How nonprofits and academia are stepping up to salvage US climate programs

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How nonprofits and academia are stepping up to salvage US climate programs

Nonprofits are striving to preserve a US effort to modernize greenhouse-gas measurements, amid growing fears that the Trump administration’s dismantling of federal programs will obscure the nation’s contributions to climate change. The Data Foundation, a Washington, DC, nonprofit that advocates for open data, is fundraising for an initiative that will coordinate efforts among nonprofits, technical experts, and companies to improve the accuracy and accessibility of climate emissions information. It will build on an effort to improve the collection of emissions data that former president Joe Biden launched in 2023—and which President Trump nullified on his first day in office. The initiative will help prioritize responses to changes in federal greenhouse-gas monitoring and measurement programs, but the Data Foundation stresses that it will primarily serve a “long-standing need for coordination” of such efforts outside of government agencies. The new greenhouse-gas coalition is one of a growing number of nonprofit and academic groups that have spun up or shifted focus to keep essential climate monitoring and research efforts going amid the Trump administration’s assault on environmental funding, staffing, and regulations. Those include efforts to ensure that US scientists can continue to contribute to the UN’s major climate report and publish assessments of the rising domestic risks of climate change. Otherwise, the loss of these programs will make it increasingly difficult for communities to understand how more frequent or severe wildfires, droughts, heat waves, and floods will harm them—and how dire the dangers could become. Few believe that nonprofits or private industry can come close to filling the funding holes that the Trump administration is digging. But observers say it’s essential to try to sustain efforts to understand the risks of climate change that the federal government has historically overseen, even if the attempts are merely stopgap measures. If we give up these sources of emissions data, “we’re flying blind,” says Rachel Cleetus, senior policy director with the climate and energy program at the Union of Concerned Scientists. “We’re deliberating taking away the very information that would help us understand the problem and how to address it best.” Improving emissions estimates The Environmental Protection Agency, the National Oceanic and Atmospheric Administration, the US Forest Service, and other agencies have long collected information about greenhouse gases in a variety of ways. These include self-reporting by industry; shipboard, balloon, and aircraft readings of gas concentrations in the atmosphere; satellite measurements of the carbon dioxide and methane released by wildfires; and on-the-ground measurements of trees. The EPA, in turn, collects and publishes the data from these disparate sources as the Inventory of US Greenhouse Gas Emissions and Sinks. But that report comes out on a two-year lag, and studies show that some of the estimates it relies on could be way off—particularly the self-reported ones. A recent analysis using satellites to measure methane pollution from four large landfills found they produce, on average, six times more emissions than the facilities had reported to the EPA. Likewise, a 2018 study in Science found that the actual methane leaks from oil and gas infrastructure were about 60% higher than the self-reported estimates in the agency’s inventory. The Biden administration’s initiative—the National Strategy to Advance an Integrated US Greenhouse Gas Measurement, Monitoring, and Information System—aimed to adopt state-of-the-art tools and methods to improve the accuracy of these estimates, including satellites and other monitoring technologies that can replace or check self-reported information. The administration specifically sought to achieve these improvements through partnerships between government, industry, and nonprofits. The initiative called for the data collected across groups to be published to an online portal in formats that would be accessible to policymakers and the public. Moving toward a system that produces more current and reliable data is essential for understanding the rising risks of climate change and tracking whether industries are abiding by government regulations and voluntary climate commitments, says Ben Poulter, a former NASA scientist who coordinated the Biden administration effort as a deputy director in the Office of Science and Technology Policy. “Once you have this operational system, you can provide near-real-time information that can help drive climate action,” Poulter says. He is now a senior scientist at Spark Climate Solutions, a nonprofit focused on accelerating emerging methods of combating climate change, and he is advising the Data Foundation’s