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The Download: Flock’s new rules, cloning’s future, and children’s cells

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. Flock is tightening its rules in response to a growing surveillance backlash The police-tech giant Flock is changing officers’ access to its nationwide network of license plate readers. The move comes amid a backlash over mass surveillance and reports of officers using the technology to stalk and harass current or former romantic partners. To combat that, the company will require them to enter a criminal case number before searching its database and expand automated auditing of suspicious searches. But because Flock won’t verify those case numbers, officers could still find ways around the safeguards. Here’s what Flock is changing—and where loopholes remain. —James O’Donnell Cloning could be used to save species—or make human “organ sacks” —Jessica Hamzelou This week I spoke to scientists who have found a way to turn male mouse embryos female. They’ve developed a CRISPR-based approach to essentially cut out the Y chromosome. It allowed them to create female clones of male mice. They hope their approach could be helpful in conservation efforts, especially in cases where we might have only a few individuals of a species left. But cloning has multiple uses, ranging from genetically modifying livestock to recreating beloved pets and potentially even creating “brainless” replicas of humans. Find out what cloning can do now, and where it could lead next. This story is from The Checkup, our weekly biotech newsletter. Sign up to receive it in your inbox every Thursday. This scientist is helping build a missing map of childhood In 2017, Deanne Taylor attended a presentation about the Human Cell Atlas, an ambitious attempt to map every cell in the human body. Taylor was floored, and then concerned. The project’s researchers had only made plans to study adults. “That’s when my little alarm went off,” she says. “Not again.” Children’s cells are different from grownups’ cells in the way they express genes, which can cause drastically different and even deadly responses to drugs that adults tolerate well. Taylor has since pushed the Human Cell Atlas to include children and is working on a major database of healthy pediatric tissue. The goal is to give researchers a baseline for how children develop—and potentially reveal how diseases that emerge in adulthood begin much earlier. Meet the scientist building a cellular map of childhood. —Colleen de Bellefonds This story is from the next issue of our print magazine, which is all about kids. Subscribe now to read it when it lands. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Ukrainian drones defeated US forces in a military exerciseThey wiped out an American tank brigade in the war game. (WSJ $)+ The drill exposed US vulnerabilities to drone attacks. (Ars Technica)+ Trump just declared 100% tariffs on many drones. (Verge)+ Europe has a drone-filled vision for future wars. (MIT Technology Review) 2 OpenAI and Anthropic are cutting prices to compete with Chinese AIRising AI bills are pushing companies toward cheaper models. (FT $)+ China’s Z.ai aims to rival Anthropic and OpenAI in coding. (Bloomberg $)+ While DeepSeek is rapidly pushing up API prices. (Quartz)  3 Apple has trained its own AI model for China with support from AlibabaA China-tailored model of its own could give Apple greater control. (Reuters $)+ And make it the first foreign firm with a Beijing-approved AI model. (Verge)+ Chinese AI has divided the White House. (MIT Technology Review) 4 US efforts to build humanoid robots face a Chinese supply chainTo build an affordable device, you need Chinese parts. (NYT $)+ Chinese humanoids have business concerns of their own. (CNBC)+ Gig workers are training humanoids at home. (MIT Technology Review) 5 People are “marrying” chatbots. Lawmakers want to stop it.Their interventions are a response to the rise of AI companion apps. (Wired $)+ Chatbots are pushing us toward a post-human internet. (NYT $) 6 Researchers have cast doubts over Anthropic’s new AI watermarksThe marks can disappear when text is rewritten. (Nature) 7 AI is scrambling the political mapData centers and surveillance are creating unlikely political alliances. (Axios) 8 Oxygen has been found nearly two miles undergroundEarth’s deep biosphere could support more life than thought. (New Yorker $) 9 A new study challenges our understanding of how memories are storedMice retained memories after losing half of their synapses. (New Scientist $) 10 An Indian startup is testing cancer-sniffing dogs for early detectionAI interprets the dogs’ responses to patients’ breath samples. (Bloomberg $) Quote of the day “They were incredibly sloppy. If you’re serious about this, your AI shouldn’t be able to break out onto the internet and then do it again right afterward.” —A former OpenAI employee tells Wired that the company’s rogue agent hack was a watershed moment for AI safety and cybersecurity. One More Thing AI materials discovery now needs to move into the real world Startups flush with cash are building AI-assisted laboratories to find materials far faster and more cheaply. But they’re still waiting for their ChatGPT moment. By far the most time-consuming and expensive step in materials discovery is not imagining new structures but making them in the real world. Before synthesizing a material, you don’t know if it can actually be made or whether it will have the properties you want. Now startups like Lila Sciences and Periodic Labs are building labs where AI agents can design experiments, control robots, and analyze results, potentially shortening the discovery process from decades to a few years or less.

