The Download: combating audio deepfakes, and AI in the classroom

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The Download: combating audio deepfakes, and AI in the classroom

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 text-to-speech programs could one day “unlearn” how to imitate certain people The news: A new technique known as “machine unlearning” could be used to teach AI models to forget specific voices. How it works: Currently, companies tend to deal with this issue by checking whether the prompts or the AI’s responses contain disallowed material. Machine unlearning instead asks whether an AI can be made to forget a piece of information that the company doesn’t want it to know. It works by taking a model and the specific data to be redacted then using them to create a new model—essentially, a version of the original that never learned that piece of data. Why it matters: This could be an important step in stopping the rise of audio deepfakes, where someone’s voice is copied to carry out fraud or scams. Read the full story. —Peter Hall AI’s giants want to take over the classroom School’s out and it’s high summer, but a bunch of teachers are plotting how they’re going to use AI this upcoming school year. God help them. On July 8, OpenAI, Microsoft, and Anthropic announced a $23 million partnership with one of the largest teachers’ unions in the United States to bring more AI into K–12 classrooms. They will train teachers at a New York City headquarters on how to use AI both for teaching and for tasks like planning lessons and writing reports, starting this fall.But these companies could face an uphill battle. There’s a lack of clear evidence that AI can be a net benefit for students, and it’s hard to trust that the AI companies funding this initiative will give honest advice on when not to use AI in the classroom. Read the full story. —James O’Donnell This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Nvidia says the US has lifted its ban on AI chip sales to ChinaJensen Huang has sweet-talked Donald Trump into reversing his three-month old ban. (BBC)+ The company will start selling its H20 chip to China. (WSJ $)+ America may slap tariffs on a raw material used for chips and solar panels. (FT $) 2 China has launched its digital ID systemIt’ll give the country even greater powers to surveil and censor its internet users. (WP $) 3 xAI has secured a contract with the US Department of DefenseJust days after its Grok chatbot had an anti-Semitic meltdown. (The Guardian)+ EU officials are holding talks with X representatives after the outburst. (Bloomberg $) 4 Meta’s data centers are on the verge of triggering a major water shortageLocal residents in Newton County, Georgia are suffering. (NYT $)+ But Zuckerberg wants to build gigawatt-size centers anyway. (Bloomberg $)+ We did the math on AI’s energy footprint. Here’s the story you haven’t heard. (MIT Technology Review) 5 The Trump administration is incinerating tons of emergency foodRather than sending it to people in need. (The Atlantic $) 6 The US is attempting to revive its rare-earth industryThe Pentagon has invested more than $1 billion in American firm MP Materials. (WSJ $)+ It’s all part of a plan to counter China’s critical mineral dominance. (FT $)+ This rare earth metal shows us the future of our planet’s resources. (MIT Technology Review) 7 AI nudifying apps are big businessThey’re making millions of dollars a year, and rely on tech built by US companies. (Wired $)+ The viral AI avatar app Lensa undressed me—without my consent. (MIT Technology Review) 8 Can anything save the web at this point?Traffic is dropping, and AI use is rising. (Economist $)+ How to fix the internet. (MIT Technology Review) 9 Bytedance is working on its own mixed reality gogglesA couple of years after it scaled back its work on an AR and VR headset. (The Information $)+ What’s next for smart glasses. (MIT Technology Review) 10 Minecraft has birthed a generation of entrepreneursThe game encourages players to learn to program. (Insider $) Quote of the day “I suddenly felt pure, unconditional love.” —Faeight, a woman ‘married’ to a chatbot named Gryff, describes her strong feelings for a previous AI partner, the Guardian reports. One more thing End of life decisions are difficult and distressing. Could AI help?End-of-life decisions can be extremely upsetting for surrogates—the people who have to make those calls on behalf of another person. Friends or family members may disagree over what’s best for their loved one, which can lead to distressing situations.David Wendler, a bioethicist at the US National Institutes of Health, and his colleagues have been working on an idea for something that could make things easier: an artificial intelligence-based tool that can help surrogates predict what the patients themselves would want in any given situation.Wendler hopes to start building their tool as soon as they secure funding for it, potentially in the coming months. But rolling it out won’t be simple. Critics wonder how such a tool can ethically be trained on a person’s data, and whether life-or-death decisions should ever be entrusted to AI. Read the full story. —Jessica Hamzelou

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 text-to-speech programs could one day “unlearn” how to imitate certain people

The news: A new technique known as “machine unlearning” could be used to teach AI models to forget specific voices.

