The Download: AI’s retracted papers problem

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The Download: AI’s retracted papers problem

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. AI models are using material from retracted scientific papers The news: Some AI chatbots rely on flawed research from retracted scientific papers to answer questions, according to recent studies. In one such study, researchers asked OpenAI’s ChatGPT questions based on information from 21 retracted papers on medical imaging. The chatbot’s answers referenced retracted papers in five cases but advised caution in only three. The bigger picture: The findings raise serious questions about how reliable AI tools are at evaluating scientific research, or answering people’s health queries. They could also complicate efforts to invest in AI tools for scientists. And it’s not an easy problem to fix. Read the full story. —Ananya Join us at 1pm ET today to meet our Innovator of the Year Every year, MIT Technology Review awards Innovator of the Year to someone whose work we admire. This year we selected Sneha Goenka, who designed the computations behind the world’s fastest whole-genome sequencing method. Her work could transform medical care by allowing physicians to sequence a patient’s genome and diagnose genetic conditions in less than eight hours. Register here to join an exclusive subscriber-only Roundtable conversation with Goenka, Leilani Battle, assistant professor at the University of Washington, and our editor in chief Mat Honan at 1pm ET today. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 There’s scant evidence tylenol use during pregnancy causes autismThe biggest cause of autism is genetic—that’s why it often runs in families. (Scientific American $)+ Anti-vaxxers are furious the White House didn’t link autism to vaccines. (Ars Technica)+ The company that sells Tylenol is being forced to defend the medicine’s safety. (Axios)2 Nvidia is investing up to $100 billion in OpenAIOpenAI is already a major customer, but this will bind the two even more closely together. (Reuters $)+ America’s top companies keep talking about AI—but they can’t explain its upsides. (FT $)3 Denmark’s biggest airport was shut down by dronesIts prime minister refused to rule out Russian involvement. (FT $)+ Poland and Estonia have been speaking up at the UN about Russian incursions into their airspace. (The Guardian)4 Google is facing another antitrust trial in the USThis one will focus on remedies to its dominance of the advertising tech market. (Ars Technica)+ The FTC is also taking Amazon to court over accusations the company tricks people into paying for Prime. (NPR)+ The Supreme Court has ruled to allow Trump’s firing of a Democrat FTC commissioner. (NYT $)5 Here’s the potential impact of Trump’s H-1B crackdown on techIt’s likely to push a lot of skilled workers elsewhere. (Rest of World) 6 How TikTok’s deal to stay in the US will workOracle will manage its algorithm for US users and oversee security operations. (ABC)+ It’s a giant prize for Trump’s friend Larry Ellison, Oracle’s cofounder. (NYT $)+ Trump and his allies are now likely to exert a lot of political influence over TikTok. (WP $)7 Record labels are escalating their lawsuit against an AI music startupThey claim it knowingly pirated songs from YouTube to train its generative AI models. (The Verge $)+ AI is coming for music, too. (MIT Technology Review) 8 There’s a big fight in the US over who pays for weight loss drugsAlthough they’ll save insurers money long-term, they cost a lot upfront. (WP $)+ We’re learning more about what weight-loss drugs do to the body. (MIT Technology Review)9 How a lone vigilante ended up blowing up 5G towersA little bit of knowledge can be a dangerous thing. (Wired $)10 The moon is rusting 🌕And it’s our fault. Awkward! (Nature) Quote of the day “At the heart of this is people trying to look for simple answers to complex problems.” —James Cusack, chief executive of an autism charity called Autistica, tells Nature what he thinks is driving Trump and others to incorrectly link the condition with Tylenol use during pregnancy. One more thing SARAH ROGERS / MITTR | PHOTOS GETTY Maybe you will be able to live past 122 How long can humans live? This is a good time to ask the question. The longevity scene is having a moment, and a few key areas of research suggest that we might be able to push human life spans further, and potentially reverse at least some signs of aging. Researchers can’t even agree on what the exact mechanisms of aging are and which they should be targeting. Debates continue to rage over how long it’s possible for humans to live—and whether there is a limit at all. But it looks likely that something will be developed in the coming decades that will help us live longer, in better health. Read the full story. —Jessica Hamzelou We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.) + This website lets you send a letter to your future self. + Here’s what Brian Eno has to say about art.+ This photographer takes stunning pictures of Greenland. + The Hungarian dish Rakott krumpli isn’t going to win any health plaudits, but it looks very comforting all the same.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

AI models are using material from retracted scientific papers

The news: Some AI chatbots rely on flawed research from retracted scientific papers to answer questions, according to recent studies. In one such study, researchers asked OpenAI’s ChatGPT questions based on information from 21 retracted papers on medical imaging. The chatbot’s answers referenced retracted papers in five cases but advised caution in only three.

