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Patient-Owned Health Data Model Reduces Clinical Trial Recruitment Redundancy
Patient-owned health data model reduces clinical trial recruitment redundancy by enabling persistent consent and longitudinal data sharing across studies.
Huawei Mate 90 series wallpapers are now up for download
Huawei Mate 90 series has launched with five models and a bunch of new wallpapers, which are now available for download. These images come in QHD+ (Quad High Definition Plus) resolution, offering a stunning vibe to the home screen. Mate 90 series debuted last week as a new performance flagship line. Like every Huawei phone, […]
Being South Asian, sports fan is not mutually exclusive
South Asian students should not be disregarded as sports fans because of the model minority myth.
Epidemiological modeling in the age of artificial intelligence
Nature Computational Science - Artificial intelligence is enabling epidemic models to learn across outbreaks. The next challenge is ensuring that these models learn and transfer not mere...
OpenAI users in Russia, Iran used models to push political agenda online, in media
OpenAI banned several accounts associated with two propaganda operations based in Iran and Russia, respectively, it confirmed Thursday. The latter of which the tech company said had the greatest re…
Bipartisan push in Texas hopes to land new U.S. Space Academy
The academy would be modeled after West Point and the Naval Academy to educate and train future leaders of the Space Force.
Iranian operatives used AI to plant fake stories in multiple US media outlets
Operatives in Iran used OpenAI models and fake personas to help plant news articles critical of the US war against Iran in multiple US media outlets, OpenAI said on Thursday.
Google brings agentic AI to Gemini, starting with businesses
Google is turning Gemini into an AI agent that can plan, execute tasks, and work across business apps and systems. The agent can delegate work to subagents, use multiple AI models, and even gets its own workplace identity, complete with an email address.
Fundamental Brings Nexus to LA Galaxy and L.A. Live Through New Official Partnership with AEG
Fundamental's NEXUS model joins two of Southern California's most iconic sports and entertainment properties, bringing predictive technology to the business of sports and live entertainment LOS ANGELES, Oct. 8, 2026 -- Fundamental, an AI company whose Large Tabular Model (“LTM”), NEXUS is reimagining enterprise decision-making, and AEG, the world’s leading
Anthropic Commits $150M To AI Science Mission
Anthropic is committing $150 million over three years to the federal government’s Genesis Mission, expanding access to its Claude AI models.
Testing 6 Completely Different Gravel Bikes Head to Head to Find the Future of Gravel
Gravel bikes are as varied as the people who ride them. We tested six completely different models at the Velo Field Test to find out where gravel is headed.
Sphere Entertainment (SPHR) Could Be 40% Undervalued As Oz Demand Worries Hit Sentiment
Craig-Hallum’s downgrade of Sphere Entertainment (SPHR) after concerns about softening demand for its The Wizard of Oz show has put fresh focus on how this experiential model supports the current valuation. Sphere Entertainment’s latest downgrade comes after a sharp pullback, with the 7-day share price return down 20.98% and the 30-day return down 25.40%. Even though the year-to-date share price return is 12.66% and the 1-year total shareholder return is 79.19%, recent momentum is clearly...
Open science is compatible with research security, says Canada’s chief science advisor
Open science is “not incompatible” with research security and science leaders and policymakers should “demystify” the false dichotomy between the two, according to Mona Nemer, Canada’s chief science advisor. More than a decade ago, EU policymakers were promoting open science, open innovation and open collaboration across the world. It was a political movement that aimed to make scientific research, data, software, publications and methodologies transparent, accessible and reusable for everyone.But that rhetoric has changed over the past few years. After Russia invaded Ukraine in 2022 and Donald Trump came back to power in 2025, international partnerships have become more pragmatic. Countries are trying to implement protectionist policies and governments are increasingly worried about technology espionage. According to Nemer, science can remain open if the sector can come up with improved security protocols that would protect research data from undue manipulation by foreign actors. “If anybody can fiddle with the with the data, then [open science] is actually quite dangerous and quite useless,” she told Science|Business. Universities and research institutions are increasingly vulnerable to attempted espionage and other types of foreign interference. In September, the UK’s domestic counter-intelligence service MI5 issued a security warning against collaborations with the China General Technology Research Institute. And earlier this year, Germany’s Helmholtz Center for Information Security was criticised by federal research minister Dorothee Bär, who told a parliamentary hearing that “existing rules and systems” at the institute “were not suitable” for preventing leaks to China. According to Nemer, universities and research institutions should perhaps follow the example of the private sector, as companies have been able to safeguard their research while still publishing results. “I think that there is a level of research security hygiene that researchers and institutions need to just adopt,” she said. “You don't have to tell Sanofi or IBM how to safeguard their research, which they end up publishing anyway.”While certain areas of research will not be open for collaboration with certain partners, in other areas cooperation is necessary even with researchers based in adversarial countries. “I stress this because politics change,” she said. “Science and politics don't make for good fellows, and whether we like it or not, politics will influence certain things.”Researchers will play an important role in “protecting the integrity of science,” said Nemer. “I think that it's time that there's a commitment to a certain scientific compact, so that citizens don't think that science is actually an open door for espionage and for anti-nationalism.”New partnershipsNemer spoke with Science|Business on the margins of the Hamburg Science Summit on September 17, the day when Canadian Prime Minister Mark Carney called for increased cooperation with the EU, including in science and technology. Canada is looking to strengthen ties with partners in other corners of the world, after the Trump administration threatened to put tariffs on Canadian goods and services and even openly suggested Canada could become the 51st state. In parallel, the US government has indicated it wants to retreat from international science projects, including US collaboration with Europe’s CERN particle accelerator and other big science labs.Related articlesThe stats we need to better understand R&DCanada looks to deepen research and education links with the EUCan researchers trust that AI models won’t leak their ideas?Nemer said the US is still a science “powerhouse,” but Canada and Europe will have to work closely together on global challenges. “It’s important for both [sides], but I think it's also important for the rest of the world, because the cut in funding for development, in health, in regions like Africa and other places, have dramatic effects.” The Trump administration is also planning a review of the Nelson memo, a Biden-era document that mandated that results of federally funded research would be openly available. With that idea being called into question, Nemer said it could be “very disruptive” to scientific collaborations and could jeopardise research on climate change, the Arctic and global health. “When your collaborator suddenly tells you I'm not going to share the data with you as a researcher, if this happens, I think it's very worrisome,” she said. “I'm certainly hoping that a lot of the Canadian institutions, funders, researchers, have started looking at joining forces on databases and using more European research infrastructures,” Nemer added.
