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Baker Mayfield Drops Clear Message on Kyler Murray

As Kyler Murray seeks a fresh start in Minnesota, former teammate Baker Mayfield defends the polarizing quarterback, predicting a dominant resurgence fueled by a much-needed change of scenery.

Jun 28 • 9:35 PM EDT • Sports • sports.yahoo.com

Brain activity under anesthesia challenges what we know about consciousness

The unconscious brain appears to be far more capable than scientists once believed. Researchers found that patients under general anesthesia could still process language at a sophisticated level, distinguishing nouns, verbs, and adjectives while listening to stories. Even more remarkably, neural activity showed signs of predicting upcoming words before they were heard. The results challenge traditional ideas about consciousness and hint at new possibilities for brain-computer interfaces.

Jun 28 • 8:00 AM EDT • Science • sciencedaily.com

Grand Theft Auto VI pre-orders open, but don’t expect a physical copy

The blockbuster launch is expected to dwarf the box office takings of the year’s biggest movies with one industry analyst predicting it could make $1bn within an hour

Jun 25 • 10:17 AM EDT • Technology • theguardian.com

Predicting the Nets 2026-27 Opening Night Starting Lineup

In the aftermath of the 2026 NBA Draft and a big trade, how do the Nets look heading into next season?

Jun 23 • 11:05 PM EDT • Sports • sports.yahoo.com

Clalit Health Services to join European AI research project predicting, managing pandemics

Clalit Health Services will join an international consortium of health authorities to create an AI research platform to predict and manage pandemics in advance.

Jun 21 • 1:37 PM EDT • Health • jpost.com

Here’s who’ll win the World Cup, according to science

Statisticians from across Europe teamed up to train a competition-predicting, machine learning algorithm. This is what they found.

Jun 20 • 7:00 AM EDT • Science • sciencefocus.com

Miami Heat or Boston Celtics? Predicting Giannis Antetokounmpo’s Landing Spot

Giannis Antetokounmpo is likely nearing the end of his tenure with the Milwaukee Bucks. Milwaukee’s self-imposed trade deadline for Antetokounmpo […]

