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The foundations of America’s prosperity are being dismantled

Ever since World War II, the US has been the global leader in science and technology—and benefited immensely from it. Research fuels American innovation and the economy in turn. Scientists around the world want to study in the US and collaborate with American scientists to produce more of that research. These international collaborations play a critical role in American soft power and diplomacy. The products Americans can buy, the drugs they have access to, the diseases they’re at risk of catching—are all directly related to the strength of American research and its connections to the world’s scientists. That scientific leadership is now being dismantled, according to more than 10 federal workers who spoke to MIT Technology Review, as the Trump administration—spearheaded by Elon Musk’s Department of Government Efficiency (DOGE)—slashes personnel, programs, and agencies. Meanwhile, the president himself has gone after relationships with US allies.    These workers come from several agencies, including the Departments of State, Defense, and Commerce, the US Agency for International Development, and the National Science Foundation. All of them occupy scientific and technical roles, many of which the average American has never heard of but which are nevertheless critical, coordinating research, distributing funding, supporting policymaking, or advising diplomacy. They warn that dismantling the behind-the-scenes scientific research programs that backstop American life could lead to long-lasting, perhaps irreparable damage to everything from the quality of health care to the public’s access to next-generation consumer technologies. The US took nearly a century to craft its rich scientific ecosystem; if the unraveling that has taken place over the past month continues, Americans will feel the effects for decades to come.  Most of the federal workers spoke on condition of anonymity because they were not authorized to talk or for fear of being targeted. Many are completely stunned and terrified by the scope and totality of the actions. While every administration brings its changes, keeping the US a science and technology leader has never been a partisan issue. No one predicted the wholesale assault on these foundations of American prosperity. “If you believe that innovation is important to economic development, then throwing a wrench in one of the most sophisticated and productive innovation machines in world history is not a good idea,” says Deborah Seligsohn, an assistant professor of political science at Villanova University who worked for two decades in the State Department on science issues. “They’re setting us up for economic decline.” The biggest funder of innovation The US currently has the most top-quality research institutes in the world. This includes world-class universities like MIT (which publishes MIT Technology Review) and the University of California, Berkeley; national labs like Oak Ridge and Los Alamos; and federal research facilities run by agencies like the National Oceanic and Atmospheric Administration and the Department of Defense. Much of this network was developed by the federal government after World War II to bolster the US position as a global superpower.  Before the Trump administration’s wide-ranging actions, which now threaten to slash federal research funding, the government remained by far the largest supporter of scientific progress. Outside of its own labs and facilities, it funded more than 50% of research and development across higher education, according to data from the National Science Foundation. In 2023, that came to nearly $60 billion out of the $109 billion that universities spent on basic science and engineering.  The return on these investments is difficult to measure. It can often take years or decades for this kind of basic science research to have tangible effects on the lives of Americans and people globally, and on the US’s place in the world. But history is littered with examples of the transformative effect that this funding produces over time. The internet and GPS were first developed through research backed by the Department of Defense, as was the quantum dot technology behind high-resolution QLED television screens. Well before they were useful or commercially relevant, the development of neural networks that underpin nearly all modern AI systems was substantially supported by the National Science Foundation. The decades-long drug discovery process that led to Ozempic was incubated by the Department of Veterans Affairs and the National Institutes of Health. Microchips. Self-driving cars. MRIs. The flu shot. The list goes on and on.  In her 2013 book The Entrepreneurial State, Mariana Mazzucato, a leading economist studying innovation at University College London, found that every major technological transformation in the US, from electric cars to Google to the iPhone, can trace its roots back to basic science research once funded by the federal government. If the past offers any lesson, that means every major transformation in the future could be shortchanged with the destruction of that support. The Trump administration’s distaste for regulation will arguably be a boon in the short term for some parts of the tech industry, including crypto and AI. But the federal workers said the president’s and Musk’s undermining of basic science research will hurt American innovation in the long run. “Rather than investing in the future, you’re burning through scientific capital,” an employee at the State Department said. “You can build off the things you already know, but you’re not learning anything new. Twenty years later, you fall behind because you stopped making new discoveries.” A global currency The government doesn’t just give money, either. It supports American science in numerous other ways, and the US reaps the returns. The Department of State helps attract the best students from around the world to American universities. Amid stagnating growth in the number of homegrown STEM PhD graduates, recruiting foreign students remains one of the strongest pathways for the US to expand its pool of technical talent, especially in strategic areas like batteries and semiconductors. Many of those students stay for years, if not the rest of their lives; even if they leave the country, they’ve already spent some of their most productive years in the US and will retain a wealth of professional connections with whom they’ll collaborate, thereby continuing to contribute to US science. The State Department also establishes agreements between the US and other countries and helps broker partnerships between American and international universities. That helps scientists collaborate across borders on everything from global issues like climate change to research that requires equipment on opposite sides of the world, such as the measurement of gravitational waves. The international development work of USAID in global health, poverty reduction, and conflict alleviation—now virtually shut down in its entirety—was designed to build up goodwill toward the US globally; it improved regional stability for decades. In addition to its inherent benefits, this allowed American scientists to safely access diverse geographies and populations, as well as plant and animal species not found in the US. Such international interchange played just as critical a role as government funding in many crucial inventions. Several federal agencies, including the Centers for Disease Control and Prevention, the Environmental Protection Agency, and the National Oceanic and Atmospheric Administration, also help collect and aggregate critical data on disease, health trends, air quality, weather, and more from disparate sources that feed into the work of scientists across the country. The National Institutes of Health, for example, has since 2015 been running the Precision Medicine Initiative, the only effort of its kind to collect extensive and granular health data from over 1 million Americans who volunteer their medical records, genetic history, and even Fitbit data to help researchers understand health disparities and develop personalized and more effective treatments for disorders from heart and lung disease to cancer. The data set, which is too expensive for any one university to assemble and maintain, has already been used in hundreds of papers that will lay the foundation for the next generation of life-saving pharmaceuticals. Beyond fueling innovation, a well-supported science and technology ecosystem bolsters US national security and global influence. When people want to study at American universities, attend international conferences hosted on American soil, or move to the US to work or to found their own companies, the US stays the center of global innovation activity. This ensures that the country continues to get access to the best people and ideas, and gives it an outsize role in setting global scientific practices and priorities. US research norms, including academic freedom and a robust peer review system, become global research norms that lift the overall quality of science. International agencies like the World Health Organization take significant