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2026 College of Engineering, Computing and Applied Sciences faculty promotion
At the beginning of the Fall semester, the University announced the tenure and promotion of 20 faculty in the College of Engineering, Computing and
U.Va. expands Fontaine data center plans
The University of Virginia is expanding its Fontaine Data Center in Charlottesville with a revised $102 million budget to support UVa Health and research computing.
Does Computer Science Need Computers?
The theoretical side of the field doesn’t require computing machines. But many questions would never have been posed without them.
Cloud AI Today - Cloud Gaming Thrives as 5G Fuels Traveler Entertainment
The cloud gaming sector is poised for substantial growth, particularly within the traveler segment, as advancements in 5G technology, edge computing, and increased travel fuel demand for entertainment on the go. Projections indicate the market will grow from $3.2 billion in 2025 to $4.1 billion in 2026, with expectations to reach $11.03 billion by 2030. This expansion is driven by factors such as enhanced mobile connectivity, widespread adoption of portable gaming devices, and rising interest...
How Innovation Could Reshape Chemistry by 2050
Chemistry and chemical engineering are fundamental to technologies that could revolutionize energy production, quantum computing, and materials and manufacturing over the coming decades. At a recent workshop, participants from academia, industry, and government considered the future of the chemical sciences, exploring scientific challenges that researchers should prioritize, where strategic investments could enable breakthroughs, and how the chemical sciences community can prepare for emerging capabilities.
Building a nation: How Clemson University engineers and scientists helped shape America
As America marks its 250th year, the College of Engineering, Computing and Applied Sciences reflects on Clemson’s role in shaping the nation — and the work still ahead.
College of Information Sciences and Technology welcomes six new faculty members
Six new faculty members recently joined the College of Information Sciences and Technology, representing the college's Department of Human-Centered Computing and Social Informatics, Department of Informatics and Intelligent Systems and Department of Privacy and Cybersecurity Informatics.
How the Advanced Light Source Is Accelerating Our Quantum Future
For over 30 years, scientists at Berkeley Lab’s Advanced Light Source have played a vital role in the advancement of new materials for quantum computing, next-generation electronics, and other quantum technologies of the future.
McVey Center and Computing Innovation Take Flight
Through the McVey Center, Colby accelerates its mission to integrate high-performance computing and data science across the liberal arts
'It's very counterintuitive': This quantum battery upends the rules of charging
The world's first quantum battery prototype is here and it has some bizarre properties. Could these devices one day power quantum computing – or even your phone?
'It's very counterintuitive': This quantum battery upends the rules of charging
The world's first quantum battery prototype is here and it has some bizarre properties. Could these devices one day power quantum computing – or even your phone?
Scientists discover asymmetric diffusion of magnetic skyrmions in simulations
Magnetic skyrmions are nanoscale spin textures that can behave like particles and move and diffuse in real space. This makes them promising information carriers for future memory and computing technologies. A new computational study in npj Spintronics shows how geometry and topology can guide asymmetric thermal diffusion of magnetic skyrmions, offering insights for unlocking unconventional computing paradigms, including future stochastic and neuromorphic computing devices for more efficient artificial intelligence (AI) applications.
Alibaba set to open down 8% in Hong Kong after $10.2 billion share placement plan
Hong Kong-listed shares of Alibaba are set to open 8% lower on Monday after the Chinese e-commerce and cloud computing giant launched a $10.2 billion share placement to fund AI development.
How to decipher smells like a fruit fly
In the animal kingdom, energy conservation is essential for survival. That’s why our brains have evolved to be extremely energy and resource efficient at storing and processing information. Since the 1980s, computational scientists have tried to mimic brain structure and function, but have not yet succeeded in creating functional, low-memory solutions that work in real-world scenarios. Published in Neuromorphic Computing & Engineering, a new fly brain-inspired algorithm developed by researchers at the Okinawa Institute of Science and Technology (OIST) demonstrates promise for achieving practical applications under realistic constraints.
Calvin University Launches New School of Computer Science
After consolidating several programs last year, a private Christian university in Grand Rapids, Mich., is launching a new school to enhance offerings in fields like AI, advanced computing and cybersecurity.
EBU and Superpositions Partner to Add Quantum Computing to Business Education
EBU and Superpositions are partnering to add quantum computing courses to business education through EBU’s new Q-Ready initiative.
Layoffs in Apple's Vision Products Group prove slow progress in spatial computing
A source has exclusively revealed to us that Apple has just laid off an unknown number of people dedicated to VR development, which aligns with incoming CEO John Ternus reportedly putting the category "on ice."
Trump keeps embracing data centers, an unpopular topic in midterm races
The race to build data centers, which power artificial intelligence and cloud computing, has run aground amid frustration from voters who don't want to live near the massive warehouse campuses.
