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How Fast Is the Universe Expanding? These Cosmologists Finally Figured It Out
The most precise measurement of the expansion rate ever made suggests an unknown force may be affecting the universe.
The merits and pitfalls of metaphor use in science communication
Effective science communication is a powerful but underrated tool. Metaphors, a common literary device, draw connections between unlike things and are often conceptually, innately understood. In science and science communication, these figures of speech act as a means of structuring concepts to provide the basis for further exploration. The use of metaphors in science can be a catalyst for change, invention, and, unfortunately, misunderstanding. Metaphors should be used responsibly when attempting to make complex scientific concepts easily understandable, and should weigh the accuracy and accessibility of information in a favorable balance.
With NCAA Tournament expansion imminent, some of the game's biggest coaches still aren't sold on the idea
From Hurley to Calipari to Few to Izzo, some of the sport's most prominent figures are lukewarm on changing March Madness
Google Chrome Might Have Installed an AI Model Onto Your Device Without You Knowing
Here's how to figure out if you have the 4GB AI model and how to get rid of it.
Physicists Say It’s Possible to Send Messages Backward in Time
A team figured out the practical mechanics behind one of sci-fi epic film Interstellar’s most out-there ideas.
Pens Points: Malkin discourse shows no signs of slowing
Here are your Pens Points for this Wednesday morning… As the debate to re-sign Evgeni Malkin continues to be the dominant news item (and figures to remain that way until a decision is made), two opposing views on Malkin’s future with the Penguins win out above everything else: one argument is that he’s still productive […]
Military Vets Finally Have a Launchpad for Their Business Dreams in SA
San Antonio is about to become the first city in the country to offer veterans — and their families — a direct path to owning their own business. District 9 Councilwoman Misty Spears is behind a new Small Business Accelerator Program that connects vets with mentors, funding resources, and even a pitch competition — and it's already gotten the green light from the city. Army veteran Melanie McCoy knows firsthand how lonely and confusing starting a business can be without support. Now she's helping lead the charge with a new non-profit called Supply SA, designed so no vet has to figure it out alone. With 75% of San Antonio's economy powered by small businesses, this program could be a game-changer for the whole city. #VeteranOwned #SmallBusinessSA #SanAntonio #MilitaryEntrepreneur #VetBiz
Exclusive: Metalenz Has Figured Out a Way to Make Face ID Invisible
Metalenz’s Polar ID face-scanning technology works even when the camera is hidden under the display.
A Figure From Democrats’ Recent Past May Hold the Key to Beating Donald Trump
The man who bested George W. Bush may have some lessons for Democrats on how to beat Donald Trump.
Who's Who in Finance: Capital Gap Widens - Los Angeles Business Journal
As one of the key figures in Los Angeles’ chapter of the Small Business Majority, Brian Pifer researches, educates and advocates for the area’s
Razer releases new 16-inch gaming laptop globally with Intel Panther Lake and up to 64 GB RAM
Razer has now released its latest 16-inch gaming laptop globally. Equipped with a 16-core Intel Panther Lake processor, the new Razer Blade 16 can also be configured with up to 64 GB of RAM and an Nvidia GeForce RTX 5090 laptop GPU. All variants feature a 240 Hz OLED display, too.
‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field
‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field ‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field A field that once seemed like a direct path to stable, lucrative work is becoming less certain under AI, students and faculty told Spectator. By Ria Vasishtha and Arjun Menon May 3, 2026 Shanying Liu / Deputy Illustrations Editor Asia Genawi, SEAS ’29, first encountered artificial intelligence during her sophomore year at her high school in Indiana. Back in 2023, policies on AI varied widely—even within the same district—and some schools had no guidance at all. As Genawi began to see the effects of AI trickle into her classroom, she turned to guidance from her home state’s Department of Education, which she said she found “outdated and inaccessible.” Genawi spent the rest of her high school career dedicated to the issue, including writing a 15-page memo exploring varying AI policies across Indiana schools, which she sent to every Indiana state senator and representative whose contact information she was able to find. She later helped draft a bill that would have required public high schools to establish and share their own AI policies with students in an accessible format. But with so many other bills already awaiting referral, hers never made it to committee. When Genawi arrived at Columbia to study computer science, she found that the gaps she had spent years trying to address in Indiana had followed her there. Many students and professors were also grappling with what AI meant for the field. Across Columbia’s undergraduate schools, computer science has become the most popular major—accounting for around 11 percent of degrees awarded in Columbia College, 32 percent in the School of Engineering and Applied Science, and 12 percent in the School of General Studies in 2024. While the number of computer science majors in SEAS grew from 166 to 173 during the 2024-25 academic year, the total number across the three schools fell around 4.5 percent from 393 to 375, driven by declines at Columbia College and General Studies. At Barnard, it has grown to become the second most popular major as of 2025, up from third the year prior. The number of degrees awarded have grown fivefold since 2016. Faculty members and students in the department told Spectator that the surge in the major’s popularity has been driven in large part by its apparent promise of a secure, well-paid career path. However, they noted that the recent rise of generative AI has compromised the sense of stability that once defined the field, even as interest in technical skills among students persists. According to data from the Federal Reserve Bank of New York in 2024, out of 74 majors tracked, computer science had the fifth highest unemployment rate among majors at 7 percent, while computer engineering had the second highest at 7.8 percent. “Anecdotally, people are moving away from CS as a major,” Daniel Bauer, a senior lecturer in the computer science department, said. “They’re still taking some of our classes, right, because they think they need that, but they’re instead majoring in other things.” Bauer described a field that had shifted from what he called a “nerdy outlier discipline” to one that “everyone needs,” a sign that technical skills have become a baseline expectation across industries with the emergence of AI. “A lot of people thought, ‘Oh, it’s a guaranteed path to a stable income. You get a six-figure job right out of your undergrad,’” Bauer said. Now, companies may see AI as a way to reduce demand for entry-level programmers, especially in what he calls “code monkey jobs,” roles where a large number of employees are “just writing out code nine-to-five.” Chris Murphy, a senior lecturer in the computer science department, described the current moment as the convergence of two forces: the downturn of the job market and generative AI coming onto the scene. “Things kind of started to really pick up in 2014, 16,” he said, recalling the years after the weaker 2010 market. Murphy added that this was also a period where “students were getting more experience outside of class than they were inside of class” through internships, jobs, and side projects. Murphy suggested that the earlier momentum helped make computer science feel like both an academic program and a reliable pathway into work. That feeling is harder to sustain now as the industry reconfigures, which is a shift that students are seeing firsthand. Rebecca Yu, SEAS ’27, said that during a recent internship in Big Tech, she saw that “every single tech company was racing to integrate” large language models. She added that her manager said her intern class was the first to complete their assigned projects, which she attributed to the increased efficiency that comes with AI. Frank Liu, SEAS ’29, said that with AI lowering the barrier to coding, companies now expect everyone to write code. “A lot of companies outright say if you’re not using coding in your job, you might get fired for not being productive enough,” Liu said. Yu similarly expressed that students increasingly have to accept AI being a part of industry workflow, adding that many also “make use of it to maximize their productivity.” Richard Li, CC ’28, described a “franticness” among his peers as the pace of change accelerates. He explained how “some new tool” is released regularly, noting that tools rise and fall in prominence within weeks. He has come to believe that he doesn’t need to “match that speed all the time” and keep up with every development. Li has learned that AI tools allow him to “take a breath” and “get back into the loop much easier than before” when he needs to. While some companies specifically target Columbia when hiring, sending representatives to campus career fairs and recruiting large numbers from Columbia, a computer science degree cannot be treated as a static credential, Yu described. “You can’t just get your degree and stop learning after that. You have to always be learning,” Yu said. “That is something you basically have to expect for your job.” AI has not only affected students’ decisions to major in computer science, but