots for stability and recovery from physical disturbances.”
“Discussion on how RL generation and training affects the total compute budget and model efficiency.”
“Technical discussion of value vs. policy networks and how they represent positive and negative rewards.”
“Discussion on the shift from scaling laws to RL and test-time compute.”
“Deep discussion on RL paradigms, hill climbing, and verification functions.”