Businesses Are Spending Big on Quantum
Many companies are pouring millions into quantum computing programs to gain a competitive edge and prepare for future encryption threats.
Florida State University Launches Quantum Science and Technology Graduate Certificate
Florida State University launches a graduate certificate in quantum science and technology covering quantum computing and engineering.
New AI technique helps robots complete tasks twice as fast by letting them 'think ahead'
A new AI system lets robots plan their next move while they're in motion — removing reaction delays and doubling task speeds without any extra computing overhead.
UCR researchers join DOE effort to speed scientific discovery
Two UC Riverside computer scientists are joining federally funded projects that use artificial intelligence to accelerate scientific discovery. Their work will focus on making quantum computing faster and more reliable and building smarter networks for sharing scientific data and research resources.
Qunova Appoints CFO and Two Business Development Executives
Qunova Computing appoints Jake Hwang as CFO and adds Evan Kang and Woomin Kyoung to expand quantum software commercialization.
USC Scientists Are Using Quantum Computing to Rethink Cancer Detection - USC Viterbi
By combining quantum computing with artificial intelligence, USC researchers are laying the groundwork for medical imaging tools that could help doctors diagnose cancer and plan treatments more precisely
Quantum trade moves beyond science fiction: AlphaCheck
Two newly public quantum computing companies are about to report earnings. Their results will test the appetite for the budding technology that has captivated some corners on Wall Street.
Scientific advancement has never been more prolific—so why has trust in science plummeted?
From genome editing to quantum computing, scientific progress is accelerating at an unprecedented pace, yet public faith in science is collapsing. Our species has mapped the human genome, created powerful ...
Quantum Computing Inc. Revenue Jumps as Acquisitions Expand Commercial Business
Quantum Computing Inc. reported $5.6 million in second-quarter revenue, largely driven by acquired businesses.
Scientists Release Biggest 2D Map of the Universe
Key Takeaways The DESI Legacy Imaging Surveys combined more than 263,000 telescope exposures to make the largest 2D map of the universe in visible and near-infrared light. Astronomers can pair the Legacy Surveys map with their own observations to explore our universe and search for rare phenomena. The 2D map serves as the foundation for the Dark Energy Spectroscopic Instrument survey to measure the universe in 3D and investigate dark energy. Hold on to your telescopes: the DESI Legacy Imaging Surveys team has released the largest-ever 2D color map of the universe. The 5.6-trillion-pixel map contains nearly 4 billion celestial objects, primarily stars and galaxies. The data is available for all to use and publicly viewable through the Legacy Survey Sky Viewer. Astronomers and citizen scientists can explore the map or combine it with their own observations to better understand our universe. Researchers can search for rare phenomena like gravitational lenses, observe fleeting events like supernovae, and investigate two of physics’ biggest mysteries: dark matter, the invisible substance that accounts for most of the mass in our universe, and dark energy, the force driving our universe’s accelerating expansion. The new map builds on earlier versions from the DESI Legacy Imaging Surveys that have already proved invaluable. To date, more than 1,800 science papers that reference the Legacy Surveys data have been published. “It’s part of the fabric of astronomy research now,” said David Schlegel, a co-lead of the Legacy Surveys and scientist at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab). “When you’re working with astronomical objects today, you often start by pulling up the Legacy Imaging Viewer to see what you’re looking at.” Covering roughly 75% of the sky in visible and near-infrared light, the updated map provides a deep view of the extragalactic universe not blocked by the dust and stars of our own Milky Way. Researchers expect it will remain the most comprehensive 2D map of our universe for years to come. More than 160 scientists contributed to data collection for the project, and a team of 20 produced the final dataset released today. It was built by combining 263,407 telescope exposures from three ground-based sky surveys: the Dark Energy Camera Legacy Survey (DECaLS) at NSF Cerro Tololo Inter-American Observatory, the Mayall z-band Legacy Survey (MzLS) at NSF Kitt Peak National Observatory, and the Beijing-Arizona Sky Survey (BASS) at the University of Arizona’s Steward Observatory. That was supplemented by years of data from NASA’s Wide-field Infrared Survey Explorer (WISE) satellite mission and additional public data. “For our team, these data are fundamental to our investigation of the expansion history of the universe and the formation of our galaxy,” said Arjun Dey, co-lead of the Legacy Surveys and an astronomer at NSF NOIRLab. “But the skies belong to everyone, and this survey gives everyone the chance to explore the sky and marvel at its wonders.” Here