also reshaped how the subject is taught. Across departments, faculty members no longer treat work done outside the classroom as a reliable measure of understanding, shifting instead toward in-person exams, quizzes, and attendance checks. While homework once made up as much as 60 to 70 percent of a student’s grade in computer science classes, Murphy said that breakdown has since flipped, with exams and quizzes now accounting for the majority. “The assumption—especially among pessimists—is that they’re using it to do their homework,” Murphy said. “They take the homework assignment. They put it into generative AI. Out comes the solution. Submit solution. The end.” Murphy said that faculty members ranged in their responses from fully prohibiting AI use to actively teaching students how to effectively work with AI. He said he shifted his approach this year after his teaching assistants called his belief that students weren’t using the technology “naïve,” and now permits students to use AI on assignments. His surveys of students in his introductory classes have told a more complicated story than the one so-called pessimists offer: Around 60 to 70 percent of students who reported using AI said they used it to have concepts explained to them, to clarify assignment instructions, to generate test cases, or to create practice questions. “Those are all ways that you might have had a tutor in the past to do that, and now you have this AI essentially as your tutor,” he said. Bauer has taken a different approach, teaching students how to use AI productively without sacrificing the core principles of the discipline. “People who are trained to actually use AI tools productively, while being in charge of designing the overall project, will be very much in demand in the next couple of years,” he said. Over the past year, a working group of computer science faculty has been redesigning the introductory and intermediate programming sequence to integrate generative AI as both a subject and a tool, representatives from SEAS wrote in a statement to Spectator. The effort is “coordinated” across the department, “not course-by-course,” with a systematic assessment of how AI integration is affecting student outcomes underway to shape the next round of changes. The goal, the department explained, is for students to be able to “read, verify, and reason about code, whether they or a model wrote it.” Tony Dear, senior lecturer in the computer science department, is piloting individualized AI feedback in a discrete mathematics course, while a machine learning course is also testing a Socratic AI dialogue system designed to “guide inquiry rather than supply answers,” the statement reads. Beyond individual courses, SEAS funded seven cross-departmental faculty projects in generative AI this past academic year, spanning biomedical engineering, chemical engineering, industrial engineering, and computer science, according to the statement. This phenomenon extends beyond the computer science department. SEAS’ new AI minor, which it announced in November 2025, reflects the University’s attempt to adapt. The minor is specifically designed for noncomputer science majors and aims to provide “essential AI knowledge” while emphasizing practical and responsible use across disciplines, according to the SEAS website. At the center of the minor is AI in Context, a course taught by a team of faculty from the departments of computer science, applied mathematics, philosophy, music, literature, and the Writing Center, the representatives told Spectator. Bauer described it as targeted at students who want to bring AI into fields like economics or biology, rather than as a path into software engineering itself. At the graduate level, SEAS announced a new Master of Science in artificial intelligence in February, with the inaugural cohort starting in the fall. While recognizing how AI has helped them navigate coursework, students also described its rise as isolating, even among members of the Application Development Initiative, one of Columbia’s largest computer science clubs. “As people start to ask AI for questions that they would normally ask students and members, it starts to isolate people” Li said. Alexa Kafka, BC ’27, echoed Li’s sentiment, pointing out that computer science has always been a collaborative discipline with code reviews and pull requests, even as AI makes independent work easier. Despite this, Kafka noted that she hasn’t been to office hours “in at least a year.” Bauer added that faculty are exploring long-term solutions to the assessment problem. “One of the things that we’re trying to do at the department or school level is to maybe move towards computerized testing facilities,” Bauer said, referring to ideas in the department to revitalize computer labs as an alternative to pen-and-paper exams. “We have to accept that this is the reality, for better or worse.” But more exams, students say, does not mean better learning, nor does it reflect how computer science is actually done. “Code is so variable and can be approached in so many directions, there’s never just going to be one correct answer. There can be multiple optimal solutions,” Kafka said. Students also expressed concern that the shift toward exam-heavy grading pulls focus away from the applied, project-based work that better reflects both discipline and industry expectations. ADI has tried to respond more quickly than the curriculum can. Through a vibe coding workshop this past semester, club members said they wanted to help students understand not just that AI exists, but how to use it deliberately. “Vibe coding” refers to the practice of prompting AI to write code for a task or project, and has become widespread enough that ADI felt the gap in formal instruction was worth addressing, according to Sophia Huang, BC ’29. The workshop introduced students to the concept of context engineering, which Shaina Sahu, SEAS ’27, described as not just writing a prompt, but optimizing “the rest of the relevant information that you would feed into the model.” Without that, students said that AI-generated code can fail at scale or introduce difficult-to-detect bugs. Genawi said the shift toward AI