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Coach Cal to be Inducted into Memphis Sports Hall of Fame
Razorback basketball coach John Calipari, who was head coach of the Memphis Tigers from 2000-09, will headline the 2026 Memphis Sports Hall of Fame class. The induction ceremony is Sept. 16.
Congratulations to the 2026-2027 APSA-Sponsored Congressional Fellows -
APSA is pleased to announce the members of the 2026-2027 Class of the APSA-Sponsored Congressional Fellows! The American Political Science Association (APSA) Congressional Fellowship Program is a highly selective, nonpartisan program devoted to expanding knowledge and awareness [...]
Weston Port, three-star LB, commits to Michigan football
Three-star linebacker Weston Port committed to U-M in the class of 2027 on Monday, June 29.
A.I. takes center stage in health topics discussed at the Aspen Ideas festival
Right now, some of the world's brightest leaders, scholars and artists are in Colorado for the Aspen Ideas festival. NBC News’ Kate Snow went to discuss how A.I. Is reshaping the classroom and how we manage our health.
Netflix and Superheroes Are Having a Rough Stretch on Streaming....
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) I have a quick prediction before we start today’s article: You might see this data in future news articles. Not my specific charts or analysis, but the core trend I’ve been monitoring—Netflix is having a lackluster Q2—will become inescapable. Often, folks want to know “What does the data say?” Well, that’s what it says. I haven’t seen this analysis hit the trades really yet, but I have a feeling some other outlets are going to start making this case soon. Remember, you read it here first. You probably have read about the problems facing superhero films at the box office this weekend. Well, this week, I explore whether superheroes are dying on TV as well! And the data says: definitely maybe! We have a lot to cover in today’s Streaming Ratings Report, which covers the two weeks of 18-May and 25-May. Today, I’m just looking at TV, like Netflix’s disappointing Q2, superhero shows underwhelming, a few TV shows dropping off the charts, The Pitt finally ending its epic run on the viewership charts (and whether “view counts” change its status as one of the biggest shows of all time), all the flops, bombs and misses, and a whole lot more. Tomorrow, I’ve got a great rundown of the film side of things. Let’s dive right in! (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, Showlabs, TV Time trend data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the weeks of May 18th to May 31st, 2026. You can find a link to my terminology here.) Subscribe Television - Netflix’s Q2 Slump Continues Having analyzed streaming ratings for going on half a decade, I have learned to trust my gut, but I’m always relieved when I can find actual data to back it up. For example, after a string of very popular shows like Stranger Things, Bridgerton, The Lincoln Lawyer and The Night Agent came out, week after week, in January and February, my gut wondered if Netflix had enough new and returning TV shows to sustain them throughout the year. Since then, Netflix’s post-March slate of shows has not impressed me. This week seemed to feature a potential new hit, but then, like a classic Duffer Bros. TV show, there was a twist. I speak of The Boroughs, Netflix’s latest (and last) Duffer Bros. produced show. The pitch is “Stranger Things with older actors”. And it topped the Nielsen charts: With just two weeks of viewership, The Boroughs would have been a top 25 debut show last year: But here’s the twist: Netflix has already cancelled The Boroughs! What happened? Likely a few things. First, the show didn’t do as well globally as it did in the US. As What’s on Netflix showed, it lagged behind several other shows that got cancelled. Second, its completion rate was likely low; after an initial burst of interest, it quickly dropped off on the Samba TV and Luminate charts. Third, the Duffer Bros. left Netflix for Paramount, and that may have factored into Netflix’s decision here. (Though I tend to believe that if a show is doing well, Netflix would have kept greenlighting seasons.) Still, just because I can explain why Netflix may have cancelled this show doesn’t mean I’m justifying it. In particular, as I’ve noted before, Netflix is losing a lot of their bigger shows as they reach their natural ends, and they need to replace those shows. This show had the hallmarks of a big new genre show, and it’s their biggest hit of the last few months (in the US at least), but now it’s done. Netflix’s other show this week—The Four Seasons, the second season of the “hit” show from last year—definitely disappointed. Its sophomore season had about half the viewership of the first, only 12.7 million hours. It also only had a two week run on Samba TV, and its numbers were all down on Luminate too. In other words, even with two successes, the Q2 slump for Netflix looks real: I could add to the list of disappointments: Both Lord of the Files and Man on Fire had short runs on the Nielsen charts. Running Point’s sophomore season also opened to about half its viewership, similar to The Four Seasons. A Good Girl’s Guide to Murder’s second season—see below—didn’t even make any of the three viewership charts I track, unlike the first season. Netflix is absolutely having a dismal second three months of 2026. If this Nielsen data is any indication, and I think it is, I think this will show up in Netflix’s engagement report, and maybe even their financial outcomes. And the rest of June doesn’t look much better. We have two hit shows coming back—Sweet Magnolias, one of their quietest big shows, and Avatar: The Last Airbender, a big hit for them in 2024—but the other big swings are limited series crime thrillers i.e. no future season potential. Like I said above, sometimes when I uncover a juicy nugget like this, other outlets end up writing very similar articles mimicking the data without credit. We’ll see if that happens this time! Share Television - The State of Superhero Shows on Streaming When I first heard the pitch for Spider-Noir—a Sony TV show on Prime Video that binge-released eight episodes first on MGM+ then on Prime Video two days later—I had my doubts. It’s a live-action Spider-Man show set in the 1930s, starring Nicholas Cage, based on a cameo of a character in Spider-Man: Into the Spider-Verse. No, seriously, that’s the pitch. That could either go terrifically well or horribly wrong. Great because, Spider-Man. He’s the biggest superhero we have. I’ve seen tracking numbers that put the new _Spider-Man: Brand New Da_y as the blockbuster of the year and initial pre-sales back that up. And yet this Spider-Noir pitch feels very esoteric. (Also, the eight-episode binge release feels very “Amazon copying Netflix” again.) So what’s the data say? And what does this say about the future of superhero shows?