be galaxies The DESI Legacy Imaging Surveys were originally conducted to prepare for the Dark Energy Spectroscopic Instrument (DESI) survey. The Legacy Surveys’ 2D map is essentially a deep photograph of the sky; it records where galaxies and stars appear and how bright they appear. This crucial step enables DESI to select objects and measure their light in different wavelengths to determine their distances, building the largest high-resolution 3D map ever made. Scientists study the way galaxies have clustered at different ages of the universe to track dark energy over time. In April 2026, DESI completed its original five-year survey ahead of schedule and with vastly more objects than expected. The early results have shown surprising hints that dark energy’s impact may be weakening over time — a paradigm shift that could potentially shape the predicted fate of our universe. DESI expects to publish improved results using their first five years of data in 2027 and is continuing observations into 2028. DESI was so efficient at observing galaxies, the Legacy Surveys map needed to expand. Early on, “it became clear we might run out of galaxies to look at and run out of sky, and we better start doing something about that,” said Schlegel, who also works on DESI. The new Legacy Surveys map has been used to select DESI targets since June 2026 and will guide the telescope’s operations over the coming years. Computing the cosmos Merging hundreds of thousands of images taken on 2,285 nights, each with unique atmospheric and telescope conditions, was a massive computational effort. It took about a year to develop the computer code and eight weeks to process all the images at the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab. Beyond supporting DESI, the Legacy Surveys will be a foundational reference for the next generation of telescopes. As new observatories like the NSF-DOE Vera C. Rubin Observatory (jointly funded by NSF and DOE’s Office of Science) and NASA’s Nancy Grace Roman Space Telescope come online, researchers can compare their observations with one of the deepest and most comprehensive views of the sky ever assembled. The Legacy Surveys data will also help scientists train artificial intelligence tools to analyze petabytes of astronomical data and accelerate new discoveries. It will be among the datasets used in an astrophysics pilot project within the American Science Cloud, part of the DOE’s Genesis Mission. The DESI Legacy Imaging Surveys are supported by the U.S. Department of Energy’s Office of High Energy Physics; the National Energy Research Scientific Computing Center, a DOE Office of Science user facility; the U.S. National Science Foundation, Division of Astronomical Sciences; and the partner institutions. DESI is supported by the DOE Office of Science and NERSC. Additional support for DESI is provided by the NSF; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the Secretariat of Science, Humanities, Technology and Innovation (SECIHTI) of Mexico; the Ministry of Science and Innovation of Spain; and by the DESI member institutions. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
Accelerating life science computing with AI-ready infrastructure
Discover how computing is transforming life science research through AI infrastructure, GPU acceleration, and genomics.
Computer Science Professor Wei Wang Receives ACM Innovation Award
Wei Wang, a professor and chair of the Computer Science Department at the UCLA Samueli School of Engineering, has received the Innovation Award from the Association for Computing Machinery, the world’s largest professional computing society
Cloudflare launches Kitesurf, a browser built for AI agents
Cloudflare has introduced Kitesurf, a cloud-hosted browser designed for AI agents instead of people. The company says the browser uses less computing power than Chromium for common automation tasks, helping developers build browser-based AI agents more efficiently.
Sunlight creates quantum entanglement once thought to require lasers
Scientists have generated quantum entanglement directly from sunlight, potentially offering a lower-energy alternative to the lasers normally used in quantum technology. Their outdoor experiment produced entangled photons with about 94% similarity to an ideal state. The result could pave the way for simpler quantum satellites, secure communications, and more energy-efficient quantum computing.
Amazon Researcher Claims Quantum Algorithm Could Challenge PQC Foundations
The Quantum Insider (TQI) is the leading online resource dedicated exclusively to Quantum Computing.
Space Compute Is Moving From Science Fiction To Infrastructure
As satellites generate more data than Earth can efficiently process, space compute is emerging as a new infrastructure category for AI, storage and edge computing.
Florida Atlantic University Launches Quantum Computing Business Strategy Certificate
Florida Atlantic University launches an eight-week quantum computing certificate to help business professionals evaluate adoption strategies
Microsoft’s Quantum Chief Doesn’t Care That Scientists Don’t Believe His Results
Zulfi Alam thinks his team doesn’t need to “prove” they engineered a new state of matter in their bid to reinvent computing. Science would disagree.
