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Kadyn Proctor Can Solidify Dolphins Offensive Line in Big Way
The Miami Dolphins' offensive line may be good, but it can reach a strong height if rookie Kadyn Proctor can live up to expectations.
A’s Fall To Angels 4-1
Not a good day at the ballpark as the Athletics fell to the Angels 4-1 in Anaheim in the series opener. More to come…
Pensacola Black-owned business show off goods during Black Business Expo
Check out the goods and services black-owned business had to offer during the Black Business Expo at Pensacola's DeVillier's Square Sunday.
I spent weeks thinking my Pixel's camera lens was smeared before discovering the real culprit
I can finally take good pictures again!
Scratching bug bites feels good – but science says don’t do it
You’ve likely heard it since childhood: Don’t scratch that bug bite or rash, you’ll make it worse. But why would something that feels so good be bad?
Americans find common ground on healthcare
Americans agree that healthcare needs to be better, cheaper, and less complicated. Good ideas toward those goals are bubbling up around the country.
After trying a Google TV projector, I may never buy another TV ever again
After spending a few weeks with a Google TV projector, I think I may be done buying actual TVs for good. Here's what changed.
Science says these 7 parenting beliefs may be quietly making life harder for parents and children
Every parent wants to give their child the best possible upbringing. But in trying to be the “perfect parent,” many may be putting unnecessary pressure on themselves. A 2023 survey of more than 700 parents by researchers at Ohio State University found that 57% reported experiencing parental burnout. Surprisingly, the biggest predictor wasn't the number of children they had or how many hours they worked- it was the pressure to live up to an impossible standard of parenting. Child development experts say many of the beliefs parents consider signs of “good parenting” may actually be making life harder for both parents and children. Here's what science says.Here are seven common parenting beliefs that science says may be working against both parents and children.
Hunter Goodman smashes three home runs vs. Twins
Colorado Rockies designated hitter Hunter Goodman hit three long home runs against the Minnesota Twins on Saturday. Goodman crushed two no-doubters — solo shots in the first and third innings — in his first two at-bats against Twins starter Mike Paredes. Then, after grounding out in the fifth, Goodman came up with two runners on base and the Rockies leading 3-2 in the seventh.
Man with same name as U.S. Sen. Dan Sullivan is eligible for Alaska's primary ballot, judge rules
The judge ruled that the division’s decision to exclude Dan J. Sullivan because his candidacy was not “in good faith” was not based on the Constitution, Alaska law or the division’s own regulations.
GOP candidate with same name as senator can stay on Alaska ballot, judge rules
Supporters of incumbent Republican Sen. Dan Sullivan say a challenger with the same name is not running in “good faith,” but a judge says that is not an issue.
Scratching that bug bite might feel good at first but science explains why it's a bad idea
You've likely heard it since childhood: Don't scratch that bug bite or rash, you'll make it worse. But why would something that feels so good be bad?
Beloved Brookline restaurant closes after over 60 years in business
A well-known Brookline restaurant announced on Instagram that it officially closed for good after over 60 years in business.
City of Palms new downtown parking program: How local business react to the change
The Fort Myers City Council recently approved a change impacting parking rates at all three of downtown Fort Myers' parking garages. As it stood, visitors would receive one hour of free parking followed by a hourly rate. Now, the change has made it so visitors are entitled to two free hours followed by a hourly rate. Local business owners and managers said it's a good idea giving visitors more time to bask under the royal palms and indulge in some shopping. But one general manager points out a problem that did not start yesterday, but years prior.
Egor Shilov Drafted 43rd Overall By Colorado Avalanche
Penn State hockey commit Egor Shilov was drafted 43rd overall by the Colorado Avalanche in the 2026 NHL Entry Draft: Shilov quickly flew up the NHL Draft radar after an outstanding 2025-26 season with the Victoriaville Tigers of the QMJHL. He had 82 points (32 goals, 50 assists) in the regular season, good for 7th […]
Scratching that bug bite might feel good at first but science explains why it's a bad idea
Now researchers better understand why even a mildly annoying itch could put you on an itch-and-scratch cycle if you give in.
