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Why A.I. Distillation Has Become a Hot Topic in the Race with China
U.S. companies complain that competitors in China are unfairly copying their A.I. systems using a technique that has been around for years.
Ford sales struggle with no Escape, F-Series woes, less rental business
Ford struggled compared to crosstown competitors General Motors Co. and Stellantis NV.
20 companies moving forward in Fort Worth Business Plan Competition
The field has narrowed in the 2026 Fort Worth Business Plan Competition, with 20 competitors moving on to participate in several weeks of business
Galaxy Z's days are apparently numbered: Accessories point to a very unusual name for Samsung's iPhone Ultra competitor
At first, it was called the Galaxy Z Wide Fold or the Galaxy Z Fold 8 Wide, then—according to generally reliable sources—simply the Galaxy Z Fold8. Now a fourth name has surfaced for the compact and wider iPhone Ultra alternative, that Samsung will unveil on July 22 alongside the updated Galaxy Z Fold 8 Ultra. However, as authentic as these images seem to be, there are doubts.
A Giant Scorpion the Size of a Coffee Table Is Forcing Scientists To Rethink Evolution
Praearcturus gigas was a meter-long Devonian scorpion whose size may reflect a world with few large competitors rather than high oxygen alone.
David P. O'Brien
About five years ago, David P. O'Brien had a comfortable position at Marsh & McLennan Cos., where he held the top post at the financial giant's Louisville, Ky., office. Despite the lofty rank, Mr. O'Brien found himself longing to be at a smaller company that had to work a little harder to land business. That desire led him away from Kentucky five years ago and to Cleveland, where he serves as executive vice president at business insurance agency Oswald Cos. "I left Marsh before it was en vogue," he said, referring to layoffs and defections at Marsh over the course of this year that followed accusations of bid rigging at the big firm. Above all, Mr. O'Brien, 38, wanted to work at a company that relied on its inventiveness, rather than its name, for business. He said he has found that at Oswald. "It causes you to be more creative, to be more resourceful," Mr. O'Brien said. For instance, an Oswald client seeking to do business internationally might be directed to the network of offices abroad run by competitors such as Marsh and Aon Risk Services Inc. "We're going to use whatever access into the market that makes the most sense for our clients," he said. Of course, using such a strategy can be dangerous for Oswald if its client decides to further a business relationship with one of the firms Oswald recommended. "That's the obvious question and why it's nontraditional," he said. "I think if we're good, and if we're bringing value to the client, then there's no risk. I'm not threatened by it." Imaginative business solutions of that type made his career move to Oswald from Marsh worthwhile. "It's very much a challenge," he said. "It helps you keep your edge. I'm all for the competition." John Jacunski, currently vice president and corporate controller at York, Pa., paper company PH Gladfelter Co., met Mr. O'Brien four years ago when Mr. Jacunski was at WCI Steel Inc. in Warren. So impressed was he with Mr. O'Brien's work for WCI that Mr. Jacunski has retained the Oswald executive at PH Gladfelter. "He's a young guy for the position he has, but he's done a great job for us," Mr. Jacunski said. Among his roles at Oswald, Mr. O'Brien leads the firm's client retention efforts and also serves as director of its property and casualty group. "You don't have the same human resources," he said of the job jump to Oswald. "You don't have, obviously, the safety net a big company has." But sometimes, it can be difficult to ascertain individual contributions when working at a big company. "I wanted to be able to see the end results of my work and my efforts," Mr. O'Brien said.
Why Small Businesses Are Winning The AI Race With Agentic AI
Small businesses building agentic AI from scratch are outpacing larger competitors. The obstacle was never the technology, but ownership and trust.
Schuylkill student places first at Future Business Leaders of America conference
Penn State Schuylkill student earned national recognition at the Future Business Leaders of America's National Leadership Conference, held June 6-8 in Las Vegas, Nevada. Carter Strouse, a third-year corporate communication major with a minor in business and the sports certificate, earned first place in Business Communication, outperforming competitors from colleges and universities across the country.