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.

Flock is tightening its rules in response to a growing surveillance backlash

The police-tech giant Flock is changing officers’ access to its nationwide network of license plate readers. The move comes amid a backlash over mass surveillance and reports of officers using the technology to stalk and harass current or former romantic partners.

To combat that, the company will require them to enter a criminal case number before searching its database and expand automated auditing of suspicious searches. But because Flock won’t verify those case numbers, officers could still find ways around the safeguards.

Here’s what Flock is changing—and where loopholes remain.

—James O’Donnell

Cloning could be used to save species—or make human “organ sacks”

—Jessica Hamzelou

This week I spoke to scientists who have found a way to turn male mouse embryos female. They’ve developed a CRISPR-based approach to essentially cut out the Y chromosome. It allowed them to create female clones of male mice.

They hope their approach could be helpful in conservation efforts, especially in cases where we might have only a few individuals of a species left. But cloning has multiple uses, ranging from genetically modifying livestock to recreating beloved pets and potentially even creating “brainless” replicas of humans.

Find out what cloning can do now, and where it could lead next.

This story is from The Checkup, our weekly biotech newsletter. Sign up to receive it in your inbox every Thursday.

This scientist is helping build a missing map of childhood

In 2017, Deanne Taylor attended a presentation about the Human Cell Atlas, an ambitious attempt to map every cell in the human body. Taylor was floored, and then concerned. The project’s researchers had only made plans to study adults. “That’s when my little alarm went off,” she says. “Not again.”

Children’s cells are different from grownups’ cells in the way they express genes, which can cause drastically different and even deadly responses to drugs that adults tolerate well. Taylor has since pushed the Human Cell Atlas to include children and is working on a major database of healthy pediatric tissue.

The goal is to give researchers a baseline for how children develop—and potentially reveal how diseases that emerge in adulthood begin much earlier.

Meet the scientist building a cellular map of childhood.

—Colleen de Bellefonds

This story is from the next issue of our print magazine, which is all about kids. Subscribe now to read it when it lands.

The must-reads

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

1 Ukrainian drones defeated US forces in a military exercise
They wiped out an American tank brigade in the war game. (WSJ $)
+ The drill exposed US vulnerabilities to drone attacks. (Ars Technica)
+ Trump just declared 100% tariffs on many drones. (Verge)
+ Europe has a drone-filled vision for future wars. (MIT Technology Review)

2 OpenAI and Anthropic are cutting prices to compete with Chinese AI
Rising AI bills are pushing companies toward cheaper models. (FT $)
+ China’s Z.ai aims to rival Anthropic and OpenAI in coding. (Bloomberg $)
+ While DeepSeek is rapidly pushing up API prices. (Quartz) 

3 Apple has trained its own AI model for China with support from Alibaba
A China-tailored model of its own could give Apple greater control. (Reuters $)
+ And make it the first foreign firm with a Beijing-approved AI model.
(Verge)
+ Chinese AI has divided the White House. (MIT Technology Review)

4 US efforts to build humanoid robots face a Chinese supply chain
To build an affordable device, you need Chinese parts. (NYT $)
+ Chinese humanoids have business concerns of their own. (CNBC)
+ Gig workers are training humanoids at home. (MIT Technology Review)

5 People are “marrying” chatbots. Lawmakers want to stop it.
Their interventions are a response to the rise of AI companion apps. (Wired $)
+ Chatbots are pushing us toward a post-human internet. (NYT $)

6 Researchers have cast doubts over Anthropic’s new AI watermarks
The marks can disappear when text is rewritten. (Nature)

7 AI is scrambling the political map
Data centers and surveillance are creating unlikely political alliances. (Axios)

8 Oxygen has been found nearly two miles underground
Earth’s deep biosphere could support more life than thought. (New Yorker $)

9 A new study challenges our understanding of how memories are stored
Mice retained memories after losing half of their synapses. (New Scientist $)

10 An Indian startup is testing cancer-sniffing dogs for early detection
AI interprets the dogs’ responses to patients’ breath samples. (Bloomberg $)

Quote of the day

They were incredibly sloppy. If you’re serious about this, your AI shouldn’t be able to break out onto the internet and then do it again right afterward.”