Google Cloud unveils persistent Gemini Agents for long-running tasks, and they get their own Gmail, Calendar, and Drive storage
While Google supplies its own Gemini models, the agent can already use Anthropic's Claude models, with support for additional proprietary and open-weight AI models planned.
Concern after Europeans endorse US science agenda
Germany’s biggest research funder has said it is “concerned” after Berlin, plus several other European countries, endorsed a controversial US-led science policy statement. On October 4, the White House announced that 16 countries, including Germany, the UK, Italy, Greece, Bulgaria, Cyprus, Poland, Japan and South Korea had backed the Kyoto Vision for a Golden Age of Science.The document, agreed on the margins of the annual Science and Technology in Society forum in Kyoto, which gathers science ministers from across the world, appears uncontroversial at first sight. It’s a one-page statement, without any concrete measures, that touches on reducing administrative burden on scientists, experimenting with new funding models and the use of “super intelligence” in science, the Trump administration’s preferred term for artificial intelligence. However, what’s controversial is that much of the language in the Kyoto Vision reflects Science: A New Golden Age, a major policy document released by the White House in July.That document attracted criticism for deriding universities as “legacy institutions” and suggesting money be diverted to new research labs. In a speech in Kyoto on October 4, Michael Kratsios, director of the White House Office for Science and Technology Policy and the report’s author, said that the US was seeking to “diversify the ways that we support research to meet our best scientists where and when they do their best work.” The worry is that the Trump administration may be using genuine dysfunctions in academia as a pretext to defund and disempower universities, which US vice president JD Vance has labelled “the enemy.” Many in Europe also want more experimentation and reform of how science is organised and funded, and agree with criticisms of academia made by Science: A New Golden Age. But some also fear that if the US pushes for reform partially in bad faith, it could politicise and undermine the whole agenda. Washington is currently trying to change federal funding rules so that political appointees can block and cancel scientific grants. It has cut grants mid-project on topics related to diversity and other politically forbidden areas. And last year, it threatened to cut Harvard University’s federal funding unless it admitted a “critical mass” of new faculty and students to create campus “viewpoint diversity.” “Particularly concerned”Because of this wider US political context, the Kyoto Vision’s otherwise innocuous sounding statement that “we encourage experimentation with new institutional models for science that provide varying levels of autonomy, resources and direction” has caused consternation in Europe, particularly from some of Germany’s biggest science organisations. A spokesperson for the German Research Foundation (DFG), the country’s biggest funder, said that it would “closely monitor whether the current US administration uses the Kyoto Vision to restructure research funding to the detriment of research institutions such as universities and their autonomy.” The DFG was “particularly concerned” with the statement’s references to Science: A New Golden Age, they continued. A spokesperson for the German Rectors’ Conference, which represents the country’s universities, said that the reference to “new institutional models” raises “questions on the underlying understanding of academic freedom and autonomy.” Research funding must “guided first and foremost by scientific not political principles,” they went on. Dampen criticismEuropean endorsement of the Kyoto Vision might dampen domestic criticism of the Trump administration’s science policy, some in the US fear, by suggesting international support. “What we saw from Germany, Japan, the UK and other countries, is an impulse that the administration has exploited with our own science reform movement, a belief they can use dialogue to make things better,” said Cole Donovan, director of science policy at the campaigning group Stand Up for Science. “In practice, the administration has done the opposite.” Not a binding statementThere’s been so much concern in Germany that the country’s federal Ministry of Research, Technology and Space put out a statement defending its endorsement of the Kyoto Vision, which it has posted on its website. Related articlesIs metascience being co-opted?European researchers sound the alarm that Trump rule changes will hit cooperationThe US ‘golden age’ science strategy: what Europeans need to know The ministry said that it “should be regarded as a basis for discussion and does not constitute a binding statement.” Backing the statement gives Germany the chance to raise “issues and concerns” with the US during upcoming talks on science and technology scheduled for November. “Although these intentions appear, in principle, to be worthy of support, they will be scrutinised and examined more closely as the process continues,” the statement continues. Super intelligence?A ministry spokesperson confirmed to Science|Business that Germany had broadly endorsed the Kyoto Vision.However, they said Berlin had not agreed to final changes in the statement to refer to AI as super intelligence. In September, facing protests against data centres and polling that suggests US citizens are far more concerned than excited by the technology, Trump issued an executive order that attempts to rebrand AI as super intelligence, following polling on social media.The name change is to “reflect the transformative capabilities of these technologies and the limitless opportunities they create for the American people,” the order says. EU askedThe UK and Italian science ministries did not respond to a request for comment on their endorsement of the Kyoto Vision. Although most EU countries did not endorse the statement, it’s not clear which states the US asked. The White House Office for Science and Technology Policy did not return a request for comment. A European Commission official, speaking under condition of anonymity, said that the US had approached the EU, but too late for the EU to quiz all its member states on whether Brussels should endorse the statement.
Blizzard is changing the appearance of WoW: Forever's new Skyborne race in response to community feedback
A new blog post from the World of Warcraft: Forever team confirms the models for Skyborne elves are being reworked following feedback, coming early 2027.
OpenAI claims we've entered the AGI era — has GPT-6 Astra really demonstrated general intelligence?
OpenAI says its newly launched GPT-6 Astra model brings humanity to the threshold of AGI, but external evaluators argue that inflated lab metrics and opaque testing obscure its true reliability.
A rural Northwest Oklahoma hospital is bringing back maternity care. Can it survive healthcare cuts?
Newman Memorial hopes the model it’s building can sustain access despite looming reductions to federal Medicaid spending signed into law last year alongside the dollars fueling its project.
Gurman: OLED MacBook Pro Won't Be 'Significantly Thinner'
Bloomberg's Mark Gurman has walked back somewhat on his previous reporting that Apple's upcoming touchscreen OLED MacBook Pro will be thinner than current models. "I don't think it'll be significantly thinner in the end," he posted on X late Wednesday in reply to a question about the machine, which is expected to launch later this month. In October 2025, Gurman reported that the OLED MacBook Pro models would have "thinner and lighter" frames.
