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

I love Qwen

It is far more likely that a woman underwater is wearing at least a bikini…

18 hours ago

100% Unemployment is Inevitable*

TL;DR AI is already raising unemployment in knowledge industries, and if AI continues progressing toward…

18 hours ago

Sample and Map from a Single Convex Potential: Generation using Conjugate Moment Measures

The canonical approach in generative modeling is to split model fitting into two blocks: define…

18 hours ago

Streamline AI operations with the Multi-Provider Generative AI Gateway reference architecture

As organizations increasingly adopt AI capabilities across their applications, the need for centralized management, security,…

18 hours ago

BigQuery AI: The convergence of data and AI is here

From uncovering new insights in multimodal data to personalizing customer experiences, AI is emerging as…

18 hours ago

OpenAI is ending API access to fan-favorite GPT-4o model in February 2026

OpenAI has sent out emails notifying API customers that its chatgpt-4o-latest model will be retired…

19 hours ago