Categories: AI/ML News

With human feedback, AI-driven robots learn tasks better and faster

At UC Berkeley, researchers in Sergey Levine’s Robotic AI and Learning Lab eyed a table where a tower of 39 Jenga blocks stood perfectly stacked. Then a white-and-black robot, its single limb doubled over like a hunched-over giraffe, zoomed toward the tower, brandishing a black leather whip. Through what might have seemed to a casual viewer like a miracle of physics, the whip struck in precisely the right spot to send a single block flying from the stack while the rest of the tower remained structurally sound.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

The Complete Guide to Data Augmentation for Machine Learning

Suppose you’ve built your machine learning model, run the experiments, and stared at the results…

7 hours ago

ParaRNN: Unlocking Parallel Training of Nonlinear RNNs for Large Language Models

Recurrent Neural Networks (RNNs) laid the foundation for sequence modeling, but their intrinsic sequential nature…

7 hours ago

Advanced fine-tuning techniques for multi-agent orchestration: Patterns from Amazon at scale

Our work with large enterprise customers and Amazon teams has revealed that high stakes use…

7 hours ago

Cloud CISO Perspectives: Practical guidance on building with SAIF

Welcome to the first Cloud CISO Perspectives for January 2026. Today, Tom Curry and Anton…

7 hours ago

Listen Labs raises $69M after viral billboard hiring stunt to scale AI customer interviews

Alfred Wahlforss was running out of options. His startup, Listen Labs, needed to hire over…

8 hours ago

Thinking Machines Cofounder’s Office Relationship Preceded His Termination

Leaders at Mira Murati’s startup believe Barret Zoph engaged in an incident of “serious misconduct.”…

8 hours ago