Viewpoint: Europe needs a new scientific contract
The White House's new science strategy should be required reading in the Berlaymont and every European capital.Not because Europe should copy it. Parts of it should concern Europeans deeply. But because it asks the question Europe has so far avoided while steadily losing ground in the global race for technological leadership.Europe already possesses many of the world's finest universities, scientists and research-intensive companies. It produces world-leading research in fields ranging from quantum technologies and biotechnology to climate science. Yet time and again Europe generates the scientific breakthroughs while others build the companies, industries and strategic advantages around them, particularly in digital technologies. Increasingly, we find ourselves regulating technologies whose underlying capabilities were developed elsewhere.This is not primarily a scientific failure. It is an institutional one.The settlement that shaped modern science policy emerged after the Second World War. In Science, the Endless Frontier, Vannevar Bush argued that governments should invest in fundamental research while protecting scientists from political direction. Public investment was justified precisely because no government, university or company could predict where the next transformative discovery would emerge.That scientific contract served liberal democracies extraordinarily well. It underpinned decades of advances in medicine, computing, energy and communications, but the world for which it was designed no longer exists.Artificial intelligence is transforming not only technology but the production of knowledge itself. Advanced chips, computing power, data and scientific instruments have become strategic assets. Scientific knowledge now diffuses globally almost instantly. Competitive advantage increasingly lies not in making discoveries first, but in possessing the infrastructure, capital, engineering capability and institutions required to translate those ideas into products, industries and strategic advantage.The old boundaries between science, industrial policy, national security and geopolitics have largely disappeared. Dual-use technologies now underpin both economic power and military deterrence.The US has recognised this shift. In July, the White House published Science: A New Golden Age, a comprehensive attempt to rethink the relationship between science and national power. The report builds on Bush's legacy, but departs from his framework in important ways. Science is no longer treated simply as the source of future discoveries. It is presented as the foundation of economic resilience, technological leadership and national security. AI, advanced infrastructure and the capacity to build become as important as discovery itself.Yet the report also reveals a striking paradox. The same administration calling for “a new golden age” of US science has simultaneously proposed deep cuts to the federal research enterprise while expanding political influence over the allocation of public research funding. Europe should therefore distinguish between the report's diagnosis and its prescription. The diagnosis, that science has become a strategic asset, is compelling. But the prescription is self-defeating. Long-term technological leadership depends on strong universities, academic freedom and the institutional autonomy that makes scientific discovery possible. This distinction matters. Bush's achievement was never simply to make science serve national strength. It was to establish a division of labour in which governments invested in research without attempting to direct discovery itself. Scientific breakthroughs emerge precisely because researchers retain the freedom to pursue questions whose value cannot yet be demonstrated and whose conclusions cannot be anticipated.Neither China, nor the USAs science becomes more strategically important, the temptation to politicise it inevitably grows. But scientific freedom is not an obstacle to technological leadership, it is an essential precondition.China represents the opposite model. For decades it has integrated science, manufacturing, infrastructure and industrial policy into a single national strategy. Its ability to mobilise resources around critical technologies is formidable. But it does so within an authoritarian system where scientific priorities are increasingly inseparable from political power.Europe should imitate neither model. It should learn from the strategic ambition of the US without importing its growing politicisation of science. And it should learn from China's capacity to build without adopting its concentration of power.Instead, Europe needs a scientific contract of its own. Bush's scientific contract protected the freedom to discover because the defining challenge of the 20th century was producing new knowledge. Europe's next scientific contract must preserve that freedom while ensuring that scientific discoveries can be converted into technological, industrial and strategic capability. Because in a transactional world, Europe's freedom to shape its own future depends on its capacity to build it.Related articlesThe US ‘golden age’ science strategy: what Europeans need to knowEuropean researchers sound the alarm that Trump rule changes will hit cooperationNIH turmoil risks reciprocal EU-US access to health research fundingThis does not mean subordinating free science to competitiveness or industrial policy. On the contrary. Scientific autonomy remains the first principle of Europe's next scientific contract. Governments should not direct scientific discovery. Their responsibility is to ensure that Europe's scientific, industrial, financial and regulatory institutions work together rather than in isolation.Meeting that responsibility requires far more than research funding. European researchers need access to world-class computing infrastructure, advanced laboratories, shared datasets and scientific facilities. Innovative companies need patient capital, testing environments and a genuine single market in which they can scale without facing 27 different regulatory regimes. Public procurement must evolve from purchasing existing technologies to creating markets for new ones. Regulators must become partners in experimentation rather than guardians of yesterday's rules.A connecting architectureEurope does not need to invent the Defense Advanced Research Projects Agency (Darpa) model from scratch. Britain's Aria, Germany's Sprind and Wellcome Leap already show that Europe can build institutions capable of taking high-risk, mission-oriented bets while preserving democratic accountability. The challenge now is not to create more isolated initiatives, but to connect them to Europe's broader scientific, industrial and financial system so that breakthrough discoveries can scale.Above all, Europe must stop treating research, innovation, industrial policy, finance and security as separate policy domains. The challenge is no longer to create excellent institutions in each of these fields, but to make them work as one European innovation system. Europe's strength will increasingly depend not on excellence within institutions, but on excellence across them.Europe's ambition should be neither to imitate the US nor to emulate China. It should demonstrate that scientific freedom, democratic legitimacy and technological capability are not competing objectives, but mutually reinforcing strengths. In an age of geopolitical rivalry, Europe's greatest advantage may ultimately be its ability to attract the world's best talent by combining scientific freedom, democratic openness and technological ambition.Bush's scientific contract helped define the 20th century because it protected the freedom to discover. Europe's challenge is not to abandon that achievement but to extend it. The defining task of Europe's next scientific contract is to preserve the freedom to discover while building Europe's capacity to translate scientific discovery into technological power.Kaare Nielsen is founder of Pomus, a Danish think tank on science and innovation.