How it works: Currently, companies tend to deal with this issue by checking whether the prompts or the AI’s responses contain disallowed material. Machine unlearning instead asks whether an AI can be made to forget a piece of information that the company doesn’t want it to know. It works by taking a model and the specific data to be redacted then using them to create a new model—essentially, a version of the original that never learned that piece of data.

Why it matters: This could be an important step in stopping the rise of audio deepfakes, where someone’s voice is copied to carry out fraud or scams. Read the full story.

—Peter Hall

AI’s giants want to take over the classroom

School’s out and it’s high summer, but a bunch of teachers are plotting how they’re going to use AI this upcoming school year. God help them.

On July 8, OpenAI, Microsoft, and Anthropic announced a $23 million partnership with one of the largest teachers’ unions in the United States to bring more AI into K–12 classrooms. They will train teachers at a New York City headquarters on how to use AI both for teaching and for tasks like planning lessons and writing reports, starting this fall.

But these companies could face an uphill battle. There’s a lack of clear evidence that AI can be a net benefit for students, and it’s hard to trust that the AI companies funding this initiative will give honest advice on when not to use AI in the classroom. Read the full story.

—James O’Donnell

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

The must-reads

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

1 Nvidia says the US has lifted its ban on AI chip sales to China
Jensen Huang has sweet-talked Donald Trump into reversing his three-month old ban. (BBC)
+ The company will start selling its H20 chip to China. (WSJ $)
+ America may slap tariffs on a raw material used for chips and solar panels. (FT $)

2 China has launched its digital ID system
It’ll give the country even greater powers to surveil and censor its internet users. (WP $)

3 xAI has secured a contract with the US Department of Defense
Just days after its Grok chatbot had an anti-Semitic meltdown. (The Guardian)
+ EU officials are holding talks with X representatives after the outburst. (Bloomberg $)

4 Meta’s data centers are on the verge of triggering a major water shortage
Local residents in Newton County, Georgia are suffering. (NYT $)
+ But Zuckerberg wants to build gigawatt-size centers anyway. (Bloomberg $)
+ We did the math on AI’s energy footprint. Here’s the story you haven’t heard. (MIT Technology Review)

5 The Trump administration is incinerating tons of emergency food
Rather than sending it to people in need. (The Atlantic $)

6 The US is attempting to revive its rare-earth industry
The Pentagon has invested more than $1 billion in American firm MP Materials. (WSJ $)
+ It’s all part of a plan to counter China’s critical mineral dominance. (FT $)
+ This rare earth metal shows us the future of our planet’s resources. (MIT Technology Review)

7 AI nudifying apps are big business
They’re making millions of dollars a year, and rely on tech built by US companies. (Wired $)
+ The viral AI avatar app Lensa undressed me—without my consent. (MIT Technology Review)

8 Can anything save the web at this point?
Traffic is dropping, and AI use is rising. (Economist $)
+ How to fix the internet. (MIT Technology Review)

9 Bytedance is working on its own mixed reality goggles
A couple of years after it scaled back its work on an AR and VR headset. (The Information $)
+ What’s next for smart glasses. (MIT Technology Review)

10 Minecraft has birthed a generation of entrepreneurs
The game encourages players to learn to program. (Insider $)

Quote of the day

“I suddenly felt pure, unconditional love.”

—Faeight, a woman ‘married’ to a chatbot named Gryff, describes her strong feelings for a previous AI partner, the Guardian reports.

