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Federal AI security center measure advanced by House Science
A measure that would put into law a key federal office focused on artificial intelligence advanced Thursday out of the House Science, Space and Technology Committee, as part of a slate of AI-focused and data center bills. The committee advanced the bills on a bipartisan basis, but put off potential changes regarding funding levels for […]
These 15+ award-winning gadgets are on sale for Prime Day - but we'd pay full price
Editor-approved tech is still on sale during Amazon's Prime Day sale - but don't wait much longer to shop.
French people are painting chalk on their windows in the heat
A simple, low-tech remedy may help cool homes. Here's the science behind the trend.
Apple to Skip M6 Pro and M6 Max, Jumps to M7 Series
Apple has reportedly canceled its M6 Pro and M6 Max processors, according to a recent note from Bloomberg's Apple insider Mark Gurman. Behind the scenes, there is a significant shift in Apple's silicon rollout strategy. The company is postponing the launch of its higher-end M6 SoC variants, like the...
Real Madrid’s summer spending spree creates unexpected Champions League problem
Real Madrid have been one of the busiest clubs in the transfer market, but their impressive recruitment spree may have created a technical issue.Notably, Jose Mourinho has already welcomed four new si...
The heatwave hacks that will actually help to keep you cool
Should you wear wet socks to bed or point a fan out the window? Can the ‘Japanese door fan’ technique cool a baking hot car? Here’s what the science says
Smart voices in business react to Apple and Xbox price hikes
After Apple and Microsoft's Xbox raised prices due to a shortage of memory chips, tech observers are not optimistic about future prices.
TravelTech Show, Business Travel Show Europe name 2026 innovation award winners
Arcube, ImpersonAlly, Acai and Nowadays were recognized in separate competitions for travel technology innovations spanning airline retailing, brand protection, contact center automation and meetings management.
‘Turf Tank’ robot elevates Oregon sports fields
The Oregon Youth Soccer Association is taking advantage of some new technology to keep its fields game day ready.
Trump nominates new top deputy to RFK Jr.
Chris Klomp, a 45-year-old tech entrepreneur, gained the president's confidence when he negotiated price cuts with drug companies.
YouTube Shorts are getting even shorter with an update that lets you double the playback speed
YouTube Shorts is getting a makeover.
Neuroimaging utilization in emergency departments has increased year-over-year for a decade
Researchers believe their new data could be used to better inform staffing coverage in modern radiology departments.
Scientists develop predictive roadmap to boost performance in next-gen spintronics
Chiral 2D metal halide perovskites (MHPs) are among the most promising materials for future technologies that exploit the spin of electrons in spin-based optoelectronics, or spintronics, but getting them ...
Valve Quietly Walks Back Steam Machine 4K 60 FPS Performance Claims
Valve's Steam Machine has earned more than its fair share of skeptics, thanks to performance claims and more recently its unfortunate pricing. More recently, though, Valve has seemingly taken some of this criticism to heart and silently changed some of those performance claims on the Steam Machine p...