cues from American guidance. US scientific leadership has long been one of the country’s purest tools of soft power and diplomacy as well. Countries keen to learn from the American innovation ecosystem and to have access to American researchers and universities have been more prone to partner with the US and align with its strategic priorities. Just one example: Science diplomacy has long played an important role in maintaining the US’s strong relationship with the Netherlands, which is home to ASML, the only company in the world that can produce the extreme ultraviolet lithography machines needed to produce the most advanced semiconductors. These are critical for both AI development and national security. International science cooperation has also served as a stabilizing force in otherwise difficult relationships. During the Cold War, the US and USSR continued to collaborate on the International Space Station; during the recent heightened economic competition between the US and China, the countries have remained each other’s top scientific partners. “Actively working together to solve problems that we both care about helps maintain the connections and the context but also helps build respect,” Seligsohn says. The federal government itself is a significant beneficiary of the country’s convening power for technical expertise. Among other things, experts both inside and outside the government support its sound policymaking in science and technology. During the US Senate AI Insight Forums, co-organized by Senator Chuck Schumer through the fall of 2023, for example, the Senate heard from more than 150 experts, many of whom were born abroad and studying at American universities, working at or advising American companies, or living permanently in the US as naturalized American citizens. Federal scientists and technical experts at government agencies also work on wide-ranging goals critical to the US, including building resilience in the face of an increasingly erratic climate; researching strategic technologies such as next-generation battery technology to reduce the country’s reliance on minerals not found in the US; and monitoring global infectious diseases to prevent the next pandemic. “Every issue that the US faces, there are people that are trying to do research on it and there are partnerships that have to happen,” the State Department employee said. A system in jeopardy Now the breadth and velocity of the Trump administration’s actions has led to an unprecedented assault on every pillar upholding American scientific leadership. For starters, the purging of tens of thousands—and perhaps soon hundreds of thousands—of federal workers is removing scientists and technologists from the government and paralyzing the ability of critical agencies to function. Across multiple agencies, science and technology fellowship programs, designed to bring in talented early-career staff with advanced STEM degrees, have shuttered. Many other federal scientists were among the thousands who were terminated as probationary employees, a status they held because of the way scientific roles are often contractually structured. Some agencies that were supporting or conducting their own research, including the National Institutes of Health and the National Science Foundation, are no longer functionally operational. USAID has effectively shuttered, eliminating a bastion of US expertise, influence, and credibility overnight. “Diplomacy is built on relationships. If we’ve closed all these clinics and gotten rid of technical experts in our knowledge base inside the government, why would any foreign government have respect for the US in our ability to hold our word and in our ability to actually be knowledgeable?” a terminated USAID worker said. “I really hope America can save itself.” Now the Trump administration has sought to reverse some terminations after discovering that many were key to national security, including nuclear safety employees responsible for designing, building, and maintaining the country’s nuclear weapons arsenal. But many federal workers I spoke to can no longer imagine staying in the public sector. Some are considering going into industry. Others are wondering whether it will be better to move abroad. “It’s just such a waste of American talent,” said Fiona Coleman, a terminated federal scientist, her voice cracking with emotion as she described the long years of schooling and training she and her colleagues went through to serve the government. Many fear the US has also singlehandedly kneecapped its own ability to attract talent from abroad. Over the last 10 years, even as American universities have continued to lead the world, many universities in other countries have rapidly leveled up. That includes those in Canada, where liberal immigration policies and lower tuition fees have driven a 200% increase in international student enrollment over the last decade, according to Anna Esaki-Smith, cofounder of a higher-education research consultancy called Education Rethink and author of Make College Your Superpower. Germany has also seen an influx, thanks to a growing number of English-taught programs and strong connections between universities and German industry. Chinese students, who once represented the largest share of foreign students in the US, are increasingly staying at home or opting to study in places like Hong Kong, Singapore, and the UK. During the first Trump administration, many international students were already more reluctant to come to the US because of the president’s hostile rhetoric. With the return and rapid escalation of that rhetoric, Esaki-Smith is hearing from some universities that international students are declining their admissions offers. Add to that the other recent developments—the potential dramatic cuts in federal research funding, the deletion of scores of rich public data sets on health and the environment, the clampdown on academic freedom for research that appears related to diversity, equity, and inclusion and the fear that these restrictions could ultimately encompass other politically charged topics like climate change or vaccines—and many more international science and engineering students could decide to head elsewhere. “I’ve been hearing this increasingly from several postdocs and early-career professors, fearing the cuts in NIH or NSF grants, that they’re starting to look for funding or job opportunities in other countries,” Coleman told me. “And then we’re going to be training up the US’s competitors.” The attacks could similarly weaken the productivity of those who stay at American universities. While many of the Trump administration’s actions are now being halted and scrutinized by US judges, the chaos has weakened a critical prerequisite for tackling the toughest research problems: a long-term stable environment. With reports that the NSF is combing through research grants for words like “women,” “diverse,” and “institutional” to determine whether they violate President Trump’s executive order on DEIA programs, a chilling effect is also setting in among federally funded academics uncertain whether they’ll get caught in the dragnet. To scientists abroad, the situation in the US government has marked American institutions and researchers as potentially unreliable partners, several federal workers told me. If international researchers think collaborations with the US can end at any moment when funds are abruptly pulled or certain topics or keywords are suddenly blacklisted, many of them could steer clear and look to other countries. “I’m really concerned about the instability we’re showing,” another employee at the State Department said. “What’s the point in even engaging? Because science is a long-term initiative and process that outlasts administrations and political cycles.” Meanwhile, international scientists have far more options these days for high-caliber colleagues to collaborate with outside America. In recent years, for example, China has made a remarkable ascent to become a global peer in scientific discoveries. By some metrics, it has even surpassed the US; it started accounting for more of the top 1% of most-cited papers globally, often called the Nobel Prize tier, back in 2019 and has continued to improve the quality of the rest of its research.  Where Chinese universities can also entice international collaborators with substantial resources, the US is more limited in its ability to offer tangible funding, the State employee said. Until now, the US has maintained its advantage in part through the prestige of its institutions and its more open cultural norms, including stronger academic freedom. But several federal scientists warn that this advantage is dissipating.  “America is made up of so many different people contributing to it. There’s such a powerful global community that makes this country what it is, especially in science and technology and academia and research. We’re going to lose that; there’s not a chance in the world that we’re not going to lose that through stuff like this,” says Brigid Cakouros, a federal scientist who was also terminated from USAID. “I have no doubt that the international science community will ultimately be okay. It’ll just be a shame for the US to isolate themselves from it.”