Climate Data Collaborative, which is overseeing the new greenhouse-gas initiative. Slashed staffing and funding But the momentum behind the federal strategy deflated when Trump returned to office. On his first day, he signed an executive order that effectively halted it. The White House has since slashed staffing across the agencies at the heart of the effort, sought to shut down specific programs that generate emissions data, and raised uncertainties about the fate of numerous other program components. In April, the administration missed a deadline to share the updated greenhouse-gas inventory with the United Nations, for the first time in three decades, as E&E News reported. It eventually did release the report in May, but only after the Environmental Defense Fund filed a Freedom of Information Act request. There are also indications that the collection of emissions data might be in jeopardy. In March, the EPA said it would “reconsider” the Greenhouse Gas Reporting Program, which requires thousands of power plants, refineries, and other industrial facilities to report emissions each year. In addition, the tax and spending bill that Trump signed into law earlier this month rescinds provisions in Biden’s Inflation Reduction Act that provided incentives or funding for corporate greenhouse-gas reporting and methane monitoring. Meanwhile, the White House has also proposed slashing funding for the National Oceanic and Atmospheric Administration and shuttering a number of its labs. Those include the facility that supports the Mauna Loa Observatory in Hawaii, the world’s longest-running carbon dioxide measuring program, as well as the Global Monitoring Laboratory, which operates a global network of collection flasks that capture air samples used to measure concentrations of nitrous oxide, chlorofluorocarbons, and other greenhouse gases. Under the latest appropriations negotiations, Congress seems set to spare NOAA and other agencies the full cuts pushed by the Trump administration, but that may or may not protect various climate programs within them. As observers have noted, the loss of experts throughout the federal government, coupled with the priorities set by Trump-appointed leaders of those agencies, could still prevent crucial emissions data from being collected, analyzed, and published. “That’s a huge concern,” says David Hayes, a professor at the Stanford Doerr School of Sustainability, who previously worked on the effort to upgrade the nation’s emissions measurement and monitoring as special assistant to President Biden for climate policy. It’s not clear “whether they’re going to continue and whether the data availability will drop off.” ‘A natural disaster’ Amid all these cutbacks and uncertainties, those still hoping to make progress toward an improved system for measuring greenhouse gases have had to adjust their expectations: It’s now at least as important to simply preserve or replace existing federal programs as it is to move toward more modern tools and methods. But Ryan Alexander, executive director of the Data Foundation’s Climate Data Collaborative, is optimistic that there will be opportunities to do both. She says the new greenhouse-gas coalition will strive to identify the highest-priority needs and help other nonprofits or companies accelerate the development of new tools or methods. It will also aim to ensure that these organizations avoid replicating one another’s efforts and deliver data with high scientific standards, in open and interoperable formats. The Data Foundation declines to say what other nonprofits will be members of the coalition or how much money it hopes to raise, but it plans to make a formal announcement in the coming weeks. Nonprofits and companies are already playing a larger role in monitoring emissions, including organizations like Carbon Mapper, which operates satellites and aircraft that detect and measure methane emissions from particular facilities. The EDF also launched a satellite last year, known as MethaneSAT, that could spot large and small sources of emissions—though it lost power earlier this month and probably cannot be recovered. Alexander notes that shifting from self-reported figures to observational technology like satellites could not just replace but perhaps also improve on the EPA reporting program that the Trump administration has moved to shut down. Given the “dramatic changes” brought about by this administration, “the future will not be the past,” she says. “This is like a natural disaster. We can’t think about rebuilding in the way that things have been in the past. We have to look ahead and say, ‘What is needed? What can people afford?’” Organizations can also use this moment to test and develop emerging technologies that could improve greenhouse-gas measurements, including novel sensors or artificial intelligence tools, Hayes says. “We are at a time when we have these new tools, new technologies for measurement, measuring, and monitoring,” he says. “To some