Making Our Own Luck
We are cross-posting a piece that former NIH official Kris Willis wrote for Macroscience. Kris is now the President and Founder of the Woodley Park Institute, for which I’m a board member. Picking winners or hedging bets? Federal science agencies have long wrestled with the question of how to ensure their billions of dollars of grants and contracts result in maximum benefits for Americans. On the surface, it might seem that a goal-oriented, interventionist style of management would be the best policy: prioritize our most pressing problems and distribute funding accordingly.This top-down strategy creates a unique hazard, though: bad choices can send resources in the wrong direction, resulting in slow progress that impedes the delivery of tangible benefits to citizens. Moreover, if decision makers pursue an applied advance when the underlying scientific principles remain poorly understood, they risk costly failures and a loss of support for the research enterprise at large. Examples include Nixon’s 1971 War on Cancer, undertaken on the premise that a cure could be achieved in less than a decade, the drive to build an operational commercial fusion plant by the mid-1990s, and the National Plan to Address Alzheimer’s Disease, which failed to produce the effective treatments and prevention strategies promised by 2025. The contrasting laissez-faire approach is to hedge your bets. If the path to an advance is impossible to predict, then the wisest choice might be to distribute funding to as widely as possible. The main risk of this strategy is that spreading funding thinly may limit the resources available to the most promising research, resulting in the same negative outcomes as the interventionist approach: limited support for the most promising topics, slow progress, and delayed returns. In reality, at science agencies like the National Science Foundation and National Institutes of Health, program managers navigate between these two extremes, setting some funds aside to target high-priority areas and using the rest to cover the widest possible range of meritorious proposals. This middle path seems like the most rational way to proceed, but it still requires making choices. How much should be set aside for high priority topics? What should those topics be? How should we define merit? Expert opinion can provide a helpful guide, but leading experts can have remarkably different opinions about what matters and what should be prioritized. Moreover, experts and administrators alike can be risk averse, giving an edge to high-profile, well-established concepts. What’s really needed is a data-driven framework to help guide decision-making, one that doesn’t simply repackage prestige or incumbency. Recognizing breakthroughs years in advance Many breakthroughs fail to attract funding or recognition at the earliest stages of development. Katalin Karikó, for example, spent years struggling to win grants for work on mRNA that would eventually win her and Drew Weissman a Nobel Prize. Similar stories can be told about Jim Allison’s groundbreaking studies leading to the development of cancer immunotherapy, Stan Pruisner’s demonstration that prions can self-replicate without DNA, or Robin Warren and Barry Marshall’s proof that Helicobacter pylori, not stress, causes ulcers. Yet at some point, the scientific community recognizes and responds to transformative breakthroughs like these. How does that change happen? And what if science funders could identify the areas that are on the cusp of a breakthrough? Those questions led my collaborators and me to study how scientists responded to past breakthroughs. Based on patterns in that data, we developed a means of predicting future breakthroughs, using biomedicine as a proof of concept. It’s worth taking a moment to describe how our approach works. Briefly, our prediction process begins by grouping the 18 million or so peer-reviewed papers in PubMed, the authoritative database of biomedical research, into roughly 50,000 unique topics. A small subset of these topics are so widely acclaimed as breakthroughs that they have been recognized with a major prize like a Nobel or a Lasker Award. We theorized that studying the development of these outliers over time, especially before they gained acclaim, was the key to identifying future instances of them. After defining topics, we chose 21 representative breakthroughs and asked what they looked like before they won prestigious prizes. To answer that question, we re-ran our topic-mapping algorithm repeatedly, winding back the clock one year each time, stringing together the years to follow the progress of each field as it grew and advanced. We found that in each case, the years leading up to a discovery followed a pattern: a burst of papers on a new, rapidly evolving topic, many of which quickly became influential. These characteristics—the percent of papers that are new, the percentage of papers that are brought in from other topics, and the influence of each individual paper—can all be measured separately for any given topic. Together, they act as a predictive signal that is detectable an average of five years before a transformative discovery is made, and up to thirty years before the discovery receives a major prize. Scanning the current research landscape for topics that display this signal allows us to predict what work will likely produce a future breakthrough. Each year we analyzed includes four or five signals, a number that appears to have remained constant across a twenty year time frame. In their