Ever since World War II, the US has been the global leader in science and technology—and benefited immensely from it. Research fuels American innovation and the economy in turn. Scientists around the world want to study in the US and collaborate with American scientists to produce more of that research. These international collaborations play a critical role in American soft power and diplomacy. The products Americans can buy, the drugs they have access to, the diseases they’re at risk of catching—are all directly related to the strength of American research and its connections to the world’s scientists.

That scientific leadership is now being dismantled, according to more than 10 federal workers who spoke to MIT Technology Review, as the Trump administration—spearheaded by Elon Musk’s Department of Government Efficiency (DOGE)—slashes personnel, programs, and agencies. Meanwhile, the president himself has gone after relationships with US allies.   

These workers come from several agencies, including the Departments of State, Defense, and Commerce, the US Agency for International Development, and the National Science Foundation. All of them occupy scientific and technical roles, many of which the average American has never heard of but which are nevertheless critical, coordinating research, distributing funding, supporting policymaking, or advising diplomacy.

They warn that dismantling the behind-the-scenes scientific research programs that backstop American life could lead to long-lasting, perhaps irreparable damage to everything from the quality of health care to the public’s access to next-generation consumer technologies. The US took nearly a century to craft its rich scientific ecosystem; if the unraveling that has taken place over the past month continues, Americans will feel the effects for decades to come. 

Most of the federal workers spoke on condition of anonymity because they were not authorized to talk or for fear of being targeted. Many are completely stunned and terrified by the scope and totality of the actions. While every administration brings its changes, keeping the US a science and technology leader has never been a partisan issue. No one predicted the wholesale assault on these foundations of American prosperity.

“If you believe that innovation is important to economic development, then throwing a wrench in one of the most sophisticated and productive innovation machines in world history is not a good idea,” says Deborah Seligsohn, an assistant professor of political science at Villanova University who worked for two decades in the State Department on science issues. “They’re setting us up for economic decline.”

The biggest funder of innovation

The US currently has the most top-quality research institutes in the world. This includes world-class universities like MIT (which publishes MIT Technology Review) and the University of California, Berkeley; national labs like Oak Ridge and Los Alamos; and federal research facilities run by agencies like the National Oceanic and Atmospheric Administration and the Department of Defense. Much of this network was developed by the federal government after World War II to bolster the US position as a global superpower. 