One more thing

End of life decisions are difficult and distressing. Could AI help?

End-of-life decisions can be extremely upsetting for surrogates—the people who have to make those calls on behalf of another person. Friends or family members may disagree over what’s best for their loved one, which can lead to distressing situations.

David Wendler, a bioethicist at the US National Institutes of Health, and his colleagues have been working on an idea for something that could make things easier: an artificial intelligence-based tool that can help surrogates predict what the patients themselves would want in any given situation.

Wendler hopes to start building their tool as soon as they secure funding for it, potentially in the coming months. But rolling it out won’t be simple. Critics wonder how such a tool can ethically be trained on a person’s data, and whether life-or-death decisions should ever be entrusted to AI. Read the full story.

—Jessica Hamzelou

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Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety

This is a linkpost for https://bit.ly/cot-monitorability-fragile

Broadcom scales up Ethernet with Tomahawk Ultra for low latency HPC and AI

Broadcom Support for minimum packet size allows streaming of those packets at full bandwidth. That capability is essential for efficient communication in scientific and computational workloads. It is particularly important for scale-up networks where GPU-to-switch-to-GPU communication happens in a single hop. Lossless Ethernet gets an ‘Ultra’ boost Another specific area

F5 streamlines application delivery, security with new AI assistant and code generation service

The AI Assistant can also reduce documentation searches and help accelerate the handling of routine tasks, such as developing traffic configurations and deploying APIs, Ford said. In addition, it can help customers optimize traffic management and app delivery flows by offering real-time AI contextual analytics that can be applied enterprise-wide,

Nvidia to restart H20 exports to China, unveils new export-compliant GPU

China re-entry impact Nvidia’s announcements mark a bid to re-enter the world’s second-largest AI market under tightened US export controls. But this return may not mean business as usual. “Despite Nvidia’s market re-entry, Chinese companies will likely continue diversifying suppliers to strengthen supply chain resilience,” said Prabhu Ram, VP of

China Refining Output Rebounds to Strongest Since 2023

China refined the most crude oil in nearly two years in June, as plants returned from seasonal maintenance to seize on better margins for fuels like diesel. Refining output rose to more than 15.2 million barrels a day, the strongest pace since September 2023, according to Bloomberg calculations based on figures released by the statistics bureau on Tuesday. Compared to June last year, volumes surged by 8.5 percent, reversing the declines seen in April and May. Improved margins and fewer idled units supported robust refining activity, with further strength expected this month as new plants come online, said Amy Sun, an analyst with GL Consulting, a think tank affiliated with Mysteel OilChem. Diesel cracks, a measure of profitability, at independent refiners rose to nearly $18 a barrel at one point late last month, the highest since 2023, according to data tracked by consultant JLC International. Run rates at state-owned refineries soared to nearly 84 percent of capacity at end-June, the highest in more than three months, JLC’s data showed. The refinery output is in line with the rise in crude purchases reported for June, which hit their highest level since August 2023 on a daily basis, according to Bloomberg calculations. Imports are expected to accelerate as the country adds as much as 140 million barrels of oil to replenish its Strategic Petroleum Reserves from later this year, Energy Aspects said in a note. What do you think? We’d love to hear from you, join the conversation on the Rigzone Energy Network. The Rigzone Energy Network is a new social experience created for you and all energy professionals to Speak Up about our industry, share knowledge, connect with peers and industry insiders and engage in a professional community that will empower your career in energy.