classic work on the sociology of science, Bruno Latour and Steve Woolgar established that the desire to participate in a major discovery is an important motivator for scientists as they consider whether they should take up (or abandon) a research problem. Although further work is needed, the simplest explanation for our results is that this behavior is widespread enough to detect at scale. A foundational advance, or something like it, draws the attention of scientists and causes them to change the direction of their research. They vote with their feet, staking their own reputation and careers by publishing on and citing the new idea. That upswell of interest is the foundation of our breakthrough signal. What kind of research does our model identify as a breakthrough? After building a model based on the patterns in our 21 preselected breakthroughs, we tested it by identifying all early signals of discovery from 1994 through 1997. Of the 18 signals we found in that time period, 17 can be traced forward in time to a breakthrough. Examples include super-resolution fluorescence microscopy (see the image above), the directed evolution of proteins and enzymes (Chemistry Nobel, 2018), and sequencing the human genome (National Medal of Science, 2008). The discovery of the role of leptin signaling in obesity is a particularly interesting case study. Around 1950, scientists noticed the existence of a type of lab mouse that suffered from a unique inherited form of obesity. When given the freedom to choose their own diet, these mice ate more than normal and preferred food that was high in fat. Researchers had few clues as to why the animals overate; early experiments pointed to the existence of a soluble ob factor found circulating in the bloodstream that regulated appetite, but its identity was unknown. In 1994, Jeffrey Friedman and colleagues identified and sequenced the ob gene, noting that the protein it encoded appeared to fit the profile of a circulating factor. A year later, a trio of high-profile publications demonstrated that ob was a hormone that regulated body weight and fat deposition by regulating appetite. One of these was co-authored by Friedman, who christened it leptin from the ancient Greek word for thin. Using our model, the data from 1996 make it clear this advance would become a breakthrough. Scientists had flocked to study the biology of the new hormone, generating the flurry of new papers and citations required to produce a signal. One of these demonstrated that serum leptin concentrations reflected the amount of adipose tissue in the human body, providing clinical validation of the earlier mouse studies. Before the identification of leptin, scientists were unable to point to a specific molecule that controlled appetite and adiposity, so that it was impossible to rule out non-physiological causes of obesity; its characterization fundamentally changed our concept of weight gain. In 2010, Friedman and fellow pioneer Douglas Coleman were awarded a Lasker for the discovery. Our work also identifies breakthroughs in clinical practice and behavioral and social sciences, even though these areas are less likely to draw the attention of major prize committees. One example that falls into this category is the introduction of endovascular aneurysm repair, a minimally invasive surgical procedure for the treatment of abdominal aortic aneurysm, a leading cause of death among Americans over the age of 65. Relative to the previous standard of care, it reduces in-hospital mortality by almost four-fold. In 2017, Timothy Chuter received the American College of Surgeons’ prestigious Jacobsen Innovation award for his multiple refinements to the technique. Another under-recognized breakthrough identified by our model is the development of standardized survey instruments to assess the quality of life for HIV+ patients. The antiretroviral cocktails introduced in the mid-1990s reduced AIDS mortality, but treatment came with serious side effects. The new evaluations showed that patients whose disease progressed had worse physical functioning than Americans with other chronic diseases, while those who were asymptomatic maintained a health-related quality of life on par with the overall US population. This evidence made it possible for patients and activists to argue that even in the absence of a total cure, and in spite of the side effects, alleviation of symptoms was a worthwhile priority for clinicians. My colleagues and I have failed to identify any significant recognition for the physicians and health policy experts who pioneered this advance, although in 2016, researchers called for the World Health Organization to set targets for good health-related quality of life as part of its framework to end the AIDS pandemic. From forecasting to funding How should science funders use our predictions? Any serious discussion of what we should do with this new capability needs to begin with an understanding of its limitations. We can’t (and shouldn’t) invest all of our resources in the small number of topics predicted to produce breakthroughs. Innovative new fields are born from existing ones; they rarely arise de novo. If funders don’t maintain a diverse portfolio, the breakthroughs of tomorrow will have no antecedents. Think of this as eating the seed corn, or killing the goose that lays the golden egg. There are also multiple goals of funding beyond basic scientific discovery, including translating discoveries into clinical practice, developing new technologies, supporting economic development, and training new