The Math Singularity Is Here, and Science May Be Next
OpenAI has released an extraordinary body of mathematical work produced by an unreleased frontier model: 722 manuscripts spanning 372 research families across fields including number theory, complexity theory, and mathematical physics. Each result required, on average, the equivalent of roughly three hours of ChatGPT Pro reasoning. A New Era of Discovery We may be witnessing the beginnings of a “math singularity”: a point at which machine-generated discovery accelerates beyond humanity’s ability to independently reproduce, verify, or fully absorb it. If frontier models can generate hundreds of meaningful results in the time it takes a human researcher to investigate one, the constraint will no longer be producing new mathematics. It will be our capacity to validate, interpret, and integrate it. This does not make mathematicians obsolete. It changes their role. They may increasingly serve as guides, critics, and meaning-makers. Increasingly, they will decide which questions matter, determining which results can be trusted, and explaining why they are important. Mathematical insight may become abundant, while human judgment becomes more valuable than ever. Mathematics May Be Only the Beginning Every scientific discipline could eventually experience a similar acceleration. AI systems could generate and test hypotheses, connect findings across specialized fields, and explore possibilities at a scale no human research community could match. In medicine, imagine models identifying overlooked disease mechanisms, designing drugs and clinical trials, personalizing treatments, or discovering cures in months rather than decades. In materials science, AI could help create better batteries and cleaner industrial processes. In climate science, it could accelerate advances in energy, forecasting, and carbon removal. In biology, it could uncover relationships hidden across enormous genomic and molecular datasets. The result would not simply be faster research. It could expand the frontier of what is scientifically possible. The New Bottleneck Scientific discovery, however, is not the same as scientific progress. A medical breakthrough must still survive laboratory testing, clinical trials, regulatory scrutiny, manufacturing constraints, and real-world deployment. As machine-generated ideas multiply, the bottleneck may shift from producing breakthroughs to validating them safely and translating them into practice. We may soon have more hypotheses than laboratories can test, more drugs than clinical trials can evaluate, and more mathematical results than experts can review. That imbalance will require better systems for automated verification, reproducible research, prioritization, peer review, and collaboration between AI and domain experts. The importance of OpenAI’s work is not merely the number of manuscripts produced. It offers a glimpse of a world in which intelligence can explore thousands of intellectual paths in parallel. If ideas cease to be scarce, humanity’s defining challenge will be deciding which are true, which matter, and how to turn them into progress. The math singularity is not the end of human inquiry. It is the beginning of a new kind—one in which machines expand the frontier of knowledge and humans decide where it should lead. Subscribe Share Leave a comment
AI use lifts participation in WorldQuant contest
Hedge fund WorldQuant said on Wednesday registrations for this year's flagship global quant research contest have almost doubled from a year earlier, as increased adoption of AI has helped more university students build trading models.
North Idaho bakery builds up skills from scratch
The Village Bakery owners, Dana and Todd Bellefeuile, have built their Hayden establishment around a workforce model that helps people with disabilities develop skills for future employment and independent living.
MSFT Stock On 4-Day Winning Streak: Microsoft Takes On Apple's Macs With Nvidia-Powered Surface Ultra, More On-Device AI
Microsoft is pushing Windows deeper into the local-AI era with Nvidia-powered Surface, on-device models and hybrid Copilot features.
As AI Learns to Write, Tuhin Chakrabarty Studies What Humans Stand to Lose
As AI models are able to generate increasingly convincing prose, what began as an experiment—can AI write something that sounds plausibly human?—is becoming a commercial reality, with blog posts, YouTube video scripts and even bestselling novels bearing AI’s fingerprints. But the speed of that shift brings unique challenges, including questions of copyright infringement and an
Task force ditches Wyoming-run health insurance plan idea, mulls unorthodox service models
Legislature-assigned panel studying healthcare affordability in Wyoming examines several alternative pricing structures. The task force hopes to continue work next year.
IQVIA Launches IQVIA Life Science Models to Help Life Sciences Companies Predict Clinical Trial Outcomes
RESEARCH TRIANGLE PARK, N.C.--(BUSINESS WIRE)--IQVIA (NYSE:IQV), a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries, today at TechIQ 2026 introduced IQVIA Life Science ModelsTM to help predict clinica
IQVIA Launches IQVIA Life Science Models to Help Life Sciences Companies Predict Clinical Trial Outcomes
RESEARCH TRIANGLE PARK, N.C.--(BUSINESS WIRE)--Oct 7, 2026--
Science on Target: Q3 Publications from our Innovation Ecosystem
Antisense Oligonucleotide Tofersen Distribution in the Central Nervous System of SOD1-ALS Autopsy Tissue Donors. Guise AJ, Sellon MT, Roemer SF, Monine M, Comfort Harris NT, […] Plowey ED. JAMA Neurol. 2026 Jul 6:e262195. doi: 10.1001/jamaneurol.2026.2195. Epub ahead of print. PMID: 42406382; PMCID: PMC13338845. Using human 3D organoid models to gain mechanistic insight in motor neuron […]
Microsoft releases new Nvidia-chip AI PCs with revamped Windows 11
Microsoft revealed the specs and price for its Surface Laptop Ultra, AI PCs that run on Nvidia chips that are designed to run AI models and agents.
IQVIA Launches IQVIA Life Science Models to Help Life Sciences Companies Predict Clinical Trial Outcomes
RESEARCH TRIANGLE PARK, N.C.--(BUSINESS WIRE)--Oct 7, 2026--
IQVIA Launches IQVIA Life Science Models to Help Life Sciences Companies Predict Clinical Trial Outcomes
RESEARCH TRIANGLE PARK, N.C., October 07, 2026--IQVIA (NYSE:IQV), a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries, today at TechIQ 2026 introduced IQVIA Life Science ModelsTM to help predict clinical trial outcomes.
Apple Watch Series 12, Ultra 4 Owners Report Skin Irritation
Some Apple Watch Series 12 and Ultra 4 owners have experienced unexpected skin irritation with the new models, according to reports on the MacRumors forums and Reddit. Affected users complain of a burning sensation and redness under the sensor area. The Apple Watch Series 12 and Ultra 4 measure heart rate every five seconds, and some people have wondered if that's the cause of the skin irritation.
The Culinary Director at a Unique California Restaurant Reveals the Key Ingredients Behind Its ‘Needle-in-a-Haystack’ Business Model
Deborah Mullin oversees a complex operation at Little Saint, the plant-based restaurant in Healdsburg, California.
Amazon US Prime Deals: the Google Pixel 11 Pro is $250 off
The $1,100 MSRP for a 256GB Pixel 11 Pro was overly ambitious - with this price cut, even the 512GB model (which has 16GB of RAM) is under $1,000.
New state program helps business owners explore employee ownership
Feasibility studies and valuations are a key first step in converting a business to an ESOP model.
Bringing local models and sandboxed tools to Windows and GitHub Copilot
Coming soon, GitHub Copilot will determine when a task is best handled by on-device intelligence and when it should leverage cloud-scale models.