Scratching that bug bite might feel good at first but science explains why it's a bad idea
For the summer itchiness of bug bites and poison ivy, dermatologists recommend hydrocortisone cream, calamine lotion or oatmeal baths.
Scratching a bug bite feels good but science says it’s a bad idea
Researchers have gained a better understanding of why we have an itch to scratch.
Scratching that bug bite might feel good at first but science explains why it's a bad idea
You scratched that bug bite and now it's a big itchier bump. Some science explains why scratching really can make things worse, even if you don't break the skin. University of Pittsburgh researchers put tiny “cones of shame” onto mice to help unravel what happens on a cellular level when an itch ...
Scratching that bug bite might feel good at first but science explains why it’s a bad idea
You scratched that bug bite and now it's a big itchier bump.
Scratching that bug bite might feel good at first but science explains why it’s a bad idea
WASHINGTON (AP) — You’ve likely heard it since childhood: Don’t scratch that bug bite or rash, you’ll make it worse. But why would something that feels so good be bad? A lot of things can cause itc…
Scratching that bug bite might feel good at first but science explains why it's a bad idea
You scratched that bug bite and now it's a big itchier bump. Some science explains why scratching really can make things worse, even if you don't break the skin. University
Scratching that bug bite might feel good at first but science explains why it's a bad idea
You’ve likely heard it since childhood: Don’t scratch that bug bite or rash, you’ll make it worse. A lot of things can cause itchiness, sometimes serious diseases. Whatever the cause, doctors have l...
Stenberg Excited To Join Sharks, Believes He’s NHL-Ready
Ivar Stenberg says he is ready to be in the NHL next season. After being drafted No. 2 overall by the San Jose Sharks, he becomes yet another another big-name, highly-skilled player in their under-23 group. “They have something really good going on, so super happy to join a special group,” Stenberg said. The 5-foot-11 […] The post Stenberg Excited To Join Sharks, Believes He’s NHL-Ready appeared first on San Jose Hockey Now.
Our Editors Found 401+ Best Amazon Prime Day Deals Worth Shopping Before the Sale Ends
You have less than 24 hours left to shop deals across categories, and some of them are so good that they’re already selling out.
Good Sports: Former Bulldog track and field athlete aims to be flag football Olympian
Last June, Kaja Bins didn't know what flag football was. Kaja now has the potential to become an Olympian in a sport she learned a year ago.
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 […]
This Week's 10 Must-Read Stories on Women in Politics: Title IX Anniversary, AI's Anti-Women Bias and Ranked-Choice Voting Victories
Weekend Reading on Women’s Representation is a weekly compilation of stories about women’s representation in politics, on boards, in sports and entertainment, in judicial offices and in the private sector in the U.S. and around the world—with a little gardening and goodwill mixed in for refreshment! Published every Friday. —This week marked the 54th anniversary of Title IX. —As the Taliban approaches the five-year mark of its return to power this August, a rare protest in western Afghanistan last week laid bare both the brutality of its rule and the resilience of those living under it. —A woman will replace Eric Swalwell in California … but for not two more months. —A study of 133 AI systems found that 44 percent demonstrated gender bias, and more than a quarter showed both gender and racial bias. ... and more.
Trump threatens 100% tax on European imports if countries impose tax on digital services
“Please let this statement serve to represent that any Country that imposes such a Tax will immediately be met with a 100% TARIFF on any and all Goods sent to the United States of America,” Trump wrote in a post on social media.
Bunnie Xo says she told ‘so many girls’ to DM Jelly Roll amid divorce: 'Good luck with that'
Bunnie Xo said that she told 'so many girls' to DM Jelly Roll amid their divorce. The country star filed for divorce from the podcaster in May after nearly 10 years of marriage.