Ravens Rookies Expected to Make Immediate Impact in ‘Projected Roles’
The Baltimore Ravens are known for drafting players who can make an immediate impact on the field. For example, look at Kyle Hamilton.Hamilton is already a three time All-Pro after being drafted by Baltimore in 2022. In this year’s draft class, Baltimore’s draft picks have the same potential to make an immediate impact as soon […] The post Ravens Rookies Expected to Make Immediate Impact in ‘Projected Roles’ appeared first on HEAVY.
Talawar Therapeutics and JATT II Acquisition Corp. Announce Definitive Business Combination Agreement to Create Publicly Listed Biotechnology Company Developing Potentially Best-in-Class Bispecifics for I&I Diseases
Oversubscribed $225 million concurrent private investment in public equity ("PIPE") with available cash to the combined company at closing anticipated to fund...
Insider Sale: CEO of Business Group of $BABA Sells 13,579 Shares
Fan (FJ) Jiang, the CEO of Business Group of $BABA, sold 13,579 shares of the company on 06-25-2026 for an estimated $164,305. We received data on the trade from a recent SEC filing. This was a sale of approximately 2.4% of their shares of this class of stock. Following this trade, they now own 556,617 shares of this class of $BABA stock.$BABA Insider Trading Activity$BABA insiders have traded $BABA stock on the open market 7 times in the past 6
Now your pet can get world-class healthcare. Here’s how.
Doubtless CEO Dirk Beeckman reveals how modern products and services are transforming the pet-parent experience
New Mexico Sports Hall of Fame 2025 inductees honored at banquet
Anita Maxwell, John Fields, and Miles Watters -- 3 of the 5 members of the class of 2025 -- were at the celebration.
Hollywood celebrates Mel Brooks' 100th birthday
Mel Brooks' 100th birthday is being celebrated by friends, fans, and the whole of Hollywood.
Landry Jones, Courtney Frerichs headline 2025 New Mexico Sports Hall of Fame class
ALBUQUERQUE, N.M. (KRQE) – Some of the biggest names in New Mexico sports were celebrated Saturday night as the New Mexico Sports Hall of Fame inducted its Class of 2025. This year’s class r…
Meet the Bruins’ 2026 draft class
Don Sweeney and the Bruins added seven new players to the organization over the weekend in the 2026 NHL Draft.
Commentary: Putting students before politics
After another school year, superintendents across Texas are not just packing up classrooms; we are staring down spreadsheets, trying to piece together next year’s budgets. It is a grueling annual...
Retro Recap: All The Classic Gaming News From The Past Week (June 28th 2026)
Sonic pinball! Retroid Pocket Nova! Star Fox 64!
‘Odyssey’ fever grips the Classics world
Fans of the ancient world are seizing their moment with the release of this summer’s blockbuster.
‘Odyssey’ fever grips the Classics world
(CNN) — As fans of Christopher Nolan eagerly await the July 17 release of his take on “The Odyssey,” a different kind of enthusiast is also bristling with anticipation: scholars
Spent 6 hours in Amtrak coach and business class, how they compare
I splurged for business class on an Amtrak ride from New York to Vermont. Here's what my $80 upgrade got me.
UAPB School of Business and Management celebrates class of 2026
The School of Business and Management (SBM) at the University of Arkansas at Pine Bluff recognized the achievements of its graduating Class of 2026 during its annual Graduates Banquet recently at the STEM Conference Center. The event, coordinated by Cynthia Sims, SBM project/program specialist, brought together students, faculty, administrators, alumni, family members and supporters to […]
Cubs Minor League Wrap: Jaxon Wiggins rehabs with South Bend
Knoxville and South Bend both win, proving again the class of the Cubs system are the middle two teams.
PHOTOS | Multitude enjoy aerial entertainment at resurgent Texarkana Airshow
Sgt. 1st Class Benjamin Hall, assistant team leader, watches the ground to help the Golden Knights line up with their jump mark at the Texarkana Airshow on Saturday at Texarkana Regional Airport. Throngs of people lined a taxiway at the airport to watch the Army parachute team and other aerial entertainment. It was the first airshow in the city in nearly 30 years. See Monday's edition for extended coverage.
