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“It Would Be A Nightmare”: A PlayStation 6 “Lite” is Not Happening Due To Development and Hardware Reasons, Leaker Says
Leaker KeplerL2 debunks PlayStation 6 "Lite" rumors, citing technical "nightmares" for devs and 4K upscaling hurdles.
Health expert explains preparing teens with autism for adulthood amid limited adult services
April is Autism Awareness Month, and on Tuesday, we focused on what comes next as your child grows into adulthood.
Alienware’s new gaming monitor offers a 240Hz QD-OLED panel for just $350
OLEDs for everybody.
Alienware AW2726DM launches at $350 with 1440p 240Hz QD-OLED panel, but only 200 nits
Alienware AW2726DM is a $350 1440p 240Hz QD-OLED monitor with 3-year burn-in warranty Alienware is preparing a lower-cost QD-OLED gaming monitor, the
World Quantum Day at UTC set to educate, intrigue and inspire
On April 14, the University of Tennessee at Chattanooga will join the global celebration of quantum science as part of World Quantum Day 2026, an annual event that promotes awareness and understanding of the field.
30 Under 30 Europe Science & Healthcare 2026: The Founders Using AI To Empower Patients And Unlock Scientific Mysteries
These young entrepreneurs, researchers and doctors are improving healthcare, empowering patients and building the hardware of the future.
ShinyHunters breached Rockstar Games in ransomware attack, sets April 14 deadline
Rockstar can't stop getting hacked.
Apple Seeds Second iOS 26.5 and iPadOS 26.5 Betas to Developers
Apple today seeded the second betas of upcoming iOS 26.5 and iPadOS 26.5 updates to developers for testing purposes, with the software coming two weeks after Apple released updated first betas. Registered developers can download the betas from the Settings app on the iPhone or iPad by going to the General section and selecting Software Update. iOS 26.5 and iPadOS 26.5 do not include new Siri capabilities, suggesting any Siri updates are being held until iOS 27.
Pirates Vs. Cancer rallies against pediatric cancer for 10th year
Medical students at the Brody School of Medicine at East Carolina University marked a decade of raising funds, awareness and hair for pediatric cancer patients during the Pirates Vs. Cancer spring event at the ECU Health Sciences Campus Student Center on April 10.
Mental health deaths may be missed in maternal data
Suicides and overdoses may be undercounted in maternal deaths, limiting awareness.
One UI 9 leak suggests Samsung is listening to our software complaints
Leaked One UI 9 changes point to smarter photo edits, a simpler 'About phone' section, and fluid animations.
Belton 'Business Park' proposal draws neighbor pushback on warehouse development
Communities in Cass County, Missouri are changing each week, especially in Belton with new development projects popping up.
Beware! This "Windows 11 24H2" update download can quietly steal your sensitive data
This Windows 11 24H2 update download could quietly compromise your system and steal sensitive personal data, putting your system's privacy and security at serious risk.
Linux 7.0 Released With New Hardware Support, Optimizations & Self-Healing XFS
As expected the stable Linux 7.0 kernel was just released today in marking this next kernel release
UNM College of Population Health Celebrates 10 Years
Friday, April 17, 2026, The University of New Mexico’s College of Population Health (COPH) will proudly celebrate its 10-year anniversary, marking a decade of measurable impact, substantial growth and future ambition. Founded in 2016, COPH became the...
Universities Allied for Essential Medicines advocates for affordable health care
While a vial of insulin takes as little as $2 to manufacture, it can cost consumers $250 in the United States. Universities Allied for Essential Medicines, an international advocacy organization that has chapters at universities including UCLA, raised awareness about medication unaffordability during its annual North American conference at the Neuroscience Research Building from April 3 to 5.
MSU hosts Out of the Darkness Campus Walk for mental health awareness
Michigan State University students gathered this morning to raise mental health awareness.
Vegas Golden Knights Announce Plans for Mental Health Awareness Knight on April 13
Mental Health Awareness Knight is presented by Zoox
Samsung to fix Adaptive Clock glitch in One UI 8.5 update
Adaptive Clock has a glitch on One UI 8.5 devices, and Samsung is working on a fix. The problem has been acknowledged by a community moderator, who promised the addressal with the next Beta software update. It’s already a big day for Samsung users, thanks to One UI 8.5 rollouts. Whether it’s new Beta releases […]
Health expert explains link between women's hormones, stress - and what to do about it
In honor of National Stress Awareness Month, health experts are drawing attention to the internal physiological shifts that contribute to rising stress levels in women, specifically menopause and perimenopause.