extent it’s a new era anyway, so it’s a great time to do some pilot testing here and to demonstrate how we can create new data sets in the climate area.” Saving scientific contributions It’s not just the collection of emissions data that nonprofits and academic groups are hoping to save. Notably, the American Geophysical Union and its partners have taken on two additional climate responsibilities that traditionally fell to the federal government. The US State Department’s Office of Global Change historically coordinated the nation’s contributions to the UN Intergovernmental Panel on Climate Change’s major reports on climate risks, soliciting and nominating US scientists to help write, oversee, or edit sections of the assessments. The US Global Change Research Program, an interagency group that ran much of the process, also covered the cost of trips to a series of in-person meetings with international collaborators. But the US government seems to have relinquished any involvement as the IPCC kicks off the process for the Seventh Assessment Report. In late February, the administration blocked federal scientists including NASA’s Katherine Calvin, who was previously selected as a cochair for one of the working groups, from attending an early planning meeting in China. (Calvin was the agency’s chief scientist at the time but was no longer serving in that role as of April, according to NASA’s website.) The agency didn’t respond to inquiries from interested scientists after the UN panel issued a call for nominations in March, and it failed to present a list of nominations by the deadline in April, scientists involved in the process say. The Trump administration also canceled funding for the Global Change Research Program and, earlier this month, fired the last remaining staffers working at the Office of Global Change. In response, 10 universities came together in March to form the US Academic Alliance for the IPCC, in partnership with the AGU, to request and evalute applications from US researchers. The universities—which include Yale, Princeton, and the University of California, San Diego—together nominated nearly 300 scientists, some of whom the IPCC has since officially selected. The AGU is now conducting a fundraising campaign to help pay for travel expenses. Pamela McElwee, a professor at Rutgers who helped establish the academic coalition, says it’s crucial for US scientists to continue participating in the IPCC process. “It is our flagship global assessment report on the state of climate, and it plays a really important role in influencing country policies,” she says. “To not be part of it makes it much more difficult for US scientists to be at the cutting edge and advance the things we need to do.” The AGU also stepped in two months later, after the White House dismissed hundreds of researchers working on the National Climate Assessment, an annual report analyzing the rising dangers of climate change across the country. The AGU and American Meteorological Society together announced plans to publish a “special collection” to sustain the momentum of that effort. “It’s incumbent on us to ensure our communities, our neighbors, our children are all protected and prepared for the mounting risks of climate change,” said Brandon Jones, president of the AGU, in an earlier statement. The AGU declined to discuss the status of the project. Stopgap solution The sheer number of programs the White House is going after will require organizations to make hard choices about what they attempt to save and how they go about it. Moreover, relying entirely on nonprofits and companies to take over these federal tasks is not viable over the long term. Given the costs of these federal programs, it could prove prohibitive to even keep a minimum viable version of some essential monitoring systems and research programs up and running. Dispersing across various organizations the responsibility of calculating the nation’s emissions sources and sinks also creates concerns about the scientific standards applied and the accessibility of that data, Cleetus says. Plus, moving away from the records that NOAA, NASA, and other agencies have collected for decades would break the continuity of that data, undermining the ability to detect or project trends. More basically, publishing national emissions data should be a federal responsibility, particularly for the government of the world’s second-largest climate polluter, Cleetus adds. Failing to calculate and share its contributions to climate change sidesteps the nation’s global responsibilities and sends a terrible signal to other countries. Poulter stresses that nonprofits and the private sector can do only so much, for so long, to keep these systems up and running. “We don’t want to give the impression that this greenhouse-gas coalition, if it gets off the ground, is a long-term solution,” he says. “But we can’t afford to have gaps in these data sets, so somebody needs to step in and help sustain those measurements.”