Jun 19 • 12:13 PM EDT • Sports • sports.yahoo.com

In Retrospect: Poland, Russia, Europe

In April I spent a few days with Zryw, a Polish non-profit organization that recruits young people to enter politics and public life. Their aim is to build a new generation of civic leaders in Poland. I’ve followed their evolution from the beginning; my son is one of the founders. (“Zryw” means “impulse” or “burst of speed” in Polish). Julie Chmielewska, one of Zryw’s leaders, interviewed me at the event. Here is the conversation, lightly edited for grammar and context: Julia Chmielewska: Assuming that culture shapes institutions, could we conclude that some cultures are more prone to authoritarianism? Anne Applebaum: I don’t think so. Every culture, every nation, and every country has the potential for change. When we look at history, we can see that nations do change. Poland has changed, for example, from the 1980s to today. There’s a completely different mentality here than the one I encountered when I first visited, in 1988. The current generation sees the world through a different frame. So no, I don’t believe that certain nations are doomed to authoritarianism, or to anything. Of course, there are political and cultural traditions, but they can always be challenged. JC: So do you think there’s something intrinsic in human nature that pushes people to democracy, freedom? AA: I think there is something in human nature, a deep instinct, that pushes people towards freedom, yes. People who live in authoritarian countries – and I’ve heard this from them over and over again – sooner or later find themselves angered by a feeling of helplessness. They can see the unfairness of crooked courts, irrational political decisions. They naturally dislike the fact that somebody has all the power while they have none. In those circumstances, people who have no political background at all sometimes are politicized just by that frustration. I’m thinking of Svetlana Tikhanovskaya, for example, who was a Belarusian housewife, until the circumstances of her husband’s arrest forced her to become a politician. I met a woman who is a Uyghur from China, and who had come to live in Turkey. After several of her family members were arrested, she too was propelled into a political role. These kinds of experiences make people interested in democracy or political reform, even if they thought they didn’t care. I also think that the opposite is true: some people instinctively prefer homogeneity, order, hierarchy. They don’t like the confrontation of opinions or the noise of debate, and they lean towards a single leader or a unified regime. I think that most of modern history is shaped by the clash between those two different sides of human nature. JC: Which force do you find more powerful today? AA: I think they both have a lot of power and there’s no way of predicting who wins. Even in countries that seem very shut off or stuck in an authoritarian system can change. We’ve seen that happen. And vice versa, I think democracies can also begin to fail and slide into authoritarianism. So it’s very important not to be complacent in either direction. JC: I want to go into your history and your experiences. You’ve lived in Russia during a time of incredible change in the late 80s, and then you came back to do research in post-Soviet Russia. AA: I was a student in Russia just before the collapse of the Soviet Union. I then traveled and worked there extensively in the 1990s, and I met people who really were full of hope. They hoped that Russia could become a democracy, or at least a place that guaranteed freedom of speech, freedom of the press. These weren’t ideas that came from Washington. Although now the narrative in the Kremlin is different, I met many people who were working towards exactly that kind of transformation. A friend of mine ran a series of seminars – once a year, and then later several times a year, in cities all over Russia – designed to get people to discuss politics in new ways. She invited young politicians and journalists, as well as foreigners. I went to many of them, in Moscow as well as Volgograd and Novosibirsk. Over two decades, hundreds of people came to these seminars, and all of them wanted Russia to be different. I remain convinced that many Russians still want Russia to be different. It’s just that the old system, in the form of Putin, a representative of that system, returned. The KGB reimposed their power. And this wasn’t because of something to do with culture, this was to do with money and politics, and who was in charge. JC: You’ve partially answered my question... I wanted to ask whether that excitement of the 1990s was an exception from the Russian historical norm which has been rather authoritarian? AA: Of course, if you look at the history of Russia since the 18th century, there have always been liberal groups, reformers and revolutionaries. There were the Decembrists, in the early 19th century, and the rural populists later on, who tried to organize the peasantry. A significant group of liberal Russians appeared at the turn of the 20th century, people like the father of the writer Vladimir Nabokov, who was a Russian politician before the revolution. These groups were small in number, but sometimes had a broader significance. The Russian dissident movement in the 1950s and 1960s actually invented the modern human rights movement. It was their idea to hold the leaders of the Soviet Union accountable for the language they used, to remind them of the treaties they had signed and the promised they had made. They created the Helsinki group, for example, that held Soviet leadership to the language of the Helsinki Treaty, which formally ended the Second World War and which contained guarantees of human rights, at least on paper. That idea spread to Eastern Europe, and similar tactics were used here in Poland. (Benjamin Nathans recently wrote a great book about the Soviet dissidents, To the Success of Our Hopeless Cause) JC: But seemingly, even if they do ever get power, they could never hold on to it. AA: We don’t know, because they have never really had power. But in any case, we also don’t know what will happen in the future. There is no reason to assume that Russia will forever be condemned to totalitarianism. Even during the first fifteen years of Putin’s regime there was some form of democratic politics. Only when the full-scale war began did he bring everything to an end: he shut down all remaining independent organizations and killed his most important opponent, Alexi Navalny. But does that mean he is popular, that he enjoys legitimacy? Even now, we don’t really know what Russians think about him, or about the war. There is no way of doing real polling in Russia because nobody will answer an independent pollster over the phone. JC: Do you think that the flock of young people, especially young men, who fled Russia after the start of the war represent a continuation of liberal movements that refuse to partake in the authoritarian state, or do you think they are moving for the sake of self-preservation – “I don’t want to go to the army, so I leave”? AA: I’m sure it’s both. I actually know many people who left Russia for political reasons either in the very last years before the war, or else just after the war began. JC: And do you see a change in the young generation versus the old one that have fled? AA: It’s hard for me to say because the people who I know were mostly already politicized. I do know some younger people who left, but most of them were already either active in the opposition, or working as journalists. Many of them very self-consciously think of themselves as maintaining Russian culture abroad, just as in the 20th century the Soviet dissidents or the anti-communist White Russians once thought of themselves as people who maintained the true Russian culture, outside of Bolshevik Russia. JC: Let’s move on to Poland. One of your first experiences with Poland was reporting on Margaret Thatcher’s first state visit, in the autumn of 1988. You followed her around the farmers’ market. AA: She was making a symbolic gesture. She wanted to welcome free markets, but the only one she could really visit was the farmers’ market at Hala Mirowska. JC: And I want to talk about this area because today you can look out of any window in that district, Mirów, and see rows and rows of skyscrapers. How does it feel to see a country built from the ground in such a short time, both politically and economically? AA: You know, when you’re living in a period of dramatic change, it’s always hard to know whether the change is positive or negative. The transformation in Poland created winners and losers, as well as new classes of people, new political movements of different kinds. At the time, it sometimes just felt like turbulence. Now, we can look back at the 1990s and early 2000s in Poland and see in retrospect that the country was headed in towards prosperity and European integration. In around 2009 or 2010, I remember speaking to a woman who worked cleaning government offices, and who asked me if her daughter should study in Amsterdam or in London. This seemed to me to be a real transformation, and it happened very fast: within a few years, Poles stopped feeling like second-class Europeans, and a generation of younger Poles appeared who had no qualms about crossing borders. JC: We again live in turbulent times. Do you think we’re heading towards positive outcomes? AA: I can’t make predictions, because everything that happens tomorrow depends on what people do today. Also, history doesn’t have a trajectory. It doesn’t move in a particular direction. You only think it does afterwards. As I said, you can look afterwards at Poland in the 1990s and you could say this was a period of great progress. But not everybody at the time saw that. Sometimes people are very wrong about a given country’s trajectory. I remember people writing about Ukraine in the 1990s, about how dangerous it was that Ukraine was independent, that this was going to be an anti-semitic state, that Ukrainian nationalism was going to come back... and although you can say many bad things about Ukraine, the country made many bad choices, actually it became a pretty tolerant state which now has a Jewish president and until recently a Muslim defense minister. JC: In the 1990s Poland’s and Ukraine’s GDP were roughly similar. Ukraine was even a bit richer. So the starting point was similar for both of these countries, but they’ve turned out very, very differently. Even if we stop in 2014. Why do you think Ukraine “chose East”? Was it external influence? AA: No, I think Ukraine was in a different position. First of all, central and eastern Ukraine had been part of the Soviet Union since the 1920s, and had therefore experienced a longer period of occupation, repression, Sovietization and even Russification. Ukraine did not have, as Poland did, an alternative elite: a large cadre of economists and politicians, who already had some experience in opposition politics and in independent thinking. In Poland, the transformative finance minister, Leszek Balcerowicz, had already thought about how an economy might be decentralized before he took office. We can argue about how successful he was, but at least he was prepared to try something new. In Ukraine, people weren’t prepared. For one, there hadn’t been much space even for an illegal opposition in the previous couple of decades. Ukraine was also in many ways still emerging from colonial occupation. For the previous couple of centuries, many of the most capable Ukrainians had moved to Russia, and the first generation of leaders in independent Ukraine tended to be former Soviet apparatchiks. They didn’t immediately seek to become closer to western Europe. Instead, they looked for some kind of economic and political “third way” and an accomodation with Russia. Ukraine became stuck in this position, half-in, half-out and became pretty profoundly corrupt. JC: The Polish alternative elite had a vision of where they wanted the country to go. I think the general perception now is that this vision ends with the next election, right? Is this a natural process of gaining power? AA: Their vision, and it was shared by the time by politicians who now call themselves both left and right, was that Poland should join the EU and NATO, as fast as possible. My husband (Radek Sikorski) was in the very first government that said it wanted to join NATO. At the time this was taken very badly in Washington: the demand for NATO membership absolutely came from Poland, not from the US. But even then, in the early 1990s, many Poles already understood that the Russian sphere of influence would grow once again, that it was important to become part of the transatlantic alliance and an integrated Europe as fast as possible: NATO, the EU, the Council of Europe, all of the trading and security alliances. That consensus lasted through several different governments and over many years, even governments containing former communists. For twenty years, right, left and center disagreed about many things, but they all agreed on the direction that the country should go. In retrospect, that consensus created the basis for prosperity in Poland. JC: And regarding the Polish-Ukrainian relations. We know that antagonisms, e.g. the myth of Wołyń [a massacre of Poles that took place in what is now Western Ukraine, in 1943] are increasingly used in Polish political discourse today. In Ukraine, nationalist historians make heroes out of UPA, the Ukrainian revolutionary army, which is held responsible for this tragedy. Where do you see a start for burying the hatchet? Is the reconciliation of our nations possible? AA: So here’s a strange thing: For more than a decade after they both gained independence, Poland and Ukraine participated in a number of projects that were designed to solve exactly these kinds of Polish-Ukrainian differences. Books were published that were jointly written by Polish and Ukrainian historians, monuments were built. These projects were successful: If you’d asked me this question in 2010, I would have said that there are no real historical issues between Poland and Ukraine, that the two countries had mostly reconciled. For a number of reasons, this began to shift. In Poland, children and grandchildren of victims of the Wołyń massacre felt their tragedy hadn’t been fully recognized. In Ukraine, nationalist groups wanted the UPA partisans who had fought against the Soviet Union recognized for their heroism, despite the fact that some in this broad and not well-defined group were also linked to Wołyń. In both eastern Poland and western Ukraine, the memory of the ethnic cleansing that took place there in the late 1940s - Poles were moved West, Ukrainians East - to accomodate new borders has left feelings of displacement and bitterness. The wave of Ukrainian immigration, which started before the war, may have provoked some of this. But don’t underestimate the role played by Russia, which has always wanted to create discord between Poland and Ukraine, and pumps out propaganda to that effect in both countries. Vandalism on both sides of the border, damage done to cemeteries and monuments, is sometimes carried out by provacateurs working for Russia, just to create bad feelings. The Polish-Ukrainian conflict also hides a different reality: although there are real grievances and bad memories, the truth is that the biggest tragedies both nations experienced in the twentieth century were inflicted by the Soviet Union and Nazi Germany. That should unite these two countries, not divide them. JC: This week (19.04.2026 – Ed.) in Hungary we saw that using historical narratives to create grievance has no longer worked. Are you optimistic about the direction after Orban’s loss? AA: The Hungarian election was really important because it shows that people can actually resist powerful, dominant propaganda. The ruling party Fidesz controlled all of the TV, 90% of the newspapers, the constitutional court, the bureaucracy... and yet people had the nerve to vote against it and resist it. It’s also an important election because Hungary created a huge network of well-funded think tanks and foundations that were funding other far right groups and projects. So that loss is going to have a knock-on effect in other places too, maybe even in Poland. JC: What you’ve said about resisting propaganda reminds me of one of the interviews you did about talking to Russians in the post-Soviet era who claimed that people knew that the system was lying. Why do people choose to believe in these regimes anyway? AA: Because it’s useful. Stephen Kotkin, an American historian, once described how people would learn how to “speak Bolshevik”: It was just a language that you needed to use in order to get by in society. If you didn’t talk the way the regime wanted you to talk, then you might have problems, or lose your job, or your kids would not get into university. It was a way of getting along. Communist Poland was similar, at least in the early years. When I was writing a book about the Sovietization of Eastern Europe after World War II, I met a lot of people who wanted to talk a lot about the war, when many of them had done really heroic things. But almost nobody wanted to talk about the decade afterwards, between 1945 and 1956. This was when you had the short period of terror, violence and Polish Stalinism. To stay safe, people felt the need to just go along with what others were saying, or stay out of politics, or use communist jargon without necessarily believing it. I don’t judge them for it, and I wouldn’t describe all of those people as collaborators. It’s easy to feel moral certainty in retrospect, because we know that communism ended. But if you were living in 1949, it might not have been clear to you that communism was going to end. In very repressive societies, maybe about 10% of people who are really evil – collaborators, torturers. Maybe 10% of people are really brave and who find ways to resist. And then around 80% of people have kids, they have parents, they have to have jobs and they’ve had to get through it somehow. Strange though it may sound, I’ve found that the work I did on that book is now very useful in explaining some of what’s going on in the United States today. There are plenty of members of the Republican Party in Congress who know perfectly well that Donald Trump says many things that aren’t true. But they avoid criticizing him because it’s inconvenient, because they would get in trouble, because someone would attack them on the internet. So actually you don’t even need mass terror to get people to conform. JC: Is Gen Z reinventing agency? AA: We’ll see. In any generation you can find groups of people who want agency. If you live in a society that’s unfair, for example where a tiny number of people have captured most of the wealth, then at a certain point people rebel. This is always easier for younger people, who have you have less to lose. The question now is how the internet will affect the relationships between citizens and the state, and how it will change organizations. The “Twitter revolutions” people spoke about as early as 2008-9, mass protests organized online, have often proved to be very superficial. Although you can easily join something just by clicking, the work of creating a real movement requires physical participation. Successful mass movements of the past, for example the Civil Rights movement in the United States, were built by people who had spent many years together. They had participated in non-violent workshops together. They practiced and prepared. Just using the you can get everybody to show up at a certain moment, but then when the protest is broken up, nothing happens. It’s also true that the repressive regimes have more recently learned how to use the internet to undermine leaders and movements. Most of all, they now understand how to make people cynical. The form of propaganda that most modern authoritarians use - and I think the Russians really pioneered this - deploys sneering cynicism. Instead of praising the rulers, the regime propagandists mock the opposition movement leadership for being supposedly corrupt or sexually degenerate, with the goal of undermining any kind of idealism. JC: MAGA grew on the internet? AA: MAGA is a real grassroots movement. They had symbols, red hats, they showed up at rallies. But you’re right that the cynicism, the sarcasm and the distrust that the movement embodies came originally from the internet, and this is different. Fifty years ago, most European political parties had a social base in real organizations, in trade unions for Social Democrats, in church groups for Christian Democrats. As people stopped going to church and as the trade unions became smaller, the social base of these parties disappeared. Now people who wouldn’t have known one another in the past meet on the internet and create new movements, many of which don’t last. JC: Is history ending? Going in stale circles? AA: History never ends. In truth, human beings want contradictory things at the same time: order and freedom, stability and change. These things are never resolved, and when a society swings too far in one direction, people always push it the other way. But each time that happens, the result is different. Certainly it is true that we are now in a period when old philosophers and ideas from the 1930s are undergoing a revival. Carl Schmitt, who was a philosopher who was very influential on the Nazis, is back as an influence on both the far left and the far right, once again inspiring people to think that all politics has to be existential, that all politics is about defining and defeating enemies. In the US, some are also bringing back dominionism, the idea that we need a Christian and not a secular state. It’s also true that we are living through a more fundamental shift. The old left-right divide, which was mostly about the size of the state, is much less important now. Instead, we are arguing about more fundamental things: what are our rights, what protects our freedom. Or how much power do we want to give small elites, versus how much power to give ordinary people. In America a small group of very wealthy people now control information, because they control the social media platforms and AI, which means they determine what people will read and learn. Finding a way to preserve preserve zones of autonomy and independent thinking, this is going to be the main task for the next generation. JC: What is the one book that a person interested in Central Europe should read? AA: You could read my book “Iron Curtain: the Crushing of Eastern Europe” which tells the story of how the Soviet Union imposed its culture on the region. Or read Tim Snyder’s history of the region, “The Reconstruction of Nations: Poland, Ukraine, Lithuania, Belarus 1569-1999.” And everyone should read “The Captive Mind” by Czesław Miłosz, which describes exactly the phenomenon we were talking about: why do people collaborate? I joined Scott Galloway and the brilliant Fiona Hill in a discussion about the wars in Ukraine and Iran, the future of global power, and what these conflicts reveal about America's role in the world. Scott told us that this was the 400th edition of his podcast, which is quite a number: My friend Francesco Chiamulera runs a brilliant series of literary events, Una Colline di Libri, A Hill of Books, in the Prosecco Hills, a region of vineyards and elegant hill towns in the Veneto, north of Venice. We did an event in Vittorio Veneto and also drove and biked around the countryside. Buy Autocracy Inc Buy Iron Curtain Open Letters, from Anne Applebaum is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe

Jun 13 • 4:15 AM EDT • Politics • anneapplebaum.substack.com

Sharks As Climate Scientists?Here’s How They Improve Ocean Forecasts.

A new study shows that data from tagged sharks can improve ocean forecasts by up to 40 percent in some regions, offering a surprising new tool for understanding and predicting climate patterns.

Jun 3 • 12:17 PM EDT • Science • forbes.com

Slick Science

Oily floors are slippery, costly, and one of the leading causes of workplace injury. Predicting just how slippery they'll be is now a good deal more reliable, thanks to a team of Swanson School of Engineering researchers whose work earned the 2025 Best Paper Award from the ASME Journal of Tribology. The winning paper, “Validation of a Multisca...

Jun 1 • 10:54 AM EDT • Science • news.engineering.pitt.edu

China Aims A.I. at Predicting Who Could Pose a Political Risk

New research examines how a Chinese company struggled to develop its predictive surveillance technology while U.S. restrictions were in place.

Jun 1 • 5:01 AM EDT • Politics • nytimes.com

I regret to inform you that ‘Steph Furry,’ the sports predicting corgi is a FRAUD

With all eyes on Game 7 of the NBA Western Conference Final between the Thunder and Spurs we’re looking for insight — the deep, analytic analysis that will tell us whether Oklahoma City has a chance to go back-to-back and potentially start or dynasty, or if Victor Wembanyama will punch his first ticket to the […]

May 29 • 10:56 AM EDT • Sports • sports.yahoo.com

AI & Science: What Is the Future of Discovery?