Trump’s Russia Threat Puts Focus on Oil Buyers India and China

President Donald Trump’s threat to impose financial penalties on Russia has put the spotlight on the two biggest buyers of Moscow’s crude — India and China — but markets remain skeptical of disruption, for now. India became a major importer of Russian oil since the invasion of Ukraine in early 2022. More than a third of overall purchases have been from the OPEC+ producer this year, compared with less than 1% prior to the war, according to data from Kpler. China’s imports have also climbed over the same period. Still, the initial reaction from the market to Trump’s remarks was nonchalance. Global benchmark Brent fell almost 2% to close below $70 a barrel on Monday, suggesting little concern around the potential impact to crude flows. Trump said penalties would come in the form of “secondary tariffs,” without providing details, and would be implemented in 50 days if Russia doesn’t end hostilities with Ukraine. Matt Whitaker, the US ambassador to NATO, said the action effectively represents sanctions on nations buying Russian oil. Whitaker specifically cited India and China. Russian flows to India reached 2.1 million barrels a day in June, the biggest monthly intake in nearly a year, and close to the record set in May 2023, data from Kpler show. China’s purchases haven’t accelerated at the same pace, but have been consistently above 1 million barrels a day since the war. “If push really comes to shove, and India cannot buy any crude oil from the Russian system, then India has optionality with the other OPEC members,” said Mukesh Sahdev, head of commodity markets at Rystad Energy A/S. But “it will be at a higher cost,” he added. Barrels from the Middle East and Africa could help plug the gap of lost Russian supply, but the crude would be more expensive. Imports from Saudi Arabia

Google to buy up to 3 GW of hydro power from Brookfield

Google will buy up to 3 GW of hydroelectric power from Brookfield Renewable, with an initial focus on the PJM Interconnection and Midcontinent Independent System Operator footprints, the companies said Tuesday. The “hydro framework agreement” will help Google run its data centers and other operations on carbon-free power all the time, according to the companies. The first 20-year contracts under the agreement are for the output from Brookfield’s Holtwood and Safe Harbor hydro facilities in Pennsylvania, which total about 670 MW, according to the companies. The contracts will generate more than $3 billion in revenue, Brookfield and Google said. Brookfield is relicensing the Holtwood and Safe Harbor hydro facilities at the Federal Energy Regulatory Commission. Brookfield said the agreement is part of its strategy to deliver dispatchable clean power to the technology sector. Brookfield’s top four corporate power purchasers are Amazon, Meta, Microsoft and Google. On May 1, Microsoft said it would buy more than 10.5 GW of clean energy projects from Brookfield Asset Management and its Brookfield Renewable affiliate between 2026 and 2030. Brookfield Renewable owns about 21 GW of hydro, wind, solar and storage assets worldwide, and its project development pipeline totals about 69 GW, according to the company. With PJM facing tight supply-demand conditions, partly driven by data center development, Joseph Bowring, the grid operator’s market monitor, has urged FERC to require that data centers use new generating resources to meet their needs instead of relying on existing resources.

Solar continues to dominate new generation … for now

Dive Brief: U.S. utilities and power plant developers added about 12 GW of new generation resources between January and April of this year, compared to 11 GW over the same period last year, according to the latest monthly infrastructure report from the Federal Energy Regulatory Commission. The vast majority of that generation — some 9.5 GW — was solar, trailed by wind with 2 GW and 500 MW of gas. “High probability” additions by April 2028 include 90 GW of solar, 23 GW of wind and 19.5 GW of gas, according to the report. It also projected the likely addition of 631 MW of hydropower and 92 MW of geothermal steam. Dive Insight: The report showed the continued dominance of solar in new generation capacity amid robust demand growth projections. That could change, however, as the Republican tax cuts and spending bill take effect. The law signed by President Donald Trump on July 4 dramatically cut incentives for wind and solar, phasing out tax credits and imposing restrictions on the types of projects that qualify. Trump followed that with an executive order instructing the Treasury Department to take a narrow approach in its interpretation of the law regarding wind and solar. The country added 62.5 miles of transmission lines from January to April, 2025, including, most recently, Entergy Louisiana’s 1.8-mile, 500-kV Wise-Bayou Labutte transmission project. The report did not include a breakdown of transmission built over the same period last year. In total, grid operators added nearly 1,700 miles of transmission in 2024, about a third of it high voltage 500 kV. FERC’s report follows a separate analysis from the U.S. Energy Information Administration that estimated solar generation would rise by a third this summer. “By summer 2026, we forecast solar generation will grow by another 19% to 147 BkWh, which means