The Data Foundation, a Washington, DC, nonprofit that advocates for open data, is fundraising for an initiative that will coordinate efforts among nonprofits, technical experts, and companies to improve the accuracy and accessibility of climate emissions information. It will build on an effort to improve the collection of emissions data that former president Joe Biden launched in 2023—and which President Trump nullified on his first day in office.

The initiative will help prioritize responses to changes in federal greenhouse-gas monitoring and measurement programs, but the Data Foundation stresses that it will primarily serve a “long-standing need for coordination” of such efforts outside of government agencies.

The new greenhouse-gas coalition is one of a growing number of nonprofit and academic groups that have spun up or shifted focus to keep essential climate monitoring and research efforts going amid the Trump administration’s assault on environmental funding, staffing, and regulations. Those include efforts to ensure that US scientists can continue to contribute to the UN’s major climate report and publish assessments of the rising domestic risks of climate change. Otherwise, the loss of these programs will make it increasingly difficult for communities to understand how more frequent or severe wildfires, droughts, heat waves, and floods will harm them—and how dire the dangers could become.

Few believe that nonprofits or private industry can come close to filling the funding holes that the Trump administration is digging. But observers say it’s essential to try to sustain efforts to understand the risks of climate change that the federal government has historically overseen, even if the attempts are merely stopgap measures.

If we give up these sources of emissions data, “we’re flying blind,” says Rachel Cleetus, senior policy director with the climate and energy program at the Union of Concerned Scientists. “We’re deliberating taking away the very information that would help us understand the problem and how to address it best.”

Improving emissions estimates

The Environmental Protection Agency, the National Oceanic and Atmospheric Administration, the US Forest Service, and other agencies have long collected information about greenhouse gases in a variety of ways. These include self-reporting by industry; shipboard, balloon, and aircraft readings of gas concentrations in the atmosphere; satellite measurements of the carbon dioxide and methane released by wildfires; and on-the-ground measurements of trees. The EPA, in turn, collects and publishes the data from these disparate sources as the Inventory of US Greenhouse Gas Emissions and Sinks.

But that report comes out on a two-year lag, and studies show that some of the estimates it relies on could be way off—particularly the self-reported ones.

A recent analysis using satellites to measure methane pollution from four large landfills found they produce, on average, six times more emissions than the facilities had reported to the EPA. Likewise, a 2018 study in Science found that the actual methane leaks from oil and gas infrastructure were about 60% higher than the self-reported estimates in the agency’s inventory.

The Biden administration’s initiative—the National Strategy to Advance an Integrated US Greenhouse Gas Measurement, Monitoring, and Information System—aimed to adopt state-of-the-art tools and methods to improve the accuracy of these estimates, including satellites and other monitoring technologies that can replace or check self-reported information.

The administration specifically sought to achieve these improvements through partnerships between government, industry, and nonprofits. The initiative called for the data collected across groups to be published to an online portal in formats that would be accessible to policymakers and the public.

Moving toward a system that produces more current and reliable data is essential for understanding the rising risks of climate change and tracking whether industries are abiding by government regulations and voluntary climate commitments, says Ben Poulter, a former NASA scientist who coordinated the Biden administration effort as a deputy director in the Office of Science and Technology Policy.

“Once you have this operational system, you can provide near-real-time information that can help drive climate action,” Poulter says. He is now a senior scientist at Spark Climate Solutions, a nonprofit focused on accelerating emerging methods of combating climate change, and he is advising the Data Foundation’s Climate Data Collaborative, which is overseeing the new greenhouse-gas initiative.

Slashed staffing and funding

But the momentum behind the federal strategy deflated when Trump returned to office. On his first day, he signed an executive order that effectively halted it. The White House has since slashed staffing across the agencies at the heart of the effort, sought to shut down specific programs that generate emissions data, and raised uncertainties about the fate of numerous other program components.

In April, the administration missed a deadline to share the updated greenhouse-gas inventory with the United Nations, for the first time in three decades, as E&E News reported. It eventually did release the report in May, but only after the Environmental Defense Fund filed a Freedom of Information Act request.

There are also indications that the collection of emissions data might be in jeopardy. In March, the EPA said it would “reconsider” the Greenhouse Gas Reporting Program, which requires thousands of power plants, refineries, and other industrial facilities to report emissions each year.

