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In principle, once cameras everywhere capture enough high-resolution, overlapping views, ordinary photographs may start to feel obsolete. Instead of saving a single flat image, those recordings could be used to reconstruct a navigable 3D representation of a scene — estimating the position, shape, depth, texture, and appearance of objects from multiple camera angles. You could then return to a particular moment, move the virtual camera to almost any viewpoint, and generate a new image from that angle. Parts of the scene that were never directly visible to any camera wouldn’t be true recordings — AI would have to infer and reconstruct them from the surrounding visual information. Author: joergkahlhoefer #gaussian #splat #3D

О, новые руки подъехали: Xynova’s Flex 2 23 степени свободы 400 грамм весят 12 кг поднимают Супер быстрые #руки #роботы ------ @tsingular

The brain of a dead male fruit fly was connected to a ROBOT — giving the fly a new body and allowing it to move freely through our world again. The fly’s neural activity is translated into commands for motors that control the robot’s legs. So, in a sense, the fly is… alive again. “Black Mirror” was a documentary. @science

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💡 Scientists Made a Semiconductor That Can Be Reprogrammed With Light Most computer chips are born with a fixed job. Once a semiconductor is fabricated, its electrical properties are largely locked in. Researchers at Princeton have now created an ultrathin semiconductor — only a few molecules thick — that can repeatedly change how it conducts electricity in response to different wavelengths of light. The effect is reversible, meaning the material can be programmed, erased and programmed again. The team achieved this by combining a two-dimensional semiconductor with light-sensitive molecules that physically change shape when illuminated. Those molecular changes alter the semiconductor’s electronic and optical behavior. And unlike a simple binary switch, the response can be adjusted gradually rather than just flipped between “0” and “1.” The researchers have already produced uniform samples about one inch across and built arrays of programmable electronic switches. Their next goal is to connect them into functioning circuits. The broader idea is striking: instead of manufacturing a chip for one fixed purpose, future electronics might be able to change their own physical behavior after they are built. Software is already reprogrammable. Now the hardware itself is starting to learn the trick. #Semiconductors #Computing #MaterialsScience #Photonics #Technology #Science https://www.science.org/doi/10.1126/sciadv.aee1510

Удивительно насколько обыденно смотрятся кадры, которые еще лет 10 назад звучали как абсолютная фантастика. #Unitree #олимпиада #роботы ------ @tsingular

🧠 Singapore Just Opened a Data Center Powered by Living Human Neurons This sounds like science fiction, but it went live on July 16. Australian startup Cortical Labs, together with the National University of Singapore and data-center operator DayOne, has launched a biological computing facility where part of the processing is performed not by GPUs — but by living human neurons grown in a lab. Inside are 20 CL1 biological computers. Each contains at least 200,000 neurons grown on a silicon chip covered with electrodes. The neurons originate from human blood cells that are reprogrammed into stem cells and then differentiated into neurons. And yes, the computers have to be fed. Every three days, technicians supply the cells with sugar, micronutrients and pH buffers, while a life-support system regulates oxygen, nitrogen and CO₂. The strange part is that these neurons can actually learn. Cortical Labs’ earlier DishBrain experiment showed human and mouse neurons learning to play Pong, with measurable learning appearing within just minutes. Earlier this year, developer Sean Cole connected around 200,000 human neurons to DOOM — allowing them to navigate the game and shoot at enemies. Biology is nowhere near silicon in raw speed. But it has another advantage: efficiency. A CL1 consumes around 30 watts. An NVIDIA H100 SXM can draw up to 700 W, while an eight-H100 server may consume roughly 10 kW including supporting hardware. Cortical Labs also argues that biological neural networks may learn from far smaller datasets — closer to how humans adapt from limited experience. Access to one CL1 currently costs about $2,200 per month. Cortical Labs already operates 120 units in Melbourne with around 20 paying customers, and Singapore could eventually expand to 1,000 biological computers. So no, neurons aren’t replacing GPUs tomorrow. But we have officially reached the stage where a data center needs electricity, an internet connection… and food. Cyberpunk is becoming an engineering discipline. #Biocomputing #Neuroscience #AI #DataCenters #CorticalLabs https://www.straitstimes.com/tech/forget-silicon-chip-servers-singapores-newest-data-centre-needs-to-be-fed