Quantum Computing: What IT and Business Leaders Need to Know
Discover how quantum computing is reshaping AI and security, why post-quantum cryptography can't wait, and how to build a quantum-ready workforce.
NYU Faculty Drive Three US Department of Energy Genesis Mission Projects to Accelerate AI-Driven Discovery
Faculty across Arts and Science, Courant, and Tandon will help develop AI tools for quantum computing, decentralized scientific reasoning, and automated hypothesis generation
Microsoft Adds $450 Billion In A Day, Beats Nvidia. What's Behind The Surge
Azure, Microsoft's cloud computing platform, reported stronger-than-expected growth as companies continued spending heavily on AI infrastructure.
Nvidia GPUs see yet another price hike of up to 30 percent, as the generative AI hardware crisis worsens
In response Samsung announced another price increase across DRAM as the personal computing nightmare deepens.
Meta narrows annual capex forecast as AI buildout grows
Meta Platforms narrowed the range of its forecast for annual capital expenditure on Wednesday, as the social media giant doubles down on building a fleet of data centers to expand its AI computing power
Microsoft tops quarterly cloud growth estimates, easing spending concerns
Revenue at the company's Azure cloud-computing business rose 43%.
Thirteen early-career professors win NSF development awards
Researchers studying ribosomes, AI and quantum computing are among 13 early-career professors from Cornell who’ve recently been awarded National Science Foundation Faculty Early Career Development Awards.
A Deluge of A.I. Computing Power Is About to Come Online, Fueling Major Leaps
The number of A.I. chips that provide the computing power to advance the fast-evolving technology is doubling every nine months.
Clemson’s Thao Tran Dominy selected to help chart chemistry’s path to 2050
National Academies workshop will focus on breakthroughs in energy, quantum computing, and materials and manufacturing
Three George Mason faculty members elected to Virginia Academy of Science, Engineering, and Medicine
The 2026 elected class includes individuals from the George Mason University: Liping Di of the College of Science, Dean Melissa J. Perry of the College of Public Health, and Siddhartha Sikdar of the College of Engineering and Computing.
Jim Cramer Discussed A Surprise For International Business Machines Corporation (NYSE:IBM) CEO
International Business Machines Corporation (NYSE:IBM) is another stock that Jim Cramer has continued to stick by, even though the shares have struggled. For more than a year, the CNBC TV host has repeatedly praised the firm for its software business and its quantum computing business. International Business Machines Corporation (NYSE:IBM)’s shares are down by 26% […]
Breaking through the quantum noise barrier
Quantum computing has spent years existing in the space between promise and practicality.The machines exist. Tech giants are building them. Researchers have shown that, for certain problems, quantum computers could one day dramatically outperform today’s fastest supercomputers.The obstacle isn’t that the computers don’t work. It’s that they’re extraordinarily fragile.
KV the Apostate: Faith-Based Computing Versus the Unnatural Science
If we use LLMs poorly—as so many people already are we will generate megabytes of utter garbage (a.k.a. AI slop, already the bane of many open source projects).
A Pitt-led team plans to automate quantum computing research with a Department of Energy grant
Part of the Genesis Mission, a national effort to harness AI for scientific discovery, the project could enable new chemistry and materials science.