In addition, the tax and spending bill that Trump signed into law earlier this month rescinds provisions in Biden’s Inflation Reduction Act that provided incentives or funding for corporate greenhouse-gas reporting and methane monitoring.

Meanwhile, the White House has also proposed slashing funding for the National Oceanic and Atmospheric Administration and shuttering a number of its labs. Those include the facility that supports the Mauna Loa Observatory in Hawaii, the world’s longest-running carbon dioxide measuring program, as well as the Global Monitoring Laboratory, which operates a global network of collection flasks that capture air samples used to measure concentrations of nitrous oxide, chlorofluorocarbons, and other greenhouse gases.

Under the latest appropriations negotiations, Congress seems set to spare NOAA and other agencies the full cuts pushed by the Trump administration, but that may or may not protect various climate programs within them. As observers have noted, the loss of experts throughout the federal government, coupled with the priorities set by Trump-appointed leaders of those agencies, could still prevent crucial emissions data from being collected, analyzed, and published.

“That’s a huge concern,” says David Hayes, a professor at the Stanford Doerr School of Sustainability, who previously worked on the effort to upgrade the nation’s emissions measurement and monitoring as special assistant to President Biden for climate policy. It’s not clear “whether they’re going to continue and whether the data availability will drop off.”

‘A natural disaster’

Amid all these cutbacks and uncertainties, those still hoping to make progress toward an improved system for measuring greenhouse gases have had to adjust their expectations: It’s now at least as important to simply preserve or replace existing federal programs as it is to move toward more modern tools and methods.

But Ryan Alexander, executive director of the Data Foundation’s Climate Data Collaborative, is optimistic that there will be opportunities to do both.

She says the new greenhouse-gas coalition will strive to identify the highest-priority needs and help other nonprofits or companies accelerate the development of new tools or methods. It will also aim to ensure that these organizations avoid replicating one another’s efforts and deliver data with high scientific standards, in open and interoperable formats.

The Data Foundation declines to say what other nonprofits will be members of the coalition or how much money it hopes to raise, but it plans to make a formal announcement in the coming weeks.

Nonprofits and companies are already playing a larger role in monitoring emissions, including organizations like Carbon Mapper, which operates satellites and aircraft that detect and measure methane emissions from particular facilities. The EDF also launched a satellite last year, known as MethaneSAT, that could spot large and small sources of emissions—though it lost power earlier this month and probably cannot be recovered.

Alexander notes that shifting from self-reported figures to observational technology like satellites could not just replace but perhaps also improve on the EPA reporting program that the Trump administration has moved to shut down.

Given the “dramatic changes” brought about by this administration, “the future will not be the past,” she says. “This is like a natural disaster. We can’t think about rebuilding in the way that things have been in the past. We have to look ahead and say, ‘What is needed? What can people afford?’”

Organizations can also use this moment to test and develop emerging technologies that could improve greenhouse-gas measurements, including novel sensors or artificial intelligence tools, Hayes says.

“We are at a time when we have these new tools, new technologies for measurement, measuring, and monitoring,” he says. “To some extent it’s a new era anyway, so it’s a great time to do some pilot testing here and to demonstrate how we can create new data sets in the climate area.”

Saving scientific contributions

It’s not just the collection of emissions data that nonprofits and academic groups are hoping to save. Notably, the American Geophysical Union and its partners have taken on two additional climate responsibilities that traditionally fell to the federal government.

The US State Department’s Office of Global Change historically coordinated the nation’s contributions to the UN Intergovernmental Panel on Climate Change’s major reports on climate risks, soliciting and nominating US scientists to help write, oversee, or edit sections of the assessments. The US Global Change Research Program, an interagency group that ran much of the process, also covered the cost of trips to a series of in-person meetings with international collaborators.

