Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Ai2 Releases ‘MolmoAct 2’ Open-Source Foundation Model for Robots
The Allen Institute for AI (Ai2) has unveiled a new open-source robotics model and an extensive training dataset, aimed at enhancing the ability of robots to execute physical tasks in real-world settings. Named MolmoAct 2, this updated system is specifically designed to improve robots' comprehension of spatial environments and their responsiveness to instructions. The initiative reflects Ai2's commitment to advancing robotics technology and making it more accessible for developers and researchers. By providing this resource, Ai2 hopes to facilitate innovations in robotic applications across various industries.
AI AI Research & Advances Robotics Ai2 Allen Institute for AI Cortex AI
Stanford’s new iISM microscope images living cells at 120-nanometer resolution
Researchers at Stanford University have developed an innovative microscope that can image nanostructures within living cells, marking a significant advancement in cellular imaging technology. This breakthrough was announced in October 2023 and aims to enhance our understanding of cellular processes at the nanoscale. By enabling scientists to observe these structures in real-time, the new microscope offers insights into cellular functions and interactions that were previously difficult to study. The motivation behind this development is to provide a more detailed view of cellular mechanisms, which could lead to advancements in medical research and treatments. The microscope employs advanced imaging techniques that allow for high-resolution visualization of nanostructures, paving the way for new discoveries in biology and medicine.
Stanford’s tiny eye chip helps the blind see again
Researchers at Stanford Medicine have made significant strides in restoring reading ability for individuals suffering from advanced macular degeneration through a groundbreaking wireless eye implant. The innovative device, known as the PRIMA chip, operates in conjunction with smart glasses to replace damaged photoreceptors using infrared light. In clinical trials, the majority of participants experienced a remarkable improvement in their vision, enabling them to read books and recognize signs. Encouraged by these results, the research team is now focused on developing higher-resolution versions of the implant, with the goal of eventually providing users with near-normal sight.
Robot learns to play music by ear, opening new possibilities in medicine and therapy
Researchers at the USC Viterbi School of Engineering have unveiled an innovative robotic hand capable of learning and reproducing melodies. This advanced technology can listen to a tune just once and, after a brief two-minute period of self-directed practice on a keyboard, accurately play it back without the need for sheet music or preprogrammed instructions. The development highlights significant progress in the field of robotics and artificial intelligence, showcasing the potential for machines to learn and adapt in ways similar to humans. This breakthrough could pave the way for more sophisticated applications in music and other areas requiring fine motor skills and auditory recognition.
Robotics
What Makes AI Art Worth Collecting?
In May, an anonymous artist who goes by SHL0MS on X posted that he had used AI to generate an image inspired by Claude Monet and asked people to weigh in on how it missed the mark. More than 600 responses called out issues, saying the colors were off, the depth was all wrong, and that AI didn’t understand how light worked.SHL0MS then revealed that the image was of a real Monet, one of around 250 variations of water lilies the artist had painted in his lifetime. He had simply downloaded a high-resolution image from Wikimedia and cropped out the signature. He minted the exchange as an NFT (a unique digital collectible recording ownership of the work), titled it “Inferior Image,” and sold it for just over US $40,000 after 28 bids.The stunt exposed how charged the conversation around AI art has become, and how quick people are to dismiss anything AI-generated as slop—even when it’s not. Yet even as those arguments continue, a market for AI-generated art has begun to form anyway. It’s fragmented and contested, but bigger than most people realize.Jediwolf, an anonymous collector who says he has spent more than 20 years acquiring digital and AI art, was watching the experiment unfold in real time on X. He had never interacted with SHL0MS before, but when the NFT went up for auction he made a bid and won. “I was buying a unique moment in time,” he says, “captured by an artist and preserved as a token.”The Monet was not AI art, but most of what Jediwolf buys is. One of Jediwolf’s digital collections, which he calls UnderTheGAN—a play on GANs, or generative adversarial networks, the AI technology that preceded today’s diffusion models—comprises roughly 100 works valued at around $72,000, focused on early AI art from 2015 to 2020, before the medium went mainstream. He describes his role as part collector, part researcher, part curator, trying to document a fast-moving field.“A decade ago, digital art was often treated as peripheral to the ‘serious’ art world,” he says. “Today, it is increasingly difficult to separate contemporary culture from the internet.”AI Art Moves Into MuseumsThe market for AI art extends beyond NFTs: AI-generated pieces are also finding their way into physical installations. Last month saw the opening of Dataland, the world’s first generative AI museum, in downtown Los Angeles. It was spearheaded by Refik Anadol, a digital artist who has built a career out of transforming data into large-scale immersive experiences. The opening exhibition has pieces that use data that Anadol collected from rainforests around the world, with real-time weather information from 16 rainforests feeding into all five galleries. In three of the rooms, the imagery also shifts in response to visitors’ own biometric data, tracked by bracelets they wear. Like any museum it sells tickets, ranging from $49 to $79, and has a gift shop. This shop, however, uses visitors’ biometric data collected during their visit to generate a unique design printed on a T-shirt. For $15,000, a robotic painting system called Qualia creates a one-of-a-kind canvas from that same data, painted once a day, with a waiting list already forming. A founding collection of 1,000 AI data sculptures that evolve based on environmental data from global rainforests sold out in 34 minutes at $5,000 each.The system running it all, which Anadol calls the Large Nature Model, was trained on more than 500 million nature images representing 2.2 million species, gathered through field expeditions to 16 rainforests and partnerships with institutions including the Smithsonian and the Cornell Lab of Ornithology.For Anadol, AI art requires a different kind of transparency than any medium that came before it. Because commercial AI tools have shaped how most people understand the technology, artists working with it seriously have to be more open about their process than painters or photographers ever did.