1 Smart Business Story: How Founders Use PR To Dominate
Media is a minefield. From Substacks and livestreams to podcasts and newspapers (where they still exist), it’s a lot for founders to juggle. Fortunately,
Amazon US Prime Deals: the Samsung Galaxy S26 Ultra is 30% off
Despite the recent price hike that put the base model at $1,400 MSRP, you can still get an S26 Ultra under $1,000. The Samsung Galaxy S26 Ultra launched at...
Beyond hours saved: Building the business case for agentic automation
The RPA-era ROI model misses most of the value agentic automation creates. This post gives AI center of excellence leaders a framework to size the full value of agents across time savings, exception handling, decision quality, and maintenance economics, and to prioritize which workflows to automate first.
You Can Get Up to $149 Off Every New Mac Mini During Prime Day
Prime Big Deal Days sales have hit Apple's brand new Mac mini and Mac Studio computers, and we're tracking up to $149 off every model of the M6 and M5 Pro Mac mini during this year's event. You'll also find $199 off the M5 Max Mac Studio below. Note: MacRumors is an affiliate partner with some of these vendors. When you click a link and make a purchase, we may receive a small payment, which helps us keep the site running.
AI behaves more like a brain than a database – cognitive science’s role in its origin story helps explain why
Modern AI owes its existence to both cognitive and computer science. What you envision as its origin story can influence how you understand what large language models can do.
AI behaves more like a brain than a database – cognitive science’s role in its origin story helps explain why
Modern AI owes its existence to both cognitive and computer science. What you envision as its origin story can influence how you understand what large language models can do.
Fastest-Ever 'Mind Reading' AI Model Can Reconstruct Images From Your Brain
See what the person saw - and what the AI recreated from their brain activity.
Nvidia RTX Spark for $2,999.99: HP leak reveals RTX Spark laptop pricing ahead of launch
HP is gearing up to launch its new OmniBook Ultra 16 and OmniBook X 14 laptops with Nvidia's new RTX Spark super chip. Ahead of launch, the two models have briefly appeared on the company's US store, revealing a higher starting price than anticipated.
Will AI kill the Asian entertainment industry, or reinvent it?
Studios in China are turning to models from ByteDance and Kling to generate 100-minute short dramas for less than $3000.
Will AI kill the Asian entertainment industry, or reinvent it?
Studios in China are turning to models from ByteDance and Kling to generate 100-minute short dramas for less than $3000.
Geoffrey Hinton suggests an FDA-style approval system for AI
Geoffrey Hinton said AI companies should have to convince a regulator their models are safe before releasing them, much like drugmakers.
Say Your Prayers: An Exclusive First Look at Scarlett Johansson in The Exorcist: Martyrs
In Mike Flanagan’s new film, she investigates slayings modeled on the gruesome suffering of saints. But the suspect may be truly inhuman.
Pokémon Fossil Museum exhibit coming to Denver Museum of Nature and Science
In 2026, the exhibit of life-sized fossil Pokémon models made its North American debut in Chicago, and it will make a stop in Denver next year.
Samsung 9100 Pro SSDs are on sale at Amazon, 1TB drive is back near its launch price
The 9100 Pro comes in four capacities: 1TB, 2TB, 4TB, and 8TB. The 1TB model is currently $206, about 39% below its regular list price of $339....
Bush-Wells Sporting Goods to close its doors at the end of the year
CASPER, Wyo. — After 63 years in business, Bush-Wells Sporting Goods will close at the end of this year. Changing business models in the industry,
Is the Steelers’ Business Model Broken?
For decades, the Pittsburgh Steelers were considered to be the gold standard of the National Football League, both on the […]
Data science professor awarded grant to support partnership with Internet Archive, preserve digital history
Alexander Nwala will develop AI models that automatically identify, archive and catalog web resources referenced in U.S. television news in a publicly accessible database.
An ambitious financial experiment tried to support struggling rural hospitals in Pa. for years. Did it work?
The Pennsylvania Rural Health Model ran from 2019 through 2024 at 18 hospitals across the commonwealth.
Tyra Banks re-releasing viral ‘Modelland’ book 15 years after it failed (exclusive)
Tyra Banks exclusively reveals to EW that she’s re-releasing her ‘Modelland’ book after its viral resurgence online amid her mom’s secret health battle: ‘A deep, almost depression for me.’
How healthcare can build a human-in-command approach to AI
Healthcare AI needs human oversight. Risk-based safeguards, meaningful authority and continuous requalification can help build a human-in-command model.
Shemar Moore reveals he needed 3 surgeries to fix his ‘ugly-ass feet’: ‘Now they’re presentable’
“God took a nap when he was making my feet,” jokes the “S.W.A.T: Exiles” star and former model.
Why I Don’t Think Ride Or Die Should Have Been Cancelled (And What Company Should Save It...)