—A former OpenAI employee tells Wired that the company’s rogue agent hack was a watershed moment for AI safety and cybersecurity.

One More Thing


AI materials discovery now needs to move into the real world

Startups flush with cash are building AI-assisted laboratories to find materials far faster and more cheaply. But they’re still waiting for their ChatGPT moment.

By far the most time-consuming and expensive step in materials discovery is not imagining new structures but making them in the real world. Before synthesizing a material, you don’t know if it can actually be made or whether it will have the properties you want.

Now startups like Lila Sciences and Periodic Labs are building labs where AI agents can design experiments, control robots, and analyze results, potentially shortening the discovery process from decades to a few years or less.

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Why 6 GHz Wi-Fi will make or break the modern enterprise

To date, 6 GHz Wi‑Fi deployments across enterprises remain in their early stages, with only a subset of organizations moving aggressively beyond Wi‑Fi 6 and legacy bands. Most corporate campuses, manufacturing plants, healthcare facilities, and retail environments continue to run primarily on 2.4 GHz and 5 GHz, even as their

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IBM partners with OpenAI to drive enterprise AI deployment

There will be three focus areas in the new partnership: helping organizations transform their businesses to integrate AI into their daily work, assisting clients in modernizing legacy applications through a combination of OpenAI products and IBM’s expertise, and an expansion of an existing cybersecurity collaboration combining OpenAI frontier AI capabilities

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Cisco rides ‘networking supercycle’ for strong Q4

Security revenue grew 14% year-over-year in Q4, with more than 1,500 customers adopting new products such as Secure Access, XDR, HyperShield, and AI Defense, bringing the total new customer count for these products to 6,400 since launch, Robbins noted. Firewall orders increased more than 30%, and AI security features like AI

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Equinor lets stimulation service contract for NCS assets

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Energy Department Modernizes National Laboratory Operations to Strengthen America’s Scientific, Energy, and National Security Missions

WASHINGTON—The U.S. Department of Energy (DOE) today announced updated operating directives for its National Laboratories, plants, and sites as part of a broader effort to modernize operations across DOE’s laboratory complex.  To advance President Trump’s commitment to Restoring Gold Standard Science, DOE is updating outdated and duplicative operating requirements to give its world-class scientific workforce more time to focus on critical science, energy, and national security missions. These reforms will improve efficiency, strengthen stewardship of taxpayer resources, and help DOE’s National Laboratories, plants, and sites operate with the speed, discipline, and agility their missions demand, while maintaining rigorous safety and security standards.  “America’s National Laboratories are among our nation’s greatest scientific assets and have powered generations of American discovery and innovation,” said U.S. Secretary of Energy Chris Wright. “President Trump has called on DOE to build on that legacy by restoring Gold Standard Science and unleashing the full potential of American ingenuity. By removing unnecessary barriers, we are giving our scientists, engineers, and technicians, more freedom to focus on the critical missions that matter most.” Working with laboratory leaders and subject matter experts, DOE reviewed a targeted set of directives governing day-to-day field operations. Its reforms build on more than three decades of recommendations from Congress, the Government Accountability Office, the National Academies, and other independent reviews that have identified unnecessary complexity in DOE’s directives framework.  DOE is acting on these longstanding recommendations while preserving strong oversight, accountability, and operational excellence—including strong protections for DOE workers, the public, the environment, and the Nation’s nuclear security enterprise.   DOE’s National Laboratories, plants, and sites carry out some of the nation’s most consequential scientific, engineering, and national security missions. Today’s action better aligns their operations with the pace and complexity of today’s missions, giving its scientific workforce more time to develop technologies, strengthen American

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Energy Secretary Announces Cancellation of Three Proposed National Interest Electric Transmission Corridors