The bigger picture: The findings raise serious questions about how reliable AI tools are at evaluating scientific research, or answering people’s health queries. They could also complicate efforts to invest in AI tools for scientists. And it’s not an easy problem to fix. Read the full story.

—Ananya

Join us at 1pm ET today to meet our Innovator of the Year

Every year, MIT Technology Review awards Innovator of the Year to someone whose work we admire. This year we selected Sneha Goenka, who designed the computations behind the world’s fastest whole-genome sequencing method.

Her work could transform medical care by allowing physicians to sequence a patient’s genome and diagnose genetic conditions in less than eight hours.

Register here to join an exclusive subscriber-only Roundtable conversation with Goenka, Leilani Battle, assistant professor at the University of Washington, and our editor in chief Mat Honan at 1pm ET today.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 There’s scant evidence tylenol use during pregnancy causes autism
The biggest cause of autism is genetic—that’s why it often runs in families. (Scientific American $)
+ Anti-vaxxers are furious the White House didn’t link autism to vaccines. (Ars Technica)
+ The company that sells Tylenol is being forced to defend the medicine’s safety. (Axios)

2 Nvidia is investing up to $100 billion in OpenAI
OpenAI is already a major customer, but this will bind the two even more closely together. (Reuters $)
+ America’s top companies keep talking about AI—but they can’t explain its upsides. (FT $)

3 Denmark’s biggest airport was shut down by drones
Its prime minister refused to rule out Russian involvement. (FT $)
+ Poland and Estonia have been speaking up at the UN about Russian incursions into their airspace. (The Guardian)

4 Google is facing another antitrust trial in the US
This one will focus on remedies to its dominance of the advertising tech market. (Ars Technica)
+ The FTC is also taking Amazon to court over accusations the company tricks people into paying for Prime. (NPR)
+ The Supreme Court has ruled to allow Trump’s firing of a Democrat FTC commissioner. (NYT $)

5 Here’s the potential impact of Trump’s H-1B crackdown on tech
It’s likely to push a lot of skilled workers elsewhere. (Rest of World)

6 How TikTok’s deal to stay in the US will work
Oracle will manage its algorithm for US users and oversee security operations. (ABC)
+ It’s a giant prize for Trump’s friend Larry Ellison, Oracle’s cofounder. (NYT $)
+ Trump and his allies are now likely to exert a lot of political influence over TikTok. (WP $)

7 Record labels are escalating their lawsuit against an AI music startup
They claim it knowingly pirated songs from YouTube to train its generative AI models. (The Verge $)
+ AI is coming for music, too. (MIT Technology Review)

8 There’s a big fight in the US over who pays for weight loss drugs
Although they’ll save insurers money long-term, they cost a lot upfront. (WP $)
+ We’re learning more about what weight-loss drugs do to the body. (MIT Technology Review)

9 How a lone vigilante ended up blowing up 5G towers
A little bit of knowledge can be a dangerous thing. (Wired $)

10 The moon is rusting 🌕
And it’s our fault. Awkward! (Nature)

Quote of the day

“At the heart of this is people trying to look for simple answers to complex problems.”

—James Cusack, chief executive of an autism charity called Autistica, tells Nature what he thinks is driving Trump and others to incorrectly link the condition with Tylenol use during pregnancy.

One more thing

A mobility walker sinking in an hourglass.

Maybe you will be able to live past 122

How long can humans live? This is a good time to ask the question. The longevity scene is having a moment, and a few key areas of research suggest that we might be able to push human life spans further, and potentially reverse at least some signs of aging.

Researchers can’t even agree on what the exact mechanisms of aging are and which they should be targeting. Debates continue to rage over how long it’s possible for humans to live—and whether there is a limit at all.

But it looks likely that something will be developed in the coming decades that will help us live longer, in better health. Read the full story.

—Jessica Hamzelou

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)

+ This website lets you send a letter to your future self.
+ Here’s what Brian Eno has to say about art.
+ This photographer takes stunning pictures of Greenland.
+ The Hungarian dish Rakott krumpli isn’t going to win any health plaudits, but it looks very comforting all the same.