But the US government seems to have relinquished any involvement as the IPCC kicks off the process for the Seventh Assessment Report. In late February, the administration blocked federal scientists including NASA’s Katherine Calvin, who was previously selected as a cochair for one of the working groups, from attending an early planning meeting in China. (Calvin was the agency’s chief scientist at the time but was no longer serving in that role as of April, according to NASA’s website.)

The agency didn’t respond to inquiries from interested scientists after the UN panel issued a call for nominations in March, and it failed to present a list of nominations by the deadline in April, scientists involved in the process say. The Trump administration also canceled funding for the Global Change Research Program and, earlier this month, fired the last remaining staffers working at the Office of Global Change.

In response, 10 universities came together in March to form the US Academic Alliance for the IPCC, in partnership with the AGU, to request and evalute applications from US researchers. The universities—which include Yale, Princeton, and the University of California, San Diego—together nominated nearly 300 scientists, some of whom the IPCC has since officially selected. The AGU is now conducting a fundraising campaign to help pay for travel expenses.

Pamela McElwee, a professor at Rutgers who helped establish the academic coalition, says it’s crucial for US scientists to continue participating in the IPCC process.

“It is our flagship global assessment report on the state of climate, and it plays a really important role in influencing country policies,” she says. “To not be part of it makes it much more difficult for US scientists to be at the cutting edge and advance the things we need to do.”

The AGU also stepped in two months later, after the White House dismissed hundreds of researchers working on the National Climate Assessment, an annual report analyzing the rising dangers of climate change across the country. The AGU and American Meteorological Society together announced plans to publish a “special collection” to sustain the momentum of that effort.

“It’s incumbent on us to ensure our communities, our neighbors, our children are all protected and prepared for the mounting risks of climate change,” said Brandon Jones, president of the AGU, in an earlier statement.

The AGU declined to discuss the status of the project.

Stopgap solution

The sheer number of programs the White House is going after will require organizations to make hard choices about what they attempt to save and how they go about it. Moreover, relying entirely on nonprofits and companies to take over these federal tasks is not viable over the long term.

Given the costs of these federal programs, it could prove prohibitive to even keep a minimum viable version of some essential monitoring systems and research programs up and running. Dispersing across various organizations the responsibility of calculating the nation’s emissions sources and sinks also creates concerns about the scientific standards applied and the accessibility of that data, Cleetus says. Plus, moving away from the records that NOAA, NASA, and other agencies have collected for decades would break the continuity of that data, undermining the ability to detect or project trends.

More basically, publishing national emissions data should be a federal responsibility, particularly for the government of the world’s second-largest climate polluter, Cleetus adds. Failing to calculate and share its contributions to climate change sidesteps the nation’s global responsibilities and sends a terrible signal to other countries.

Poulter stresses that nonprofits and the private sector can do only so much, for so long, to keep these systems up and running.

“We don’t want to give the impression that this greenhouse-gas coalition, if it gets off the ground, is a long-term solution,” he says. “But we can’t afford to have gaps in these data sets, so somebody needs to step in and help sustain those measurements.”

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Abbe Ramanan is a project director at Clean Energy Group. In 2020, the Virginia Assembly passed the Virginia Clean Economy Act, a law that required the state’s largest utility, Dominion Energy, to generate all its electricity from renewable resources by 2045. However, Dominion has found a useful loophole to get around the law’s requirements — data centers. Viriginia hosts the largest data center market in the world, and is home to at least 150 hyperscale data centers, with more being proposed. In its recent integrated resource plan, Dominion cited projected energy demand from these data centers as a key reason to delay retiring existing power plants, including the Clover Power Station, a coal-powered peaker plant in Halifax County, a disproportionately low-income region. In addition to delaying peaker retirements, Dominion has proposed building new gas-powered generation, including a 1-GW peaker plant in Chesterfield, a community that already shoulders an undue environmental burden from existing natural gas- and coal-fired generation. Similar stories have played out across the country as data centers become more and more ubiquitous, particularly in the Southeast. Utilities in Virginia, Georgia, North Carolina and South Carolina have proposed building 20,000 MW of new gas power plants by 2040. Data centers driving the projected load growth are being used to justify this buildout. In Virginia, Georgia and South Carolina, data centers are responsible for at least 65% of projected load growth. Data centers are also delaying the retirement of fossil fuel power plants nationwide, with at least 17 fossil fuel generators originally scheduled for closure now delaying retirement. This new gas buildout, as well as the delayed retirement of fossil fuel generators, overwhelmingly harms Black and brown communities, who face higher energy and environmental burdens. The gas bonanza is especially concerning because the projected demand from data centers could be