has changed what it means to be good at computer science. “I think the shift has kind of gone towards what can you create and what can you do, instead of, what do you know,” she said. Indeed, during ADI DevFest, its annual hackathon, Li said more teams are trying to complete their projects than in years past. While sign-ups have historically outpaced submissions, Li said this is beginning to change because teams “have a tool that completes the vision for them.” While many students see AI as an equalizer that lowers the barrier to entry for coding and technical work, Murphy said it also creates new equity concerns inside the classroom around who can afford stronger tools and who already knows how to use them. “The equity issues I worry about are students who have access to paid versions of things versus free versions of things,” he said. Although popular AI models like ChatGPT and Claude have free versions available, both have paid models that can reach over $100 per month, which output different qualities of code. Murphy also pointed to differences in prior exposure to AI literacy itself. “Students who go to high schools or K-12 education, where they’re taught AI literacy, prompt engineering, context engineering, they understand how to do this, as opposed to students who go to schools who don’t teach that,” he said. “Then they come in, and then they’re somehow expected to know how to use these tools.” For Genawi, those disparities begin long before students arrive on campus. “It’s very interesting to consider how lucky you were geographically,” she said. “To be born where you were is influencing your ability to get access to these spaces.” Students like Yu, though broadly apprehensive about the future of computer science, are not without hope. “I’m optimistic, because I think if you’re truly passionate about CS, there will definitely be a place in the field to do something you want to do,” she said. Senior Staff Writer Ria Vasishtha can be contacted at ria.vasishtha@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Staff Writer Arjun Menon can be contacted at arjun.menon@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Want to keep up with breaking news? Subscribe to our email newsletter and like Spectator on Facebook. Produced with Spectate by Emily Ta
Scientists Say They’ve Figured Out What Causes “Ghosts”
New research suggests that inaudible sound waves produced by old buildings could be behind why we perceive the presences of ghosts.
The ‘Diablo 4: Lord Of Hatred’ Build And Class Tier List Is Out
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What Trump’s post as a Jesus‑like figure tells us about political messianism
In a democracy, it’s dangerous for leaders to see themselves as better than or morally superior to the people they serve.
Watch India's Woes Bigger Than Any One Political Figure, Amitav Ghosh Says
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How I'd Turn a Side Hustle Into a 7-Figure Business in 12 Months Using These 4 AI Tools
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In a study, Australian cockatoos figured out that a new food was OK to consume by observing one another, a vivid example of “social learning” in animals.
States Rush To Figure Out How To Enforce Trump's Medicaid Work Requirements
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Community-Based Preventive Health Interventions and Their Impact on Population Health Outcomes: A Narrative Review
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What Trump’s post as a Jesus-like figure tells us about political messianism
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Who was invited to dinner with King Charles: Justices, business leaders and Palm Beach friends
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In Japan, US nationalism and conservatism has fed the growth of a political party
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Dam Nation files federal lawsuit against Blueprint Sports
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Ex-NBA player Damon Jones 1st to plead guilty in gambling case
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Brain Health Across the Life Span: A Framework for Future Studies
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Political violence is rising. Can we stop it? Tell us.
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AMC Entertainment Scores a Thriller Weekend as MICHAEL Delivers a Record-Breaking Debut
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Even Before the Gunfire. Many Guests Bore the Scars of Political Violence
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Trump speaks on political violence following Correspondents' Dinner shooting
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Valve reportedly close to announcing Steam Machine price and release date
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Philadelphia museum brings Rocky statue inside after decades of tension
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If I lost everything tomorrow and had to rebuild to seven figures in 12 months using only AI, I wouldn't guess — I'd reverse-engineer the people who already did it.
Daiichi pushes back annual report, citing reviews amid ‘rapidly changing business conditions’
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Longtime DJs John Smith and Bill Harper team up during SOS
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You Can Actually Regrow Your Fingertips. Scientists Just Figured Out How.
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'Self-aware' robots can learn complex tasks by watching humans. Is that a good thing?
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Trump is facing an increasingly patient Iran
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Preorders Are Live for the Switch 2-Exclusive Splatoon Raiders and Its Three Accompanying Amiibo Figures
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Offworld Life Science: Research Hardware For A Biotechnology Investigation
configures research hardware inside a portable glovebag for a biotechnology investigation exploring how bacteria affect heart tissue in the microgravity environment.