Black Maternal Health Week highlights disparities, solutions at Hampton Roads conference
Held as part of the national awareness week from April 11 to 17, the conference brought together doctors, nurses, social workers and midwife advocates to address inequities in maternal health care and outcomes.
10 Vintage Plates That Are Worth a Small Fortune
Vintage dining ware from these 10 makers has become highly collectible, often selling for thousands. See which creators' pieces are most valuable today.
Mental Health Awareness of Michiana holds cake fundraiser
Mental Health Awareness of Michiana offers a bite of comfort food — cake. The fundraiser at Howard Park will feature professional and amateur bakers.
MacBook Neo punches above its weight in Windows 11 gaming test
YouTuber ETA Prime has tested Windows 11 on the MacBook Neo through a virtualization app called Parallels. With full 3D hardware acceleration, the Apple A18 Pro SoC smoothly ran some Windows games on it as well.
Nintendo's Animated Films Challenge Disney's Box Office Dominance
Nintendo's expansion into theatrical animation, with billion-dollar films and an annual release slate, is challenging Disney's dominance while strategically promoting its gaming hardware and franchises like the successful Switch 2.
Mt. Carmel church hosts Minority Health Month men’s breakfast to raise awareness
Men gathered at Mt. Carmel Community Baptist Church on Saturday for the annual Minority Health Month Men’s Breakfast, an event aimed at raising awareness about
One UI 8.5 rollout possibly delayed for these two reasons
With the 9th beta, Samsung has delayed the One UI 8.5 rollout for the Galaxy S25 series, and these two reasons could be responsible for this move. It’s expected that the 9th beta may not be the final, and we may have a 10th coming soon. These test firmwares may be released in April, and […]
Dragon Age: Inquisition Servers Going Offline Later This Month
The online features have outlasted many live-service games, including Bioware’s own Anthem
Anthropic's Claude for Word is a new challenge to Microsoft's empire
Anthropic launched a beta version of Claude for Word. It's another challenge to Microsoft's software empire, and a bid to appeal to lawyers.
“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.
Fort Myers Community’s Choice Awards business spotlight: Gavins Ace Hardware
We’re in the final stretch! Ready to recognize your favorite local businesses? Submit your nominations for the Fort Myers Community’s Choice Awards today.
Framework CEO warns AI boom may lead to a scenario where "personal computing as we know it is dead”
Framework CEO Nirav Patel warns that the AI boom and a “winner-takes-all” scramble for chips and storage could drive up component costs and push consumers toward cloud-leased, closed devices, effectively ending personal computing as traditionally understood. While acknowledging progress in repairability across the industry, he positions Framework’s upcoming Next Gen Event as part of a renewed pledge to defend user ownership through upgradable, repairable hardware and local control over data and computation.
Delaware County election board member's voter status, candidacy revoked
Delaware County elections board voted 2-1 to cancel Melanie Leneghan's voter registration and candidacy for an Ohio GOP State Central Committee seat.
Laredo proclaims April Autism Awareness Month, underscores challenges
Laredo proclaimed Autism Awareness and Acceptance Month as officials, families and community members urged others to move beyond awareness and address barriers.
FBI: Health care was top target for ransomware, other cyberthreats in 2025
Health care and public health was the top sector targeted for cyberthreats in 2025, according to the FBI’s latest annual report on internet crimes. There were 460 ransomware attacks and 182 data breaches, totaling 642 cyber events. Financial services was the next highest sector at 447 total events.
Samsung says it has a One UI 8.5 device plan for ‘later’
Samsung has announced that the company will release a One UI 8.5 device plan once the software is ready for rollout. However, there are a couple of things you should know about this new statement. This statement comes after a wide user-based criticism of Samsung’s new feature limitation to the Galaxy S26 series. Users alleged that the company […]
A local sports bar and grill is opening doors for inclusion and opportunity
As Autism Awareness Month continues, Wayne’s journey serves as a reminder of the importance of community support and the impact of giving everyone a chance to succeed.