AI Project Stargate struggles to get off the ground

Analysts aren’t surprised at the news. “Big IT projects have a long history of dramatically overpromising and it appears that trend is quickly moving into the world of AI data center-based projects as well. The Stargate project, in particular, also seems to have more of a political bent to it than many other projects so that’s likely complicating matters as well,” said Bob O’Donnell, president and chief analyst with TECHnalysis Research. “There’s little doubt we will see massive investments by many different organizations to build out AI infrastructure here in the US, but I’m not convinced that individual projects will end up mattering that much in the long run,” he added. “I have always been skeptical about the huge number that was projected. In the hundreds of billions,” said Patrick Moorhead, CEO & chief analyst with Moor Insights & Strategy. “The only problem was that only a few billion in new funding was raised. And now there’s strife between OpenAI and SoftBank. To be fair, Oracle is part of Stargate now and OpenAI will soak up many GPUs in the Texas facility, but this was already in process when the Stargate announcement happened.”

Storage vendors bring record capacity devices to handle massive data generation

Both are built on Seagate’s Mozaic3+ with advanced storage technology called HAMR, or Heat-Assisted Magnetic Recording. By heating the platter to as much as 500°C, they can squeeze up to 3TB per platter. Other than that, it looks like a standard hard drive: 3.5-inch enclosure, 7,200 RPM spin rotation, and SATA III interface with 6Gbps/s transfer speeds. The drivers are available now and are rather affordable. The 30TB Exos is just $599 on NewEgg.com. On the enterprise solid state drive (SSD) front, KIOXIA America has expanded its high-capacity KIOXIA LC9 Series enterprise SSD lineup with the introduction of a 245.76TB NVMe SSD. The drive comes in a 2.5-inch and Enterprise and Datacenter Standard Form Factor (EDSFF) E3.L form factor and is purpose-built for the performance and efficiency demands of generative AI environments.

Technology is coming so fast data centers are obsolete by the time they launch

Tariffs aside, Enderle feels that AI technology and ancillary technology around it like battery backup is still in the early stages of development and there will be significant changes coming in the next few years. GPUs from AMD and Nvidia are the primary processors for AI, and they are derived from video game accelerators. They were never meant for use in AI processing, but they are being fine-tuned for the task. It’s better to wait to get a more mature product than something that is still in a relatively early state. But Alan Howard, senior analyst for data center infrastructure at Omdia, disagrees and says not to wait. One reason is the rate at which people that are building data centers is all about seizing market opportunity.” You must have a certain amount of capacity to make sure that you can execute on strategies meant to capture more market share.” The same sentiment exists on the colocation side, where there is a considerable shortage of capacity as demand outstrips supply. “To say, well, let’s wait and see if maybe we’ll be able to build a better, more efficient data center by not building anything for a couple of years. That’s just straight up not going to happen,” said Howard. “By waiting, you’re going to miss market opportunities. And these companies are all in it to make money. And so, the almighty dollar rules,” he added. Howard acknowledges that by the time you design and build the data center, it’s obsolete. The question is, does that mean it can’t do anything? “I mean, if you start today on a data center that’s going to be full of [Nvidia] Blackwells, and let’s say you deploy in two years when they’ve already retired Blackwell, and they’re making something completely new. Is that data