Ismael Kone: World Cup injury footage – how do sports broadcasters cover serious injuries?
When competitors suffer terrible injuries, broadcasters face difficult ethical choices
Microsoft (MSFT) Is Building A Billion Dollar AI Business In China
Microsoft (NasdaqGS:MSFT) is building a large AI and cloud business in China, supplying OpenAI models through Azure to major local technology companies. ByteDance is reported to spend over US$1b annually on Microsoft AI and cloud services, with Ant Group, Meituan, and Tencent also using Microsoft models. Microsoft has emerged as a key provider of OpenAI technology in China at a time when several US competitors are not active in the region. For investors watching Microsoft, this growing AI...
OhioHealth agrees to void contracts that allegedly punished payers for including competitors in-network
The U.S. Department of Justice said the settlement will save citizens of the state money and open up the market to competition.
Happy Hour and humor with a local historian
Join the Key West Art & Historical Society for the next installment of Happy Hour with the Historian series at 5 p.m. on Thursday, June 18, featuring Cori Convertito at
“Dancing With the Stars ”announces beloved late-night personality as newest competitor
The comedian joins Maura Higgins, Ciara Miller, and Jackson Olson in the season 35 cast.
'Dancing With the Stars' announces beloved late-night personality as newest competitor
'Dancing With the Stars' is dipping into the late-night pool for season 35, as the show announced this talk-show mainstay as the newest competitor to join Maura Higgins, Ciara Miller, and more.
Is SEO Dead? Here's What I'm Telling Every Client Who Asks Me in 2026
The version of SEO your competitors are selling is dying. The version that actually drives revenue isn't.
Tito Double P to headline BelicoFest
Tito Double P will headline BelicoFest in Los Angeles at BMO Stadium on July 12.
Siri AI in iOS 27: Features, Requirements, and How It Works
The biggest change in iOS 27 is Apple's total overhaul of Siri, with Siri turning into Siri AI. Apple delivered on the features originally promised at WWDC 2024 and added new capabilities that turn Siri into a viable competitor to chatbots like Claude and ChatGPT. Siri AI is available in the iOS 27 beta, but everyone will get access this fall. Below, we walk through everything new you can expect from Siri.
Samsung's iPhone Ultra rival reportedly more crease-free than the Galaxy Z Fold8 Ultra thanks to thicker UTG
An industry report from South Korea suggests a significant difference between the more compact and wider Galaxy Z Fold 8 on the one hand, and the "Ultra" version of the classic foldable form factor on the other. According to the report, the wider iPhone Ultra competitor from South Korea appears to be significantly less prone to creases than the Galaxy Z Fold 8 Ultra.
Apple Could Eventually Bring An OpenClaw-Like Competitor To Multiple Platforms, Offering Personalized AI Agents At Flexible Pricing
Consumers could have another reason to invest in a Mac, iPad or iPhone, as Apple could bring its own AI agent like OpenClaw in the future
Senior Games draws competitors from across U.S.
Sporting venues across the Columbia area hosted the Missouri State Senior Games this weekend, an Olympic-style tournament for athletes aged 50 and up.
DJI sues Insta360 for how similar the Luna Ultra is to the Osmo Pocket 4P
Perhaps surprisingly, the lawsuits are being filed in the US. A couple of days ago, Insta360 made its DJI Osmo Pocket 4P competitor official in the Luna...
What Brands Get Wrong About Sports Sponsorships—and How to Get Them Right
Companies spend billions sponsoring major sporting events, yet many still evaluate success primarily through exposure metrics such as logo visibility and immediate brand recall. New research suggests those measures increasingly misrepresent sponsorship effectiveness because consumers form long-lasting, overlapping associations among brands, events, and competitors within crowded sponsorship ecosystems. Brands generate more enduring value when they focus less on visibility and more on authentic participation, distinctive experiences, and emotional engagement that strengthen trust and meaningful long-term recall.