Continued progress in artificial intelligence, its expanding usefulness in science, and its contributions to landmark advances suggest that we may have entered a new era of AI for science.The breakthroughs so far—such as predicting the structure of practically every known protein, with profound implications for our understanding of biology, health, and the treatment of disease—are notable not only for what was achieved but also how it was achieved and what that suggests for scientific progress. This special double issue of Dædalus poses the question: What is the future of scientific discovery in this new age of AI? Thirty-three scientists responded. Bringing perspectives from life sciences and medicine, cognitive science and neuroscience, the physical and earth sciences, chemistry and materials science, computer science, mathematics and the social sciences—they draw on their work at the frontier of AI and science. The authors write with an eye to the future, not just the present. They explore what is being achieved and what possibilities lie ahead; examine AI’s limitations and efforts to move forward; and investigate the larger implications of AI-assisted science—on how science is done, the role of the scientist, and the scientific method, as well as the challenges and complexities involved.The authors together exemplify a long-standing bidirectional relationship: AI advancing science, while science advances AI. Where that relationship will take us—a golden age of discovery? New scientist-machine collaborations? Autonomous labs? Discoveries without human understanding?—is a future we are only beginning to imagine, and one we must also shape if the beneficial possibilities are to be realized.Image: UMAP sculptures visualizing three Dædalus volumes on artificial intelligence. © 2026 by Refik Anadol.

May 21 • 8:00 AM EDT • Science • amacad.org

MEET THE SAILORS, FLY-BYS AND NON-STOP ENTERTAINMENT – WHAT NOT TO MISS IN CAGLIARI THIS WEEKEND

The first stop on the ‘Road to Naples’ for the Louis Vuitton 38th America’s Cup is happening this weekend in Sardinia, on the beautiful waters of the Bay of Angels sat before the bustling port city of Cagliari. Forecasters are predicting ‘champagne’ conditions for the eight teams contesting the Prelim Regatta, and if the sea-breeze comes in, we can expect a feast of top-class international foiling in the world’s most exciting fleet-racing class – the AC40.

May 19 • 8:09 AM EDT • Entertainment • americascup.com

Modeling context-dependent RNA splicing by deep learning

Nature Computational Science - A framework called HELIX provides a strategy for predicting full-length transcript isoform usage across diverse biological contexts by integrating sequence features...

May 18 • 8:00 PM EDT • Science • nature.com

A strange ripple in spacetime could be the first fingerprint of dark matter

Black holes crashing together may be revealing clues about dark matter hidden across the universe. Physicists created a new model predicting how dark matter could subtly distort gravitational waves produced during black hole mergers. When they tested the method on real LIGO data, one signal stood out as potentially carrying a dark matter imprint.

May 18 • 8:00 PM EDT • Science • sciencedaily.com

New MatterChat Model Helps AI to ‘See’ the Language of Science

From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models depend on the high-resolution, three-dimensional data of the physical world, like the intricate lattice of atoms in a crystal. Delivering on the promise of using AI for science requires teaching these data-driven text models to seamlessly “talk to” physics-based models. Now, a new AI framework from Lawrence Berkeley National Laboratory (Berkeley Lab), called MatterChat, solves this problem by creating a specialized “bridge.” It connects the conversational power of a Large Language Model (LLM) with a physics-based AI that models “interatomic potentials”: the complex physical forces between atoms. The resulting system already significantly outperforms general-purpose AI tools like GPT-4 at predicting material properties, and the team hopes it can accelerate scientific discovery by serving as a robust research partner that provides grounded insights and generates step-by-step instructions for synthesizing novel materials. A paper describing this work was recently published in Nature Machine Intelligence. “Traditional simulations can provide the physical rigor required for materials science, yet their computational cost remains prohibitive for high-throughput screening. Conversely, while LLMs excel at rapid knowledge synthesis, they inherently lack the ‘structural vision’ to interpret materials directly from their underlying atomic coordinates,” said Yingheng Tang, a postdoctoral researcher in Berkeley Lab’s Applied Math and Computational Research Division (AMCR) and lead author on the paper. “MatterChat was built to solve this dilemma, empowering LLMs with a structural ‘vision’ that allows researchers to leverage their full potential for solving complex, real-world materials challenges.” Empowering language models to solve complex challenges in materials science To build MatterChat, the Berkeley Lab team drew inspiration from technologies like Vision Question Answering (VQA) and Text-to-Image (T2I) generation. In these tasks, AI must translate high-level text concepts into visual images, or vice versa. Doing so requires developers to build tools that “bridge” two fundamentally different forms of data. The researchers adapted this concept to the physical sciences. With MatterChat, they created a “bridge model” that successfully connects an LLM’s general knowledge with the deep understanding of the atomic-scale world encoded in scientific interatomic potentials. Until now, researchers using LLMs to solve materials problems usually had to feed them raw data files as if they were just strings of text. It’s like asking an AI to understand a complex 3D engine based only on a parts list: the LLM can read the names, but it can’t “see” how the atoms fit together in space. MatterChat solves this by training a specialized AI bridge model, pre-trained on millions of crystal structures and an LLM, to align the LLM’s representation of the world with the interatomic potential’s representation of the world. The bridge model can translate physical insights into a format the LLM can actually understand. By giving the LLM these “scientific eyes”— a scientific “inductive bias” in the terminology of AI — the Berkeley Lab team has transformed it into a robust research tool capable of providing grounded scientific insights into complex materials challenges, such as predicting thermal stability or analyzing electronic band gaps. “We think of atoms as living in a physical space, but from a machine learning perspective, they are just vectors living in some very non-trivially structured manifold in a high-dimensional Euclidean space; and, of course, the same is true for the sentences and paragraphs that we use to express our ideas about those atoms,” said co-author Michael Mahoney, Berkeley Lab’s Scientific Data Division (SDD) AI Initiative Research Lead. “The bridge model basically gets those two structures to ‘talk with’ each other.” As a proof-of-concept of this general approach, the team trained their bridge model on a dataset curated by pairing nearly 143,000 stable atomic structures from the Materials Project with their corresponding physical properties. This training data was automatically assembled using the Materials Project’s API and deliberately enriched with properties fundamental to microelectronics design — like formation energy and bandgap — allowing MatterChat to learn the complex patterns connecting a material’s atomic blueprint to its functional performance. To validate their model, the researchers benchmarked MatterChat against a suite of other AI systems, from general-purpose LLMs to other specialized scientific AI methods. The results show that MatterChat consistently outperformed its competitors across a range of tasks. The model was more accurate in classifying material types and demonstrated superior precision in predicting numerical properties. For example, it excelled at predicting a material’s bandgap, a property critical for designing new electronics from high-capacity energy storage to next-generation computer chips. “Our design is significantly more efficient because we don’t have to build a massive AI model from the ground up,” said co-author Zhi (Jackie) Yao, a research scientist in Berkeley Lab’s AMCR. “Instead, we take two powerful, pre-trained models — a structural encoder for materials physics and an open-source LLM — and use them off-the-shelf. The only component we actually train is the lightweight ‘bridge model’ that translates between them. It’s the difference between building an entire car factory and simply designing a smart adapter that connects a world-class engine to a world-class navigation system. This approach is not only computationally efficient, but also makes the system modular, so we can easily upgrade components or adapt the bridge for other scientific domains in the future.” Crucially, this modular design highlights exactly how institutions like Berkeley Lab and the Department of Energy are carving out a highly valuable niche in the booming AI landscape. Rather than competing with Silicon Valley tech giants to build ever-larger language models from scratch, the lab is focusing on the specialized connective tissue that makes commercial AI useful for hardcore science. Because the bridge model approach underlying MatterChat is forward-compatible, it is perfectly positioned to leverage these parallel tracks of innovation. As Mahoney pointed out, “We expect that industry will continue to develop improved LLMs, and we expect domain scientists and facilities will continue to generate new data. An important part of scientific machine learning is not simply to solve problems on today’s data, but instead to develop general methods that will be forward-compatible with orders of magnitude more data, whether from scientific domains or from LLMs.” According to Yao, the MatterChat project, which was initially developed and enhanced with funding from a Berkeley Lab Laboratory Directed Research & Development (LDRD) Program, will now expand its capabilities. In a collaboration with Fermilab, MatterChat is already contributing to a U.S. Department of Energy Genesis Mission project — called Accelerating eXtreme Environment Specs-to-Silicon (AXESS) — that aims to speed up the development of next-generation, high-speed, radiation-hardened detectors for challenging particle physics experiments by using advanced 3D integrated circuits (chiplets) and AI-driven data analysis. In addition to the LDRD support, the team also credits supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab, with MatterChat’s success. “We are incredibly grateful to NERSC; this research simply would not have happened without access to the Perlmutter supercomputer through their AI for Science program,” said Tang. Wenbin Xu, a NERSC postdoctoral fellow at the time, was also a major co-author of the work, as was Benjamin Erichson, a research scientist in Berkeley Lab’s SDD, highlighting the benefits of AMCR-SDD collaboration on AI for science. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