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Stay ahead with more perspectives on cutting-edge power, infrastructure, energy, bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Network resiliency climbs in importance for businesses

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Australian provider outage leaves emergency callers unable to connect

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9 Linux certifications to boost your career

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Nvidia reportedly acquires Enfabrica CEO and chip technology license

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Carbon markets are incomplete without nuclear

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BP Halts Plans to Build Biofuels Plant in the Netherlands

BP Plc is to forgo building a biofuels plant in the Netherlands as the UK energy giant continues to focus its downstream portfolio, following a strategic pivot earlier this year to return to focusing on its core oil and gas business. The decision, confirmed by a company spokesperson on Monday, marks the second Dutch biofuels plant to not move ahead this year, after Shell Plc shelved its facility under construction in favor of shedding low-carbon businesses to boost profitability. BP hadn’t begun construction of its site in Rotterdam, and previously stopped plans to build biofuels plants at its Kwinana facility in Australia. BP has also paused work at plants in Germany and the US, leaving its Spanish site of Castellon as the possible long-term option for development. Reuters first reported BP scrapping plans to build the Dutch plant. BP has previously said it needs a 15% return on investment on biofuels investments. The London-based company plans to invest $1.5 billion to $2 billion a year through 2027 on energy transition businesses, down from plans of spending more than $5 billion annually on the transition. WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed.

Strategists Expect USA Crude and Product Draws This Week

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Revolution Wind to resume construction after judge grants injunction

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New DOE Initiative Seeks to Hasten US Grid Projects

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Community Watch: Data Center Pushback – Q3 2025

As the pace of data center construction accelerates, so too does the wave of local resistance. While multi-billion-dollar investment announcements often draw national or even global attention, the disputes that arise around individual projects typically play out at the local or regional level — and receive far less visibility. With this recurring feature, Data Center Frontier will highlight community opposition efforts that are shaping, delaying, or in some cases halting, data center development. Tarboro, North Carolina: Energy Storage Solutions Project At first glance, the proposal seemed like a win for Tarboro: a $6.2 billion hyperscale data center on a 50-acre site already zoned for heavy industrial use. But after more than five hours of deliberation, the town council voted 6–1 against granting a special use permit for the project. North Carolina’s unusual quasi-judicial process limited how the council could reach its decision. Because the permit required a courtroom-style proceeding, members were allowed to weigh only factual evidence and expert testimony, not personal opinions or community objections. Developer Danieal Schaffer has since stated he will take the next step of appealing the decision to the Edgecombe Superior Court. Menomonie, Wisconsin: Mystery Data Center Raises Alarm When the town of Menomonie annexed more than 300 acres of farmland, residents quickly grew uneasy about the project’s true purpose. Official information was limited to a vague reference to a “potential data center,” accompanied by a FAQ article on the town’s website. According to Fox Business News, city officials were told only that the project involved a U.S. company and one of the five major tech firms. In a community of just over 16,000 people, opposition has gained significant traction. A Facebook group called Save Our City. Stop the Menomonie Data Center now counts more than 8,000 members. With no clear tenant identified and only

Who wins/loses with the Intel-Nvidia union?

In announcing the deal, Jensen Huang emphasized the client aspect of the deal, saying future Intel chips would have Nvidia GPUs baked into them instead of Intel’s own GPU technology. But there will be impact for the server business as well. There are two things the analysts all agree on: AMD is the big loser in this deal. It had the advantage of CPU and GPU combination that Intel and Nvidia didn’t have individually. It was apparent in supercomputers like Frontier and El Capitan, which are an all-AMD design of CPUs and GPUs working in tandem. Now the two companies are joined at the hip and will have a competitive offering in due time. The second area of agreement is that the future of Jaguar Shores, Intel’s AI accelerator based on its GPU technology and the Gaudi AI accelerator is uncertain. “Nvidia already has solutions here and it doesn’t make sense for Intel to work on a redundant product that needs to be marketed over an established one,” said Nguyen. A significant event coming from this deal is that Intel is adopting the Nvidia proprietary NVlink high-speed interconnect protocols. “This means that Intel has essentially determined its ability to compete head-to-head with Nvidia in the current large scale AI marketplace, despite its best efforts, have mostly failed,” wrote Jack Gold of J. Gold Associates in a research note. Gold notes that Nvidia already uses a few Xeon data center chips to power their largest systems, and the x86 chips provide most of the controls and pre-processing that their large-scale GPU racks require. By accelerating the performance of the Xeon, the GPU benefits as well. That leaves the question mark hanging over Nvidia’s Arm CPUs, which is likely to continue for “niche areas,” Gold wrote. “But with this announcement, it now