scientists. The investments needed to accomplish these goals are likely different from those required to support emerging breakthroughs. Finally, we must be aware that we may not capture every instance of a breakthrough. The concept is fuzzy, and not every significant discovery is recognized with a major award. Further, breakthroughs are rare, meaning that our dataset is, by necessity, small. This makes formal estimates of accuracy challenging. Although our overall success rate appears to be high, any one signal may turn out to be a false positive. We found one apparent example: the development of the third generation COX-2 inhibitors, Vioxx and Celebrex, which were much celebrated in the early 2000s as effective but non-addictive pain relievers, meets all the algorithmic criteria of a breakthrough. Five years after it received FDA approval, researchers demonstrated that Vioxx was associated with serious cardiovascular complications, and the manufacturer voluntarily pulled the drug from the market. Celebrex remains available, although like other NSAIDs, it carries an FDA warning for increased cardiovascular risk. Decision makers who were overly focused on the breakthrough potential of this research might have wasted substantial resources nurturing an area that ultimately proved to be a failure—but so would those who relied on expert opinion at the time. That said, the potential benefits of funding the next mRNA vaccine or cancer immunotherapy years earlier than we might have are large. When we can’t assume the outcome of an action, it’s worth conducting an experiment. Can targeted support for areas that are poised to produce a breakthrough increase the return on scientific investment without cannibalizing future advances? With the necessary administrative infrastructure in place, conducting this experiment would be straightforward. First, identify all the breakthrough signals between 2018 and 2023, select half at random, and commit to a decade of investment. For biomedicine, a six year window should yield about 30 topics with the potential to produce a breakthrough. Providing strong support to half of these might be accomplished for $300 million a year. That’s roughly half of the recent annual budget of the NIH Common Fund or around 20% of the fiscal year 2025 budget for ARPA-H. After five years, then again at ten, compare to see which group — the one that was actively managed, or the control — produced more breakthroughs, and on what timescale. Although we used biomedicine as an example, the same experiment could just as well be run for physics, materials science, or any other discipline. Any attempt to undertake such an experiment should keep three points top of mind. First, we can predict the topic of future breakthroughs, but the people and vision for how to move the work forward are still important. In practice, this means success requires active program managers with the expertise to develop the science and the authority to do so, including by recruiting investigators. Second, we would be wise to learn from the failures of past attempts to fund transformative research. High among these are funding modestly repackaged work, confusing the genuinely novel with the merely unfamiliar, and relying too much on incumbent investigators. All of these risks can be mitigated by thoroughly and intelligently integrating high quality data into portfolio management. Finally, we need to have patience. Even with strong funding support, producing a breakthrough takes time. If supporting breakthroughs is the best way to nurture the birth of new fields, we also need to accurately describe and properly manage the other two stages, so that we invest wisely throughout the productive lifetime of ideas and divest once they reach the point of diminishing returns. We would benefit from more study of all of these phases, especially the transition from one to another. More research could answer questions like: When does a breakthrough become an established field? How do the availability of funding, the size and characteristics of the available workforce, and the accumulation of evidence that disagrees with prevailing models affect a field’s decline? Exactly how do old ideas give birth to new ones, and can we speed up the process? The more we understand about the dynamics of scientific progress, the better we can maximize the odds that our curiosity leads to results. I’d call that finding a way to make our own luck.
Microsoft adds another year to Windows 10 extended update program
About a quarter of PCs are still running Microsoft's previous operating system.
Following IAM Union Advocacy, Kansas PERB Orders Count of Timely Cast Ballots in KU Health System Pharmacy Technician Union Election
KANSAS CITY, Kan. — Following weeks of advocacy from the IAM Union, Pharmacy Technicians, elected officials and community supporters, the Kansas Public Employee Relations Board (PERB) has ruled that 37 previously uncounted ballots will be included in the final tally of the recent union representation election involving Pharmacy Technicians at the University of Kansas (KU)
Transcription by Ben Lerner wins Orwell prize for political fiction
Judging chair calls Lerner’s novel a ‘funny, brainy and timely’ study of our appetite for technology, while Karen Bartlett wins the nonfiction prize for The Escape from Kabul
If I were traveling, Anker is the only company I would trust with my life to keep my tech fully charged at all times — and 11 of its best items are on sale right now
Get these Anker products to keep your gear always charged!
