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Temporal and spatial alignment between glove and camera data. It is not an easy task, but it’s coming together. Human data for robots. #Robotics

Yu Xiang

5,836 subscribers

50,151 次观看 • 5 个月前 •via X (Twitter)

科学技术 #Robotics

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Robotics is obsessed with foundation models and humanoids. It’s missing the most critical piece. One founder just raised $3M to build the “AWS for robots.” Fixing the silent bottleneck for most robotics startup: Data Infrastructure: 🧵

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Sensei Robotics (YC S24) helps robotics companies generate high-quality robotics training data at scale. Their platform collects human demonstration data at a tenth of the cost and twice the speed of current approaches.

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Y Combinator

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Two spacetimes, one data value chain >India: Workers’ headcams record garment sewing egocentric data flows to AI/robotics companies. >China: Operators teleoperate humanoid robots in warehouses, sorting packages …validating the system ,collecting real-world training data.

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🚨 THE BIGGEST BOTTLENECK IN AI ISN'T COMPUTING POWER ANYMORE IT'S MOVING DATA. Instead of laying new cables, Chinese researchers have upgraded existing fiber infrastructure by doing two things at once: Using three wavelength bands (C + L + S) instead of the usual two. Using four cores inside each fiber instead of one. Each core acts like an independent highway, and each band acts like an extra lane on that highway. Together, they’ve reportedly increased transmission capacity per core by nearly 50% and overall data throughput by up to 5×. This matters enormously for AI. Modern AI clusters move terabits of data per second between thousands of GPUs. The biggest bottleneck is often not the chips themselves, but moving data fast enough between them. If you can push 5× more data through the same physical cables, you can train bigger models faster and reduce network congestion. Why this is significant: • It shows multi-core + extended spectrum technology moving from labs into real-world commercial use • The system has already run over 35 km of existing telecom network • It could be especially useful for submarine cables and large-scale data center interconnects • China is also eyeing it for its “Eastern Data, Western Computing” project The deeper implication: We’re reaching the physical limits of how much data we can push through single-core fibers using traditional methods. By combining spatial multiplexing (multiple cores) with spectral multiplexing (more wavelength bands), engineers are finding new ways to keep scaling bandwidth without having to dig up the planet to lay new cables. This kind of breakthrough is quiet but foundational it’s the kind of infrastructure upgrade that will determine how fast AI and cloud computing can actually grow in the coming years. The future of data movement might not require more cables. It might just require smarter ones. How important do you think multi-core and multi-band fiber will be for keeping up with AI’s exploding data demands? Follow for more frontier networking, photonics, and infrastructure technology.

TheNewPhysics

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Nicely done. Not an easy task on rough and uneven surface 😂

Nicely done. Not an easy task on rough and uneven surface 😂

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Some robots run fast. Some run like humans! And honestly, the second kind is more interesting—like this: HONOR Yuanqi. From the perspective of embodied intelligence, "running like a human" is not just an aesthetic choice—it’s a functional milestone. That's where robotics starts to shift from performance… to understanding.

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