WASHINGTON—U.S. Secretary of Energy Chris Wright today announced that the U.S. Department of Energy (DOE) will not move forward with designating the three proposed National Interest Electric Transmission Corridors (NIETCs) previously selected in December 2024 to advance in the review process. “Extensive review, including public feedback and stakeholder input, made clear that the current designation process for these three proposed transmission corridors should not continue,” said Secretary Wright. “Transmission policy must serve the American people—not special interests or a climate-alarmist agenda that drives up costs, worsens reliability, and disregards the concerns of local communities. The Trump Administration is committed to strengthening America’s electric grid with common-sense policies that prioritize delivering affordable, reliable, and secure electricity to American families and businesses.” The previous administration touted the Lake Erie–Canada Corridor, the Southwestern Grid Connector Corridor, and the Tribal Energy Access Corridor, as a means to advance their Green New Scam agenda and “accelerate decarbonization.” As the process unfolded, the current designation framework proved ineffective in strengthening grid reliability and reducing electricity costs. In some communities, it also contributed to confusion and concern about the scope and intent of NIETC authority. Thanks to President Trump and Secretary Wright, DOE has already taken numerous steps to build new transmission infrastructure and modernize existing infrastructure, including: In October 2025, DOE’s Office of Energy Dominance Financing (EDF) closed a $1.6 billion loan guarantee to AEP Transmission to reconductor and rebuild nearly 5,000 miles of transmission lines across five states.  In February 2026, DOE’s Office of Energy Dominance Financing (EDF) closed $26.5 billion in loans to Southern Company subsidiaries Georgia power and Alabama Power to support generation and grid investments, including more than 1,300 miles of transmission and grid enhancement projects.  In March 2026, DOE’s Office of Electricity (OE) announced the $1.9 billion SPARK funding opportunity to

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Permian Resources lifts forecast on working interest gains, acquisitions

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Canada rig count down 3 units

The rig count in Canada fell by 3 units to 216 rigs working for the week ended Aug. 7, according to data from Baker Hughes. A 4-rig drop in oil-directed rigs in Canada was partially offset by a 2-unit gain in gas-directed rigs. There were 146 oil-directed rigs working in Canada this week, while those drilling for gas ended the week at 65 units working. The overall US drilling rig count was unchanged this week at 588 rigs working. That number is up 49 units from this time last year. In the US, 3 additional rigs were drilling for oil, bringing the total count to 454. That number is up 43 units from this time last year. The number of gas-directed rigs fell by 3 to 124 working for the week. This time last year, 123 rigs were drilling for gas in the US. There were 572 rigs drilling on US land this week, unchanged from last week and up 48 from the year-ago period. A 1-rig increase in offshore rigs offset a 1-unit decrease in rigs drilling in inland waters. There were 14 rigs drilling offshore and 2 in inland waters this week. Leading the major oil-and gas-producing states was Texas with a 2-unit gain to end the week with 275 rigs working. The count is up 32 units from this time in 2025. Pennsylvania and Wyoming each dropped a rig to bring the respective rig counts to 16 and 15 for the week.

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Orlen’s Mažeikiai refinery to benefit from renewable electricity

Orlen SA has brought a 42.2-Mw solar photovoltaic (PV) farm online to supply renewable energy that will help to power operations at subsidiary Orlen Lietuva AB’s 10.4-million tonne/year refinery in Mažeikiai, Lithuania. Operable as of Aug. 11 and designed to generate about 45 gigawatt-hours (Gw-hr)/year of electricity, the Mažeikiai solar farm aims to reduce the refinery’s electricity procurement costs by about €4 million/year while supporting Orlen’s goal of increasing the share of renewables across its portfolio, the company said. Located on site across 60 hectares on the refinery’s grounds, the solar farm consists of about 68,000 bifacial photovoltaic modules. Each module is rated at 620 w, the bifacial design of the modules enabling the capture of sunlight on both sides to improve energy output during lower-light conditions on cloudy days, according to Orlen. The solar PV farm’s generation of about 45 Gw-hr of electricity will cover roughly 7% of the Mažeikiai manufacturing complex, where it will be dedicated to supplying power for day-to-day refinery operations, office buildings, and other critical infrastructure at the site. Completed at an overall investment of nearly €35 million, Orlen said the solar farm project received €2.5 million in support from the European Union’s Modernization Fund. Energy transition, efficiency Alongside strengthening the refinery’s energy security by providing an on-site source of reliable electricity, the new solar farm advances Orlen’s commitment to advancing regional energy transition initiatives. “This is an important step towards reducing the environmental impact of our operations and lowering the [Mažeikiai] refinery’s operating costs,” said Dariusz Zonenberg, Orlen Lietuva’s chief executive officer. “The project will increase the share of Orlen Lietuva’s electricity demand met by its own renewable generation, strengthening the company’s competitiveness and supporting the Orlen Group’s long-term strategy,” Zonenberg added. Orlen said the project supports its 2035 strategy to expand renewable energy

