low-effort well-curated nonsense
Joined March 2010
- Tweets33
- Following346
- Followers410
- Likes4.7K
devang adhyaru retweeted
Devang from @TheHumanoidHub visited us last week in our Mountain View office! Fun moment from our conversation: he guessed the thumb is the most important finger for grip strength. It's actually the pinky. Small detail, but it's the kind of thing that shapes how we design these hands to actually work like a human's.
Full thing's linked below.
Thanks for stopping by, @dev_and_ !
devang adhyaru retweeted
.@JanLiphardt is a Professor of Bioengineering at Stanford and the founder of OpenMind.
Jan is building an open, decentralized ecosystem for real-world robotics and AI. We took Iris (the robot) for a walk across the street from their office and had a chat about the vision behind OpenMind.
00:17 – Intro
01:00 – Vision for OpenMind
03:01 – Software offering
08:23 – Future tasks
10:42 – Modular approach
14:08 – Jan's Bioengineering background
16:28 – Developer Access
devang adhyaru retweeted
Eric Jang weighs in on RL vs. supervised learning for humanoid robot manipulation tasks.
devang adhyaru retweeted
Super honored to have @dev_and_’s (who runs the #1 authoritative breaking news on humanoid robotics ) do his public face reveal at our new office and have a chat with us about @1x_tech’s recent AI updates. Thanks for the great discussion Devang!
.@ericjang11 is spearheading AI at 1X.
Eric believes 1X is on the path to becoming an AGI company — not just a robotics company.
I sat down with him at 1X’s new Palo Alto office to discuss the key AI building blocks needed to bring humanoid robots into homes at scale.
00:00 Eric Jang joins Humanoid Hub
00:27 Move to Palo Alto
01:02 Why 1X targets the home
02:01 The AGI company
02:49 Redwood AI overview
04:01 Unified control, modular stack
06:07 Data labeling at scale
07:10 RL mobility update for NEO
10:03 GPU and onboard compute
11:09 World model explained
13:34 Trusting world models for evaluation
15:05 Synthetic data generation
16:30 A world model Turing Test
17:41 RL in manipulation
20:08 Lessons from early NEO deployments
21:00 Full autonomy
22:18 1X’s unique edge in AI
24:02 Eric asks Devang a question