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) So…I recently came across a Reddit thread, talking about films on streaming, wondering why there are no reliable sources out there for streaming ratings data. Sigh. Honestly, as annoyed as I am that so many still don’t realize that we have streaming ratings, I somewhat get it. Until now, there was such a long delay between when a show or film came to streaming and when we got its viewership data; I understand why people were confused. (But, as you know, this just changed.) Also, even back in the day, how many people knew how well films did on television? Luckily, as a reader, you’re in the know. Okay, on to this week’s issue. I want to take a look at Prime Video cancelling Ride or Die and whether I agree with that decision. Overall, we didn’t have any breakout hits (no TV shows landed over 20 million hours according to Nielsen) but we have a lot of steady performers on the streaming charts. Plus, we’ll look at where $50 million in missing box office dollars went. (Spoiler: straight-to-streaming.) All that, plus new episodes of The Secret Lives of Mormon Wives, Supergirl heads to streaming, a new YA show does well on Netflix, the viewership for the Daily Wire’s $50 million fantasy show, what TV show hit-maker can’t make streaming hits, CD sales, all the flops, bombs and misses, and a whole lot more. Let’s dive right in! (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, JustWatch and Reelgood interest data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the weeks of September 7th to September 13th, 2026. You can find a link to my terminology here.) Subscribe Television - Ride or Die Is a Hit…But It Got Cancelled? What The Data “Says” I hate the phrase “here’s what the data says”, even though sometimes I find myself using it. If data just told us everything, we data folks would be out of a job! Data is often messy, complicated and nuanced. When it comes to strategy, many of the best decisions can’t actually use “data”, since it’s vastly too complicated to model. Anyways, I’ve been singing the praises of Prime Video’s Ride Or Die this summer, a show that did very well for them. And yet…it got cancelled. Now, usually when a show gets cancelled, a bunch of websites say “a hit show got cancelled”... Here’s the thing, though: in this case, they’re right! The data “says” that this show was a hit. Specifically, out of 522 first seasons to make a week on the Nielsen charts since 2020, it’s the 75th biggest. On Amazon, Ride or Die is eighth out of 41 first seasons: That’s top 15th percentile all time, almost exactly, which is my definition of a “hit”! I mean, outside of Reacher, Amazon needed a hit this summer! (Admittedly, Off Campus did well for Amazon in the spring, but Ride or Die performed even better.) So what happened? Why did Amazon cancel one of their rare 2026 bright spots? Well, Deadline reported a reason—which I’ll get to—but I’d break it down into three relevant questions: What is a given streamer’s reasoning? Is that reasoning sound? Could the stated reason not be the real reason? According to Deadline, Amazon felt the show “over-indexed” in middle-aged women. (This was based on leaks from within Amazon.) The logic is this: Amazon already reaches this demographic because of unlimited two-day shipping bundled with Prime, so they don’t really need more shows like this. Now, it’s my job to ask if that’s a good reason, and I’ll be honest, in this case, I don’t think it is. Sure, this show may “over-index” in middle-aged women—I’ll just assume that’s the case here—but I think folks often oversell how important over-indexing actually is. When a show is a “hit”, it isn’t a bit bigger than its rivals; it’s usually multiples bigger. For example, Elle only made the charts for two weeks at 8.3 million hours each. So Ride or Die was 80% bigger in its first two weeks, and likely had a much stronger hold, with its terrific 13 million hours in week three. Ride or Die was nearly three times bigger than Sterling Point through three weeks too. And that means that _Elle, Sterling Point a_nd other Amazon YA shows need to not just over-index a little with younger women (assuming that’s who Amazon prefers over middle-aged women), but massively over-index. Otherwise, more people in that demo (and a bunch more besides) likely watched Ride or Die. (I’ll try to explore this concept more in a future article.) And don’t get me started on how Ride or Die did compared to a certain (very, very popular, possibly the world’s most popular) YouTuber’s reality show…which didn’t make the charts after its first week and likely cost much, much more than Ride or Die. All to say, Amazon-MGM Studios/Prime Video can tell reporters that this show didn’t reach the right audience, but that excuse feels weak to me. So this leads to the third question: could other reasons have come into play? Yes! Renewal or cancellation decisions rarely (I’m tempted to say “never”) boil down to one variable. At its simplest, it’s two things: budget versus viewership. But often factors like critical acclaim, ownership and, yes, personal opinion come into play. In this case, Amazon has a new executive running things, and this show isn’t owned by Amazon-MGM Studios (unlike Elle). And yes, it may not have indexed with the right target viewers, too. Likely all of those factors came into play.1 My guess is ownership ended up mattering most. Amazon doesn’t own Ride or Die. It’s actually produced by another major studio. Fortunately/allegedly, this show is being shopped around. I can think of one brand new CEO who should consider it for one of his two major streamers…especially if he wants to rebuild goodwill in Hollywood. His name is on this list of exec producers of Ride or Die… If David Ellison needs some goodwill—and he does—rescue this female-led show tomorrow and grab some good headlines for a day. The data justifies it. Quick Notes on TV We’re just getting started with this issue, but the rest is for paid subscribers of the Entertainment Strategy Guy, so if you’d like to find out… How The Secret Lives of Mormon Wives latest season did on Hulu, post-controversy... Whether Supergirl soared on HBO Max... Why the box office is losing money due to the streamers... The viewership for the Daily Wire’s $50 million fantasy show... Updates on The Gentlemen, Lanterns, Outer Banks, King of the Hill and more... What former hit-maker has three streaming flops in a row... Whether The Mandalorian and Grogu popped in week two... All the flops, bombs and misses... And a whole lot more... ...please subscribe! We can only keep doing this great work with your support. If you want an idea of just how much content you’d get in a full issue, check out this older issue. Coming Soon! Oh man, we’re almost caught up! We just have two more issues, then the streaming Ratings Report will be coming out just two weeks after a TV show premieres! Next issue, I’ll be looking at the first two weeks of the NFL Thursday night games on streaming, a huge new spinoff, Reacher’s Neagly on Prime Video, and the latest edition of Monster: The Lizzie Borden Story on Netflix, the return of Slow Horses on Apple and MobLand (quietly one of their biggest shows) on Paramount+, and Dancing with the Stars on both ABC and Disney+. Plus I’ll take a look at animation for adults in 2026. The week after, a ton of movies are coming to streaming: Toy Story 5 on Disney+, Backrooms on HBO Max, Jackass: Best and Last on Paramount+ and The Breadwinner on Netflix, plus a Unabomber film on Netflix and a romcom on Prime Video. Woody Harrelson and Matthew McConaughey have a show on Apple, along with a game show inspired by Willy Wonka that everyone seems to hate. Long term, some crazy (but hopefully crazy like a fox) IP news. FX ordered a new Sons of Anarchy show from Charlie Hunnam, but it’s not about the biker gang. No, it features the show’s cast playing themselves in a new “meta-thriller”. Huh. And a lot of the cast is coming back. Next, Ryan Gosling is producing a Flintstones movie about a “grown-up Bamm-Bamm Rubble”. Also, huh. This one is in “early development” so we’ll see what happens. Both projects are based on IP, but also seem to have crazy takes on the IP, which I like.