Fredericksburg region business figures weigh in on state minimum wage bill
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How a babywearing business hit seven figures with community marketing
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Kentucky governor blasts UK athletics' 'decision-making'
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Super Bowl parade poured cash into Seattle businesses, new figures show
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New megafauna looked like spiky, 30-pound hamster
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Entertainment figures reject calls for Israel Eurovision boycott
Public letter says kicking the Jewish state out of song contest would be "inversion of justice."
Orioles news: The yo-yo offense continues
There are days where you think they’ve got it figured out, and days where you don’t.
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How much influencer earn at Coachella, the 'Influencer Olympics'
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Trump wants a sculpture garden for America’s 250th birthday. Sources say it’s unlikely even one statue will be ready.
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I was laid off in 2020. My uncle's inheritance changed everything.
Steph Mahon used an $80,000 inheritance from her uncle to start a real estate business that's now nearing seven figures.
Stanford grad couldn't find job, so created a six-figure business
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How is the business community going to tackle health care costs?
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How is the business community going to tackle health care costs?
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Time for government, business leaders to figure out AI cybersecurity regulation
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Over 1,000 Entertainment Figures — Including Gene Simmons and Amy Schumer — Reject Eurovision Israel Boycott
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Texas Tech Tradition Takes Center Stage: Transfer of Reins, Passing of Guns
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Fans Begging For Chrono Trigger Remake Get Figures Instead
Also: the Gears of War movie lives, sorta
Alliance Entertainment’s Handmade by Robots debuts Record Store Day Exclusive Figures
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Japan: Chrono Trigger form-ism figures spotted at official pop up store leading to speculation about remake
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South Africa's Malema faces political crisis after jail sentence in firearm case
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Snail-Borne Diseases in Central Africa: Lessons from Citizen Science
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Analysis | Trump tests loyalty of Christian supporters as erratic behavior escalates
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PinkPantheress makes strong Seattle debut after Coachella 2026 performance
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Brian Kelly lands new job following LSU firing
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Six-figure offers and hundreds of calls, all-conference guard details portal decision
Hudson Mayes had \
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As screen presences and cultural figures, Ian McKellen and Michaela Coel could hardly be more different | WWJ Newsradio 950
Ian McKellen and Michaela Coel on art, their friendship and 'The Christophers'
As screen presences and cultural figures, Ian McKellen and Michaela Coel could hardly be more different | WWL
Operation Metro Surge costs Minnesota schools, businesses millions as relief bills advance
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International Collaboration Helps Pinpoint Universe’s Expansion Rate
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After Criticizing Pope, Trump Posts Image of Himself as a Jesus-Like Figure
The image, posted on Truth Social, appeared to be A.I.-generated and depicts the president as a divine leader healing the sick.
“The choice is yours…”, an analysis of Wilders’ algorithmic politics on platform X
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Patient-Provider Discussions on Lung Cancer Screening: Insights From the Health Information National Trends Survey (HINTS)
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California Democrats Rushed to Back Eric Swalwell — and Quickly Abandoned Him
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Hacking women's political underrepresentation, Dutch-style
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Legendary basketball coach, broadcaster Dick Vitale reveals health status
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ON THE JOB: “What is the Best Business Advice You’ve Ever Received?