Unique X, Imagica Entertainment Media Services Partner to Transform Japanese Cinema Advertising Business
Digital cinema software provider Unique X and Imagica Entertainment Media Services (Imagica EMS), the market leader in Japan for post-production and media services, today announced the signing of a full long-term agreement, building upon their original Memorandum of Understanding (MOU). This strategic partnership establishes a robust framework for an exclusive collaboration aimed at transforming and […]
GlassWorm Campaign Uses Zig Dropper to Infect Multiple Developer IDEs
GlassWorm uses a fake WakaTime VS Code extension to infect IDEs, deploy RATs, and steal data, prompting urgent credential rotation.
CPUID site hijacked to serve malware instead of HWMonitor downloads
: Six-hour breach turned trusted links into a coin toss between legit tools and credential stealers
Student-Led Fresh Check Day Promotes Importance of Student Mental Health - University of New Haven
A public health capstone course empowers students to design and lead an evidence-based mental health initiative, building peer-to-peer support and enriching campus awareness and suicide prevention readiness.
Framework Computer To Announce Their Next-Gen Hardware Later This Month
Linux-friendly hardware vendor Framework Computer sent out a notice this morning that they will be announcing their new 2026 hardware products later this month.
Scientists to discuss Suncoast environmental threats at free Sarasota panel
One researches dolphin pods in Sarasota Bay. Another studies the impacts of pollution in area waterways. A third leads a consortium that strives to bring awareness to the work of local scientists. Those experts, along with another local environmental advocate, will lead a panel discussion moderated by Suncoast Searchlight on
Why we must invest to sustain Delaware life science firms
Delaware is the best place for life science innovation and investment to thrive. Our homegrown life science firms need sustained investment.
CPUID compromise: users report getting malware with HWMonitor and CPU-Z tools
Multiple users are reporting that the CPUID website has been compromised, leading to popular Windows utilities such as CPU-Z and HWMonitor delivering multi-stage, evasive malware.
Google Chrome adds infostealer protection against session cookie theft
Google has rolled out Device Bound Session Credentials (DBSC) protection in Chrome 146 for Windows, designed to block info-stealing malware from harvesting session cookies.
Apple Releases macOS Tahoe 26.4.1 With Bug Fixes
Apple today released macOS Tahoe 26.4.1, a minor update to the macOS Tahoe operating system that came out last September. macOS Tahoe 26.4.1 comes two weeks after Apple launched macOS Tahoe 26.4. Mac users can download the new software by opening up the System Settings app and navigating to the Software Update section. Mac users can download the new software by opening up the System Settings app and navigating to the Software Update section.
US software stocks fall as Anthropic's new AI model revives disruption fears
U.S. software shares tumbled on Thursday after Anthropic held back the wide release of a powerful AI model over concerns it could expose hidden cybersecurity vulnerabilities, deepening investor fears about the threat to traditional software firms.
Samsung is expanding AirDrop to these Galaxy devices, but only if you install this update
Samsung is officially expanding AirDrop over Quick Share support to more Galaxy devices, but it requires a specific software update...
Samsung expands One UI 8.5 beta to even more Galaxy phones
Samsung is expanding the One UI 8.5 Beta Program to even more Galaxy phones so that more users can test the new software version.
Ex-Apple engineers create an AI button – but can't explain why
I said a couple of years ago that AI hardware devices were like trying to invent the iPod after the...
Scientists create new type of encryption that protects video files against quantum computing attacks
A newly developed encryption framework aims to protect video data from future quantum attacks, all while running on today's conventional hardware.
Galaxy S25 and S24 users get AirDrop and 3 new camera filters
With new One UI 8.5 Beta updates, Samsung has fresh perks for the users of Galaxy S25 and S24 series: AirDrop sharing and three new camera filters. Samsung just dropped One UI 8.5 Beta 9 and Beta 2 updates for the S25 and S24 series, respectively. Changelog of both updates carry exact the same content, […]
WireGuard VPN developer can't ship software updates after Microsoft locks account
The popular open source VPN maker is the second high-profile developer to say Microsoft locked his account without notifying him and are blocking their ability to send software updates to users.