Amazon Hires Three Netflix Business Affairs Execs
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MacBook Pro With OLED Display Rumored to Be 'Significantly Lighter'
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This week in health care policy: September 28 – October 2, 2026
Drug pricing CMS finalizes GLOBE pilot. On September 30, CMS finalized the Global Benchmark for Efficient Drug Pricing model, a program that ties Part B drug rebates to prices paid in 19 countries. It will cover physician-administered drugs in randomly selected communities throughout the US, representing about 25 percent of Part B beneficiaries. It runs […]
Studying Science in an Anti-Scientific Time
This Chronicle Review Deep Cut was first published in 2025. By Julianne Werlin Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe The last two decades have not been kind to science studies. Already bruised and battered by the “science wars” of the 1990s, by the 2000s sociologists of science — who had long argued that science had to be understood in its human context — were encountering the funhouse-mirror version of their own views in right-wing critiques of climate scientists. It was enough to give some prominent scholars pause. “Was I wrong to participate in the invention of this field known as science studies?” asked Bruno Latour, the most famous sociologist of science in the world, in 2003. “Should we apologize for having been wrong all along? Or should we rather bring the sword of criticism to criticism itself and do a bit of soul-searching here: What were we really after when we were so intent on showing the social construction of scientific facts?” In response, Latour proposed a change of method and attitude. Science studies, now chastened and contrite, would no longer seek to strip facts of their authority, but to enrich and enhance them. What this meant in practice was never fully clear. But his diagnosis of problems resonated, even if his solutions did not. Latour’s exercise in public hand-wringing signaled a shift in mood. By 2016, with the first election of Donald Trump, the idea that skepticism of science was a right-wing position, not a left-wing one, had become a commonplace, discussed eagerly in The New York Times. For liberals, vaccine denial during the Covid era and Trump’s second-term attacks on the funding of scientific research, covered extensively in these pages, added a new urgency to the defense of science on both practical and principled grounds. There was little appetite for a sociology or philosophy of science that emphasized the messiness and missteps of the scientific process rather than its integrity and triumphs. The distinguished historian of science Peter Dear’s new book, The World as We Know It: From Natural Philosophy to Modern Science (Princeton University Press, 2025), which seeks to tell the story of 18th- and 19th-century science for a general public, may seem comfortably remote from these bitter contests. In its 16 short chapters, Dear draws swift, sure sketches of major discoveries from Newton to Einstein, ably guiding the reader through debates on stellar nebulae, animal taxonomy, atomic chemistry, evolution, and other flashpoints in the history of science. But though a work of history, Dear’s book must still negotiate our polarized present. In a blurb on its back cover, the historian of biology Lynn K. Nyhart alludes to the “present moment, when scientific knowledge is being swamped by misinformation and its institutions are under siege.” Dear himself, in his conclusion, refers to the “yard signs” and “bumper stickers” that proclaim “Science Is Real.” One antidote to both anti-science propaganda and to reductive slogans in science’s defense is a robust history and philosophy of science: exactly what Dear’s scholarship has long offered. But his new book illustrates how difficult such work has become. Dear, an emeritus professor of history at Cornell University, is best known as a creative and philosophically minded historian of the Scientific Revolution. His edited volume The Literary Structure of Scientific Argument (1991) analyzed the rhetoric of Galileo’s thought experiments to brilliant effect. Discipline and Experience: The Mathematical Way in the Scientific Revolution (1995) was a major contribution to the analysis of scientific experiments in early modern Europe and beyond, while Revolutionizing the Sciences: European Knowledge in Transition, 1500-1700 (2001), now in its third edition, remains one of the best overviews of the profound epistemological upheavals of 16th- and 17th-century science. But Dear has also ventured into later periods. Nearly two decades ago, in The Intelligibility of Nature: How Science Makes Sense of the World (2006), he turned to the 18th and 19th centuries to sketch a history and theory of scientific knowledge. Aimed at a generalist audience, Dear’s simple prose belied serious philosophical ambitions. Science, Dear argued, has two aspects: “natural philosophy,” the quest to understand the true nature of the universe, and “instrumentality,” the applied skills and technologies that allow us to manipulate the world for human advantage. Both strands are ancient, but the innovation of the phenomenon we call “science” was to yoke them together. As Francis Bacon wrote, “Human knowledge and human power meet in one; for where the cause is not known, the effect cannot be produced,” an insight typically abridged to “knowledge is power.” Or, in Bertrand Russell’s characteristically blunt phrase, science has two functions, “1. to enable us to know things, and 2., to enable us to do things.” So far, so conventional. But Dear took issue with this familiar story in one respect. Bacon’s formula implied that theory and practice could be fused in a single method. In fact, Dear argued, the quest to understand nature and the desire to manipulate it were coupled only loosely. They could come together, but they could also pull apart. Focusing on natural philosophy, the “knowing” half of the scientific circle, he used a series of case studies from cosmology, taxonomy, chemistry, electromagnetism, and quantum theory to show how theories changed over time, in dialogue with practice, but never reducible to it. Take the case of matter, the basic substrate of the physical world. In the 18th and 19th centuries, scientists not only disagreed about what it was, but also about how well it could be known. In 1789, the chemist Antoine Lavoisier dismissed speculation about the atomic composition of chemicals as “discussions entirely of a metaphysical nature,” as he sought to orient chemistry away from philosophical abstraction and toward laboratory results. But in the 19th century, atoms returned with a vengeance in the atomic chemistry of John Dalton, who wanted to explain the underlying structure of nature. It was not just that Dalton and Lavoisier had a different set of experimental results, or even a different theory, Dear showed. What counted as an explanation had changed. In arguing that scientific theories depended on their intelligibility to human beings with complex arrays of beliefs and commitments, Dear was in sympathy with science studies. Key figures such as the sociologist Steven Shapin emphasized the importance of psychological mechanisms like trust in the formation and acceptance of scientific ideas. But in focusing on the scientific pursuit of knowledge, not its politics or economics, Dear resisted the more cynical perspective of some of his colleagues. The Intelligibility of Nature strikes a very different note than Shapin’s collection of a few years later, Never Pure: Historical Studies of Science as If It Was Produced by People With Bodies, Situated in Time, Space, Culture, and Society, and Struggling for Credibility and Authority (2010), to name just one example. Walking a very fine line, Dear depicted science as driven at once by complex social dynamics and by the intellectual power of real discoveries. It was a testament not only to his own acumen but also to the vitality of the field that he was able to do so. Nearly two decades later, The World as We Know It returns to the questions broached in The Intelligibility of Nature. Like Dear’s earlier study, it begins with the Newtonian cosmos and ends with debates between Einstein and Bohr on quantum physics. Beyond its terminal figures, many of the same characters appear in both studies, including the naturalists John Ray and the Comte de Buffon; the chemists Étienne François Geoffroy, Antoine Lavoisier, and John Dalton; as well as Charles Darwin and Michael Faraday, among others. Its subject is nearly identical: As in The Intelligibility of Nature, The World as We Know It considers natural philosophy as opposed to instrumentality, here defined as the “desire to create a picture of what the world is really like — the world as God knows it — rather than simply having instrumental or operational control over it.” The two books also overlap in insights — and sometimes even in language. The reader who has learned in The Intelligibility of Nature that Buffon’s method of classifying animals “reflected his belief in the importance of the senses and empiricism in learning about nature (a doctrine associated with Newton and the philosopher John Locke)” will