An anonymous reader quotes a report from Popular Science: On the early evening of June 22, 2010, American tennis star John Isner began a grueling Wimbledon match against Frenchman Nicolas Mahut that would become the longest in the sport's history. The marathon battle lasted 11 hours and stretched across three consecutive days. Though Isner ultimately prevailed 70-68 in the fifth set, some in attendance half-jokingly wondered at the time whether the two men might be trapped on that court for eternity. A similarly endless-seeming skirmish of rackets is currently unfolding just an hour's drive south of the All England Club -- at Google DeepMind. Known for pioneering AI models that have outperformed the best human players at chess and Go, DeepMind now has a pair of robotic arms engaged in a kind of infinite game of table tennis. The goal of this ongoing research project, which began in 2022, is for the two robots to continuously learn from each other through competition. Just as Isner eventually adapted his game to beat Mahut, each robotic arm uses AI models to shift strategies and improve. But unlike the Wimbledon example, there's no final score the robots can reach to end their slugfest. Instead, they continue to compete indefinitely, with the aim of improving at every swing along the way. And while the robotic arms are easily beaten by advanced human players, they've been shown to dominate beginners. Against intermediate players, the robots have roughly 50/50 odds -- placing them, according to researchers, at a level of "solidly amateur human performance." All of this, as two researchers involved noted this week in an IEEE Spectrum blog, is being done in hopes of creating an advanced, general-purpose AI model that could serve as the "brains" of humanoid robots that may one day interact with people in real-world factories, homes, and beyond. Researchers at DeepMind and elsewhere are hopeful that this learning method, if scaled up, could spark a "ChatGPT moment" for robotics -- fast-tracking the field from stumbling, awkward hunks of metal to truly useful assistants. "We are optimistic that continued research in this direction will lead to more capable, adaptable machines that can learn the diverse skills needed to operate effectively and safely in our unstructured world," DeepMind senior staff engineer Pannag Sanketi and Arizona State University Professor Heni Ben Amor write in IEEE Spectrum.

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Surface, connectivité, relief, obstacles, entretien : les critères à prendre en compte lors de l'achat d'un robot tondeuse sont nombreux. On vous aide à y voir plus clair.

Cet article a été réalisé en collaboration avec Lymow

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An anonymous reader quotes a report from The Guardian: Automated surgery could be trialled on humans within a decade, say researchers, after an AI-trained robot armed with tools to cut, clip and grab soft tissue successfully removed pig gall bladders without human help. The robot surgeons were schooled on video footage of human medics conducting operations using organs taken from dead pigs. In an apparent research breakthrough, eight operations were conducted on pig organs with a 100% success rate by a team led by experts at Johns Hopkins University in Baltimore in the US. [...] The technology allowing robots to handle complex soft tissues such as gallbladders, which release bile to aid digestion, is rooted in the same type of computerized neural networks that underpin widely used artificial intelligence tools such as Chat GPT or Google Gemini. The surgical robots were slightly slower than human doctors but they were less jerky and plotted shorter trajectories between tasks. The robots were also able to repeatedly correct mistakes as they went along, asked for different tools and adapted to anatomical variation, according to a peer-reviewed paper published in the journal Science Robotics. The authors from Johns Hopkins, Stanford and Columbia universities called it "a milestone toward clinical deployment of autonomous surgical systems." [...] In the Johns Hopkins trial, the robots took just over five minutes to carry out the operation, which required 17 steps including cutting the gallbladder away from its connection to the liver, applying six clips in a specific order and removing the organ. The robots on average corrected course without any human help six times in each operation. "We were able to perform a surgical procedure with a really high level of autonomy," said Axel Krieger, assistant professor of mechanical engineering at Johns Hopkins. "In prior work, we were able to do some surgical tasks like suturing. What we've done here is really a full procedure. We have done this on eight gallbladders, where the robot was able to perform precisely the clipping and cutting step of gallbladder removal without any human intervention. "So I think it's a really big landmark study that such a difficult soft tissue surgery is possible to do autonomously." Currently, nearly all of the NHS's 70,000 annual robotic surgeries are human-controlled, but the UK plans to expand robot-assisted procedures to 90% within the next decade.