BladderShield Claims Evaluated: Potent Bladder Leak Trick Supports Men's Health
A 2026 consumer awareness overview of BladderShield's bladder leak trick marketing claims, urobiome rebalancing positioning, ingredient research for overactive bladder and urinary urgency, men's bladder health context, pricing structure, and what men should verify before purchasingTallmadge, OH, April 08, 2026 (GLOBE NEWSWIRE) -- This article contains affiliate links. If a purchase is made through these links, a commission may be earned at no additional cost to the buyer. This is an informationa
Samson Dev: DLSS 5 Needs Full Pipeline Integration & Broad Hardware Support to Be Viable
Samson dev Liquid Swords explains what DLSS 5 needs: pipeline integration, broad hardware support, and artistic control over character visuals
Form Bio: The Operating System for Science
Ben Lamm (left) and George Church (right) pose in front of a woolly mammoth. By Futurist Thomas Frey When Colossal Biosciences launched in 2021, one of the first things Ben Lamm did was sit down with his team and map out all the software they would need to actually do the work. The list came […]
Developer of VeraCrypt encryption software says Windows users may face boot-up issues after Microsoft locked his account
The maker of the popular open-source file encryption software VeraCrypt said Microsoft locked his online account, which may prevent device owners from booting up their computers.
Viewpoint: FP10 should remain open, excellent and secure
Europe is right to worry about research security. Foreign interference is real. So is the misuse of sensitive knowledge. Universities working in sensitive areas such as AI, quantum, semiconductors and advanced materials cannot afford to ignore the geopolitical environment around them.But Europe is in danger of drawing the wrong conclusion, one that would increase, not reduce, its strategic vulnerabilities.If the EU applies an “EU preference” logic to the next Framework Programme for research and innovation (FP10), it will weaken one of its greatest strategic assets: a research system built on openness, excellence and international collaboration. In the name of security, Europe could end up advancing science more slowly, innovating less effectively and making itself less attractive to global talent and partners in advanced science and technology.That would be a serious mistake.The EU preference included in Article 10 of the proposed European Competitiveness Fund may make sense in some industrial or deployment contexts, but is far harder to justify when applied to collaborative research in advanced science and technology, where excellence and global connectivity are crucial. Research is not procurement. It does not thrive when isolated. It advances through access to the best ideas, the best people, the best facilities and the best data, wherever they are found. This is why FP10 should not simply absorb industrial policy logic by default. Doing so would risk importing instruments that are ill-suited to research and that ultimately increase vulnerability rather than resilience.For universities of science and technology, the issue is especially acute. These institutions sit at the frontier of knowledge and technology creation in the very fields Europe sees as critical for its future competitiveness and resilience. They know better than most that security risks are real. But they also know that openness and security are not opposites. In practice, they have to be made to work together. Research security is not about closing doors. It is about building resilience through collective responsibility, trust, proportionate safeguards and better governance. That is a fundamentally different approach from default restriction.The risks of non-collaborationThe real danger in the current debate is that Europe talks too much about the risks of collaboration and not enough about the risks of non-collaboration. Those risks are strategic too. Cut researchers off from international networks and Europe loses access to knowledge, data, infrastructures and talent. Slow down global collaboration in critical technologies and Europe slows down its own progress on cutting-edge science. Make participation rules unpredictable and Europe weakens its attractiveness to researchers and investors alike.In other words, over-restricting collaboration will create strategic vulnerabilities, particularly in advanced science and technologies.This point is often underestimated in policy discussions that frame openness mainly as a value to be defended. Europe’s scientific strength, technological development and long-term competitiveness depend on remaining connected to the best research ecosystems in the world. For a continent that wants to accelerate deep tech, strengthen industrial capacity and reduce strategic dependencies, weakening the excellence base would be self-defeating. That does not mean ignoring risk. Quite the opposite. Universities are already strengthening due diligence, internal governance, awareness-raising, screening procedures and compliance support. Across Europe, institutions are working to manage risks linked to foreign interference, sanctions, export controls and the misuse of research. The right response is not complacency. It is better risk management. But that means targeted, evidence-based and proportionate measures, not blunt top-down restrictions with wide spillover effects. In the daily reality of universities, openness and restriction often coexist. The real challenge is how to apply safeguards without sliding into securitisation that damages academic freedom, open science and international cooperation. Restrict partners, not nationsMore restrictive treatment of collaborators from European Economic Area members Iceland, Liechtenstein and Norway, or from Switzerland and the UK, is strategically very difficult to justify. These are deeply embedded partners in Europe’s research and innovation ecosystem. Beyond that, Europe should still resist default exclusion and instead rely on case-by-case assessment. The relevant question is not nationality in the abstract. It is the actual risk profile of a collaboration: the institution, the affiliations, the field, the knowledge involved, the intended use and the safeguards available. Screening should focus on institutions and affiliations rather than nationality alone. Related articlesParliament ‘misreads’ link between Horizon Europe and ECF, Commission official saysFrustration grows at governance gap in next Horizon EuropeIf EU preference logic is imported into research without careful calibration, the likely result is a chilling effect. Researchers may step back from legitimate and beneficial collaboration, even where risks are manageable. International partners may see Europe as less predictable. And Europe may end up undermining the very excellence base it needs to compete, scale up and lead in strategic technologies, thereby increasing its dependence on others.FP10 should do the opposite. It should remain open by default, with restrictions used only exceptionally, and then on the basis of clear evidence. It should integrate research security into open science and research integrity frameworks, not set them against each other. And it should recognise that academic freedom, scientific excellence and responsible international collaboration are not obstacles to Europe’s security, they are part of it. Europe needs stronger tools to protect itself. But it also needs the discipline to avoid measures that would weaken it and increase its strategic vulnerabilities in the process. In FP10, that means staying open, excellent and secure.Louise Drogoul is senior advisor for innovation and sustainability at the Cesaer university association.