experience a sense of déjà vu on reading, in The World as We Know It, that the classification “reflects Buffon’s commitment to the epistemological stance of Newton and his philosophical underlaborer John Locke, who stressed the role of the senses in creating natural knowledge.” Later in the passage, we read that, “because of its stress on understanding the ways of life of animals in their environments, Buffon’s approach could almost be labeled (anachronistically) as ‘ecological.’” And again, “an anachronistic way of putting it would be to say that Buffon recommends an ecological mode of understanding.” Likewise, in The Intelligibility of Nature we read of Dalton that he was initially drawn to meteorology, and that: He did a bit of experimental work on these things, especially having to do with the water-holding capacity of gases, but his real interest lay in understanding what, at an underlying natural-philosophical level, was really going on physically.” Whereas, in The World as We Know It: He did experimental work on these things, especially concerning the water-holding capacity of gases — although not at a very refined level quantitatively — but he was continually trying to develop a theoretical conception of what was happening physically. The final full chapter of each book closes on the same resigned note. Intelligibility: These days, most serious work on the natural philosophical underpinnings and implications of quantum mechanics is performed not by physicists but by philosophers of science. Among scientific practitioners themselves, Bohr’s attempt to use instrumentality as sufficient grounds for a respectable science has met with a high degree of success. And again, in The World as We Know It: Bohr’s and Einstein’s concerns are now questions that are mostly discussed by philosophers of science rather than by physicists themselves. The marginalization of these sorts of questions amounts to the demise of natural philosophy, at least in physics, in the 20th century. Quantum mechanics “works,” and that’s good enough for most scientists who encounter it. Examples could be multiplied. When handling the same subject matter, some echoes are inevitable. Scholars should not feel that because they have written “Isaac Newton died in 1727” in one book, in the next they must describe him as perishing, expiring, or meeting his maker. But the repetitions of language and arguments (not to mention six reproduced images) threaded throughout The World as We Know It are more extensive than that. They should have been caught by Princeton University Press or its reviewers, and revised. Because the two books have so much in common, it is easy to see where they diverge. The World as We Know It is a less theoretical work than its predecessor. The sociology of knowledge that organized The Intelligibility of Nature has been reduced in scale and folded into readings and examples. The taut interplay between history and theory, which gave the earlier study so much interest, is there, but it is subtle. In the earlier book, the case studies demonstrated theoretical claims about the character and development of science. In the later work, each narrative of discovery is an end in itself. Insights emerge from the history, but they do not control the organization of the study. With the theory muted, it can be hard to understand the logic uniting Dear’s sprawling history of more than two centuries of scientific knowledge. The 16 brisk chapters cover an enormous amount of material. But the closer the volume edges to comprehensiveness, the more obvious the missing elements become. A chapter on “Institutions and Pedagogy,” describing the birth of the research university, illustrates the problem. Inserted roughly halfway through the book, the unnumbered chapter is designed as an “entr’acte,” in acknowledgement that it does not fit the study’s organization around scientific discoveries. Yet as Dear is well aware, no general history of the development of modern science can bracket its 19th-century institutionalization and professionalization. It was the 19th-century university, after all, that gave us the “scientist,” a term coined by the Cambridge philosopher William Whewell. Dear’s history of scientific discoveries implies a wider social and institutional history, but it remains largely subterranean, only occasionally extruded under the pressure of the narrative. It must be said that the balance is not all on the side of the earlier study. There are some advantages to the more historical, less theoretical organization of The World as We Know It. Dear’s accounts of paradigm shifts are remarkably lucid, no small accomplishment given that they span fields and centuries. He makes excellent use of the wealth of new scholarship on Darwin and his influences, to which he has himself contributed. It is satisfying to see puzzle pieces from Buffon’s natural history, Georges Cuvier’s animal taxonomy, Thomas Robert Malthus’s demography, and Charles Lyell’s geology recombined seamlessly in the Darwinian jigsaw. Likewise, Dear’s discussion of stellar nebulae, divided between chapters two and 15, shows vividly how Newton, Kant, Herschel, and Hubble reimagined insights and observations as they sought to discover whether the diffuse light that filtered through early telescopes was a glowing, gaseous substance or discrete but distant stars. Yet despite such pleasures, the book remains a more modest work than The Intelligibility of Nature. Dear has clearly not changed his views about the history of science. But in the two decades that have elapsed, the discipline and the world around it have changed, making it harder to write a sociologically and philosophically ambitious history of science for the general reader. That is a shame, because in the age of Silicon Valley and biotechnology, both the reciprocity and the tensions Dear identified between the epistemological and instrumental ambitions of science are more evident than ever. In recent years, some of the most exciting new books on the history of science in early modernity have focused precisely on this pressure point. Important studies such as Pamela H. Smith’s From Lived Experience to the Written Word (2022), James Poskett’s Horizons: The Global Origins of Modern Science (2022), and Vera Keller’s The Interlopers: Early Stuart Projects and the Undisciplining of Knowledge (2023) all shed new light on how early modern science negotiated the relationship between its instrumental and epistemological ambitions, or in Russell’s phrase, knowing and doing. There is every opportunity for a philosophically informed approach to draw new insights from this wealth of material. Dear, unfortunately, has not done so in The World as We Know It. But for future scholars of the history of science, his body of work over nearly four decades may provide just the model. Julianne Werlin is an associate professor of English at Duke University. Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe
Bishop’s computer science chair says AI is eliminating ‘grunt work’ and reshaping digital jobs
Dr. Russell Butler, chair of Bishop’s University’s Department of Computer Science, says artificial intelligence is increasingly taking over routine digital “grunt work,” changing the skills students and workers may need in the years ahead. Photo courtesy of Bishop’s University. Click here to read our platform! Get local news like this every morning. Subscribe free below. Subscribe Pulse Newsroom Artificial intelligence is already taking over some of the routine digital work once performed by entry-level employees, according to Bishop’s University Computer Science chair Dr. Russell Butler — a shift he believes will make expertise, judgement and the ability to evaluate AI-generated work increasingly important. Butler described the change as automation reaching what he calls the “bottom of the cognitive pyramid” during an interview with The Pulse about AI, university education and the future of digital work. His argument is not that humans are disappearing from the workplace. Instead, he sees their role changing as AI becomes capable of handling more of the repetitive tasks involved in computer-based work. “Everything’s converging on just AI basically doing all the grunt work,” Butler said. The bottom of the cognitive pyramid Butler is from Lennoxville, completed his undergraduate studies at Bishop’s and later earned his PhD at the Université de Sherbrooke. He joined Bishop’s in 2019 and now chairs its Department of Computer Science. He uses AI in research, teaching and other creative work, and said the technology is increasingly capable of handling routine digital tasks that once required substantial human time. “You’ve got the grunt work, like moving things around in Excel, doing basic programming tasks,” Butler said. “That’s like the bottom grunt work that the entry-level worker would have done two or three years ago.” Butler went further, saying in his view that much of this type of work has already been absorbed by AI tools. He connected that change to a shift he sees taking place in computer science, where entry-level roles have declined while experienced workers can use AI to increase what they can produce. “A senior developer now has access to essentially an unlimited