Before the Trump administration’s wide-ranging actions, which now threaten to slash federal research funding, the government remained by far the largest supporter of scientific progress. Outside of its own labs and facilities, it funded more than 50% of research and development across higher education, according to data from the National Science Foundation. In 2023, that came to nearly $60 billion out of the $109 billion that universities spent on basic science and engineering. 

The return on these investments is difficult to measure. It can often take years or decades for this kind of basic science research to have tangible effects on the lives of Americans and people globally, and on the US’s place in the world. But history is littered with examples of the transformative effect that this funding produces over time. The internet and GPS were first developed through research backed by the Department of Defense, as was the quantum dot technology behind high-resolution QLED television screens. Well before they were useful or commercially relevant, the development of neural networks that underpin nearly all modern AI systems was substantially supported by the National Science Foundation. The decades-long drug discovery process that led to Ozempic was incubated by the Department of Veterans Affairs and the National Institutes of Health. Microchips. Self-driving cars. MRIs. The flu shot. The list goes on and on. 

In her 2013 book The Entrepreneurial State, Mariana Mazzucato, a leading economist studying innovation at University College London, found that every major technological transformation in the US, from electric cars to Google to the iPhone, can trace its roots back to basic science research once funded by the federal government. If the past offers any lesson, that means every major transformation in the future could be shortchanged with the destruction of that support.

The Trump administration’s distaste for regulation will arguably be a boon in the short term for some parts of the tech industry, including crypto and AI. But the federal workers said the president’s and Musk’s undermining of basic science research will hurt American innovation in the long run. “Rather than investing in the future, you’re burning through scientific capital,” an employee at the State Department said. “You can build off the things you already know, but you’re not learning anything new. Twenty years later, you fall behind because you stopped making new discoveries.”

A global currency

The government doesn’t just give money, either. It supports American science in numerous other ways, and the US reaps the returns. The Department of State helps attract the best students from around the world to American universities. Amid stagnating growth in the number of homegrown STEM PhD graduates, recruiting foreign students remains one of the strongest pathways for the US to expand its pool of technical talent, especially in strategic areas like batteries and semiconductors. Many of those students stay for years, if not the rest of their lives; even if they leave the country, they’ve already spent some of their most productive years in the US and will retain a wealth of professional connections with whom they’ll collaborate, thereby continuing to contribute to US science.

The State Department also establishes agreements between the US and other countries and helps broker partnerships between American and international universities. That helps scientists collaborate across borders on everything from global issues like climate change to research that requires equipment on opposite sides of the world, such as the measurement of gravitational waves.

The international development work of USAID in global health, poverty reduction, and conflict alleviation—now virtually shut down in its entirety—was designed to build up goodwill toward the US globally; it improved regional stability for decades. In addition to its inherent benefits, this allowed American scientists to safely access diverse geographies and populations, as well as plant and animal species not found in the US. Such international interchange played just as critical a role as government funding in many crucial inventions.

Several federal agencies, including the Centers for Disease Control and Prevention, the Environmental Protection Agency, and the National Oceanic and Atmospheric Administration, also help collect and aggregate critical data on disease, health trends, air quality, weather, and more from disparate sources that feed into the work of scientists across the country.

The National Institutes of Health, for example, has since 2015 been running the Precision Medicine Initiative, the only effort of its kind to collect extensive and granular health data from over 1 million Americans who volunteer their medical records, genetic history, and even Fitbit data to help researchers understand health disparities and develop personalized and more effective treatments for disorders from heart and lung disease to cancer. The data set, which is too expensive for any one university to assemble and maintain, has already been used in hundreds of papers that will lay the foundation for the next generation of life-saving pharmaceuticals.

Beyond fueling innovation, a well-supported science and technology ecosystem bolsters US national security and global influence. When people want to study at American universities, attend international conferences hosted on American soil, or move to the US to work or to found their own companies, the US stays the center of global innovation activity. This ensures that the country continues to get access to the best people and ideas, and gives it an outsize role in setting global scientific practices and priorities. US research norms, including academic freedom and a robust peer review system, become global research norms that lift the overall quality of science. International agencies like the World Health Organization take significant cues from American guidance.

US scientific leadership has long been one of the country’s purest tools of soft power and diplomacy as well. Countries keen to learn from the American innovation ecosystem and to have access to American researchers and universities have been more prone to partner with the US and align with its strategic priorities.

Just one example: Science diplomacy has long played an important role in maintaining the US’s strong relationship with the Netherlands, which is home to ASML, the only company in the world that can produce the extreme ultraviolet lithography machines needed to produce the most advanced semiconductors. These are critical for both AI development and national security.

International science cooperation has also served as a stabilizing force in otherwise difficult relationships. During the Cold War, the US and USSR continued to collaborate on the International Space Station; during the recent heightened economic competition between the US and China, the countries have remained each other’s top scientific partners. “Actively working together to solve problems that we both care about helps maintain the connections and the context but also helps build respect,” Seligsohn says.