From Classroom to Racetrack: How Charlie Baur is Building a Motorsports Career in a Business Discipline
Charlie Baur can trace his racing story back to a Christmas morning in Michigan — the kind that starts with snow on the ground and ends with a throttle in a kid’s hands. “I remember being 3 years old and then for Christmas that year, my parents had gotten me a 120 cc snowmobile,” Baur said. Long before sprint cars, he was a Michigan kid on snowmobiles, dirt bikes, four-wheelers and jet skis — and a regular at car shows and races with his family. Photo courtesy of Charlie Baur That early exposure became a calling. At 12, he sat in a sprint car for the first time and knew he’d found the next chapter. He started in quarter midgets, moved to go-karts, and the day before he turned 16 — one day shy of the minimum age required by track insurance — he made his first sprint car start after convincing officials to let him race. Five years later, Baur is still pushing forward, now racing sprint cars on both pavement and dirt while pursuing an automotive business education at Northwood University — with a clear-eyed understanding that motorsports encompasses more than what happens under the lights on Saturday night. “It’s a business,” said Charlie, a 20-year-old who calls Fenton, Michigan, home when he’s not at a racetrack or at Northwood’s residential campus in Midland, Michigan. Photo courtesy of Charlie Baur Racing is the product — but preparation is the job To the average fan, race day begins around dinner time. For a team, race day can be a 12-hour shift — plus the work that came before it. And Baur’s racing operation is a family affair. “The team is my parents and myself,” he said, explaining they own the cars, maintain equipment and manage the business side — from sponsor relations to budgeting. On race weekends, the core group includes Baur and his parents (Eric and Stefanie), plus a couple of additional hands (Alex Photiou and Robert Flannigan) who help with the intensity and pace of trackside work. That structure has shaped how he thinks about efficiency and professionalism. “We’ve always kind of had the mentality of we’re never working on the car for maintenance at the track,” he said. “Our goal is to do as little work as possible to the car because it should be ready when that car rolls out of the trailer to go racing.” That mindset shows up in routines: bolt checks, tire procedures, safety equipment and a repeatable process designed to limit errors. “Once I fire the car up and put my helmet on, that’s when it’s go time,” he said. “You can plan as much as possible for how the race is going to play out, but until you take the green flag … you don’t know how it’s going to go.” Photo courtesy of Charlie Baur First-generation driver, student of the game In racing, “first-generation” matters — and Baur wears that label with pride. “A lot of the drivers are third or fourth generation,” he said. “My family has never been in motorsports. So for me, we’ve always looked at it as we’re new to it and we want to be as different as possible. From a marketing standpoint, it helps us stand out.” It also pushes him to seek out mentors — especially veteran drivers who have seen every scenario, solved every problem and won in multiple eras. Baur credits accomplished driver Jason Blonde, a 10-time champion, for becoming his driver coach and helping him develop as a competitor. “To me, learning from Jason helps me because he has had lots of success and knows what to do,” Baur said. “You have to humble yourself and say, ‘I don’t know what to do; can you help me out?’” That willingness to learn extends off the track, too. Baur says one of his biggest challenges is not a mechanical limitation, but credibility. “It’s my age,” he said. “Some people won’t take me seriously because I’m so young. Even though … I do know what we’re talking about and have a general idea.” His answer has been to out-prepare, out-communicate and treat the operation like a real enterprise — because it is. Photo courtesy of Charlie Baur Northwood’s role: Turning passion into a plan Baur is majoring in automotive aftermarket management and pursuing an accelerated path that pairs undergraduate study with graduate work. He’s also exploring how to align his studies with motorsports-focused coursework as Northwood advances related programs and pathways. He sees the value clearly: motorsports needs business-literate professionals who understand budgets, sponsorship, marketing, operations and long-term strategy — and who can translate between the language of the shop and the language of the boardroom. That’s why his Northwood experience isn’t limited to the classroom. He