Interviews by Deborah Jeanne Sergeant Sound advice can contribute to your success. We recently asked area business leaders, what was their best advice they’d ever received. Here’s what they said: “The best advice I ever received was from my then –boss, Gerry Church, Fulton plant manager at Miller Brewing Co. He told me that whenever I wanted to discuss a business problem or issue with him, I should also be prepared to offer possible solutions. It’s the difference between being proactive or reactive. It’s also the difference between being a leader or follower. That has served me well in any business relationship I have had since then.” — Stephen Chirello, Owner, Steve Chirello Advertising, Fulton “Someone will always do it for less; they will also take the most effort to service or satisfy and leave you for the next lower price.” — John M. Henry, Owner, Speedway Press, Mitchell Printing, Phoenix Press, Oswego “I’m going to answer this question by turning it around and giving my own advice that is, ‘Always treat every customer as if they were your only customer!’ We are celebrating our 50th anniversary in business this year. We started our business on March 25, 1976. My advice works.”” — Nick Chervinsky, President, Brewerton Pharmacy, Brewerton “’You need to toot your own horn, my grandfather, Howard D. Dice, told me.” — Beth Ann Dice, Women’s active aging and cancer recovery coach, Mission Movement Wellness Studio & Breast Cancer Recovery Studio, Fulton “In the micro enterprise class, they taught, ‘Get a good lawyer, accountant and bank.’ That was over 30 years ago and I still have those three today. I chose good people I could grow with.” — Tony Pauldine, Owner, Anthony M. Pauldine General Contractors Inc., Oswego “From my grandfather; ‘Listen to everyone! You never know where you will get the solution you need.’” — Kevin Dean, Executive director, Oswego County Opportunities, Fulton “‘Preparation is the mother of success.’ My dad always drilled that into my head growing up, and it has helped me avoid a lot of snags in both my personal and professional life. Thanks, Dad!” — Bekkah Frisch, Owner and president, iHeart Holdings, Inc., Fulton “If you don’t take a risk and try, you will never know.” — Justin Taber, Owner, Torbitt’s Service Center, Oswego “Be ready to take a loss.” — Cody Seymour, Manager, Damiano’s Eatery, Mexico “I’ve received so much good business advice over the years. When people are giving you advice, always be curious rather than judgmental. Follow your gut. Doing the right thing is never the wrong thing.” — Dana Decker, Principal owner/broker, Berkshire Hathaway Home Services, Oswego ’Do it and figure it out later.’ It hasn’t failed me yet. Too many people take time to think about doing this and this and this and then the opportunity is over with. If it’s somewhat reasonable — if it’s not something outrageous — do it and figure it out later.” — Jeremy Allen, Licensed real estate salesperson, Acropolis Realty Group, Syracuse “’Try to meet the needs of the customer. Treat them like you’d like to be treated.’ It’s like the Golden Rule says.” — Douglas Dickson, Physician and associate at CNY Foot Surgery and Podiatry Care, East Syracuse “The best piece of business advice I’ve ever received applies to life in general: always be honest. Never overstate your capabilities and always be willing to ask questions. The more specific you can be in any given topic will always lead to a better outcome.” — Tom Fernandez, President, Woodbine Hospitality, Syracuse “As a business owner, the advice would be ‘Don’t overextend yourself. Especially in agriculture, expect issues to come up.’ If something is going right, it’s not true agriculture. This last season, we scaled very hard to field another crew. We got more drones, crew and generators based on projections. This last season hit the ag community hard with a very wet spring. We did 15,000 to 20,000 acres for fungicide and the same for cover crop seeding in 2024. We scaled to 25,000 to 30,000 for 2025. We ended up doing 2,000 for fungicide and 3,000 for cover crop seeding. That’s why that advice was good.” — Rick Jordan, Operations manager, CNY Drove Services, Clinton “’Keep your head down, mind your own business and do the best for your clients that you can do.’ It has a lot to do with my success in working for Galloway Century 21.” — Ed Fayette, New York state licensed real estate agent, Century 21 Galloway, Oswego “’Expand in all ways, always.’ It just keeps you going and keeps you growing.” — Stephen Baier, Licensed real estate person, The Real Estate Agency & Bouck Commercial, Auburn “The best advice is, ‘Your biggest asset you won’t see on the books because it comes from your employees.’” — David Flickinger, Owner, Edible Arrangements, Syracuse “Don’t take things personally when you’re working with the public.” — Leeann Desimone, Manager, Annie’s Hallmark Shop, Auburn “‘Follow up.’ The customer knows that you care about what you are doing and that their opinion counts. Sometimes they might be on the fence about whether they want to use your company. If they’re asking your opinion on things, they feel you are concerned about what you’re doing. They like to be kept in the loop if they’re spending money with you.” — Dorothy Casper, Saslesperson, SweetWoods Memorials, Phoenix “The best business advice I received is ‘Never be the smartest person in the room. Surround yourself with people who are smarter than you.’ That’s how you learn.” — Debbie Bilello, Owner, Virtual Office Solutions, Central Square “’You need to grow your business but you can’t grow too big too fast.’ That’s what we’ve done at Pinnacle Maintenance. We’ve tried to grow but not too fast. Along those same lines, there’s another good piece of advice, ‘Don’t take on more than you can handle because it only leads to a bad name for your business and a bad experience for your customers.’ It goes along the same lines as growing your business slowly and carefully.” — David Wines, Owner, Pinnacle Maintenance, Central Square “Always be on time and do what you say you are going to do.’ I’ve done very well following that advice. Most of my work is referral and I don’t really do any advertising so I have a pretty good customer base. It’s mostly word-of-mouth from satisfied customers.” — Robert J. Fleming, Owner, Bob Fleming Windows & Doors, Brewerton “’Concentrate on your finances, always pay your taxes, and form a team you can depend on. Try to help the community you’re in as much as you can.’ We do all of these all the time here. We give and give and give to the community and the community gives back to us always.” — Susan Bonnet, Co-owner, Bonnet Sales and Service, Central Square “Keep smiling. It brings a positive attitude to the workplace.” — Karin Lindsley, Vice president, DTS Truck Service, Syracuse “‘Customer service above all.’ Following this advice has served us very well.’ — Guy Fox, Owner, Fox’s Discount Parts, West Monroe “The best thing to do is to make sure you’re taking in more money than you’re spending. I wish I could say I’m a good businessman but I have been in business since 1981. I’m not a bean counter but work well with my hands and its’s served me well all these years and I am still in business.” — Matt McGill, Owner, Matt McGill Collision, Brewerton
U.S. Moves to Deport Son of Prominent Figure in Iranian Revolution
Federal agents arrested a man whose mother served as a spokeswoman for the Islamist embassy captors during the hostage crisis that began in 1979.
Brice Barnes raises six-figures in first day as candidate
The North Florida seat she seeks will be open in November.
“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.
Apple @ Work: How to add an existing Mac to Apple Business Manager without wiping it
A new open source script called add2abm allows IT administrators to retroactively add configured Macs to Apple Business Manager without erasing the hard drive.
In praise of popular science
As a kid, I was enthusiastically and unreservedly in favor of a manned space program. Our destiny lay in the stars, I figured. Get people out there. We need Star Trek here and now. As I got older, I became rather disenchanted with the idea. Humans are expensive, fragile, and inefficient as space cargo. We could flood the solar system with 100 robotic probes for the price of any single manned mission and get back just as useful data. Besides, it turns out space travel is dangerous. Tusk is a reader-supported publication. To support this work, please become a paid subscriber. Subscribe When it came to the recent Artemis II mission, my cynical side didn’t really see the point. Flying around the Moon and back is literally something we did before I was born, and I once owned a Members Only jacket. Apollo 8 circled the Moon ten times and returned to Earth safely the same month that “Chitty Chitty Bang Bang” was released. What was the point of repeating a feat that far braver people once did with tin foil and slide rules? Yet I’ve surprised myself with how moving I’ve found the Artemis II mission to be. The photos have been stunning. The crew has been professional and engaging. There have been modest but important milestones — the farthest humans have travelled from Earth; the first woman, person of color, and non-American to leave low-Earth orbit; innovations in communication, and more. One thing that really stood out is that this is really NASA at its finest. Not that this is the most important mission they ever pulled off, but they did this in a competent way that celebrated the achievements and kept the crew and the science at the forefront of the project. This wasn’t some billionaire throwing celebrities or cars into orbit as a vanity project — this was a collective effort to send experts in to do a job and come home safely. We don’t see that sort of thing much these days. I’m guessing few people would describe many government agencies as inspiring, but this one counts for me. We’re living through a profoundly anti-science era, in which pathbreaking, lifesaving discoveries like mRNA vaccines are routinely downplayed or even vilified. As I’ve noted previously, this era is something like that of the Red Scare in the 1940s and 50s, in which “egghead” professors were portrayed as out of touch or even hostile to regular Americans. One of the things that helped break that spell was Sputnik — the Soviet communications satellite that demonstrated that the United States was falling behind in crucial scientific research and applications. Its launch triggered a new appreciation for American science and goaded the federal government into supporting research universities and labs. I’m not saying that Artemis is the equivalent of Sputnik, but it potentially reminds people that there’s some value to scientific endeavors and the human faces attached to them. Despite my love for the show “For All Mankind,” I’m far from convinced that there’s any real value to putting colonies on the Moon or Mars that would justify the capital investment and the massive health risks to the astronauts. But sending scientific good will ambassadors on a trip into space once in a while? Bring it. Share