Car-Mart to close 42 dealerships, lay off staff - Talk Business & Politics
Rogers-based America’s Car-Mart Inc. will close 42 dealerships over the next week as market challenges impact its establishment of a “non-recourse revolving warehouse credit facility,” according to a Tuesday (April...
500 Million Windows PCs Are About to Become Unsafe—Now There's a Free Upgrade to Keep Them Running
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Gemma 4 and what makes an open model succeed
Having written a lot of model release blog posts, there’s something much harder about reviewing open models when they drop relative to closed models, especially in 2026. In recent years, there were so few open models, so when Llama 3 was released most people were still doing research on Llama 2 and super happy to get an update. When Qwen 3 was released, the Llama 4 fiasco had just gone down, and a whole research community was emerging to study RL on Qwen 2.5 — it was a no brainer to upgrade. Today, when an open model releases, it’s competing with Qwen 3.5, Kimi K2.5, GLM 5, MiniMax M2.5, GPT-OSS, Arcee Large, Nemotron 3, Olmo 3, and others. The space is populated, but still feels full of hidden opportunity. The potential of open models feels like a dark matter, a potential we know is huge, but few clear recipes and examples for how to unlock it are out there. Agentic AI, OpenClaw, and everything brewing in that space is going to spur mass experimentation in open models to complement the likes of Claude and Codex, not replace them. Especially with open models, the benchmarks at release are an extremely incomplete story. In some ways this is exciting, as new open models have a much higher variance and ability to surprise, but it also points at some structural reasons that make building businesses and great AI experiences around open models harder than the closed alternatives. When a new Claude Opus or GPT drops, spending a few hours with them in my agentic workflows is genuinely a good vibe test. For open models, putting them through this test is a category error. Something else to be said about open models in the era of agents is that they get out of the debate of integration, harnesses, and tools and let us see close to the ground on what exactly is the ability of just a model. Of course, we can’t test some things like search abilities without some tool, but being able to measure exactly the pace of progress of the model alone is a welcome simplification to a systematically opaque AI space. Share The list of factors I’d use to assess a new open-weight model I’m considering investing in includes: Model performance (and size) — how this model performs on benchmarks I care about and how it compares to other models of a similar size. Country of origin — some businesses care deeply about provenance, and if a model was built in China or not. Model license — if a model needs legal approval for use, uptake will be slower at mid-sized and large companies. Tooling at release — many models release with half-broken, or at least substantially slower, implementations in popular software like vLLM, Transformers, SGLANG, etc due to pushing the envelope of architectures or tools. Model fine-tunability — how easy or hard it is to modify the given model to your use-case when you actually try and use it. The core problem is that some of these are immediately available at release, e.g. general performance, license, origin, etc. but others such as tooling take day(s) to week(s) to stabilize, and others are open research questions — with no group systematically monitoring fine-tunability. In the early era of open models, the days of Llama 2 or 3 and Qwen pre v3.5, the architectures were fairly simple and the models tended to work out of the box. Some of this was due to the extremely hard work of the Llama, Qwen, Mistral, etc. developer teams. Some is due to the new models being genuinely harder to work with. When it comes to something like Qwen 3.5 or Nemotron 3, with hybrid models (either gated delta net or mamba layers), the tooling is very rough at release. Things you would expect to “just work” often don’t. I’ve been following this area closely since we released Olmo Hybrid with a similar architecture, and Qwen 3.5 is just starting to work well in the various open-source tools that need to all play nice together for RL research. That’s 1.5 months after the release date! This is just to start really investing more into understanding the behavior of the models. Of course, others started working on these models sooner by investing more engineering resources or relying on partially closed software. The fully open and distributed ecosystem takes a long time to get going on some new models. All of this is lead-in for the most