Merck KGaA to Acquire Bio-Techne for $11.3B, Expanding Life Science Tools Presence
Merck KGaA, Darmstadt, Germany, has agreed to acquire Bio-Techne for approximately $11.3 billion, the companies said today, in a deal designed to position the buyer as more of a leader across the life science value chain by expanding its presence in high-growth, next-generation life-sci markets with Bio-Techne’s tools, analytical technologies, and consumables.
Notion killing Skiff-influenced email app since most users use AI agents instead
Notion is "going all in on using agents to run your inbox."
Google Finance finally gets a mobile app as AI-powered overhaul leaves beta
It took 20 years, but the Finance app arrives just in time to be packed full of AI.
Bio-Techne, a Minneapolis life sciences firm with 500,000 products, to be sold to German company for $11.3 billion
Samsung Reportedly Starts OLED Panel Production for Apple’s First Foldable iPhone
Apple reportedly cleared Samsung Display to make OLED panels for its first foldable iPhone, with hinge issues still shaping launch timing.
From the Beginning, Politics Triggered Broadcasting
Media scholars argued that politics, not technology, shaped American broadcasting from 1927 on, repeatedly shielding incumbents from competition.
Rogers Computer Science Teacher Named Tops in the State
Instructor and coach, Anthony Hanos with members of the cyber security program, students Brandon Wilson, Kerian Santiago and Alex Bettencourt. The sister sectors of computer science, information technology and cybersecurity, continue to be among the fastest growing industries in the country, according to the U.S. Bureau of Labor Statistics. Luckily, Newport area high schoolers interested
Merck KGaA bolsters life sciences business with $11.3B Bio-Techne buy
The deal comes a matter of weeks after Kai Beckmann was promoted to CEO at Merck and signalled his intent to broaden the company's scope for M&A.
Databricks’ former AI chief thinks he can cut AI’s power bill by 1,000x
Un0 is an image-generation system tool that shows for the first time how the company's technology can replicate conventional AI systems.
Agentic-Native Platforms Are Creating A New Technology Business Model
For decades, the enterprise technology industry operated on a simple principle: software companies built products, and services firms helped enterprises.
Tech: House Science advances AI bills
The House Science Committee advanced a bipartisan bill that would codify increasingly prominent artificial intelligence oversight work being done by the Commerce Department.
Google Finance gets a dedicated app for Android
Users will be able to access their watchlists, real-time market data, live financial news, and Google's AI-powered "Key Moments" feature, which explains why stocks moved.
Ranking Big 12 recruiting classes via average commit distance
The Big 12 recruiting landscape continues to change as programs continue to shuffle throughout the conference. Texas Tech is pushing to sign the nation’s No. 1 class in the 2027 cycle and it firmly sits atop the league’s recruiting rankings. The Red Raiders are the only Big 12 team with a top-25 haul, per the […]
Seton Hall's Industry Partnership with NJSIM Opens Doors for a Rising
Seton Hall junior Thaddius Gamueda earns a $2,500 NJSIM scholarship, highlighting student success and the impact of CEPS industry partnerships in business and technology.
New Health Sciences Provost Named
Wake Tech Community College is pleased to announce that Dr. Jennifer Bray has been selected as the next Provost of the Perry Health Sciences Campus.
Scientists measure hidden quantum forces that could power a new generation of pharmaceutical drugs
Researchers invent a laser technique that reveals the hidden forces shaping proteins, advancing a future of precision medicine engineered with quantum precision.
CT AHEC Introduces New Public Health Programs and Partnerships
New public health and public health careers enrichment programs for high school and emergency medical technician (EMT) and paramedic college students launch ...