May 18 • 11:00 AM EDT • Science • newscenter.lbl.gov

ESPN expects a breakout season for Raiders RB Ashton Jeanty

ESPN is predicting a breakout season for Las Vegas Raiders running back Ashton Jeanty

May 18 • 10:00 AM EDT • Sports • sports.yahoo.com

'The Boys' showrunner reacts to show again predicting the future, as Trump unveils gold statue of himself

'The Boys' showrunner Eric Kripke reacted to the superhero show again predicting the future, after President Donald Trump unveiled a 22-foot gold statue of himself that's been dubbed 'Don Colossus': 'Seriously what the f---?'

May 10 • 10:13 PM EDT • Entertainment • ew.com

2026 NFL schedule release: Predicting matchups for Thanksgiving and Christmas games, plus season opener

Who will be playing on Thanksgiving this year? We've got predictions for that and five other games.

May 8 • 11:44 AM EDT • Sports • cbssports.com

2026 NFL schedule: Predicting who the Seahawks will play in Week 1 to open the season

May 7 • 9:05 AM EDT • Sports • sports.yahoo.com

Translating biodiversity into chemical diversity

Nature Computational Science - DeepSeMS, a transformer-based generative framework, translates biodiversity into chemical diversity by predicting microbial secondary metabolite structures directly...

May 4 • 8:00 PM EDT • Science • nature.com

Michigan football predicted to land another 4-star commitment

Michigan football recruiting could land another big commitment soon, with experts predicting 4-star EDGE Jayce Brewer.

May 4 • 7:44 PM EDT • Sports • sports.yahoo.com

Scientists discover a universal law across every form of life on Earth, severely challenging evolution theory

Study reveals a Universal Thermal Performance Curve, UTPC, predicting how all life responds to heat, challenging evolution theory.

May 4 • 6:54 PM EDT • Science • earth.com

Senate Bans Prediction Markets for Its Members and Staff

Senators voted unanimously to prohibit betting practices in the chamber after some users made hundreds of thousands of dollars online by accurately predicting U.S. military actions.

Apr 30 • 6:13 PM EDT • Politics • nytimes.com

Predicting consequences of new hepatitis B vaccine recs

New data on public trust in science, AI and mental health, and other news from Morning Rounds

Apr 28 • 7:46 AM EDT • Health • statnews.com

Youtility Decision Science: $4.2 Million Raised To Build Behavioral AI Platform For Predicting Customer Decisions

Youtility Decision Science, a behavioral AI company focused on understanding and predicting consumer decision-making, announced that it has completed the second close of its seed funding round, bringing total capital raised to $4.2 million. The round was backed by a consortium of strategic investors, including Silver Falcon Capital, Fyllo, and National Media, along with additional industry investors and family offices.

Apr 26 • 8:55 AM EDT • Science • pulse2.com

2026 NFL Draft Gambo 5: Predicting the Cardinals' pick

John Gambadoro names a group of five players, and he guarantees one of them will be picked by the Arizona Cardinals if they stay put at No. 3.

Apr 23 • 11:54 AM EDT • Sports • arizonasports.com

NFL insider predicts Anthony Richardson gets traded to the Steelers

Kay Adams was right on the money predicting Dexter Lawrence getting traded to the Bengals… does lightning strike twice with her prediction of the Steelers getting Anthony Richardson?

Apr 23 • 7:44 AM EDT • Sports • sports.yahoo.com

The Science of piRNA and Predicting Death With a Blood Test

A new study analyzed piRNA — first discovered in 2006 — as a strong predictor of short-term survival in older patients. It could one day be a simple blood test.

Apr 20 • 8:00 PM EDT • Science • medscape.com

Predicting every game left in the Premier League title: How Manchester City will edge out Arsenal by a goal

If the two teams are tied on points, goal difference could decide the title, so the score of every match matters

Apr 20 • 2:42 PM EDT • Sports • cbssports.com

2026 NFL Draft: Seven-round full mock draft picks for every team

Predicting every pick of the 2026 NFL Draft and 32 teams' paths to success.

Apr 20 • 7:00 AM EDT • Sports • cbssports.com

Markets are correctly perceiving that politics will steer rate policy, says CIO

Rich Weiss, CIO of Multi-Asset Strategies at American Century Investments, says that markets are correctly predicting that politics will triumph over economics in pressuring the Fed to cut rates.

Apr 16 • 2:20 AM EDT • Politics • cnbc.com

UFC White House adds historic $1 million fighter bonus

If the stakes at the UFC White House weren't already high enough, fighters will now get the chance to collect a $1 million bonus when the event rolls around on June 14. Upon the announcement of the event, there was excitement in the air with many predicting who they believed would feature on the ...

Apr 13 • 5:05 PM EDT • Sports • sports.yahoo.com

How aggressive breast cancer turns off the immune system

Researchers are launching a new project to crack the mystery of aggressive breast cancer, where predicting disease progression remains a major hurdle. By studying how tumors interact with and suppress the immune system, scientists aim to identify new biomarkers that reveal how the cancer evolves. Using real patient samples, the team hopes to turn earlier discoveries into practical clinical tools. The goal: more precise, personalized treatments that can outsmart even the most dangerous tumors.