The federal government itself is a significant beneficiary of the country’s convening power for technical expertise. Among other things, experts both inside and outside the government support its sound policymaking in science and technology. During the US Senate AI Insight Forums, co-organized by Senator Chuck Schumer through the fall of 2023, for example, the Senate heard from more than 150 experts, many of whom were born abroad and studying at American universities, working at or advising American companies, or living permanently in the US as naturalized American citizens.

Federal scientists and technical experts at government agencies also work on wide-ranging goals critical to the US, including building resilience in the face of an increasingly erratic climate; researching strategic technologies such as next-generation battery technology to reduce the country’s reliance on minerals not found in the US; and monitoring global infectious diseases to prevent the next pandemic.

“Every issue that the US faces, there are people that are trying to do research on it and there are partnerships that have to happen,” the State Department employee said.

A system in jeopardy

Now the breadth and velocity of the Trump administration’s actions has led to an unprecedented assault on every pillar upholding American scientific leadership.

For starters, the purging of tens of thousands—and perhaps soon hundreds of thousands—of federal workers is removing scientists and technologists from the government and paralyzing the ability of critical agencies to function. Across multiple agencies, science and technology fellowship programs, designed to bring in talented early-career staff with advanced STEM degrees, have shuttered. Many other federal scientists were among the thousands who were terminated as probationary employees, a status they held because of the way scientific roles are often contractually structured.

Some agencies that were supporting or conducting their own research, including the National Institutes of Health and the National Science Foundation, are no longer functionally operational. USAID has effectively shuttered, eliminating a bastion of US expertise, influence, and credibility overnight.

“Diplomacy is built on relationships. If we’ve closed all these clinics and gotten rid of technical experts in our knowledge base inside the government, why would any foreign government have respect for the US in our ability to hold our word and in our ability to actually be knowledgeable?” a terminated USAID worker said. “I really hope America can save itself.”

Now the Trump administration has sought to reverse some terminations after discovering that many were key to national security, including nuclear safety employees responsible for designing, building, and maintaining the country’s nuclear weapons arsenal. But many federal workers I spoke to can no longer imagine staying in the public sector. Some are considering going into industry. Others are wondering whether it will be better to move abroad.

“It’s just such a waste of American talent,” said Fiona Coleman, a terminated federal scientist, her voice cracking with emotion as she described the long years of schooling and training she and her colleagues went through to serve the government.

Many fear the US has also singlehandedly kneecapped its own ability to attract talent from abroad. Over the last 10 years, even as American universities have continued to lead the world, many universities in other countries have rapidly leveled up. That includes those in Canada, where liberal immigration policies and lower tuition fees have driven a 200% increase in international student enrollment over the last decade, according to Anna Esaki-Smith, cofounder of a higher-education research consultancy called Education Rethink and author of Make College Your Superpower.

Germany has also seen an influx, thanks to a growing number of English-taught programs and strong connections between universities and German industry. Chinese students, who once represented the largest share of foreign students in the US, are increasingly staying at home or opting to study in places like Hong Kong, Singapore, and the UK.

During the first Trump administration, many international students were already more reluctant to come to the US because of the president’s hostile rhetoric. With the return and rapid escalation of that rhetoric, Esaki-Smith is hearing from some universities that international students are declining their admissions offers.

Add to that the other recent developments—the potential dramatic cuts in federal research funding, the deletion of scores of rich public data sets on health and the environment, the clampdown on academic freedom for research that appears related to diversity, equity, and inclusion and the fear that these restrictions could ultimately encompass other politically charged topics like climate change or vaccines—and many more international science and engineering students could decide to head elsewhere.

“I’ve been hearing this increasingly from several postdocs and early-career professors, fearing the cuts in NIH or NSF grants, that they’re starting to look for funding or job opportunities in other countries,” Coleman told me. “And then we’re going to be training up the US’s competitors.”

The attacks could similarly weaken the productivity of those who stay at American universities. While many of the Trump administration’s actions are now being halted and scrutinized by US judges, the chaos has weakened a critical prerequisite for tackling the toughest research problems: a long-term stable environment. With reports that the NSF is combing through research grants for words like “women,” “diverse,” and “institutional” to determine whether they violate President Trump’s executive order on DEIA programs, a chilling effect is also setting in among federally funded academics uncertain whether they’ll get caught in the dragnet.

To scientists abroad, the situation in the US government has marked American institutions and researchers as potentially unreliable partners, several federal workers told me. If international researchers think collaborations with the US can end at any moment when funds are abruptly pulled or certain topics or keywords are suddenly blacklisted, many of them could steer clear and look to other countries. “I’m really concerned about the instability we’re showing,” another employee at the State Department said. “What’s the point in even engaging? Because science is a long-term initiative and process that outlasts administrations and political cycles.”

Meanwhile, international scientists have far more options these days for high-caliber colleagues to collaborate with outside America. In recent years, for example, China has made a remarkable ascent to become a global peer in scientific discoveries. By some metrics, it has even surpassed the US; it started accounting for more of the top 1% of most-cited papers globally, often called the Nobel Prize tier, back in 2019 and has continued to improve the quality of the rest of its research. 