‘Significant’ outage at Alaska Airlines not a security incident, but a hardware breakdown

The airline told Network World that when the critical piece of what it described as “third-party multi-redundant hardware” failed unexpectedly, “it impacted several of our key systems that enable us to run various operations.” The company is currently working with its vendor to replace the faulty equipment at the data center. The airline has cancelled more than 150 flights since Sunday evening, including 64 on Monday. The company said additional flight disruptions are likely as it repositions aircraft and crews throughout its network. Alaska Airlines emphasized that the safety of its flights was never compromised, and that “the IT outage is not related to any other current events, and it’s not connected to the recent cybersecurity incident at Hawaiian Airlines.” The airline did not provide additional information to Network World about the specifics of the outage. “There are many redundant components that can fail,” said Roberts, noting that it could have been something as simple as a RAID array (which combines multiple physical data storage components into one or more logical units). Or, on the network side, it could have been the failure of a pair of load balancers. “It’s interesting that redundancy didn’t save them,” said Roberts. “Perhaps multiple pieces of hardware were impacted by the same issue, like a firmware update. Or, maybe they’re just really unlucky.”

Cisco upgrades 400G optical receiver to boost AI infrastructure throughput

“In the data center, what’s really changed in the last year or so is that with AI buildouts, there’s much, much more optics that are part of 400G and 800G. It’s not so much using 10G and 25G optics, which we still sell a ton of, for campus applications. But for AI infrastructure, the 400G and 800G optics are really the dominant optics for that application,” Gartner said. Most of the AI infrastructure builds have been for training models, especially in hyperscaler environments, Gartner said. “I expect, towards the tail end of this year, we’ll start to see more enterprises deploying AI infrastructure for inference. And once they do that, because it has an Nvidia GPU attached to it, it’s going to be a 400G or 800G optic.” Core enterprise applications – such as real-time trading, high-frequency transactions, multi-cloud communications, cybersecurity analytics, network forensics, and industrial IoT – can also utilize the higher network throughput, Gartner said.

Supermicro bets big on 4-socket X14 servers to regain enterprise trust

In April, Dell announced its PowerEdge R470, R570, R670, and R770 servers with Intel Xeon 6 Processors with P-cores, but with single and double-socket servers. Similarly, Lenovo’s ThinkSystem V4 servers are also based on the Intel Xeon 6 processor but are limited to dual socket configurations. The launch of 4-socket servers by Supermicro reflects a growing enterprise need for localized compute that can support memory-bound AI and reduce the complexity of distributed architectures. “The modern 4-socket servers solve multiple pain points that have intensified with GenAI and memory-intensive analytics. Enterprises are increasingly challenged by latency, interconnect complexity, and power budgets in distributed environments. High-capacity, scale-up servers provide an architecture that is more aligned with low-latency, large-model processing, especially where data residency or compliance constraints limit cloud elasticity,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research. “Launching a 4-socket Xeon 6 platform and packaging it within their modular ‘building block’ strategy shows Supermicro is focusing on staying ahead in enterprise and AI data center compute,” said Devroop Dhar, co-founder and MD at Primus Partner. A critical launch after major setbacks Experts peg this to be Supermicro’s most significant product launch since it became mired in governance and regulatory controversies. In 2024, the company lost Ernst & Young, its second auditor in two years, following allegations by Hindenburg Research involving accounting irregularities and the alleged export of sensitive chips to sanctioned entities. Compounding its troubles, Elon Musk’s AI startup xAI redirected its AI server orders to Dell, a move that reportedly cost Supermicro billions in potential revenue and damaged its standing in the hyperscaler ecosystem. Earlier this year, HPE signed a $1 billion contract to provide AI servers for X, a deal Supermicro was also bidding for. “The X14 launch marks a strategic reinforcement for Supermicro, showcasing its commitment

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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