has been involved with the Northwood University International Auto Show and serves as motorsports chair — a leadership role that demands outreach, contracts, coordination and a steady professional demeanor. “There’s so much outside work that makes the auto show successful that people don’t realize,” he said. “And it is truly student led.” He’s also participated in industry experiences through Northwood at major events such as AAPEX, SEMA and PRI, along with other automotive networking events — opportunities he describes as a fast track to understanding how business really gets done. “You learn a lot in the classroom,” he said. “But if you learn it and you can’t apply it to the real world, it loses its value. Or if you learn it and can apply it, but you don’t know anyone, it is still of no value.” In his words, Northwood helps him win because it “gives me the tools to succeed” — including flexibility and faculty support as he balances travel and racing commitments with academics. Photo courtesy of Charlie Baur Racing as an ecosystem — and a talent gap waiting to be filled Baur is blunt about what he sees across the motorsports world: a deep bench of experienced professionals, and not enough young talent entering the pipeline. “I go to car shows, I go to these different events, and typically … the average age is between 45 to 55,” he said. “There’s not a lot of young people going into the motorsports world.” That reality reinforces Northwood’s communications focus: positioning motorsports not as a narrow lane, but as a wide ecosystem of business careers — sponsorship, logistics, data, media, leadership, hospitality and innovation — with real demand for prepared graduates. It also shapes how Baur talks to younger students who love racing but aren’t sure what their future looks like. “If you have a passion for motorsports, there’s gonna be a spot for you somewhere,” he said, emphasizing that driving is only one of many career paths — and that local tracks and hands-on experience are often the best first step. But if someone is interested in driving as a career path, it will take a team to make that happen. Baur’s team includes Stahl’s Motors and Music Experience, Rhino Racing, Randy Wise Buick GMC Chevrolet, Western Michigan Fleet Parts, Mother’s Polish, Schaeffer’s Oil, Hepfner Racing Products, Ameriguard Storage Centers, Justice Brothers, Race 1 Wraps, TBM Brakes, Behind Your Design, CharlieBaur.com and Northwood University. “There are so many people who invest not only in myself but in my race team and who believe in us to succeed,” he added. Pictured: Charlie Bauer’s sprint race car. Looking ahead: A headline worth chasing Ask Baur to imagine 2035, and he’ll give you two answers — one dream, one blueprint. “In a perfect world,” he said, “winning the Indy 500.” Realistically, he wants to build a life where business ownership and racing reinforce each other and where he can pay forward the help he has received by mentoring younger drivers, especially those trying to break into motorsports without a family legacy. “When I retire from full-time racing, I want to be able to provide the same opportunities that were presented to myself to the next generation of drivers,” Baur said. “I know how difficult it is to get your foot in the door.” For now, the focus is simple: keep building the operation, keep learning the business, and keep showing up prepared — because in sprint car racing, as in life, process matters. And once the helmet goes on? “It’s go time,” Baur said. Photo courtesy of Charlie Baur Learn more Students interested in motorsports careers — whether in competition, team operations, marketing, finance, sponsorship, data, or management — can explore opportunities through Northwood University’s Center for Automotive and Mobility Studies. For Charlie Baur’s latest motorsports adventures, follow Charlie_Baur and Charlie Baur Racing on social media. To learn more about Northwood’s Bachelor of Business Administration in Automotive and Mobility Studies and motorsports management concentration, visit www.northwood.edu/programs/automotive-mobility-studies/. Photo courtesy of Charlie Baur Pictured: Charlie Baur at Butler Motor Speedway on May 31, 2026. Share this page
In-Room Entertainment Influences Guest Decisions
Hotels that continue to treat in-room entertainment as a cost to be minimized are ceding ground to competitors.
HCA, VCU Health seek dismissal of Bon Secours legal challenges to Chesterfield hospital projects
"Bon Secours, alone amongst the three health systems, has refused to take yes for an answer,” HCA argued in its response to Bon Secours' calls for its competitors' projects to be denied by the state.