Where Chinese universities can also entice international collaborators with substantial resources, the US is more limited in its ability to offer tangible funding, the State employee said. Until now, the US has maintained its advantage in part through the prestige of its institutions and its more open cultural norms, including stronger academic freedom. But several federal scientists warn that this advantage is dissipating. 

“America is made up of so many different people contributing to it. There’s such a powerful global community that makes this country what it is, especially in science and technology and academia and research. We’re going to lose that; there’s not a chance in the world that we’re not going to lose that through stuff like this,” says Brigid Cakouros, a federal scientist who was also terminated from USAID. “I have no doubt that the international science community will ultimately be okay. It’ll just be a shame for the US to isolate themselves from it.”

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Beacon advances deepwater Gulf developments with Monument, Zephyrus field work

Beacon Offshore Energy LLC is advancing two deepwater Gulf of Mexico developments, having drilled the first development well at Monument field and brought a second production well online at Zephyrus field. At Monument in Walker Ridge Block 315, the first development well reached a total depth of 32,250 ft and encountered 245 ft of net pay (true vertical thickness) in Lower Wilcox reservoirs, confirming pre-drill expectations for reservoir quality, the operator said. Beacon will continue drilling a second development well before completing the initial two-well program. First oil from the Wilcox development is expected before yearend 2026. Monument is being developed through a two-well, 17-mile subsea tieback to the Beacon-operated Shenandoah floating production system, which was designed as a regional host platform for developments in the northwestern Walker Ridge area, including Shenandoah, Monument, and Shenandoah South fields. Partners are Navitas Petroleum and Talos Energy Inc. At Zephyrus in Mississippi Canyon Block 759, production from the Zephyrus #2 well began in late April after the well was completed in first-quarter 2026. The well is producing from Miocene sands.  Combined with Zephyrus #1, which started production in late 2025, the field is expected to reach peak production of more than 20,000 boe/d. The Zephyrus development is tied back to the Shell plc-operated West Boreas subsea infrastructure, with production processed on the Olympus tension-leg platform in the Mars corridor. Partners are Houston Energy, HEQ II, Red Willow Offshore, Westlawn Americas Offshore, and Murphy Exploration & Production.

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Greece approves Chevron’s farm-in for offshore Block 10

Greece approved Chevron Corp.’s farm-in to offshore Block 10, clearing the way for the US major to complete its acquisition of a 70% interest and operatorship from HELLENiQ Energy. Greece’s Ministry of Environment and Energy and the Hellenic Hydrocarbon and Energy Resources Management Co. (HHRE) said June 15 that all administrative approvals have been completed for the transfer of the interest and operatorship. Chevron and HELLENiQ submitted the request for approval May 28. The companies also requested a 15-month extension of the second exploration phase for the block, which lies offshore the Kyparissia Gulf in the southern Ionian Sea. Following completion of the transfer, Chevron will hold a 70% interest and serve as operator, while HELLENiQ will retain the remaining 30%. Geological, geophysical, and environmental studies have been completed on the concession, including acquisition of 1,210 km of 2D seismic data in 2022 followed by 2,416 sq km of 3D seismic covering 88% of the block. The partners will use the seismic data to evaluate potential drilling targets before deciding whether to proceed to a third exploration phase, which includes an exploratory well. Chevron and HELLENiQ are already partners in four offshore concessions south of Crete and the Peloponnese, making Block 10 their fifth joint offshore license in Greece. Chevron said the agreement advances its strategy of expanding its exploration portfolio in the Eastern Mediterranean. Greek officials said the investment reflects confidence in the country’s offshore licensing framework and supports its long-term goal of strengthening Greece’s role in regional energy supply if exploration proves successful.

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Comstock farms out minority interest in midstream subsidiary for $600 million

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Equinor aims to boost oil, gas production to 2.3 MMboe/d by 2030

Equinor ASA said it plans to increase oil and gas production to about 2.3 MMboe/d by 2030, supported by higher output from the Norwegian continental shelf (NCS) and international upstream growth.  The company, as part of its Capital Markets Day 2026, said it expects total production to rise by 150,000 boe/d by 2030, with NCS output increasing about 100,000 boe/d to 1.35 MMboe/d and international oil and gas production growing about 30% to roughly 950,000 boe/d. NCS-led upstream growth strategy Equinor described the NCS as the backbone of its upstream business and a key driver of long-term cash flow and value creation, with around 60% of capital expenditure directed to the basin. The operator plans to industrialize subsea field developments and increase recovery activity to accelerate resource maturation and reduce costs, targeting 6-8 new tieback projects per year toward 2035, noting the operating model shift aims to support a larger portfolio of subsea developments and increased recovery projects across the NCS. The NCS portfolio includes projects with break-even prices below US$35/bbl and payback times of less than 2.5 years. Continued increased recovery and exploration activity are expected to add new recoverable resources and extend field life, the company said. International oil and gas will account for about 30% of capital expenditure, with growth supported by assets in the United States, Brazil, Angola, the United Kingdom, and Canada. Across its international portfolio, production is expected to increase about 30% to roughly 950,000 boe/d by 2030. Total annual capex is guided to $11-13 billion in 2028-2030, following about $12 billion in 2027, including an additional $1 billion investment in high-return oil and gas projects that year.