ResearchGate partners with Science China Press
Participating journals will span subjects including medicine, physical sciences, mathematics, technology and computing
When It Comes to Fusion, Materials Matter
Fusion at high temperatures powers the sun and, if harnessed, could provide a potential source of energy here on Earth. But controlling fusion reactions has other benefits. The process also generates subatomic particles called neutrons that are used in a range of applications spanning medicine, research, and national security. Now, scientists at the University of California, Davis (UC Davis), and the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have found that the materials surrounding a fusion reaction can dramatically increase how often it occurs, particularly at low energies where fusion is rare. The study was published July 18 in Nature Communications. Their approach sets up a way to study and engineer nuclear reactions within solid materials, opening a new field of “materials-driven fusion.” Instead of designing materials just to survive the harsh conditions of fusion, researchers might be able to design materials that boost the reaction in specific conditions, similar to the way catalysts speed up chemical processes. “It gives you a new knob to turn that you didn’t have before,” said Arun Persaud, head of the Fusion Science & Ion Beam Technology group in Berkeley Lab’s Accelerator Technology & Applied Physics (ATAP) Division. “If we understand this effect better, it opens the door to engineering new materials that would affect the fusion rate under certain conditions. Someday future progress might enable more compact and efficient neutron generators, which have all kinds of applications, like cargo screening, planetary science, and medical therapy and imaging.” In the experiment, researchers used two different methods to pack deuterium, a heavy form of hydrogen atoms that is often used in fusion, into thin foils of palladium and titanium. They then fired a beam of deuterium ions at the foils at different energies and measured how often fusion happened. Then they compared the rates from the different materials and methods with the “bare” fusion reaction (not in a material). The team found that fusion rates depended on how the deuterium was loaded into the metal foils. The biggest effect was at the lowest energies, below 2.5 kiloelectronvolts (keV), where theory predicts fusion rates drop off sharply. Instead, researchers found a surprising plateau: Some samples showed elevated fusion rates roughly a quintillion times higher than bare fusion reactions. (A quintillion is a 1 followed by 18 zeroes.) Researchers are not exactly sure why that’s happening, though they have some ideas and ways to test them. The electrons and defects within the material might partially shield repulsive electrostatic forces between deuterium nuclei, making it easier for them to get close together and fuse. Tuning the electronic structure, defects, and composition of materials could help make nuclear reactions happen more readily. “It comes down to better understanding the mechanism so that we can try to enhance it,” said corresponding author Jeremy Munday, a professor at UC Davis. “We’ve seen that we can increase fusion rates, but what is the limit? Can we bring it to lower temperatures or energies? There’s obviously a lot of interest and excitement about fusion, so if there’s something we can learn about the physics at these lower energy scales, maybe there’s something we can translate to other areas of nuclear science.” The team plans to explore a wider range of materials and continue probing the unexpected fusion plateau at lower energies. Their work establishes a reproducible experimental platform to study how solid materials influence nuclear reactions, creating a new area of research that links fusion science with materials science and chemistry. “The work shows conclusively that the material environment where fusion occurs at low temperatures is an active participant rather than a passive container,” said Cameron Geddes, director of ATAP. “That adds a new dimension to fusion research.” This work was funded by the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E). ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
Harnessing Abundant Electricity From the Sun—and Other CU Boulder Science Tapped for Genesis Mission
Three CU Boulder-led projects and three collaborative projects selected through the U.S. Department of Energy's Genesis Mission. Research will advance artificial intelligence for fusion energy, quantum computing, particle physics and water prediction. Awards recognize CU Boulder's leadership in applying AI to some of the nation's most complex scientific challenges.
Canadian cryogenics company coming to South Side quantum park
A Canadian manufacturer of cryogenic equipment that’s crucial to quantum computing is coming to The Illinois Quantum & Microelectronics Park on the South Side.
5 projects at UW–Madison aimed at transforming science and energy with AI receive DOE Genesis Mission funding
The projects, spanning fusion to critical minerals, are among 278 funded awards to national labs, companies, universities and non-profits in order to accelerate breakthroughs in energy, scientific discovery and national security through a new platform that combines AI, supercomputing, quantum systems and advanced scientific instruments.
Berkeley Lab to Lead 13 New Genesis Mission AI Projects
Researchers will apply AI, supercomputing, and advanced instruments to accelerate discoveries for energy, science, and national security.
Rice joins Department of Energy’s Quantum Science Center to Advance QEC Research
Rice University joins the DOE Quantum Science Center to research quantum error correction methods for future fault-tolerant quantum computing systems.
Bristol Myers, NVIDIA join forces to build life science’s ‘most powerful’ AI factory
BMS enhances its AI computing power with NVIDIA's DGX SuperPOD as big pharma race to stay competitive within the shifting global landscape.
What China's internet is saying about Moonshot's hot new Kimi model
Just days after launching Kimi K3, Moonshot AI temporarily suspended new subscriptions, saying demand had overwhelmed its computing capacity.
Beyond rockets and satellites, SpaceX is quietly building an AI compute business that may become key to its eye-popping valuation
Deals with Google and Anthropic to rent out computing capacity could generate $26 billion a year.
Thermodynamic Computers Go With the (Energy) Flow
Today’s computers need safeguards against random energy fluctuations. Thermodynamic computers would put those fluctuations to use.
A 200-year-old physics experiment could help build future computers
Scientists at Nanyang Technological University in Singapore have discovered a surprisingly simple way to create exotic light structures called optical skyrmions using a 200-year-old optical effect known as the Poisson spot. Instead of relying on expensive, highly engineered materials, they simply shine a laser at a tiny circular disc, producing stable swirling patterns in light that researchers believe could one day help power advanced data storage, communications, and computing technologies.
Cloud Computing for Life Science Research: AWS, Google Cloud, and HPC—Which Do You Need?
A practical, no-hype comparison of cloud computing for life science research: when AWS, Google Cloud, or institutional HPC actually fits. Explore the guide.