“For AI art, we have to know where the data comes from, we have to know which model is trained and how it’s trained,” he says. “We can’t just think about authenticity and uniqueness if a service and product is the fundamental layer of the artwork.”The reviews for Dataland have mostly been positive, with one critic calling it the Citizen Kane of immersive experiences. But Anadol is used to a more divided reception. His 2022 installation at MoMA—a 7-by-7-meter screen of AI-generated fluid forms with shifting colors and sounds—drew 3 million visitors and entered the permanent collection, even as New York Magazine called it “a massive techno lava lamp.” Anadol sees the skepticism as nothing new, just the latest version of a resistance that has greeted all new media. “Every art form has gone through similar cycles of denial,” he says. “We are living in a renaissance that started 10 years ago, and I just don’t think everyone is aware of it yet.”Who Is Buying AI Art?The broader market data points in multiple directions at once. According to the Art Basel and UBS Art Market Report 2026, digital art’s share of sales nearly tripled between 2024 and 2025, and just over half of all fine art collectors surveyed had purchased a digital artwork in 2025, making it the third most popular category after painting and sculpture (the report does not break out AI art specifically).Meanwhile, Christie’s shuttered its pioneering digital art department in September, folding digital works back into its broader contemporary sales after none of its dedicated auctions broke $400,000.The most data-rich window into buyer behavior comes from a less glamorous corner of the market. After one major stock image platform allowed AI-generated images, monthly sales jumped 80 percent, according to Samuel Goldberg, an economist at Stanford Graduate School of Business who published a research paper about the shift. Traditional contributors began leaving the platform as generative images flooded in, and creators using AI tools rushed to fill the gap. “It looks like consumers like generative AI,” Goldberg says, “and it seems like nongenerative artists could be getting crowded out of the market.” Stock images are essentially a commodity version of art, according to Goldberg, and because image-generating models are already very good at producing them, what’s happening there may be a preview of what’s coming for other creative goods markets—including fine arts—as the technology improves.Artists are typically among the first to test the limits of a new technology; early adopters have created AI art since the 1970s. What’s new now is the ability for anyone to generate an image in seconds with a text prompt. That, according to Christiane Paul, curator of digital art at the Whitney Museum of American Art, is not the same thing at all. What fills those stock-image platforms, and what most people encounter when they think of AI art, does not qualify as art.True AI art, Paul says, is a subcategory of digital art that uses artificial intelligence as both a tool and a medium, engaging with it practically and conceptually, doing things like training custom models, building extensions, and layering control systems. “A visual created by a prompt is not art,” she says. What serious AI artists are actually doing is much more than typing a few words into DALL-E.Far from the shortcut most people assume, working seriously with AI as an artistic medium is, by her account, brutally hard. Every artist she talks to says the same thing. “It is much, much harder than a paintbrush to handle,” she says. “You are literally communicating with a system with a completely different logic.”Thanks to bubblemaps.io for its research assistance on the NFT market.
Ai-art Generative-ai Digital-art Blockchain
Can AI Chatbots Reason Like Doctors?
A recent study published on April 30 in the journal Science reveals that OpenAI's large language model (LLM) has outperformed physicians in clinical reasoning tasks using real emergency room records. This research comes amid growing scrutiny of the reliability of medical information provided by chatbots, with some studies highlighting impressive diagnostic capabilities while others point to inaccuracies and fabricated information. OpenAI has introduced tools like ChatGPT for Clinicians and ChatGPT for Healthcare, aiming to assist medical professionals. The study involved comparing the performance of the LLM with that of physicians during various stages of emergency care, demonstrating that the AI model consistently provided accurate or close diagnoses more frequently than human doctors. Despite the promising results, researchers, including coauthor Arjun Manrai from Harvard Medical School, caution against interpreting these findings as a signal that AI could replace doctors. Instead, they emphasize the need for further research and clinical trials to explore how LLMs can be effectively integrated into medical practice. Experts like Mickael Tordjman from the Icahn School of Medicine stress the importance of developing reliable evaluation methods for LLMs in clinical settings. As the technology evolves rapidly, there is an urgent need to address regulatory and liability questions surrounding its use in healthcare. While acknowledging the potential benefits of AI in medicine, researchers advocate for responsible innovation and careful evaluation to ensure patient safety and effective integration into clinical workflows.
Large-language-models Llms Chatbots Medical-ai Ai-safety Openai
US’ heat-activated knot robots leap hundreds of times their height without electronics
Researchers at the University of Pennsylvania's School of Engineering have developed an innovative heat-activated robot using a common nuisance: a knotted string. This groundbreaking project, unveiled recently, showcases the potential of transforming everyday materials into advanced robotic systems. The team aimed to explore new avenues in robotics by harnessing the unique properties of strings that can change shape and function when exposed to heat. By strategically manipulating the knots and applying thermal energy, the researchers were able to create a robot capable of performing various tasks, demonstrating versatility and efficiency. This advancement not only highlights the ingenuity of the engineering team but also opens up new possibilities for the application of soft robotics in diverse fields, including medicine and manufacturing. The research reflects a growing trend in the engineering community to utilize unconventional materials for innovative solutions, emphasizing the importance of creativity in technological development.
Robotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
