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There’s a mathematical concept called the ‘kissing number.’ Somewhat disappointingly, it’s got nothing to do with actual kissing; It enumerates how many spheres can touch (or ‘kiss’) a single sphere of equal size without crossing it. In one dimension, the kissing number is two. In two dimensions it’s 6 (think the New York Times’ spelling bee puzzle configuration). As the number of dimensions grows, the answer becomes less obvious: For most dimensionalities over 4, only upper and lower bounds on the kissing number are known. Now, an AI agent developed by Google DeepMind called AlphaEvolve has made its contribution to the problem, increasing the lower bound on the kissing number in 11 dimensions from 592 to 593.This may seem like an incremental improvement on the problem, especially given that the upper bound on the kissing number in 11 dimensions is 868, so the unknown range is still quite large. But it represents a novel mathematical discovery by an AI agent, and challenges the idea that large language models are not capable of original scientific contributions. And this is just one example of what AlphaEvolve has accomplished. “We applied AlphaEvolve across a range of open problems in research mathematics, and we deliberately picked problems from different parts of math: analysis, combinatorics, geometry,” says Matej Balog, a research scientist at DeepMind that worked on the project. They found that for 75 percent of the problems, the AI model replicated the already known optimal solution. In 20 percent of cases, it found a new optimum that surpassed any known solution. “Every single such case is a new discovery,” Balog says. (In the other 5 percent of cases, the AI converged on a solution that was worse than the known optimal one.)The model also developed a new algorithm for matrix multiplication—the operation that underlies much of machine learning. A previous version of DeepMind’s AI model, called AlphaTensor, had already beat the previous best known algorithm, discovered in 1969, for multiplying 4 by 4 matrices. AlphaEvolve found a more general version of that improved algorithm. DeepMind’s AlphaEvolve made improvements to […]

Humans are messy. We spill drinks, smudge screens, and bring our electronic devices into countless sticky situations. As anyone who has accidentally dropped their phone into a toilet or pool knows, moisture poses a particular problem. And it’s not a new one: From early telephones to modern cellphones, everyday liquids have frequently conflicted with devices that must stay dry. Consumers often take the blame when leaks and spills inevitably occur. Rachel Plotnick, an associate professor of cinema and media studies at Indiana University Bloomington, studies the relationship between technology and society. Last year, she spoke to IEEE Spectrum about her research on how people interact with buttons and tactile controls. In her new book, License to Spill: Where Dry Devices Meet Liquid Lives (The MIT Press, 2025), Plotnick explores the dynamic between everyday wetness and media devices through historical and contemporary examples, including cameras, vinyl records, and laptops. This adapted excerpt looks back at analog telephones of the 1910s through 1930s, the common practices that interrupted service, and the “trouble men” who were sent to repair phones and reform messy users. Mothers never liked to blame their babies for failed telephone service. After all, what harm could a bit of saliva do? Yet in the early decades of the 20th century, reports of liquid-gone-wrong with telephones reached the pages of popular women’s magazines and big-city newspapers as evidence of basic troubles that could befall consistent service. Teething babies were particularly called out. The Boston Daily Globe in 1908 recounted, for instance, how a mother only learned her lesson about her baby’s cord chewing when the baby received a shock—or “got stung”—and the phone service went out. These youthful oral fixations rarely caused harm to the chewer, but were “injurious” to the telephone cord. License to Spill is Rachel Plotnick’s second book. Her first, Power Button: A History of Pleasure, Panic, and the Politics of Pushing (The MIT Press, 2018), explores the history and politics of push buttons. The MIT Press As more Americans encountered telephones in […]