Quantum Computers Identify Nuclear Fusion Fuel Chemistry in Major First
Computing the future of fusion.
Scientists’ Side Hustle? Using AI and Quantum Computing to Generate New Peptides
Researchers cobbled together funding and time to show how quantum computing could aid in the development of drugs to help underserved populations and combat rare diseases.
Meta Weighs Renting AI Compute as Cloud Business Takes Shape
Zuckerberg says strong demand for AI computing power could support cloud services and premium infrastructure deals.
Meta’s Zuckerberg Says Exploring AI Cloud Business Makes Sense
Meta Platforms Inc. needs all the computing power it can get, Chief Executive Officer Mark Zuckerberg said, but in a market starved for resources necessary to run and develop artificial intelligence products he’s also considering whether some of Meta’s AI infrastructure could be more valuable if rented to outsiders.
Quantum computing wielded to create extremely rare material critical to nuclear fusion
Nuclear fusion inches closer after scientists combine supercomputing, AI and quantum computing to blueprint a way to create more tritium.
Three New College of Arts and Sciences Masters Programs Will Take Students to the Cutting Edge
School launches graduate degrees in quantum computing, data-driven economics, and artificial intelligence
Khosla-Backed Startup Claims Breakthrough With Largest-Ever AI Model on an iPhone
Apple is on a quest to shrink powerful AI models to run on iPhones, which could cut down on cloud computing costs and enhance user privacy. But a small startup that emerged from stealth mode earlier this year says it recently got an AI model running on an iPhone bigger than any previous mobile ...
China bets on AI to speed up science despite chip limits
Driven by aggressive state policies and a national supercomputing network, Chinese labs are rapidly embedding AI into daily research
International Business Machines (IBM) Unveils New AI Infrastructure, Is The Stock Fully Priced?
International Business Machines (IBM) stock has been in focus after a cluster of technology announcements, including quantum computing work on fusion energy, new z17 and LinuxONE 5 rack mount systems, and expanded cybersecurity partnerships. See our latest analysis for International Business Machines. Against this backdrop of quantum computing progress, new z17 and LinuxONE systems, and expanded cybersecurity partnerships, International Business Machines’ share price has moved sharply, with a...
Intelligent Computing appoints Philip S. Yu and Osmar R. Zaïane as new editors-in-chief
Intelligent Computing, a Science Partner Journal co-founded by Zhejiang Lab and the American Association for the Advancement of Science(AAAS), has appointed Philip S. Yu and Osmar R. Zaïane as its new Editors-in-Chief. Philip S. Yu and Osmar R. Zaïane succeed the journal's founding Editors-in-Chief at a pivotal stage of development, as Intelligent Computing continues its rapid growth as an international open-access journal dedicated to advancing the convergence of intelligence and computing.
Computer science society creates new research integrity role to address case backlog
AndreyPopov/iStock Over the last five years, the Association for Computing Machinery has been dealing with a rapid rise in allegations of research misconduct that have created a backlog of cases to…
Meta stock soars as Mark Zuckerberg explores cloud business
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How should European scientists respond to the US AI kill switch?
Earlier in June, Europe’s worst fears of technological dependence were confirmed when the White House ordered the AI firm Anthropic to stop non-US citizens using its leading models. This kill-switch moment crystalised anxieties in Brussels that the continent, lagging the US on the creation of leading-edge AI models, is now a technological of vassal of Washington. The shock has specific implications for European scientists and universities. Some governments are now worried that with AI being integrated into labs, Donald Trump now has his finger hovering over an off switch for European science. “Having restrictions on this tool, it can have an impact on our own research,” said France’s research minister, Philippe Baptiste, at the VivaTech conference in Paris on June 18.Baptiste, himself a former academic, said that colleagues in mathematics had recently warned him they were now cut off from leading-edge US models, risking their work. “This model is not available anymore now because of the US restriction, and for the first time this had an impact on mathematics,” a field where large language models (LLMs) are making a significant contribution, said Baptiste. So, should European scientists avoid relying on US models in the future? Or would this be a self-harming overreaction? And how is AI being used in science, anyway? What happened?On June 12, it emerged that Washington, citing cybersecurity concerns, had ordered Anthropic to stop non-US citizens using two models: Claude Mythos 5, and Claude Fable 5, a version of Mythos but with guardrails to prevent abuse. Anthropic said Washington’s concerns were overblown. But forced to follow the order, yet with no way to check who was using the models, the company suddenly shut down access for everyone, US citizens included. There’s still no agreement on how to restore broad access. But last week, Bloomberg reported that select US companies, and the US government, still had access to Mythos despite the ban, but the EU’s cybersecurity agency Enisa had been shut out. Class division of researchersIn the longer term, access outside the US should be restored, said Marcel Salathé, co-director of the AI centre at the Federal Polytechnic School of Lausanne (EPFL), because a permanent restriction would be financially ruinous to US AI firms. “Even Trump will eventually budge to economic pressure,” he said.However, US AI firms might end up