Executive Roundtable: The Integration Imperative

Mukul Girotra, Ecolab: The AI infrastructure revolution is forcing a complete rethinking of how thermal, water, and power systems interact. It’s breaking down decades of siloed engineering approaches that are now proving inadequate given the increased rack demands. Traditionally, data centers were designed with separate teams managing power, cooling, and IT equipment. AI scale requires these systems to operate holistically, with real-time coordination between power management, thermal control, and workload orchestration. Here’s how Ecolab is addressing integration: We extend our digitally enabled approach from site to chip, spanning cooling water, direct-to-chip systems, and adiabatic units, driving cleanliness, performance, and optimized water and energy use across all layers of cooling infrastructure. Through collaborations like the one with Digital Realty, our AI-driven water conservation solution is expected to drive up to 15% water savings, significantly reducing demand on local water systems. Leveraging the ECOLAB3D™ platform, we provide proactive analytics and real-time data to optimize water and power use at the asset, site and enterprise levels, creating real operational efficiency and turning cooling management into a strategic advantage. We provide thermal, hydro and chemistry expertise that considers power constraints, IT equipment requirements, and day-to-day facility operational realities. This approach prevents the sub-optimization that can occur when these systems are designed in isolation. Crucially, we view cooling through the lens of the water-energy nexus: choices at the rack or chiller level affect both Power Usage Effectiveness (PUE) and Water Usage Effectiveness (WUE) of a data center, so our recommendations balance energy, water, and lifecycle considerations to deliver reliable performance and operational efficiency. The companies that will succeed in AI infrastructure deployment are those that abandon legacy siloed approaches and embrace integrated thermal management as a core competitive capability.

Executive Roundtable: CapEx vs. OpEx in the AI Era – Balancing the Rush to Build with Long-Term Efficiency

Becky Wacker, Trane: Focusing on post-initial construction CapEx expenditures, finding a balance between capital expenditure (CapEx) and operational expenditure (OpEx) is crucial for efficient capital deployment for data center operators. This balance can be influenced by ownership strategy, cash position, budget planning duration, sustainability goals, and contract commitments and durations with end users. At Trane, we focus on understanding these key characteristics of operations and tailor our ongoing support to best meet the unique business objectives and needs of our customers. We address these challenges through three major approaches: 1. Smart Services Solutions: Our smart services solutions improve system efficiency through AI-driven tools and a large fleet of truck-based service providers. By keeping system components operating at peak efficiency, preventing unanticipated failures, and balancing the critical needs of both digital monitoring and well-trained technicians, we maintain critical systems. This approach reduces OpEx through efficient operation and minimizes unplanned CapEx expenditures. Consequently, this enables improved budgeting and the ability to invest in additional data centers or other business ventures. 2. Sustainable and Flexible System Design: As a global climate innovator, Trane designs our products and collaborates with engineers and owners to integrate these products into highly efficient system solutions. We apply this approach not only in the initial design of the data center but also in planning for future flexibility as demand increases or components require replacement. This proactive strategy reduces ongoing utility bills, minimizes CapEx for upgrades, and helps meet sustainability goals. By focusing on both immediate and long-term efficiency, Trane ensures that data center operators can maintain optimal performance while adhering to environmental standards. 3. Flexible Financial Solutions: Trane’s Energy Services solutions have a 25+ year history of providing Energy Performance Contracting solutions. These can be leveraged to provide upgrades and energy optimization to cooling, power, water, and

OpenAI and Oracle’s $300B Stargate Deal: Building AI’s National-Scale Infrastructure

Oracle’s ‘Astonishing’ Quarter Stuns Wall Street, Targeting Cloud Growth and Global Data Center Expansion Oracle’s FY Q1 2026 earnings report on September 9 — along with its massive cloud backlog — stunned Wall Street with its blow-out Q1 earnings. The market reacted positively to the huge growth in infrastructure revenue and performance obligations (RPO), a measure of future revenue from customer contracts, which indicates significant growth potential and Oracle’s increasing role in AI technology—even as earnings and revenue missed estimates. After the earnings announcement, Oracle stock soared more than 36%, marking its biggest daily gain since December 1992 and adding more than $250 billion in market value to the company. The company’s stock surge came even as the software giant’s earnings and lower-than-expected revenue. Leaders reported company’s RPO jumped about 360% in the quarter to $455 billion, indicating its potential growth and demand for its cloud services and infrastructure. As a result, Oracle CEO Safra Catz projects that its GPU‑heavy Oracle Cloud Infrastructure (OCI) business will grow 77% to $18 billion in its current fiscal year (2026) and soar to $144 billion in 2030. The earnings announcement also made Oracle’s Co-Founder, Chairman and CTO Larry Ellison the richest person in the world briefly, with shares of Oracle surging as much as 43%. By the end of the trading day, his wealth increased nearly $90 billion to $383 billion, just shy of Tesla CEO Elon Musk’s $384 billion fortune. Also on the earnings call, Ellison announced that in October at the Oracle AI World event, the company will introduce the Oracle AI Database OCI for customers to use the Large Language Model (LLM) of their choice—including Google’s Gemini, OpenAI’s ChatGPT, xAI’s Grok, etc.—directly on top of the Oracle Database to easily access and analyze all existing database data. Capital Expenditure Strategy These astonishing numbers are due

Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs). In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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