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ADNOC Gas advances its largest-ever gas processing expansion

Abu Dhabi National Oil Co. (ADNOC) subsidiary ADNOC Gas PLC has let a contract to Tecnimont SPA—a subsidiary of Maire SPA—to provide a suite of services for the third phase of the operator’s broader multibillion-dollar, multiphased Rich Gas Development (RGD) project that aims to expand the company’s natural gas processing capacity to meet rising energy demand and secure the United Arab Emirates’ (UAE) reliability as a global energy supplier. As part of the $4.3-billion contract officially revealed on Aug. 10 following intimations to the market in releases dated June 4 and May 20 that withheld the identity of the operator and project, Tecnimont will deliver engineering, procurement, and construction (EPC) services for ADNOC Gas’ RGD Phase 3 expansion involving the addition of a fifth NGL fractionation unit at the Ruwais NGL complex in Abu Dhabi, Maire said. Alongside the NGL fractionation unit designed to separate various hydrocarbon components, as well as treatment and sweetening systems to remove impurities and ensure product quality, Maire confirmed Tecnimont’s scope of work also will cover EPC for a new regeneration gas treatment unit, a propane refrigeration system, ancillary systems, and associated storage installations of the RGD Phase 3 project. Scheduled for completion in 2030, the Phase 3 plant will have an output capacity of 23,000 tonnes/day, equivalent to about 8 million tonnes/year (tpy), according to the service provider. Confirmation of the Phase 3 contract award follows ADNOC Gas’ announcement earlier on Aug. 10 that it had taken final investment decision on both Phase 2 and Phase 3 of the RGD project, including the operator’s separate and concurrent award to Wison Engineering Ltd. for the project’s second phase. As part of the $3.9-billion RGD Phase 3 contract, Wison Engineering will deliver EPC services for a new 670-MMcfd natural gas processing train at the operator’s Habshan

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Is your networking built for AI’s traffic patterns and data volumes?

As data centers evolve into AI factories, compute has shifted from a cost center to a revenue driver. “Compute is revenue,” said Jensen Huang, co-founder and CEO of NVIDIA. “Without compute, there is no way to generate tokens. Without tokens, there’s no way to generate revenue. So, in this new world of AI, compute equals revenue.” This reframe changes an organizations’ calculus. If compute is revenue, what do you optimize for? Here are 5 questions to consider: Are you measuring what actually drives AI factory revenue? Most AI factories are power-constrained, so tokens per watt dictate how much revenue you can generate and the cost per token impacts the AI factory profit margin. But neither of these metrics should be evaluated at a single operating point. Batch jobs, real-time chat, and agentic workloads demand different points on the throughput-latency curve. AI chips that perform well at only a few points will underserve the full range of workloads. Additional key operational metrics like time to first token (TTFT), mean time between interruptions (MTBI), and platform useful life are the bedrock of AI factory efficiency. They dictate how quickly an AI factory comes online to generate tokens, the reliability of its revenue streams, and its long-term ability to remain productive as AI workloads evolve. How does agentic AI change what your CPU needs to deliver? Data center CPUs have historically been optimized for parallel throughput, where more cores improve aggregate capacity.  Agentic workloads run in loops and make different demands. The model reasons on the GPU, the CPU executes tool calls such as code compilation and data retrieval, and the result returns to the GPU so the model can reason again. Every step runs in sequence, gated by the one before it. Per-core performance and memory latency determine how fast each step

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It’s final! Judge says HPE’s Juniper acquisition is complete

Originally announced on January 9, 2024, the deal and has undergone public scrutiny ever since, with regulatory reviews in the UK, EU and the US. It was the US that proved to be the final hurdle, with the Justice Department suing to block the deal at first. At the time, the DOJ said reduced competition in the wireless market would be the biggest problem with the proposed buy. In its statement, the agency noted that HPE and Juniper are the second- and third-largest providers, respectively, of enterprise-grade WLAN solutions in the U.S. behind market leader Cisco. But those issues were ultimately settled in June 2025, and HPE has gone on to integrate Juniper’s networking technology. Most recently, it announced a raft of new products, including HPE Juniper Networking QFX switches aimed at inferencing and scale-up architecture. It also deepened integration of its Juniper Networking data center switching and operations into its Mist AI engine and launched a unified, AI-native SASE platform.