Apr 11 • 8:00 PM EDT • Science • sciencedaily.com

“AI polls” are fake polls

A few weeks after Donald Trump’s second presidential win, I took the train up from London (where I was living at the time) to Oxford to attend a conference on polls and forecasts of the 2024 election. Most of the attendees were pollsters or academics, but I also watched presentations from Aaru and Electric Twin, two companies that do what is interchangeably called synthetic sampling, silicon sampling, or synthetic audiences. Stripped of startup jargon, that means they use large language models (LLMs) to simulate responses to public opinion polls by having AI agents take on the role of survey respondents. I had already heard of Aaru thanks to some articles with eye-catching headlines like “No people, no problem: AI chatbots predict elections better than humans” in the months leading up to Election Day. The founders were making some big, some might even say far-fetched claims, such as: “within two years, we will simulate the entire globe — from the way crops are grown in Ukraine to how that impacts production of oil in Iraq, trade through the strait of Malacca, and elections for the mayor of Baltimore.” When Semafor asked Aaru’s cofounders — Cameron Fink and Ned Koh — about my boss, they said “we respect all those who came before us.” Nate (as he so often does) shared his thoughts on Twitter: Fink and Koh were relatively good-natured about this back-and-forth when we spoke at Oxford. They even offered to mail me one of the t-shirts featuring Nate’s quote they apparently had made. I never took them up on the offer, which I now somewhat regret. These synthetic sampling companies fell off my radar for a while, but they do still exist. In fact, Aaru recently received a $1 billion valuation. Is what they’re doing anywhere close to the most important frontier in AI development? Not by a longshot, especially when Anthropic just developed a model so adept at exploiting software vulnerabilities that it’s only being released to 40 companies. Still, silicon sampling is increasingly finding its way into public polling. Axios reported in March that “a majority of people trust their own doctors and nurses” based on findings from Aaru — without mentioning that the “people” in that sentence were actually LLMs. Around the same time, the Public Sentiment Institute “boosted” their online sample of 373 real survey respondents with 114 AI agents.1 (Spoiler alert: even the co-founder of Electric Twin doesn’t think that’s a particularly defensible approach.) Polling companies like Qualtrics and Ipsos are also developing synthetic data panels. So, what should we make of these … “polls”? Let’s get one thing out of the way: whatever they are, they’re not polls in the way that term is usually defined. Subscribe You can’t replace polls with AI On one hand, using LLMs to essentially make up fake survey respondents sort of sounds like the dumbest idea ever, one that will at best imperfectly replicate real polls while introducing all sorts of biases. On the other hand, with LLMs improving at a remarkable, perhaps even alarming rate, maybe that means I’m a dinosaur at the ripe old age of 24 because I still want to rely on polls that talk to actual people. I’m not going to argue that synthetic samples are completely useless. In fact, as I’ll return to later, there is evidence that some techniques can replicate topline survey results quickly and cheaply. But the marketing from certain companies can be slightly optimistic. “No traditional poll will exist by the time the next general election occurs,” said Fink in 2024. We’re just 206 days away from the midterms, and based on the fact that I still have to collect a bunch of polls every day, I’d say he should have run that prediction by a sample of AI agents before the interview.2 To see why synthetic samples can’t replace polls, here’s a quick primer on how they work. The simplest version of these models involves taking a LLM (like ChatGPT or Claude), giving it a demographic profile (e.g., a white, college-educated woman who lives in Utah and makes $70k a year), and then asking it to respond to a survey question. You repeat that process a few thousand times using different demographic profiles and end up with a sample of synthetic survey responses. The actual models used by private companies are more sophisticated than this, usually because they incorporate more hypothesized demographic characteristics for each agent and provide them with extra information. Aaru, for example, feeds agents a diet of news and information they’d be likely to consume, while Electric Twin incorporates their customers’ proprietary data about the audience they’re trying to replicate. The way Ben Warner, the co-founder of Electric Twin, explained it to me was “we have a large amount of data on […] for instance, 5,000 people. Can we make an accurate prediction of how they would respond to another question?” Still, it should be obvious why synthetic samples can’t replace polls. Polling is fundamentally a data collection process. We might use surveys to make predictions by feeding them into election forecasts, but the main purpose of a poll isn’t prediction, it’s gathering new data about what people think and how they feel. Silicon sampling, on the other hand, produces no new data. It’s simply a model: you input LLM training data, demographic prompts, and a bunch of other information, and it spits out a prediction for what a poll would say. We love models here, but models aren’t polls. That difference is an important philosophical sticking point for most pollsters I talk to. “I think politics should stay away from [synthetic sampling], because we’re trying to […] represent the voice of the people,” said Natalie Jackson, a vice president at GQR Insights. Democratic pollster John Hagner told me: “I think I’m just incredibly skeptical of this idea. I don’t think it’s research. At that point, you’re asking the machine to tell you what you already believe.” Hagner has seen some presentations of early synthetic sampling experiments, but so far, “if it’s being used in a campaign, people are keeping it incredibly quiet.”3 But Eli, I hear you saying, aren’t polls themselves increasingly governed by modeling decisions? Indeed they are: pollsters’ choices on which sampling method to use, how to define their likely voter models, and how to weight their samples can and do lead to dramatic differences in the results they publish. Aaru even referenced these limitations in the methodology statement included with that maternal mortality “poll” — although I’m using the term “methodology statement” loosely here, because it doesn’t really explain how the model works at all. We can ignore the (frankly preposterous) implication that synthetic sampling isn’t subject to a separate set of biases. The important point is that there’s still a meaningful difference between using weighting and other statistical techniques on actual polling data and using a model to predict what a poll would say. The latter is far closer to election forecasts or techniques like MRP — potentially useful models, but not a replacement for polls.4 To be fair, other synthetic sampling companies are perfectly happy with the distinction between polls and models. Warner compared polling and synthetic sampling to different tools in a toolbox. “The mistake I think we make is we think that these new tools should either work in exactly the same way or somehow replace these old tools,” he said. “Rather than thinking of it as, okay, so we’ve always had the hammer, we’ve always had the screwdriver, now we’ve got a saw. But don’t use a saw to try [to] do the job of a hammer.” A quick comment from Nate Eli didn’t ask me for a comment — rather rude of him, don’t you think? But since I’m editing this story, I figured I’d add a few quick thoughts rather than putting words in his mouth. Beyond the frequently misleading marketing, what bothers me about the AI “poll” hype is that as AI tools make statistical inference cheaper and/or better (note that these are not synonyms) that actually increases the comparative value of collecting original data. You might be able to train a model to make a reasonable estimate of what some hard-to-reach poll respondent would say — say, a young Black man who voted for Trump. (Such a person checks a number of boxes for a voter who is usually hard to reach in surveys.) Indeed, this is closely related to what models like the Silver Bulletin forecast already do. They essentially smooth out the kinks in noisy survey data by making inferences based on past voting patterns or national polls or surveys of other states. But you don’t actually know what these voters think unless you’re reaching them directly. If there’s a shift in opinion among this subgroup, you’re not going to detect it. So if I were running a campaign, I’d invest more in going the extra mile to find a representative sample of those voters. And then I’d hire some smart quants — or Claude? — to figure out the implications for campaign strategy based on proprietary data that my competitors didn’t have access to. -Nate Silver Are these models any good? If synthetic surveys are just a new type of model, the next obvious question is whether the models are at least accurate. The answer very much depends on who you ask. On one end of the spectrum, you have the maximalist argument that synthetic sampling is more accurate than actual polls. “It’s an incredibly challenging problem to go to someone and say ‘hey, we’re going to be more accurate at predicting human behavior than you, even when you talk to your customers directly’,” Koh recently told CNBC. In his view, synthetic sampling isn’t a saw to polling’s hammer, it’s “magic.” There’s certainly evidence that synthetic samples can replicate certain survey toplines. But if Aaru does have any examples of their approach outperforming the polls, they’re keeping those to themselves.5 Aaru’s 2024 election model, for example, had Kamala Harris leading in Michigan, Nevada, Pennsylvania, and Wisconsin on November 4th. And although they’ve since taken down their forecast page, they gave Harris a 50.5 percent chance of winning the race on November 2nd.6 After the election, Fink told Semafor he was happy enough with those results because they were “within margin of error,” a term that is completely meaningless when applied to a “sample” of AI agents. And of course, Aaru says their models have improved since 2024, so supposedly now they’d be more accurate than the polls? Still, their stronger argument is on cost: “We are significantly faster and cheaper than traditional polling, and still more accurate,” said Fink. The first two claims are undeniably true, but the third brings us to the opposite end of the spectrum. Both Jackson and Hagner are skeptical that these models are reliable for anything beyond replicating common survey toplines. “I just […] don’t think the machines are what we want when we’re looking for nuanced views. My example on this is people in Arizona and Nevada in 2024 who voted for Trump and voted for expanding abortion in their states on ballot initiatives,” said Jackson. Hagner identified another issue. Maybe the synthetic respondents, like sycophantic LLMs, are inhuman in one important way: they’re too nice. “The reports that have come through at the meetings that I’ve been at are that the early experiments on this, they cannot get respondents to be as racist or sexist or, frankly, as negative as human respondents,” he said. Academic research mostly agrees on this point. While there are some papers that show promising results when using LLMs to replicate polling data, most show that LLMs suffer from various quirks like producing too few “don’t know” responses and can seriously overpredict the favorability of politicians like Donald Trump and Kamala Harris. They also seem to struggle with too little variation between demographic subgroups, so the difference in predicted opinion between Democrats and Republicans, for example, is too small. When I asked Warner about these studies, his response to these papers was that just because academics can’t get synthetic sampling to work doesn’t mean that the technique doesn’t work in general. “Actually, the argument is, okay, yours does not [work]. That does not mean […] for this complex set of machinery, which uses a lot of investment, a lot of time, a lot of money, you can’t get it to work.” Cards on the table, I’m somewhat sympathetic to this argument because academics aren’t exactly great at making election forecasts. Usually, the people with skin in the game are the most accurate. Warner’s argument is that the approach Electric Twin takes — which includes, for example, making multiple predictions for each synthetic respondent using different models and prompts and subsequently averaging those to get a final prediction in a sort of ensemble forecast — produces better results than the simpler academic models. Warner shared a comparison between his method and the method from a recent academic paper with me, and Electric Twin was indeed able to get more accurate replication. But even still, he acknowledged that synthetic sampling “is not a crystal ball.” “If you asked me, do I think using other data sources will be more accurate than asking somebody who they will vote for, I would probably say no. But if you asked me ‘would your system be useful for our turnout modeling today?’ I would say yes.” For better or worse, it looks like the method is already getting more popular in the market research world. Most of the clients Aaru touts these days are businesses like EY and McDonald’s. And AI will probably begin to pop up in other parts of the political polling process. Pollsters are already using it to code open-ended survey responses, and some firms, like YouGov, are testing using LLMs to ask survey respondents questions. More worryingly, one danger to actual polls is that AI agents can be used to infiltrate online surveys. Most online polls use various checks to prevent that from happening, but there’s conflicting evidence on how effective those filters are and how prevalent AI agents currently are in online panels. If those agents ever become impossible to detect, it might spell the end of online polling, but the solution isn’t to replace all of your respondents with ChatGPT. Silver Bulletin is a reader-supported publication. To receive new posts and support our work, consider becoming a subscriber. Subscribe 1 That particular poll obviously doesn’t meet Silver Bulletin standards for aggregation. But we exclude all Public Sentiment Institute polls from our averages because we classify them as an amateur polling firm. 2 You could argue that Fink meant the next presidential election, but (a) I’m also confident we’ll still have real polls in 2028 and (b) in that case he should have asked an LLM to define “general election.” 3 Quick caveat: that’s reporting from a Democratic pollster. It’s possible that Republicans are more willing to use AI in political campaigns. 4 Indeed, Silver Bulletin does not include “polls” produced by MRP in our forecasts or averages, and we think it’s extremely misleading when their practitioners describe them in a way that suggests original data had been collected among a large number of states or Congressional districts. 5 A recent report from Aaru and EY did show two examples of a synthetic estimate being closer than a survey to a real-world benchmark — but I’d take those findings with a grain of salt because the report reads more like an ad and didn’t involve any sort of prediction being made ahead of time. 6 For comparison, our odds for Harris on the same day were 48.2 percent.