FDA's breakthrough pipeline fills up with generative AI devices
In this edition of STAT Health Tech: FDA drops enforcement against Whoop, more AI devices get FDA 'breakthrough' label, and more.
Ohio State–led team secures NSF award to advance to next phase of the National Quantum Virtual Laboratory program
The Ohio State University is strengthening its growing prominence in quantum science, technology, and education with a $4 million, two‑year Phase II design award from the U.S. National Science Foundation (NSF) to advance a national effort focused on next‑generation quantum sensing.The funding is helping to bring together top researchers and ...
'This is the next jump in technology': World's first sub-1nm chip keeps Moore's Law alive a little longer
IBM's NanoStack architecture has helped scientists cram 100 billion transistors onto a computer chip, delivering 50% better performance and consuming 70% less energy than the current generation.
Merck KGaA to buy Bio-Techne for $11.3bn in life science footprint expansion
The deal is Merck’s largest since 2015, when it spent $17bn on acquiring Sigma-Aldrich, also a life sciences specialist.
Moody Center announces exhibition exploring math, science and tech rooted in Indigenous knowledge systems
Through a framing of North, Central and South America as interconnected regions, “Radiant Geometries: Vectors of Knowledge from the Indigenous Americas” brings together contemporary Indigenous and Latin American artists whose practices illuminate knowledge as a living technology, through which the mathematical, metaphysical and artistic realms converge.
Merck Expands Life Science Leadership with Planned $11.3 Billion Bio-Techne Acquisition
Merck Expands Life Science Leadership with Planned $11.3 Billion Bio-Techne Acquisition
Paranovus Entertainment Technology Limited Announces 1-For-100 Reverse Share Split
NEW YORK, NY / ACCESS Newswire / June 25, 2026 / Paranovus Entertainment Technology Limited (NASDAQ:PAVS) ("we" or the "Company"), today announced that it will effect a reverse share split of its outstanding Class A ordinary shares, par value $0.000012 ...
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.
The 124 best tech deals for day three of Prime Day
The deals will keep coming until morale improves.
Germany's Merck to buy Bio-Techne for $11.3 billion
Merck KGaA has agreed to acquire biotech firm Bio-Techne for $11.3 billion, the German science and healthcare firm said in a statement on Thursday.
Oakland Athletics Partners with Motion Sports
ROCHESTER, Mich. - Oakland University has announced a new partnership with Motion, the modern technology platform built for college athletic departments. The Golden Grizzlies will implement Motion across their athletic department, giving coaches, academic staff, and student-athletes a cleaner, more connected way to work.
Germany's Merck to buy Bio-Techne for $73 per share
Merck KGaA has agreed to acquire biotech firm Bio-Techne Corp for $73 per share in cash, the German science and healthcare firm said in a statement on Thursday.
Germany’s Merck to Buy Bio-Techne for $11 Billion
Merck KGaA offered $73 a share in cash to buy Bio-Techne, representing a 24% premium to the U.S. lab-tools supplier’s closing price Wednesday.
CEOs and CIOs Differ Sharply on AI Business Impact and Transformation Success, Protiviti Survey Finds
/PRNewswire/ -- A new Protiviti Global Transformation Survey, The Alignment Advantage in Transformation, finds a significant gap between CEOs and technology...
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Rebound in tech shares pushes Asian shares higher, while oil prices fall
Shares are mostly higher in Asia, led by tech-driven gains in Japan and South Korea.
Binghamton University creates an open-source healthcare simulation repository
Staff from Binghamton University’s Information Technology Services and Decker College of Nursing and Health Services recently collaborated to create the SUNY Share Simulation and IPE Activity Repository.
South Korea juggles digital sovereignty and alliance politics
South Korea’s closest allies are increasingly challenging its control over digital platforms, data and technological infrastructure.
Micron and Qualcomm forecasts ignite $400 billion AI chip stock rally
Shares of chipmakers surged late on Wednesday, adding over $400 billion in market value after strong forecasts from Micron Technology and Qualcomm breathed fresh life into Wall Street's recently waning AI stock rally.