By 2030, there will be a global shortage of 85 million workers, many of them in technical fields, according to the World Economic Forum. Many industries that need to employ technical workers will be impacted by the shortage, which is projected to cost them up to US $8.5 trillion in unrealized revenue. Many technical roles now require university degrees. However, as companies consider how to overcome the worker shortage, some are reevaluating their higher education requirements for certain roles requiring specialized skills. Those jobs might include technician, electrician, and programmer, along with other positions that compose the skilled technical workforce, as described by SRI International’s Center for Innovation Strategy and Policy. Positions that don’t require higher education widen the pool of candidates. Even if they eliminate the need for a degree, organizations will still need to rely on some kind of credential to ensure that job candidates have the skills necessary to do the job. One option is the skills-based microcredential. Microcredentials are issued when learners prove mastery of a specific skill. Unlike traditional university degrees and course certificates, microcredential programs are not based on successfully completing a full learning program. Instead, a student might earn multiple microcredentials in a single program based on demonstrated skills. A qualified instructor using an assessment instrument determines if a learner has acquired the skill and earned the credential. The IEEE microcredentials program offers standardized credentials in collaboration with training organizations and universities seeking to provide skills-based credentials outside formal degree programs. IEEE, as the world’s largest technical professional organization, has decades of experience offering industry-relevant credentials and expertise in global standardization. A seal of approval IEEE microcredentials are industry-driven professional credentials that focus on needed skills. The program allows technical learning providers to supply credentials that bear the IEEE logo. When a hiring organization sees the logo on a microcredential, it confirms […]

Researchers who are developing electrolyzers for hydrogen production are increasingly turning to a membrane platform originally used in fuel cells to scale up their technology. Their strategy: use anion-exchange membranes, which could be more cost-effective and combine the best features of conventional proton-exchange membranes and alkaline approaches. Anion-exchange membrane (AEM) technology enables the selective transport of negatively charged ions between cathode and anode. In a hydrogen fuel cell, the membrane helps facilitate the chemical reactions needed to generate electricity. In hydrogen electrolysis, the membrane helps split water by separating hydrogen from oxygen. So far, AEM has only been deployed at a small scale. But several renewable hydrogen companies are poised to change that. On 7 May, Ithaca, N.Y.–based Ecolectro announced a partnership with Framingham, Mass.–based Re:Build Manufacturing to deploy advanced AEM electrolyzers in the United States. And in March the French tire company Michelin and several French research institutions launched a multiyear collaboration to develop more durable versions of these membranes as part of Michelin’s expansion into renewable markets.These companies, and several others globally, are betting on AEM technology to fulfill the long-sought promise of “green” hydrogen produced with renewable energy. “This has long been considered the potential savior to a lot of issues with other types of electrolysis that we’ve been trying to scale,” says Lindsey Motlow, a physicist and research director at Darcy Partners, a market intelligence firm in Houston.Challenges in Scaling Green HydrogenScaling up green hydrogen comes with challenges that have rendered it less competitive than other hydrogen production methods. The field relies on electrolyzers, which use electricity to split water molecules to release hydrogen. Most employ either a proton-exchange membrane (PEM), which uses precious metal catalysts and polymer membranes to split the molecules, or alkaline electrolysis, which works with an electrolyte solution.PEM can quickly ramp up and down in response to variable energy sources like wind and solar […]

The main assumption about humanoid robotics that the industry is making right now is that the most realistic near-term pathway to actually making money is in either warehouses or factories. It’s easy to see where this assumption comes from: Repetitive tasks requiring strength or flexibility in well-structured environments is one place where it really seems like robots could thrive, and if you need to make billions of dollars (because somehow that’s how much your company is valued at), it doesn’t appear as though there are a lot of other good options.Cartwheel Robotics is trying to do something different with humanoids. Cartwheel is more interested in building robots that people can connect with, with the eventual goal of general-purpose home companionship. Founder Scott LaValley describes Cartwheel’s robot as “a small, friendly humanoid robot designed to bring joy, warmth, and a bit of everyday magic into the spaces we live in. It’s expressive, emotionally intelligent, and full of personality—not just a piece of technology but a presence you can feel.” This rendering shows the design and scale of Cartwheel’s humanoid prototype.CartwheelHistorically, making a commercially viable social robot is a huge challenge. A little less than a decade ago, a series of social home robots (backed by a substantial amount of investment) tried very, very hard to justify themselves to consumers and did not succeed. Whether the fundamental problems with the concept of social home robots (namely, cost and interactive novelty) have been solved at this point isn’t totally clear, but Cartwheel is making things even more difficult for themselves by going the humanoid route, legs and all. That means dealing with all kinds of problems from motion planning to balancing to safety, all in a way that’s reliable enough for the robot to operate around children.LaValley is arguably one of the few people who could plausibly make a commercial social humanoid actually happen. His extensive background in humanoid robotics includes nearly a decade at Boston Dynamics working on the Atlas robots, followed by five years at Disney, where he led the team that developed Disney’s […]