important question for open models — how easy is it to adapt to specific use-cases? This is a different problem for different model sizes. Large MoE open-weight models may be used by entities like Cursor who need complex capabilities in their domain, e.g. Composer 2 trained on Kimi K2.5. Other applications can be built on much smaller models, such as Chroma’s Context-1 model for agentic search, built on GPT-OSS 20B. The question of “which models are fine-tunable” is largely background knowledge known by engineers across the industry. There should be a thriving research area here to support the open ecosystem model. The first step is to understand characteristics of different base and post-trained models to understand what they look like. The second step is to tune pretraining recipes for open models so they’re more flexible. Interconnects AI is a reader-supported publication. Consider becoming a subscriber. Subscribe For The ATOM Project and other Interconnects endeavors, we’ve put in substantial effort to measuring adoption trends in the open ecosystem. Everything takes a long time to unfold after a model is first publicly available — and adaptability is why. What we know for sure now, when Qwen has been going from strength to strength with its releases, is that technical staff across the industry has gotten comfortable working with Qwen models. Countless research methods and datasets were made to work with Qwen. It’ll take patience for any other model family to get to this point — a patience I’m not sure many open model builders have. This takes us to Gemma 4, Google’s latest open models. Gemma 3 was released more than a year ago, in March of 2025, and is a bit underrated. Gemma 4 comes in 4 sizes for now, with a bigger, MoE model of over 100B total parameters rumored but not released yet. The models we have today come in sizes of ~5B dense, 8B dense, 26B total 4B active MoE, and 31B dense. I’m most excited that they’re finally adopting a standard Apache 2.0 open source license. This’ll massively boost adoption. The standard of better licenses for strong open-weight LLMs was set by mostly Chinese open model labs in the last 1-2 years, and now U.S. companies are following suit. I will personally be so happy if the horrible Llama licenses and Gemma terms of service were an ~18-month transient dynamic of the industry being nervous about releasing strong open models. The Gemma 4 scores look very solid, the small models have incredible benchmark scores (especially in general domains like LMArena) and the 31B model rivals the recent Qwen 3.5 27B, which is the leading member of that class. The ~30B size range is an important one, as it’s accessible both to researchers and to enterprises looking to deploy the model in real use-cases. Where the 7B model scale is the default for tinkering and research, a 30B model is the default for seeing if an open model can unlock substantial value in your specific workflow — a good mix of intelligence, low price, tractability for downstream training, etc. This takes us back to the above adoption criteria I mentioned for open models and the bigger question — do I think Gemma 4 will be an overwhelming success? Previous Gemma models have been plagued by tooling issues and poorer performance when being finetuned. Gemma 4’s success is going to be entirely determined by ease of use, to a point where a 5-10% swing on benchmarks wouldn’t matter at all. It’s strong enough, small enough, with the right license, and from the U.S., so many companies are going to slot it in. I’m cautiously optimistic that Gemma 4 is going to work better here. Winds are shifting for open models built in America. We saw GPT-OSS go through a bumpy launch to become an overwhelming success. There’s a collective energy around the likes of Reflection, Arcee, Nemotron, Gemma, Olmo, and peers that show substantial demand for building new stacks around open models. There’s capital to be spent on AI stacks across the economy by those who want more ownership of everything, including the model. After launching The ATOM Project 240 days ago, the conversation is shifting into the next stage. Summer of 2025 was a crisis moment where the U.S. AI scene realized it can’t wait and figure out open models after building AGI. The two markets will capture different areas and proceed in parallel. Now that more companies in the U.S. are releasing strong models, we need to improve the ecosystem so that these models are easy to use, understand, and build value around. It’s the hard work to build another inflection point in these adoption plots I’ve been updating consistently, but that’s the work to be done. Join me in it. More data coming soon! Here’s a sneak peek:
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