Last Chance To Fix Destiny 2 Delayed After Bungie Lays Off Devs
Bungie is running out of chances to set things right in its sci-fi MMO before it's left behind for good
The 5 Healthiest Fats You Can Eat
Fat has historically been demonized, but some types can be good for you.
Case Studies From Ireland: Making Sustainability Good Business
From Kinisla to Strong Roots, these food companies are making the business case for sustainable practices.
Sugar is not uniquely bad for you. But it’s undermining good habits.
Is sugar more harmful than other carbohydrates? The evidence is far from compelling.
Is Mega Skarmory good for Pokémon GO Raids?
Super Mega Skarmory Raid Day brings one of the new Legends: Z-A Mega Evolutions to Pokémon GO, and gives the undeniably cool Skarmory a new lease of life in the Raids meta. A popular / type from Gen 2, Skarmory has been a staple in the Little and Great League formats, but has never made […]
Healthy Employees Are Good. Healthy Leaders Matter More
Healthy, sharp employees are essential to a strong organization. But sequencing matters. High-performing organizations start with leaders.
It's Summer Sale Season, So I Tracked Down 25 Actually Good Gaming Deals Under $20
There's a million sales happening right now, so I sifted through them all to find 25 genuinely solid gaming deals that are each under $20.
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.
Steam Summer Sale 2026 arrives: 10 hot video game deals
Do you like Star Wars? We have good news.
Original 'Drag Race' star reportedly hospitalized in critical condition after fatal car crash
'RuPaul's Drag Race' season 1 queen David 'Jade' Sotomayor reportedly hospitalized after a fatal car crash in Chicago, with Monica Beverly Hillz telling EW she wants fans to send the family 'good vibes.'
Brad Stevens discusses ‘excitement’ surrounding Chris Cenac Jr.
“I hope we’re good enough that it’s hard for any 18-year-old or 19-year-old to come in here and be really good out of the gate.”
Cheshire orchard closes after 75 years in business
A longtime Cheshire orchard has announced its closing for good. In a message shared with customers, the family that owns Drazen Orchards said it is now permanently closed and will not reopen for the foreseeable future. The orchard has been open since 1951. The Drazen family said the decision was difficult, citing rising operating costs, the physical demands of running…
The Overlooked Reason ‘Destiny 2’ Is So Fantastically Fun Right Now
Destiny 2 is in an amazing state right now, which is unfortunately right at the end of the game. I think one thing deserves a good amount of credit.
David P. O'Brien
About five years ago, David P. O'Brien had a comfortable position at Marsh & McLennan Cos., where he held the top post at the financial giant's Louisville, Ky., office. Despite the lofty rank, Mr. O'Brien found himself longing to be at a smaller company that had to work a little harder to land business. That desire led him away from Kentucky five years ago and to Cleveland, where he serves as executive vice president at business insurance agency Oswald Cos. "I left Marsh before it was en vogue," he said, referring to layoffs and defections at Marsh over the course of this year that followed accusations of bid rigging at the big firm. Above all, Mr. O'Brien, 38, wanted to work at a company that relied on its inventiveness, rather than its name, for business. He said he has found that at Oswald. "It causes you to be more creative, to be more resourceful," Mr. O'Brien said. For instance, an Oswald client seeking to do business internationally might be directed to the network of offices abroad run by competitors such as Marsh and Aon Risk Services Inc. "We're going to use whatever access into the market that makes the most sense for our clients," he said. Of course, using such a strategy can be dangerous for Oswald if its client decides to further a business relationship with one of the firms Oswald recommended. "That's the obvious question and why it's nontraditional," he said. "I think if we're good, and if we're bringing value to the client, then there's no risk. I'm not threatened by it." Imaginative business solutions of that type made his career move to Oswald from Marsh worthwhile. "It's very much a challenge," he said. "It helps you keep your edge. I'm all for the competition." John Jacunski, currently vice president and corporate controller at York, Pa., paper company PH Gladfelter Co., met Mr. O'Brien four years ago when Mr. Jacunski was at WCI Steel Inc. in Warren. So impressed was he with Mr. O'Brien's work for WCI that Mr. Jacunski has retained the Oswald executive at PH Gladfelter. "He's a young guy for the position he has, but he's done a great job for us," Mr. Jacunski said. Among his roles at Oswald, Mr. O'Brien leads the firm's client retention efforts and also serves as director of its property and casualty group. "You don't have the same human resources," he said of the job jump to Oswald. "You don't have, obviously, the safety net a big company has." But sometimes, it can be difficult to ascertain individual contributions when working at a big company. "I wanted to be able to see the end results of my work and my efforts," Mr. O'Brien said.