operating rather like banks, doing due diligence on users of their leading-edge AI models, he went on.European scientists are unlikely to fall foul of such checks, he said. But having a Chinese postgraduate in their lab, or doing a type of research the US disapproved of, could potentially result in access being denied. “It will create a sort of class division of researchers,” he said. More than frontier modelsHowever, successfully deploying AI in science is about far more than just having access to leading LLMs such as Mythos.Instead, many science-specific tools, most famously Alphafold, which predicts protein folding structures, require “far less” computing power to train than frontier models, well within the capabilities of European supercomputers, according to a recent analysis by the Arq Foundation, a Brussel-based AI think tank. Instead, tools such as Alphafold are possible because certain fields, like protein folding, weather prediction or astronomy, have large, clean, standardised datasets that can be used to train predictive models. Rather than compute, “data is the central constraint for AI for science,” the report says. For example, a less powerful physics model trained on CERN’s data “will be more valuable than the best model without certain data,” said Bengüsu Özcan, author of the report. European advantage?Europe could therefore steal a march by using its scientific data and infrastructure to create models US digital giants cannot. “They might actually match or go even beyond what these big [US] companies are doing,” said Özcan.Indeed, some European start-ups hope to create automated testing labs to create the kind of standardised data that could speed up the discovery of new materials. Materials scientists say there’s currently too little data to train models. AI scientistsHowever, even if the bottleneck for AI in science is often data, rather than compute, being at the mercy of the US for LLM access could still become a problem for European scientists. A new class of “AI scientists” based on leading LLMs is also emerging, Özcan’s report says.Unlike domain-specific tools like Alphafold, these try to automate day-to-day scientific work, by providing an overarching tool that coordinates specific models to synthesise existing literature, generate hypotheses or run analysis of data. The problem for Europe, however, is that these tools are sometimes based on US leading models. Google Deepmind’s AI Co-Scientist, for example, is built on Google’s Gemini LLM. Systematic failureThese scientific automation tools are still in their early stages, and still exhibit “systematic failures on scientific tasks,” Özcan’s report says. One of the problems is that the messy, day-to-day process of scientific discovery is largely not documented, meaning LLMs don’t have a good source of data to learn how scientists actually work. Meanwhile, some tasks, such as literature synthesis, don’t typically require access to leading edge models.However, the performance of AI scientific assistants could improve as companies such as Google pour resources into developing them. Rely on US“Unfortunately, for scientific assistants, there is not much we can do right now except rely on US frontier AI,” said Antoine Bosselut, a natural language processing expert based at EPFL. Chinese-built open models, which can run on local computers, lessening the risk of a shutdown, are touted as one alternative to US dependence. There’s also Mistral, once seen as Europe’s main AI hope, but the Paris-based company has seen its recent models fall behind in performance. But the Chinese alternatives are generally not as capable as US frontier AI models, said Bosselut, unless paired with fiddly, custom tools that allows them to act as independent agents. “Most scientists do not have the time,” he said. Don’t jump ship yetAlthough the kill switch moment is seen a warning shot for European scientists, it doesn’t mean labs should abandon US AI tools immediately. “I do not think the right response is simply to abandon US-based models and systems under the banner of sovereignty or independence,” said Mattias Björnmalm, secretary general of the Cesaer university association. “That would be an overreaction.”Related articlesEuropean sovereignty in AI requires ‘ugly trade-offs,’ say experts Robotic lab start-up makes case for €500M EU-funded materials testing facilityAI in science: is it useful? Instead, European researchers need to ask themselves whether they’re becoming dependent on technology that could be turned off in Washington, said Özcan. “They might not see this today, but they should really start asking this question,” she said. European researchers need a plan B, said Salathé. “I would recommend to every researcher, very proactively explore alternatives.”Own toolsIn addition, Björnmalm and others want European research institutions to develop their own scientific AI tools.Instead of signing AI deals with US digital giants, European universities should be using this money to create their own models, which may end up being superior for research, said Sabine Leonelli, an expert on the use of AI in science at the Technical University of Munich. “Universities in Europe seem to be happy to sign commercial contracts with US companies on the assumption [their AI tools] are better,” she said. But US frontier LLMs are typically opaque, and have been developed without independent scientific input, she said. “This is not good enough for science.”Last year, Swiss researchers released Apertus, an LLM designed to be completely transparent, from its development methods to its training data. The idea is that this makes scientific tools built on top of the model far more reproducible than with closed, commercial alternatives.“Europe needs more of this: serious capacity-building that gives researchers, universities and companies credible options,” said Björnmalm.
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