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An anonymous reader quotes a report from VentureBeat: Hugging Face, the $4.5 billion artificial intelligence platform that has become the GitHub of machine learning, announced Tuesday the launch of Reachy Mini, a $299 desktop robot designed to bring AI-powered robotics to millions of developers worldwide. The 11-inch humanoid companion represents the company's boldest move yet to democratize robotics development and challenge the industry's traditional closed-source, high-cost model. The announcement comes as Hugging Face crosses a significant milestone of 10 million AI builders using its platform, with CEO Clement Delangue revealing in an exclusive interview that "more and more of them are building in relation to robotics." The compact robot, which can sit on any desk next to a laptop, addresses what Delangue calls a fundamental barrier in robotics development: accessibility. "One of the challenges with robotics is that you know you can't just build on your laptop. You need to have some sort of robotics partner to help in your building, and most people won't be able to buy $70,000 robots," Delangue explained, referring to traditional industrial robotics systems and even newer humanoid robots like Tesla's Optimus, which is expected to cost $20,000-$30,000. Reachy Mini emerges from Hugging Face's April acquisition of French robotics startup Pollen Robotics, marking the company's most significant hardware expansion since its founding. The robot represents the first consumer product to integrate natively with the Hugging Face Hub, allowing developers to access thousands of pre-built AI models and share robotics applications through the platform's "Spaces" feature. [...] Reachy Mini packs sophisticated capabilities into its compact form factor. The robot features six degrees of freedom in its moving head, full body rotation, animated antennas, a wide-angle camera, multiple microphones, and a 5-watt speaker. The wireless version includes a Raspberry Pi 5 computer and battery, making it fully autonomous. The robot ships as a DIY kit and can be programmed in Python, with JavaScript and Scratch support planned. Pre-installed demonstration applications include face and hand tracking, smart companion features, and dancing moves. Developers can create and share new applications through Hugging Face's Spaces platform, potentially creating what Delangue envisions as "thousands, tens of thousands, millions of apps." Reachy Mini's $299 price point could significantly transform robotics education and research. "Universities, coding bootcamps, and individual learners could use the platform to explore robotics concepts without requiring expensive laboratory equipment," reports VentureBeat. "The open-source nature enables educational institutions to modify hardware and software to suit specific curricula. Students could progress from basic programming exercises to sophisticated AI applications using the same platform, potentially accelerating robotics education and workforce development." "... For the first time, a major AI platform is betting that the future of robotics belongs not in corporate research labs, but in the hands of millions of individual developers armed with affordable, open-source tools."

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An anonymous reader quotes a report from The Guardian: Swarms of tiny robots, each no larger than a speck of dust, could be deployed to cure stubborn infected sinuses before being blown out through the nose into a tissue, researchers have claimed. The micro-robots are a fraction of the width of a human hair and have been inserted successfully into animal sinuses in pre-clinical trials by researchers at universities in China and Hong Kong. Swarms are injected into the sinus cavity via a duct threaded through the nostril and guided to their target by electromagnetism, where they can be made to heat up and catalyze chemical reactions to wipe out bacterial infections. There are hopes the precisely targeted technology could eventually reduce reliance on antibiotics and other generalized medicines. [...] The latest breakthrough, based on animal rather than human trials, involves magnetic particles "doped" with copper atoms which clinicians insert with a catheter before guiding to their target under a magnetic field. The swarms can be heated up by reacting to light from an optical fibre that is also inserted into the body as part of the therapy. This allows the micro-robots to loosen up and penetrate viscous pus that forms a barrier to the infection site. The light source also prompts the micro-robots to disrupt bacterial cell walls and release reactive oxygen species that kill the bacteria. The study, published in Nature Robotics, showed the robots were capable of eradicating bacteria from pig sinuses and could clear infections in live rabbits with "no obvious tissue damage." The researchers have produced a model of how the technology could work on a human being, with the robot swarms being deployed in operating theatre conditions, allowing doctors to see their progress by using X-rays. Future applications could include tackling bacterial infections of the respiratory tract, stomach, intestine, bladder and urethra, they suggested. "Our proposed micro-robotic therapeutic platform offers the advantages of non-invasiveness, minimal resistance, and drug-free intervention," they said.

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Google DeepMind has launched Gemini Robotics On-Device, a new language model that enables robots to perform complex tasks locally without internet connectivity. TechCrunch reports: Building on the company's previous Gemini Robotics model that was released in March, Gemini Robotics On-Device can control a robot's movements. Developers can control and fine-tune the model to suit various needs using natural language prompts. In benchmarks, Google claims the model performs at a level close to the cloud-based Gemini Robotics model. The company says it outperforms other on-device models in general benchmarks, though it didn't name those models. In a demo, the company showed robots running this local model doing things like unzipping bags and folding clothes. Google says that while the model was trained for ALOHA robots, it later adapted it to work on a bi-arm Franka FR3 robot and the Apollo humanoid robot by Apptronik. Google claims the bi-arm Franka FR3 was successful in tackling scenarios and objects it hadn't "seen" before, like doing assembly on an industrial belt. Google DeepMind is also releasing a Gemini Robotics SDK. The company said developers can show robots 50 to 100 demonstrations of tasks to train them on new tasks using these models on the MuJoCo physics simulator.

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