Lydian Energy lands $233M in financing for 550 MW/1.1 GWh of Texas storage

Lydian Energy has secured $233 million in financing for three, two-hour battery storage projects in Texas totaling 550 MW. ING served as the lender for the Pintail and Crane projects in San Patricio and Crane Counties, Texas, respectively, Lydian said July 9. The 200 MW/400 MWh systems represent a combined investment of about $139 million, according to Lydian, a Washington, D.C.-based solar and battery storage developer backed by Excelsior Energy Capital. KeyBank provided a $94 million financing package for Headcamp, a 150 MW/300 MWh project in Pecos County, Lydian said. KeyBanc Capital Markets also structured the financing package for Headcamp. The facilities in the Electric Reliability Council of Texas footprint are under construction and Lydian expects to bring them online in the fourth quarter. The projects were developed under Excelsior Energy Capital’s Fund II, which closed at more than $1 billion in April. The tax credit bridge financings from ING and KeyBank are being complemented by co-investment capital from Excelsior’s Fund II limited partners, Lydian said. The company said it is pursuing additional financing for other projects that Lydian expects to start building later this year. Lydian’s development portfolio includes 20 solar and storage projects totaling 4.7 GW, according to the company. “These financings represent more than capital – they reflect the strong demand for reliable energy infrastructure in high-growth U.S. markets,” Anne Marie Denman, co-founding partner at Excelsior Energy Capital, said in the press release. The financial commitments by ING and KeyBank underscore growing institutional confidence in battery storage as a strategic asset class, Lydian said. Lydian’s three Texas projects are part of a surge in energy storage development in the ERCOT market. ERCOT expects it will have 12,863 MW of storage on its system in September, according to the grid operator’s most recent Monthly Outlook for Resource Adequacy

The regulator’s dilemma: balancing grid modernization with rising power bills

The regulator’s dilemma: balancing grid modernization with rising power bills | Utility Dive Skip to main content An article from Deep Dive Load growth and aging infrastructure require investment, but customer electricity prices are up 4.5% nationally, almost twice the 2.4% national inflation rate. Published July 15, 2025 High voltage power lines run along the electrical power grid on May 16, 2024, in Pembroke Pines, Florida. Utilities need to invest in grid modernization to meet rising electricity demand. At the same time, customer electricity prices are up 4.5% nationally — almost twice the 2.4% national inflation rate, according to the June Bureau of Labor Statistics Consumer Price Index. Joe Raedle via Getty Images Utility regulators across the U.S. face a paradox that demands resolution, panelists at the American Clean Power Association’s CleanPower 2025 conference said. There were 726 policy actions on grid modernization in the U.S. in the first quarter of this year, many requiring significant new investments, per the Clean Energy Technology Center’s most recent Grid Modernization policy update. But customer electricity prices are up 4.5% nationally, almost twice the 2.4% national inflation rate, according to the June Bureau of Labor Statistics Consumer Price Index. “Utility regulation has always been a complex balancing act and the lesson learned is the need to ensure investment value and utility accountability,” said Regulatory Assistance Project, or RAP, Principal, Research and Strategy, Mark LeBel. Regulators must choose “the most cost-effective investments from a realistic set of alternatives,” he added. Almost 80% of $186.4 billion spent by U.S. investor-owned utilities in 2024 went to infrastructure, according to September 2024 data from the Edison Electric Institute. And more spending must follow: April’s 120 GW five-year load growth forecast was over five times higher than 2023’s five-year forecast of 23 GW, according to the recent GridStrategies update. “Regulators