Apple’s iPhone Ultra Hinge Will Double As A Heatsink, With Its Liquidmetal Construction Stronger Than Titanium
Apple appears to be sparing no expense to ensure that its iPhone Ultra would turn out to be a consummate stunner of a device.
Meta AI Chief Sees Opportunity in Models’ Giving Health Advice
Meta Platforms Inc. Chief AI Officer Alexandr Wang said the company’s future artificial intelligence models will differentiate themselves from competitors through their consumer health capabilities.
Baton Rouge’s economy is booming, report says
Baton Rouge is outperforming many of its regional competitors on several key economic measures, from job growth and pay to housing affordability and worker productivity. That’s according to the G… Already an INSIDER? Sign in. Already an INSIDER? Sign in
Dell is bringing back the XPS 13 as a MacBook Neo competitor — with a temporary discount to $599
The XPS 13 returns, and is cheaper than ever.
AMC's Downfall Can Be Traced Back To One Tragic Moment
The American Motors Corporation was once a genuine competitor to the Big Three, but under French ownership, things went wrong very quickly and tragically.
Xbox will "adjust" its promotional materials after fans slam decision to use rival logos in its showcases
Xbox boss Asha Sharma has admitted that including competitor logos in Xbox teasers and showcase presentations is "a miss", confirming this will be "adjusted".
Gamification and memes lure young people to sports wagering apps, prediction markets
When Rory McIlroy won the Masters for the second year in a row, Kalshi shared a photo of him on Instagram with the words, “Wait he’s goated.” When a video of NBA player Damian Lillard recovering from an injury circulated online, Kalshi’s main competitor Polymarket posted, “The league is cooked.”
Google’s AI Search is pushing users away, and Bing has a rare opening it has not seen in years. What happens next is up to Microsoft.
As competitor search engines surge on Google's AI obsession, Microsoft should exploit the situation. But it'll go against everything it's been doing up until now.
Building Toward the Games: Army Team Sports Competitors Train in San Antonio Ahead of 2026 Warrior Games
U.S. Army Staff Sgt. Chelsey Scott, left, participates in wheelchair basketball training during Army Team Sports Camp in San Antonio, May 2026. The camp helps Team Army competitors strengthen teamwork, resilience and adaptive sports skills ahead of the 2026 Warrior Games. (U.S. Army photo by Corey Wallace)
Lantheus weighs potential sale with $7B valuation
The Bedford, Massachusetts-based company has reportedly been approached about a possible acquisition by competitor Curium Pharma, Bloomberg reported May 22.
What do professional athletes and Scripps Bee contestants have in common? Host Mina Kimes knows
Mina Kimes, ESPN senior writer and Emmy Award-winning analyst, talks about how her experience as a school spelling bee competitor prepared her for hosting the 2026 Scripps National Spelling Bee.
Dunbar Students Win International Science Awards
The Regeneron ISEF drew over 1,700 competitors from some 60 countries.
Kroger plans biggest price cuts in years to take on Walmart, Costco
Kroger Co.'s new CEO is looking at big price cuts in order to win back market share and take on his former employer, Walmart Inc., and other competitors.
What Customer Workarounds Can Reveal About Your Business Model
Customer workarounds (such as customers sharing accounts, or teams stitching together third-party tools) are not merely signs of product friction but early evidence that a company’s business model no longer matches how customers want to access, use, and pay for value. If firms fail to respond to customer workarounds, they leave themselves open to new competitors or to customers simply leaving. Companies should detect workaround patterns early, map them to distinct customer needs, build a portfolio of complementary business models, and monitor these signals continuously to capture demand before competitors do.
Two brothers raised $12m for an OpenClaw competitor
NanoClaw's enthusiastic users include AI researcher Andrej Karpathy and Singapore's foreign minister.