FIFA World Cup: England is coming to Atlanta
As the Group Stage concludes, Atlanta has more world-class soccer and excitement to look forward to.
Fidelio: Classical music meets politics
Vitali Alekseenok is passionate about classical music and politics. He is actively involved in Ukraine, advocates for a free Belarus, and conducts Beethoven's opera of freedom, 'Fidelio,' at the Deutsche Oper am Rhein.
McArthur Center to prepare University of Rio Grande health care and manufacturing students
A facility at the University of Rio Grande has opened, offering new educational opportunities for students.The McArthur Center features nine modern classrooms a
Week in Politics: Trump and bipartisan housing bill, John Bolton; Democratic socialists
President Trump canceled a signing for major housing legislation, former National Security Advisor John Bolton pled guilty to mishandling classified documents, and Democratic Socialists made gains.
LVMH and Accor's Orient Express sets its sights on new tech billionaire class
Shuttling across the French and Italian Riviera, Orient Express's first giant yacht aims to attract a new class of billionaire.
Cool Desert Nights returns to Richland with classic car show, entertainment
RICHLAND, Wash. — One of Tri-Cities’ biggest events, Cool Desert Nights, returns to Richland with a weekend of classic cars, live entertainment, food and community events.
Jackson Parish young business leaders class
Town of Jonesboro and Mayor James Harris look to host class for young kids learn the business world
Ohio State Buckeyes projected to land elite offensive lineman
Ohio State sits on the cusp of another top-5 recruiting class, and the Buckeyes could be receiving even more good news this weekend. Four-star Jackson (Miss.) offensive lineman Caden Moss is set to commit Friday night, and the Buckeyes are surging late as the favorite to land him. Over the past 24 hours, Rivals national […]
We almost had a smartphone in the 90s. Why did it fail?
In the early 90’s, a company called General Magic began working on a portable device that would allow people to check email, make phone calls, even play games. It was basically a smartphone. But it never caught on.On today’s show, a theory about why this device failed. General Magic had generous investors, world-class talent and creative freedom. But is it possible what they needed was constraints?Support:Planet Money+Read: Our book: Planet Money: A Guide to the Economic Forces That Shape Your Life Our weekly longform Planet Money newsletterOur weekly Indicator round-up newsletterFollow: InstagramTikTokYouTubeFacebookThis episode was hosted by Erika Beras and Emma Peaslee. It was produced by Emma Peaslee with help from Sam Yellowhorse Kesler and James Sneed. It was edited by Marianne McCune and fact-checked by Charlotte Isidore. It was engineered by Jimmy Keeley with help from Cena Loffredo. Alex Goldmark is Planet Money’s executive producer.
Moment of Science: Music and Color
Dr. Stefan Wienzierl at TU Berlin studies how the architecture of a classroom or concert hall can impact the quality of music or speech.
Health system CEO fired without cause in wake of class-action lawsuit over unnecessary surgeries
Reese Jackson, the former president and CEO of Chesapeake Regional Healthcare was unceremoniously dismissed from his role on June 1. Jackson has been named as a defendant in a pending class-action lawsuit filed by 900 women.
Ex-national security adviser John Bolton pleads guilty to illegally retaining classified information
Former Trump administration national security adviser John Bolton pleaded guilty on Friday to illegally retaining classified information, sealing a deal with federal prosecutors that could allow him to avoid a prison term.
John Bolton pleads guilty to illegally retaining classified information
His plea deal with federal prosecutors could help him avoid prison time
HYPE: Joe Horn to enter Louisiana Sports Hall of Fame
New Orleans Saints legend Joe Horn will be inducted into the Louisiana Sports Hall of Fame as part of the 2026 class! Horn caught 523 passes for 7,622 yards and 50 touchdowns in 102 games for the Saints from 2000-06.
Six Watauga students graduate from N.C. School of Science & Mathematics
MORGANTON/DURHAM — Six students from Watauga County were part of 470 from all across North Carolina who graduated this year as members of the residential Class of 2026 of the
Ex-Trump adviser John Bolton expected to plead guilty in classified information case
Bolton to plead guilty charges that he unlawfully retained sensitive national security information in agreement that includes $2.25m fine
First Look: Breguet Releases 3 new Tourbillon Watches for the 225th Anniversary of its Invention
New takes on the Breguet Classique Tourbillon Sidéral, the Tradition Tourbillon and the Marine Tourbillon Équation Marchante.
Louisiana Sports Hall of Fame Preview: Mike McConathy
Our preview of the 2026 Louisiana Sports Hall of Fame Class concludes with Northwestern State’s legendary basketball coach - Mike McConathy!
Meeting the dozen new inductees in the 2026 Louisiana Sports Hall of Fame class
New inductees for Louisiana Sports Hall of Fame honored at press conference
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.
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 […]
Entertainment this week: Paul Thorn, Hike for Hope and more
Friday, June 26 Annual Ian Casey Classic – Tahoe Donner Golf Course. Our most popular event of the year, a full field of 130+ golfers will team up in foursomes and hit the links to...
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.
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'Unions built the American middle class.'
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