Intel CEO: We are not in the top 10 semiconductor companies

The Q&A session came on the heels of layoffs across the company. Tan was hired in March, and almost immediately he began to promise to divest and reduce non-core assets. Gelsinger had also begun divesting the company of losers, but they were nibbles around the edge. Tan is promising to take an axe to the place. In addition to discontinuing products, the company has outsourced marketing and media relations — for the first time in more than 25 years of covering this company, I have no internal contacts at Intel. Many more workers are going to lose their jobs in coming weeks. So far about 500 have been cut in Oregon and California but many more is expected — as much as 20% of the overall company staff may go, and Intel has over 100,000 employees, according to published reports. Tan believes the company is bloated and too bogged down with layers of management to be reactive and responsive in the same way that AMD and Nvidia are. “The whole process of that (deciding) is so slow and eventually nobody makes a decision,” he is quoted as saying. Something he has decided on is AI, and he seems to have decided to give up. “On training, I think it is too late for us,” Tan said, adding that Nvidia’s position in that market is simply “too strong.” So there goes what sales Gaudi3 could muster. Instead, Tan said Intel will focus on “edge” artificial intelligence, where AI capabilities Are brought to PCs and other remote devices rather than big AI processors in data centers like Nvidia and AMD are doing. “That’s an area that I think is emerging, coming up very big and we want to make sure that we capture,” Tan said.

AMD: Latest news and insights

Survey: AMD continues to take server share from Intel May 20, 2025: AMD continues to take market share from Intel, growing at a faster rate and closing the gap between the two companies to the narrowest it has ever been. AMD, Nvidia partner with Saudi startup to build multi-billion dollar AI service centers May 15, 2025: As part of the avalanche of business deals that came from President Trump’s Middle East tour, both AMD and Nvidia have struck multi-billion dollar deals with an emerging Saudi AI firm. AMD targets hosting providers with affordable EPYC 4005 processors May 14, 2025: AMD launched its latest set of data center processors, targeting hosted IT service providers. The EPYC 4005 series is purpose-built with enterprise-class features and support for modern infrastructure technologies at an affordable price, the company said. Jio teams with AMD, Cisco and Nokia to build AI-enabled telecom platform March 18, 2025: Jio has teamed up with AMD, Cisco and Nokia to build an AI-enabled platform for telecom networks. The goal is to make networks smarter, more secure and more efficient to help service providers cut costs and develop new services. AMD patches microcode security holes after accidental early disclosure February 3, 2025: AMD issued two patches for severe microcode security flaws, defects that AMD said “could lead to the loss of Secure Encrypted Virtualization (SEV) protection.” The bugs were inadvertently revealed by a partner.

Nvidia hits $4T market cap as AI, high-performance semiconductors hit stride

“The company added $1 trillion in market value in less than a year, a pace that surpasses Apple and Microsoft’s previous trajectories. This rapid ascent reflects how indispensable AI chipmakers have become in today’s digital economy,” Kiran Raj, practice head, Strategic Intelligence (Disruptor) at GlobalData, said in a statement. According to GlobalData’s Innovation Radar report, “AI Chips – Trends, Market Dynamics and Innovations,” the global AI chip market is projected to reach $154 billion by 2030, growing at a compound annual growth rate (CAGR) of 20%. Nvidia has much of that market, but it also has a giant bullseye on its back with many competitors gunning for its crown. “With its AI chips powering everything from data centers and cloud computing to autonomous vehicles and robotics, Nvidia is uniquely positioned. However, competitive pressure is mounting. Players like AMD, Intel, Google, and Huawei are doubling down on custom silicon, while regulatory headwinds and export restrictions are reshaping the competitive dynamics,” he said.

