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Packers Insider Reveals Offseason Move That Already Backfired
The Green Bay Packers bet big on their top three wide receivers staying healthy this year. After Jayden Reed was injured in Week 2, the bet on consolidating the Packers’ targets is already backfiring, according to Bill Huber of Packers OnSI. Huber noted after Week 2 that it could be an overreaction, but the Packers […] The post Packers Insider Reveals Offseason Move That Already Backfired appeared first on HEAVY.
Biggest Overreaction USC Trojans Fans Should Avoid
The USC Trojans wide receiver room will look different in 2026, but here's why fans shouldn't overreact.
Scientists find an immune “false alarm” that may drive rapid aging
Scientists have discovered that some severe genetic disorders linked to rapid aging may be driven not just by damaged DNA, but by the body’s overreaction to that damage. When broken DNA fragments leak into the wrong part of a cell, an immune sensor called cGAS can mistake them for signs of a viral infection, triggering chronic inflammation and even interfering with DNA repair itself.
CFP overreactions: Indiana's Curt Cignetti on Hall of Fame track
The quarterfinal round of the College Football Playoff provided plenty of material for overreactions
Breaking down Bills problems after Week 4; concern or overreaction?
Should the Bills be concerned with these developments or is concern now an overreaction?
49ers overreactions: Are Eddy Piñeiro's misses creating another kicker problem?
NBC Sports Bay Area's Matt Maiocco responds to the latest 49ers overreactions from San Francisco's Week 6 win over the Washington Commanders.
Predicting conference championship game overreactions: Notre Dame gets bounced
Conference championship game weekend should provide plenty of fuel for overreactions
The business case for human rights is more important and urgent than ever
The continuing backlash against corporate sustainability today risks becoming something more consequential: a retreat from responsible business itself. This overreaction, driven in part by domestic political pressures in the U.S., is a short-sighted course for American multinationals.
Bills Week 4 Takeaways: Broken Mess or an Elite Team?
Bills Week 4 Takeaways: Overreactions and reality checks. Are the Bills broken, or are they an elite team? Is Buffalo a top team and a Super Bowl contender?
4 overreactions from the Chargers' preseason win over the Texans
A handful of standout Chargers players have fans extrapolating the team's regular-season potential. Here are four of the biggest overreactions.
Jose Caballero's "routine'' sparks Yankees-Pirates bench clearer
Pirates' reliever Dennis Santana's overreaction to Jose Caballero's habitual, but legal, stall tactics at the plate led to an eighth inning incident.
Could the Vikings win the NFC North this season?
CBS Sports discussed if the idea of the Vikings winning the NFC North is an overreaction.
Ja’Marr Chase concern labeled big NFL Week 1 overreaction
Ja’Marr Chase had a quiet season opener for the Bengals, but one NFL analyst says there is little reason for concern.
One major overreaction to Browns' horrible performance in Jacksonville
It might not be possible to underreact to what the Browns put onto the football field in Week One against the Jacksonville Jaguars in week one.
Saints’ slow starts could become a problem if they continue
For this week’s overreaction, New Orleans showed plenty of fight in Detroit, but another slow start raises questions.
Mazzulla’s group is ahead of schedule
Preseason overreaction’s are dumb — most of the time. But the Celtics have earned it.
Championship games overreactions: Say goodbye to conference title games
There's plenty to overreact to after a stunning weekend of championship football
Reality or overreaction? Breaking down the biggest takes of 2026 NFL Draft week
Separating fact from fiction when it comes to the craziest parts of 2026 NFL Draft week.
Overreaction or Not? Dontrelle Willis Assesses Yankees Rotation Dominance, More
Is the Yankees' rotation historically great? Are the Angels a playoff team? Dontrelle Willis plays overreaction or not through the first two weeks of the season.
Seven Minutes Was All Newcastle Needed to Answer Their Critics
Five days ago, Alan Shearer called it embarrassing. Newcastle had just been taken apart 4-1 at Elland Road, undone by a Lewis Miley own goal and three more from a Leeds side that looked sharper, hungrier, and considerably better organized than the visitors. It was the kind of result that invites overreaction, and for a […]
Big Ten post-spring overreactions: Indiana thrives without Fernando Mendoza, West Coast crashes CFP party
The Big Ten, which has produced the previous three national champions, has multiple contenders again in 2026
Corn Nation Overreaction: Huskers Dominate Spartans, Remain Undefeated
Nebraska moved to 4-0 with a convincing 31-13 road victory over Michigan State, and Greg and Jake broke down an “ugly win” that still showed how far the Huskers have come. Nebraska didn’t play its best football, particularly in the running game, but the defense dominated with six sacks, multiple takeaways, excellent tackling, and impressive […]
5 overreactions to Cincinnati Bearcats opening win vs. Boston College
Here are five overreactions to the Sept. 5 Cincinnati Bearcats football win vs. Boston College
Miami Dolphins overreaction Sunday: Could Dolphins go 0-17?
he Miami Dolphins lost to the New York Giants in their preseason home opener. It is time to overreact?
Fetterman aligns with Trump on AI push, warns China benefits from US 'overreaction'
Sen. John Fetterman rejected "AI doomsdaying" and echoed President Donald Trump's push for AI development, warning that U.S. overreaction could benefit China.
CFP overreactions: Miami discipline issues will prove costly vs. Indiana
There's plenty to overreact to after an eventful semifinal round of the College Football Playoff
Corn Nation Overreaction: Huskers Start 3-0, MSU Next
Jon Johnston put out a video this morning wondering if this is Nebraska’s best team ever. At least, that’s the headline. It’s much more captivating than “Huskers Start 3-0, MSU Next.” As of this writing, I haven’t watched the video yet. This is probably the best team in the Matt Rhule era. And the team […]
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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