Apr 11 • 11:38 AM EDT • Technology • natesilver.net

Interview: Rob McClure on the Unsettling Reality of SPARE PARTS – “This Isn’t Science Fiction. It’s Just Science.”

“Experimenting on yourself is insane. An experiment on a single person, with no controls, tells you nothing. It is incapable of predicting anything.” Or… is it? Such is the premise of Spare Parts, the darkly comedic and deeply twisted new drama currently shaking up Theatre Row through April 30th — and subverting our standards of what …Read more

Apr 10 • 10:15 AM EDT • Science • stagebuddy.com

Is the Options Market Predicting a Spike in Tencent Music Entertainment Stock?

Investors need to pay close attention to TME stock based on the movements in the options market lately.

Apr 9 • 8:00 PM EDT • Entertainment • zacks.com

Teen Science Cafe/ AI in Everyday Life and Healthcare

We are excited to invite you to the Alexandria Teen Science Café on April 16, where we’ll explore how emerging technologies are reshaping the future of health. This month’s café will show you how the data behind everyday apps is being transformed into powerful tools that help solve medical challenges once considered impossible, even predicting

Apr 3 • 7:37 PM EDT • Science • arlnow.com

How Will Reading’s Playoff Rivals’ Seasons Pan Out?

Jamie has a crack at predicting how the teams around Reading will fare in the rest of the season.

Apr 2 • 4:00 PM EDT • Sports • sports.yahoo.com

Predicting the Lions’ 2026 starting offensive line

A detailed look at what the Detroit Lions’ offensive line could look like for the 2026 season.

Apr 2 • 7:00 AM EDT • Sports • sports.yahoo.com

Predicting Harmful Algal Blooms and Toxicity in the San Francisco Estuary

In fall 2023, National Oceanic and Atmospheric Administration (NOAA) awarded a five‑year, $3 million Monitoring and Event Response Research Program (MERHAB) grant to improve Harmful Algal Bloom (HAB) detection in the San Francisco Estuary.

Mar 31 • 8:00 AM EDT • Science • usgs.gov

Predicting Falcons QB battle as Kevin Stefanski discusses expectations for Tua Tagovailoa, Michael Penix Jr.

Let's take the temperature of the upcoming competition in Atlanta.

Mar 30 • 1:44 PM EDT • Sports • cbssports.com

How sports traditions like March Madness can support brain health

Three experts from the University of Kentucky say the answer may be yes. Research shows that staying mentally, socially and emotionally engaged can help support long-term brain health. Activities tied to sports — like predicting tournament outcomes, reminiscing about past games or gathering with friends and family to watch — can stimulate memory, strengthen cognitive skills and foster meaningful social connections.

Mar 18 • 4:00 AM EDT • Sports • uknow.uky.edu

Hail Yeah! NASA Researchers Use Volunteer Observations for Hail Estimates

The bigger the hailstone, the more damage it can cause. But scientists find that predicting hailstone size can be challenging. How quickly does hail melt as it falls?

Mar 17 • 8:28 AM EDT • Science • science.nasa.gov

'Super El Niño' could push global temperatures to unprecedented highs, forecasters say

A "super El Niño" could emerge by the end of the 2026 hurricane season, with forecasters predicting that the ongoing La Niña is about to finish.