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Edge networks a particular challenge for summer power, IT staffing needs

Power failures continue to dominate data center outage causes, accounting for 45% of impactful outages in Uptime Institute’s recently released 2026 Annual Outage Analysis report. While that figure declined from the previous year, it remains significantly higher than any other category. Within power-related incidents, UPS failures, transfer switch failures, and generator failures are the leading root causes. Uptime analysts said growing grid instability, power constraints, and high-density compute deployments are creating new pressure points for operators already running closer to capacity limits, according to a recent story on the report in Network World. Beyond power issues, hardware failures—particularly related to storage—also contribute to downtime. He noted that a lack of routine updates, especially to firmware, can make these problems worse, even when the underlying hardware is still functional.

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Turn enterprise AI into real business value with a secure, scalable factory

Building an enterprise AI factory is a complex endeavor that few organizations can tackle alone. The solution requires infrastructure capable of managing massive compute workloads generated by AI training and inferencing, high-capacity/low-latency networking within data centers and to the edge, and security to mitigate the risks that AI introduces. Abhinav Joshi, leader of AI solutions and product marketing at Cisco, identifies three key challenges inherent in building enterprise AI infrastructure: deployment complexity, security vulnerabilities, and performance bottlenecks. Agentic AI, with its heavy reliance on inferencing, places greater demands on infrastructure across all three dimensions. 3 challenges in building enterprise AI factories The deployment complexity challenge is driven by the need to quickly operationalize an AI infrastructure that fully integrates compute, networking, storage, security, and observability. A Kubernetes-based container management platform and a robust AI software toolchain are likewise essential to ensure the consistent development, testing, and deployment of containerized AI applications, Joshi says. The second challenge is mitigating security vulnerabilities. “Many organizations lack integrated security measures to protect the AI models, frameworks, applications, and the supporting infrastructure throughout the stack,” Joshi says. Attackers can exploit vulnerabilities by manipulating large language models (LLMs) with malicious inputs, which can disrupt operations and extract sensitive information. As AI agents ingest diverse data and act independently, they introduce new attack surfaces, including prompt injection, model poisoning, and data leaks.  Performance, especially around networking, is the third challenge. Tasks such as pre-training, post-training, and fine-tuning AI models, along with retrieval-augmented generation (RAG) pipelines and inferencing (including reasoning and agentic) all generate enormous amounts of network traffic. This creates severe bottlenecks across three critical communication paths: high-speed interconnects between graphics processing unit (GPU) servers, data throughput to storage layers, and real-time response delivery to end users. Without high-performance network connections, GPUs may be underutilized and jobs

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MSI’s Strategic Shift: From Server Vendor to Full-Spectrum AI Infrastructure Provider

The 100 kW rack figure places MSI’s offering squarely in the world of AI-era rack densities, where conventional air cooling becomes increasingly difficult or inefficient. The announcement also suggests that MSI is aligning with hyperscale and large cloud design principles, particularly through ORv3 and 48V power distribution. The company is moving from the “we have servers that can be liquid cooled” message, to “we can participate in rack-level AI infrastructure design.” The EIA air-cooled architecture, by contrast, is designed for more conventional data center environments. MSI says its 19-inch, 48RU EIA air-cooled rack supports standard deployments and can be configured with 16 2U2N multi-node systems, with AMD EPYC 9005 and Intel Xeon 6 platform options. That split matters because the AI infrastructure market is not moving in one uniform direction. Hyperscalers, neoclouds, and AI factories may move aggressively into ORv3, liquid cooling, busbar power, and rack-scale designs. Enterprise data centers, managed service providers, and colocation customers often need to work within existing 19-inch rack footprints and existing facility constraints. MSI wants to supply both markets. The CG681-S6093: MSI’s Flagship Liquid-Cooled AI Server The centerpiece of MSI’s NVIDIA-based AI server announcement is the CG681-S6093, a 6U liquid-cooled AI server based on NVIDIA MGX architecture. MSI says the system supports dual AMD EPYC processors and up to eight NVIDIA RTX PRO 6000 Blackwell Server Edition Liquid Cooled GPUs. It also supports 32 DDR5 DIMMs and NVIDIA ConnectX-8 SuperNICs with up to 8×400Gbps networking. This system is a direct entry into high-density AI inference, HPC, simulation, graphics, video, and physical AI workloads. The server is not positioned only for frontier model training. Instead, MSI appears to be aiming at the expanding middle of the AI infrastructure market: large inference clusters, visual computing, simulation, industrial AI, scientific computing, and agentic AI workloads. The next

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Cooling at AI Scale: Inside Motivair’s Blueprint for the Liquid-Cooled Data Center