Enterprises will strengthen networks to take on AI, survey finds

Private data centers: 29.5% Traditional public cloud: 35.4% GPU as a service specialists: 18.5% Edge compute: 16.6% “There is little variation from training to inference, but the general pattern is workloads are concentrated a bit in traditional public cloud and then hyperscalers have significant presence in private data centers,” McGillicuddy explained. “There is emerging interest around deploying AI workloads at the corporate edge and edge compute environments as well, which allows them to have workloads residing closer to edge data in the enterprise, which helps them combat latency issues and things like that. The big key takeaway here is that the typical enterprise is going to need to make sure that its data center network is ready to support AI workloads.” AI networking challenges The popularity of AI doesn’t remove some of the business and technical concerns that the technology brings to enterprise leaders. According to the EMA survey, business concerns include security risk (39%), cost/budget (33%), rapid technology evolution (33%), and networking team skills gaps (29%). Respondents also indicated several concerns around both data center networking issues and WAN issues. Concerns related to data center networking included: Integration between AI network and legacy networks: 43% Bandwidth demand: 41% Coordinating traffic flows of synchronized AI workloads: 38% Latency: 36% WAN issues respondents shared included: Complexity of workload distribution across sites: 42% Latency between workloads and data at WAN edge: 39% Complexity of traffic prioritization: 36% Network congestion: 33% “It’s really not cheap to make your network AI ready,” McGillicuddy stated. “You might need to invest in a lot of new switches and you might need to upgrade your WAN or switch vendors. You might need to make some changes to your underlay around what kind of connectivity your AI traffic is going over.” Enterprise leaders intend to invest in infrastructure

CoreWeave acquires Core Scientific for $9B to power AI infrastructure push

Such a shift, analysts say, could offer short-term benefits for enterprises, particularly in cost and access, but also introduces new operational risks. “This acquisition may potentially lower enterprise pricing through lease cost elimination and annual savings, while improving GPU access via expanded power capacity, enabling faster deployment of Nvidia chipsets and systems,” said Charlie Dai, VP and principal analyst at Forrester. “However, service reliability risks persist during this crypto-to-AI retrofitting.” This also indicates that struggling vendors such as Core Scientific and similar have a way to cash out, according to Yugal Joshi, partner at Everest Group. “However, it does not materially impact the availability of Nvidia GPUs and similar for enterprises,” Joshi added. “Consolidation does impact the pricing power of vendors.” Concerns for enterprises Rising demand for AI-ready infrastructure can raise concerns among enterprises, particularly over access to power-rich data centers and future capacity constraints. “The biggest concern that CIOs should have with this acquisition is that mature data center infrastructure with dedicated power is an acquisition target,” said Hyoun Park, CEO and chief analyst at Amalgam Insights. “This may turn out to create challenges for CIOs currently collocating data workloads or seeking to keep more of their data loads on private data centers rather than in the cloud.”

CoreWeave achieves a first with Nvidia GB300 NVL72 deployment

The deployment, Kimball said, “brings Dell quality to the commodity space. Wins like this really validate what Dell has been doing in reshaping its portfolio to accommodate the needs of the market — both in the cloud and the enterprise.” Although concerns were voiced last year that Nvidia’s next-generation Blackwell data center processors had significant overheating problems when they were installed in high-capacity server racks, he said that a repeat performance is unlikely. Nvidia, said Kimball “has been very disciplined in its approach with its GPUs and not shipping silicon until it is ready. And Dell almost doubles down on this maniacal quality focus. I don’t mean to sound like I have blind faith, but I’ve watched both companies over the last several years be intentional in delivering product in volume. Especially as the competitive market starts to shape up more strongly, I expect there is an extremely high degree of confidence in quality.” CoreWeave ‘has one purpose’ He said, “like Lambda Labs, Crusoe and others, [CoreWeave] seemingly has one purpose (for now): deliver GPU capacity to the market. While I expect these cloud providers will expand in services, I think for now the type of customer employing services is on the early adopter side of AI. From an enterprise perspective, I have to think that organizations well into their AI journey are the consumers of CoreWeave.” “CoreWeave is also being utilized by a lot of the model providers and tech vendors playing in the AI space,” Kimball pointed out. “For instance, it’s public knowledge that Microsoft, OpenAI, Meta, IBM and others use CoreWeave GPUs for model training and more. It makes sense. These are the customers that truly benefit from the performance lift that we see from generation to generation.”

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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