Mar 16 • 2:03 PM EDT • Science • livescience.com

Consulting firms say AI agents are upending the company org chart

As a torrent of AI agents enter the workforce, consulting firms are predicting a new "Great Flattening" of the corporate management structure.

Mar 9 • 5:04 AM EDT • Business • businessinsider.com

Rare ‘blood moon’ total lunar eclipse to loom over North America, Australia and New Zealand

Eclipse will feature a deep, coppery-red full moon on 3 March, with scientists predicting the best times to see it

Mar 1 • 7:50 PM EST • Science • theguardian.com

Amazon CEO: Many jobs won't need as many humans due to AI

"You won't need as many human beings doing those same jobs," Amazon CEO Andy Jassy said, predicting AI would also create new jobs as well.

Feb 27 • 11:34 AM EST • Business • businessinsider.com

March Madness bracketology: NCAA Tournament field projection has new look

As the dawn of March is nearly here, the final bracketology predicting the NCAA men's tournament has a new No. 1 seed after a week full of results.

Feb 27 • 5:50 AM EST • Sports • sports.yahoo.com

Yankees news: Spring training games show ABS success

Yanks proving strong on challenges; CC’s No. 52 to be retired; the next steps for Warren; predicting the Opening Day roster.

Feb 26 • 12:00 AM EST • Sports • sports.yahoo.com

NFL mock draft roundup: Experts predict first round before NFL combine

The NFL combine starts on Feb. 26. The NFL draft begins on April 23. Here's how draft experts are predicting the first round before the combine.

Feb 23 • 6:30 AM EST • Sports • usatoday.com

Deep learning for asymmetric catalysis

Nature Computational Science - A recent study develops a model for predicting stereoselectivity and absolute configurations in asymmetric hydrogenation of olefins.

Feb 9 • 7:00 PM EST • Science • nature.com

AI to track icebergs adrift at sea in boon for science

British scientists said Thursday that a world-first AI tool to catalogue and track icebergs as they break apart into smaller chunks could fill a "major blind spot" in predicting climate change.But scientists have long struggled to keep track of these floating behemoths once they break into thousands of smaller chunks, their fate and impact on the climate largely lost to the seas.

Feb 4 • 8:02 PM EST • Science • yahoo.com

This Breakthrough Lets Scientists See Arctic Ice Loss Coming

Scientists have unveiled a powerful new method for predicting Arctic sea ice months in advance, just as climate change drives rapid ice loss.

Feb 3 • 11:00 AM EST • Science • scitechdaily.com

DiffSyn: a generative diffusion approach to materials synthesis planning

Nature Computational Science - A generative AI approach is developed for predicting materials synthesis recipes—a complex challenge in materials science. Using this approach, the authors...

Feb 1 • 7:00 PM EST • Science • nature.com

Predicting Jahmyr Gibbs’ Contract Extension With Detroit Lions

The Detroit Lions are expected to exercise Jahmyr Gibbs’ fifth-year option and pursue a long-term extension.

Jan 27 • 7:09 PM EST • Sports • detroitsportsnation.com

Health officials share safety tips for freezing temperatures ahead of Alabama cold snap

Starting next week, WSFA meteorologists are predicting a significant drop in temperatures across Alabama.

Jan 23 • 9:34 PM EST • Health • wsfa.com

Kyle Tucker joins the Dodgers: Predicting the lineup with Ohtani, Betts and Freeman

Tucker joins an impressive roster that already includes Shohei Ohtani, Mookie Betts and Freddie Freeman

Jan 15 • 11:28 PM EST • Sports • cbssports.com

Chuck Schumer Calls His Shot

After securing strong recruits on a tough Senate map, the Democratic leader is not only predicting an upset 2026 victory, but also naming the states he thinks his party can flip.

Jan 14 • 5:02 AM EST • Politics • nytimes.com

World Baseball Classic: Predicting the Team USA lineup

How will Mark DeRosa organize his star-studded roster?

Jan 13 • 9:16 AM EST • Sports • cbssports.com

This simple math trick could transform earthquake science

Earthquakes happen daily, sometimes with devastating consequences, yet predicting them remains out of reach. What scientists can do is map the hidden layers beneath the surface that control how strongly the ground shakes. A new approach speeds up complex seismic simulations by a factor of about 1,000, making risk assessments far more practical. While it won’t forecast the next quake, it could help cities better prepare for one.

Jan 6 • 7:00 AM EST • Science • sciencedaily.com

NFL Week 18 Game Picks

Predicting the winners of this week’s football matchups.

Jan 3 • 1:16 PM EST • Sports • sports.yahoo.com

Happy new year: what's happening in physics in 2026?

Predicting the future is hard, but here’s a flavour of what’s hot in physics right now

Dec 31, 2025 • 7:15 PM EST • Science • physicsworld.com

The business of predicting the future is booming but EU regulators remain uneasy

Prediction markets are ushering in a new era where collective judgement and "crowd wisdom" are no longer theoretical concepts but tradable commodities. Yet despite their growing success, they remain banned in many EU countries.View on euronews

Dec 30, 2025 • 1:01 AM EST • Business • euronews.com

Predicting Hollywood in 2026

Educated guesses, smart takes and back-of-the napkin math on what entertainment industry insiders will be talking about in the next 12 months.

Dec 27, 2025 • 9:09 AM EST • Entertainment • hollywoodreporter.com

The biggest political headlines from 2025!

This Sunday, Host Matt O'Donnell and the Panel are dressed to the nines to discuss biggest political stories from 2025 ... while predicting the biggest headlines for 2026 in the New Year's edition!

Dec 26, 2025 • 7:24 PM EST • Politics • 6abc.com

NFL Week 17 Game Picks

Predicting the winners of this week’s football matchups.

Dec 25, 2025 • 1:04 PM EST • Sports • bleedinggreennation.com

NFL Week 17 predictions by Microsoft Copilot AI for every game

Microsoft Copilot picks all of the NFL Week 17 games after going 12-4 predicting the results of the previous week's contests.

Dec 25, 2025 • 12:18 PM EST • Sports • usatoday.com

Predicting NFL Week 16 winners: Odds, picks for Sunday

Week 16 is underway. We pick the winners for each game on the Sunday schedule.

Dec 21, 2025 • 10:33 AM EST • Sports • thephinsider.com

The ironic case for Tom Brady as my sports media person of the year: Deitsch

Richard Deitsch started the year predicting Tom Brady wouldn't last. He ends it making the case Brady is the Sports Media Person of 2025.

Dec 18, 2025 • 6:05 AM EST • Sports • nytimes.com

The AI industry wants to turn the routine mammogram into a powerful multitool

A new generation of AI algorithms aim to go beyond detecting cancers to predicting risk for cardiovascular diseases.

Dec 15, 2025 • 4:30 AM EST • Health • statnews.com

Predicting conference championship game overreactions: Notre Dame gets bounced

Conference championship game weekend should provide plenty of fuel for overreactions

Dec 4, 2025 • 12:58 PM EST • Sports • cbssports.com

The world's business leaders are predicting some AI 'blow-ups'

At the DealBook Summit, Larry Fink, Dario Amodei, and other business leaders predicted that AI is here to stay — but not all the AI players are.

Dec 3, 2025 • 6:39 PM EST • Business • businessinsider.com

Predicting college basketball AP rankings: Michigan set to rise into top five

Michigan is poised to ascend the rankings after a big week in Vegas, while Purdue should continue its stay at No. 1

Nov 30, 2025 • 6:25 PM EST • Sports • cbssports.com