High school athlete slams CIF's shared podium rule as humiliating response that fails female competitors
Trans athlete AB Hernandez dominated CIF Southern Section girls' track finals, reigniting debate over California's transgender sports policies.
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.
Five Points businesses say IRONMAN road closures hurt access, customers; city promises better communication
Jacksonville’s first-ever IRONMAN brought nearly 2,000 competitors to a route spanning parts of Duval and St. Johns counties this weekend, drawing crowds downtown, and prompting widespread complaints about traffic, road closures and access issues in neighborhoods like Riverside’s Five Points.
Fitbit Air: 24 Hours Later First Impressions
Here's your first impressions of the Fitbit Air, and how it compares physically to Whoop 5.0/MG, Amazfit Helio, and the Polar Loop.
Employee misconduct is becoming harder for companies to ignore
Rising workplace misconduct is becoming a growing concern for employers, with new research suggesting the problem may be rooted in shifting attitudes toward ethics and accountability, Inc. writes. A U.K. fraud prevention survey found notable tolerance for behaviors like expense fraud, moonlighting for competitors and even selling company login credentials, while a separate U.S. survey […]
Parents of girls' track star facing trans athlete speak out against Newsom over Title IX crisis
Parents of high school athlete Reese Hogan condemn Gov. Newsom as their daughter faces a trans competitor in California girls' track sectional finals.
Canadian-based company ceases operations; dozens of people laid off in Pennsylvania
The company said its financial position has worsened significantly since 2021, and that it had faced additional pressure since 2024 due to the imposition of tariffs by the U.S. government, post-pandemic reductions in consumer demand, increased competition from offshore competitors, and ongoing cash constraints.
Britain Has Entered a New Era of Multiparty Politics. It’s Messy.
A voting system created when two parties dominated is being tested by the rise of newer competitors.
Amazon just expanded its shipping business. What does that mean for UPS?
The shipper's wind-down with Amazon has caused the company to give up some of its market share to competitors like FedEx.
Blame towering market power for soaring hospital prices: Healthcare affordability specialist
“When hospitals that were once competitors merge, prices go up—often by double-digit percentages—with no measurable improvement in patient outcomes.”
Hisense’s new RGB Mini-LED TV is now available with Google TV for less than TCL can offer
Hisense has a new Google TV-powered RGB mini-LED TV series available at nearly half the price of direct competitors, like...
We Compared Similar Tool Boxes From Home Depot & Lowe's, And One Is Way Cheaper Online
Both of these home improvement stores had similar offerings in the tool box department, but one pulled ahead of its competitor when it came to price.
Boulet Brothers Reveal What They Want From Future ‘Dragula’ Competitors
The duo share their insights on becoming a pop culture phenom, as well as favorite horror movie influences.
Microsoft’s DLSS competitor is now available on the Xbox Ally X handheld
Xbox Insiders get early access today
Why Academy Sports & Outdoors is going against the grain with store openings
Executives touted the retailer’s “outside-in” strategy for new locations, which prioritizes markets that are further away from big cities — and big competitors.
Meet Jenni Peters, one of the Capital Region 500
Jenni Peters, a former USA Track & Field athlete and a competitor in the first-ever Olympic Marathon Trials in 1984, turned her passion for running into a thriving business. She launched Varsity Sports in 2000 near the Perkins Road overpass, growing it into a beloved local chain with four locations. The stores, often set in […]
This Holy Cross baseball star is 'a super competitor' and has anchored the team as a senior
This Holy Cross senior is a Tulane signee and described as "a once in coaching career player."
Apple Is Working On A High-Resolution Camera Upgrade That Its Chinese Competitors Have Been Investing Millions To Implement
A rumor claims that Apple is working to bring a high-resolution camera upgrade to its iPhones, but Chinese manufacturers are investing millions to bring it
Leander launches free data tool to support small businesses
SizeUpLeander is a free online platform that provides data on the local business ecosystem, including existing competitors and key market insights.