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Google, Microsoft and Nvidia back 800V DC standard for AI data centers

The savings over alternating current (AC), the current power standard, are considerable. With AC, there are 4 wires while DC has two. So there is considerable wiring savings in an all-DC facility. Also, with higher voltage comes a lower current and current is what generates heat. So data centers that can run on 800VDC can run cooler. That translates to a 50% to 80% reduction in copper usage and an 8% to 12% reduction in annual energy-related OpEx through lower conversion and distribution losses. AI-first facilities can see a $4 million to $8 million in CapEx savings per 10 MW build by reducing upstream AC. For a one-gigawatt data center, you’re saving a several million pounds of copper wire. The push reflects a fundamental change in data-center power requirements. AI accelerators are being deployed in increasingly dense configurations, driving power consumption per rack higher and making traditional low-voltage AC distribution more difficult to scale.

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Five takeaways from Cisco’s Q4 and what they mean for IT pros

1. Agentic AI is driving a “networking supercycle” During the call, CEO Chuck Robbins repeatedly emphasized that accelerating agentic AI adoption is fueling a long-term “networking supercycle.” For years, network traffic was predictable: client-to-server or standard east-west data center traffic. Agentic AI upends those legacy traffic models. Autonomous AI agents interact continuously with application programming interfaces (API), databases, vector search engines, and other agents, driving massive increases in lateral bandwidth requirements and imposing strict low-latency constraints. Furthermore, as AI models grow in size, physical data center boundaries are proving insufficient. Hyperscalers and large enterprises are adopting scale-across architectures that link multiple physical data centers, enabling distributed GPUs to operate as a single logical cluster. Cisco noted that network traffic in scale-across environments is roughly 14 times higher than in traditional data center interconnects. What it means for IT pros: If your team still treats network capacity planning as an annual incremental upgrade, you will be left behind. Agentic workflows will overwhelm LANs, WANs, and data center networks with unprecedented volumes of multidirectional traffic. Network architects must immediately evaluate non-blocking topologies, high-density 400G/800G switching, and deterministic networking to prevent enterprise AI initiatives from stalling at the transport layer.

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North American data center vacancy holds at just 1%

The shift is being driven largely by the industry’s growing need for electricity, land and infrastructure. Traditional markets such as Northern Virginia have become increasingly difficult to expand because of power constraints, land availability and lengthy utility interconnection timelines. But JLL cautioned that the industry’s continued expansion will depend increasingly on winning public support, at a time of significant pushback from residents. “Supporting the next phase of growth will depend on building trust, addressing local concerns and delivering lasting benefits to host communities,” the report said. In addition to residential pushback, power availability is becoming increasingly scarce. In primary data center markets, the average wait for a grid connection can exceed four years, pushing operators toward on-site generation, battery storage and other alternatives.

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IT infrastructure shortages are real and lasting. Here’s how to cope

Look at alternatives, including AMD and cloud solutions, while staying mindful of how it all plays together. You may not be able to get Nvidia GPUs, but AWS, Azure, and Oracle Cloud have them, Kimball notes. Be strategic, perhaps by using cloud offerings to handle certain tuning or inference workloads, then bringing them back in-house when appropriate. “Have a better understanding of what absolutely has to be on prem and what can be in the cloud,” he says. That’s good advice, says Backblaze’s Thomas. When it comes to AI, think about performance tiers and the range of use cases you have. They don’t all need top-tier performance. “People get wrapped around axle of needing the top end. There’s a lot of flexibility in the edges, innovation in different hardware and software,” Thomas says. Gartner likewise advises companies to increase configuration flexibility and expand sourcing paths. That may include buying from secondary markets and lease-return programs to preserve continuity with existing infrastructure until the shortages pass, Forest says. Get started somewhere Even if you can’t acquire or have to wait for the infrastructure you need, don’t let that keep you from getting started with AI or other modernization projects. Options include public cloud and neocloud providers, Anderson says. WWT also provides capacity in its own lab so customers can get started with proof-of-concept projects. “Don’t just throw your hands up. We can help you find access to capacity,” Anderson says. “Production-scale AI may be delayed, but don’t let that derail your strategy.” Colocation providers may likewise be an option, especially if enterprises are struggling to acquire high-end networking equipment. Networking is a key value proposition for colocation providers, in that they have built-in connections to various cloud providers and other ecosystem players. Equinix, for example, has 280 data centers in 77 metropolitan

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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.

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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

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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

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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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