The biotech founder asking why good science gets stuck
As an undergraduate, Alinta Furnell led student societies, pitched startup ideas and built biotechnology ventures. Now, the UNSW alumna is investigating one of innovation’s biggest challenges – why so many scientific breakthroughs never make it beyond the lab.
Grand Theft Auto VI will cost $80 without a physical disc
GTA6 might be an outlier, though—at least for now.
New website names and shames companies that still don't offer passkeys to users
According to a new site, 24% of the most popular websites in the world don't offer support for passkeys, which are considered the most secure way to log into apps and services.
Micron forecasts quarterly revenue above estimates
Micron Technology forecast quarterly revenue above Wall Street estimates on Wednesday, signaling that insatiable demand for AI-related infrastructure will continue to drive strong demand for its memory chips.
Steam Machine Sells Out in Japan Despite Woeful Pricing
As was the case with the Steam Deck, Valve is selling the Steam Machine via Komodo Station, an Asian reseller that serves much of South-East Asia, and as a result, it skips the reservation and lottery system that is currently in place on Valve's own Steam Store. While this doesn't combat issues like...
Online violence against women in politics: what shapes political party responses to technology-facilitated gender-based violence?
Political parties have a primary role to play in tackling online violence against women and gender diverse politicians. While the prevalence and impact of TFGBV, such as coordinated disinformation campaigns, deepfake image-based sexual abuse or trolling are well documented, many parties are still building their knowledge on how to respond effectively and have not put in place internal practices and policies that respond to the rapidly evolving, poorly regulated digital ecosystem. About the ReportIn order to promote and protect fair and democratic participation in politics, this ALIGN Report explores what political parties are doing in response to TFGBV and what factors shape their action. The findings, based on existing literature and interviews with gender and politics professionals, indicate there are three sets of factors which donors, civil society and practitioners should consider when designing action to support political parties to respond to TFGBV internally. These are: (1) gender norms; (2) socio-political environment; and (3) internal party factors.Key messagesUnequal gender norms are ubiquitous across politics, shaping expectations of leaders to be strong and assertive, and practices of political parties to uphold masculinist values and sustain cultures of silence. These often lead to weak response to TFGBV against women politicians.The socio-political context can incentivise or disincentivise action, depending on the salience of gender issues, which are increasingly weaponised. Electoral competitiveness, domestic laws (i.e. quota requirements), and even the political system or global normative frameworks influence political will to act.Internal party factors that shape responses will vary across countries and contexts, but include: structures to enforce codes of conduct, policies and reporting mechanisms on (TF)GBV, political ideology, extent of centralisation of leadership, and crucially the meaningful participation of women in decision-making positions, not least through internal women’s wings.Party responses can be seen as a spectrum, with actions falling between active discouragement to address TFGBV to commitment to transform unequal norms and practices within the party.About the ToolkitTogether with the report, this ALIGN toolkit offers gender professionals and others working on democratic strengthening a set of guiding questions and reflection prompts to identify which responses could be most effective and suitable in different contexts. These actions can complement other solutions to TFGBV, such as regulations promoting safety by design. The assessment spans a broad range of factors including: (1) different manifestations of gender norms, (2) the socio-political environment and (3) internal party structures.Key messagesPolitical parties are duty-bound to take action internally to respond to the significant threats posed to women members and candidates, including from their own party colleagues, affiliates and political peers.Existing party approaches to TFGBV can be assessed along a spectrum which ranges from active discouragement and passive acceptance to minimal response and transformative change.To generate effective and context-appropriate solutions to TFGBV, it is important to consider how gender norms shape leadership expectations and internal party practices, while also analysing the impact of the socio-political environment. While actions to support women to stay safe online are very common, codes of conduct and measures to strengthen women’s voice and power in the parties are proposed as most transformative solutions.
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