amount of junior developers on demand,” Butler said. He was describing AI systems metaphorically, not literal employees. His point was that one experienced developer can now ask AI tools to produce code or other technical work that might previously have been assigned to more junior workers. That raises a broader question for universities and employers. If some of the simpler work traditionally given to newcomers can now be done by machines, how do people gain the experience needed to become senior workers themselves? Students doing work that once required years of programming Butler said he is already seeing the change inside his classroom. He created a Bishop’s course called CS208, Coding in Plain English, to show students — including those without traditional programming backgrounds — what they can accomplish using AI. Some come from disciplines such as psychology or neuroscience with no previous programming experience. “What I’m finding is that students who have zero programming experience, they come in from another discipline like psychology or neuroscience or something, they are now able to get up and running with real data sets,” Butler said. Butler’s own doctoral work involved neuroimaging, and he said he has assigned students work he considers comparable to the kinds of analysis he performed during his PhD. He described giving students a real dataset, an expected result and instructions to use AI to complete the analysis. Butler said those students have been able to carry out work at a level he associates with tasks he once performed after years of programming experience. That does not mean a student using AI instantly acquires the same knowledge as an experienced computer scientist. But Butler sees it as evidence that AI can dramatically lower the technical barrier between having a problem to solve and producing a working result. The role of the person using the system then changes. They need to know what to ask for, understand enough about the subject to judge the answer and take responsibility for what is ultimately produced. What about AI hallucinations? One persistent concern surrounding generative AI is hallucination — when a system produces information that sounds convincing but is false or unsupported. Butler said that problem has improved substantially in newer systems and is not as severe as it was with earlier models. He pointed in particular to newer AI systems’ ability to search the web, consult scientific databases and return source links rather than simply generating a citation from their internal model. Butler nevertheless said users should verify what AI produces. “You should verify,” he said while discussing citations generated with AI. His position is that hallucinations have become less common in the systems he uses, not that incorrect AI output is impossible. Human checking remains part of the process. Hours of work compressed Butler offered another example from his administrative work at Bishop’s. The university has been comparing CEGEP courses with first-year Bishop’s courses to determine where students may qualify for advanced standing. Traditionally, Butler said, that means reviewing two sets of course descriptions and manually matching one institution’s courses with another’s. As department chair, that could require hours of reading and comparison. He said AI can now be given both sets of material and asked to generate an initial mapping automatically. “It saves me hours and hours of work,” Butler said. Butler said the AI-generated mapping can also produce a better result than he would produce himself. He sees similar opportunities in businesses. A company may receive specifications, drawings, emails or other digital material from customers and then have employees convert that information into an internal format before anything can be manufactured or delivered. AI can increasingly perform parts of that intermediate processing. In Butler’s view, the employee does not necessarily disappear. Instead, the job becomes more about checking the result. “The human is still there,” he said. Judgement could become more valuable That change is central to Butler’s view of where digital work may be headed. If AI can produce a first draft, write basic code, compare documents or process large amounts of information, he argues that knowledge and judgement become increasingly important. “The real scarce resource going forward is going to be domain knowledge, expertise, and… credentials, authority, the ability to work with other people,” Butler said. He is therefore encouraging students not only to learn AI tools but also to broaden their education. He mentioned acting, fine art and photography as examples of courses that can help develop what he described as taste and intuition — the ability to recognize what is good, what is not and what should be changed. “And that’s the skill that they need now because the grunt work has been automated and now it’s about evaluating what the AI produces and telling it how to improve or expand the output,” Butler said. That does not remove the need for technical knowledge. Butler’s argument is that the emphasis may shift away from manually completing every step of a task and toward directing, checking and improving work produced with AI assistance. He also stressed that humans remain responsible for final decisions. “At the end of the day, the human has to make the final call,” Butler said, pointing to the question of accountability. Physical work may be different Butler draws a distinction between digital work and jobs requiring people to manipulate the physical world. He expects AI to continue advancing quickly in tasks performed almost entirely on computers. He is more cautious about claims that humanoid robots will soon be able to replace workers such as plumbers or electricians. Butler said those trades would not be replaced “anytime soon” in his view and described some current robotics demonstrations as overhyped. He described the situation as counterintuitive. “It’s almost like we solved the highest level first,” he said, contrasting advances in digital AI with the harder problem of building robots capable of operating reliably in the physical world. Butler’s argument is that some digital occupations could face automation sooner than trades requiring complex physical work. The wider AI shift in the Townships Butler’s comments come as local institutions are increasingly grappling with how AI should be used. The federal government recently announced up to $162 million over five years for 10,000 AI-related placements through Mitacs. The Université de Sherbrooke told The Pulse that the number of its collaborative research and innovation projects supported through Mitacs has approximately doubled since 2018-19, while the number of placements has approximately tripled. UdeS also said it already has projects involving both AI adoption and the application of AI to other fields. At Bishop’s, Butler said part of his role involves building the Computer Science department’s local presence, connecting students with regional partners and strengthening relationships with the Sherbrooke technology ecosystem. Those developments put universities in a difficult position. They have to prepare students to use the tools employers increasingly have available while also making sure graduates understand enough to recognize when those tools are wrong, incomplete or being applied to the wrong problem. The risk of losing human skills Butler does not see AI as risk-free. Later in the interview, he raised a separate concern: as AI becomes better at reading, writing, programming and other cognitive tasks, people could lose some of the underlying skills that historically helped produce new ideas. “The other danger is that we’re going to lose the human skills,” Butler said. He specifically mentioned reading and writing and argued that people could lose some of the lower-level understanding that contributes to breakthroughs. Butler said AI systems are based on existing human knowledge and argued that they become much more powerful when paired with a capable person. That tension runs through his view of the technology. AI can remove hours of routine work. It can allow beginners to perform tasks that once required substantial technical training. It can give experienced workers significant leverage. But the more capable the technology becomes, the more important it may be for people to develop the judgement needed to decide what should be done in the first place. For Butler, that is where education may have to change. Students still need to understand their field. They still need to know when something is wrong. And they still need to be able to make the final decision. But if AI increasingly handles the bottom of the cognitive pyramid, the value of a worker may depend less on how quickly they can perform the grunt work and more on whether they understand what the work is supposed to accomplish. Don’t miss the next story that affects your community. Join thousands of readers getting The Pulse every morning—plus breaking news alerts when it matters most. If you value this kind of local journalism, consider supporting it. Subscribe, share and like! Subscribe Share
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