"Real API calls, real latency, real bills. Caveats are stated, not buried." -- Gosh, who talks like this? No human would. Claude does. Wannable confident, arrogant, and super annoying. Stated, not implied. ;-)
We've added support for VR controllers and mouse gestures to our Transitive Remote Teleop capability. This means you can now control your robotic arms over the internet from anywhere in the world (with live video and low latency).
Congrats on the launch! At Transitive Robotics we make full-stack modules so robotics companies like you can build their operational systems faster and with greater quality. We have a number of modules you might be interested in, e.g., for remote video-streaming and tele-op/-assist: https://transitiverobotics.com/caps/.
Let me know if you want to chat.
Very much besides the point. The point being that automation often enables other things, not just making the thing they automate directly more efficient.
"So if you can't collect enough data before building, and simulation won't give it to you, where does the data come from? Goldberg's answer is what he calls the data avalanche: build a working system using engineering plus some learning, ship it, then let production generate the training data." -- agreed! This is also the approach taken by Field AI if I'm not mistaken. Rather than calling it the data avalanche, you could also just describe it as "learning by doing".
nice idea and setup, but it doesn't work. I can request control, it will say "you are next" or similar, and then right away "time's up, return to games". I never get control.
great idea! Now, you are running into the same issue Google Trends had to solve: term disambiguation. For instance, "atom" is ambiguous in a comparison of editors like this: https://hackernewstrends.com/?q=sublime&q=atom&q=vscode. Given LLMs it might be possible to use an embedding vector (with context) instead of a text string for indexing, and if you do, this problem might go away.
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