Fitbit Air reportedly launching May 16, could cost around $100 with several bands & colors
Over the weekend, we first reported the name of Google’s Whoop competitor as “Fitbit Air,” and now more details are...
Nike's comeback attempt: better shoes, more retail sales, sports focus
The sportswear giant got lapped by competitors like New Balance, On, and Hoka. Now Nike is racing to catch up.
Sources: ‘Fitbit Air’ is a screen-less Whoop competitor debuting with ‘Google Health’ subscription
At the end of March, Google started teasing a screen-less Fitbit band. 9to5Google can now report that this device will...
Playnix launches Steam Machine competitor with Radeon RX 9060 XT 16GB, now costs €1140
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“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.
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On plant health and embracing new plant-breeding techniques in South Africa
The major challenge currently confronting South Africa’s agriculture is the spread of foot-and-mouth disease. For many farmers across the country, the most urgent tasks are both securing sufficient vaccines and rolling them out quickly in the coming months, particularly as the beef and dairy industries continue to suffer big losses. There is also pressure on sheep, goats, and other livestock to prevent the disease from spreading. As efforts to get the country through this monumental challenge continue, I believe it is important to sharpen our focus on the broader task at hand: strengthening biosecurity. This covers both animal and plant health. In recent years, we haven’t focused much on plant health, except a few times, such as when we had a goss’s wilt scare in the maize industry, a few cases of citrus black spot, or cases of sclerotinia in sunflower seeds. But the fact that South Africa managed to control the outbreaks of these particular diseases when they occurred a few years ago was due to organized agricultural and government scientific capabilities, and, most importantly, the availability of crop protection or agrochemicals necessary to address some of them. Therefore, as the animal health division in the Department of Agriculture focuses on the pressing challenge of the day, the foot-and-mouth disease, there is an opportunity for the plant health division to assess if they have all the requirements to tackle any outbreak that may occur on fruits, vegetables or crops in future. The challenge with crop diseases is that they can spread quickly and cause much more rapid damage in the field than we typically see with livestock. Therefore, speed is everything in ensuring the appropriate controls are available. I raise this as an important area, particularly given the drastic climate variation we observe across the country. The production conditions in some areas have changed noticeably over time, which may introduce new risks. The other essential part is ensuring that South Africa has access to the best crop protection technology available in the market. Many technology developers worldwide have operations in South Africa. Therefore, the Department of Agriculture, along with the Agricultural Research Council, must continuously interact with technology developers to assess the various crop protection technologies they are releasing globally and determine their suitability and need in South Africa. This will require a proactive approach from the government, unlike the current approach, in which technology developers typically approach regulators with new technologies. The government, recognising the food security risks, must take a proactive approach to ensure that South African farmers have access to the latest crop protection technologies, thereby safeguarding the country’s food security. Beyond crop protection, we must never forget that South Africa’s agriculture is key to ensuring that the country is the most food-secure country at the national level in sub-Saharan Africa. South Africa is also the only African country in the top-40 global agricultural exporters, having more than doubled since 1994 on the back of the adoption of high-yielding seed cultivars. South Africa has been the only African country to adopt a bold approach to embracing science and adopting genetically engineered seeds for grains and oilseeds in the early 2000s. Since then, we have seen crop yields improve noticeably, contributing to the gains we mentioned above. But ensuring that South Africa improves further is not a given. The key lies in South African regulators’ attitudes towards new technologies. We have to maintain a progressive approach and not give in to the politics of non-food and non-scientific voices that shout on the sidelines. Food security is national security, and the government must ensure we progress, leaning on science. Therefore, the registration of high-yielding new genomic techniques is required. South Africa cannot afford to fall behind the EU, the USA, South America, and many of its competitors in global agriculture. The Department of Agriculture’s crop science division must adopt a progress-and-science-embracing approach for the good of the country. Thanks for reading AgriView! Subscribe for free to receive new posts and support my work. Subscribe Share
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