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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(Welcome to the “Most Important Story of the Week”, my bi-weekly strategy column analyzing the most important (but often not buzziest) news story of the last two weeks. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. Please subscribe.) Scrolling through links over the last week, I stumbled across this fun headline: Wow. Formula 1 (the sport, not the docu-series) is the perfect “dog not barking”. As a reminder, each week in my Streaming Ratings Report, I call out the shows that miss every viewership chart. I dub them “dogs not barking”—like the Sherlock Holmes mystery—because without any data, we forget they even exist. This is in contrast to something like, say, a film flop—cough The Mandalorian and Grogu cough—where even underperforming at the box office is widely discussed here, there and everywhere. In the US, Formula 1 is now in “no public viewership data, so not discussed” territory. After moving to Apple TV from its former home of ESPN, basically no one talks about it. Apple did publish an initial, unsourced, unsubstantiated, (dare I say unserious) datecdote claiming more folks are watching Formula 1 on Apple than ESPN, but we haven’t gotten any updates since. This stands in contrast to when the sport streamed on ESPN, and ESPN PR provided weekly viewership figures. Formula 1 was, at best, a niche sport in America—averaging 1.3 million viewers in the Big Data Plus era—but now it’s basically anonymous. (And yeah, after moving to Apple, I very, very, very much doubt its ratings increased.) Unfortunately, that story isn’t quite big enough to warrant a section in today’s “Most Important Story of the Week” column, but I wanted to call it out, because otherwise, no one else will! Certainly, no one will write articles about the silence/ratings decline, unlike when they wrote breathless articles connecting the rise in viewership to Netflix’s Drive to Survive, including Reuters just last month. (This is a topic I’ve tried to provide a moderate/nuanced/non-hyped take since 2022.) Anyway, on to this week’s issue. I was a bit worried I didn’t have a juicy topic, then the Murdochs went out and did their Murdoch thing: buying Roku. So that’s the story of the week, and it happens to touch on quite a few themes of the streaming wars and the disruption therein. I’ll cover that, plus why more consolidation in Hollywood media looks likely, more good news on the Hollywood labor front, whether we’ll see an uptick in production in Los Angeles, some Broadway and theme park news, cellphone prices going up in the third world (and possibly everywhere), and more. Subscribe Most Important Story of the Week - Another Big Media & Entertainment Merger The story of the week is clearly Fox is buying Roku for $22 billion. I read a lot of good strategy takes on why Fox bought this streaming TV device maker—and I’ll have mine below—but what fascinates me more is how this deal connects to quite a few themes of the streaming wars, linking to everything from the pace of M&A to “aggregeddon” to Netflix’s recent M&A actions/inactions to the shift to advertising from pure play streaming and more. The only topic I can’t really connect it to is my old theory, “never bet against Rupert Murdoch” because he isn’t the one who did this deal; his son Lachlan inked it. (Do I think he provided advice, even at his 95 years of age? Sure.) That plus I have one additional piece of strategy for all entertainment players, inspired by this deal. So let’s dive into all those topics, starting with why I like this deal. Roku is a Great M&A Buy
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