BUFFALO, N.Y. — In the race to build AI infrastructure, the industry often focuses on GPUs, power availability, and the massive capital investments reshaping the digital infrastructure landscape. But a walk through Motivair’s manufacturing facility in Buffalo, as provided on the eve of the Motivair-Schneider Electric Global Press Event’s tour of the nearby Terawulf Lake Mariner AI campus, offers a reminder that another critical component of the AI boom is being built one coolant distribution unit at a time. During a recent Data Center Frontier Show podcast recorded at Motivair’s Buffalo headquarters, CEO Rich Whitmore described a reality that is becoming bedrock across the industry: Liquid cooling is now very far from being an emerging technology. It is now a prerequisite for deploying the most advanced AI systems. “You cannot deploy AI servers—at least the cutting-edge AI servers—without liquid cooling,” Whitmore said. That observation may be obvious to infrastructure veterans. Yet it points to a larger shift now underway across the data center ecosystem. As AI workloads drive rack densities beyond the practical limits of air cooling, thermal infrastructure has moved from a supporting role to a primary design consideration. For Whitmore and Motivair, that transition did not begin with ChatGPT. From Supercomputing to Commercial AI Long before AI became the defining growth story of the data center sector, Motivair was developing liquid cooling systems for high-performance computing and supercomputing environments. Whitmore describes today’s AI market as less of a technological revolution than a commercialization of capabilities that have existed for years inside elite computing environments. “We cut our teeth in high-performance computing and supercomputing,” Whitmore explained. “What we’re seeing today as we go into the AI era is really a commercialization of traditional supercomputing.” That experience has positioned Motivair differently than many newer entrants rushing into the liquid cooling

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From Components to AI Factories: Peter Panfil Says the Future of Data Centers Is All About Integration at Scale

ORLANDO, Fla. — For years, the data center industry optimized individual systems: power distribution, cooling, racks, UPS equipment, and mechanical infrastructure. In the AI era, according to Vertiv Distinguished Engineer and Vice President of Technical Business Development Peter Panfil, that approach is no longer sufficient. Speaking during Wednesday morning’s keynote at the 2026 7×24 Exchange Spring Conference, Panfil presented a vision in which the data center itself becomes a single, tightly orchestrated computing appliance—truly an “AI factory” whose success depends less on standalone components than on the seamless interaction between them. Throughout his presentation, titled “Scale at Speed: How Massively Parallel Compute GPUs Are Revolutionizing Data Center Design,” Panfil repeatedly returned to a single imperative: the AI infrastructure race is increasingly defined by execution velocity. “If you think you’re going big enough, go bigger,” he told attendees. “If you think you’re going fast enough, you’re going to have to go faster.” For an industry gathered under the conference’s overarching theme of future-proofing AI infrastructure, Panfil’s message suggested something subtly different. Rather than trying to predict the future, operators should build systems capable of adapting to it. “I would much rather be future ready,” he said, “than future proof.” Speed Becomes the New Competitive Metric One of the keynote’s recurring themes was that deployment speed has become an economic variable in its own right. Panfil argued that hyperscalers and AI providers increasingly view time-to-capacity as directly tied to business value, making delays in construction or commissioning far more expensive than traditional infrastructure inefficiencies. “The cost of speeding up has real benefits right now,” he observed. That urgency is changing the way facilities are assembled. Rather than coordinating numerous independent contractors and subsystem vendors on-site, Panfil described an emerging model built around highly standardized, factory-produced HAC [hot aisle containment] modules—or “hacks”—that arrive

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Beyond the GPU: Cisco Says AI’s Biggest Challenge May Be the Network That Connects It All

For much of the AI boom, the industry’s attention has centered on GPUs, power availability, and liquid cooling. But according to Cisco Senior Business Development Manager Robin Olds, another critical constraint is rapidly moving to the forefront: the network itself. Speaking with Data Center Frontier on the show floor at Fiber Connect 2026, Olds argued that AI represents a once-in-a-generation shift comparable to the birth of the commercial internet, fundamentally changing traffic patterns and forcing service providers, data center operators, hyperscalers, and emerging neoclouds to rethink infrastructure design. “It’s really like the internet when it was created,” Olds said. “We’re at another intersection in time where we could really see things happening.” AI Is Rewriting the Bandwidth Equation The most significant change may not be compute density alone but the sustained demand AI places on transport networks. According to Olds, service providers are already seeing AI traffic account for roughly 30% of utilization on backbone infrastructure; a dramatic increase from less than 1% only two years ago. As AI workloads continue to proliferate, those utilization levels are expected to rise further. The next wave of agentic AI could amplify that trend. Unlike consumer chatbots, which generate bursty request patterns, autonomous AI agents continuously interact with applications and external services, creating more persistent traffic flows. “Everything’s about chatbots,” Olds observed. “It’s very spiky—up, down. Agentic AI is going to maintain utilization because now I have agents working on my behalf.” For data center developers, network operators, and cloud providers alike, that implies planning not just for peak demand but for elevated baseline utilization across metro and long-haul infrastructure. Compressing the Network Stack Cisco’s response centers on architectural simplification. Olds highlighted the company’s Agile Services Networking framework, which combines router and optical networking technologies with coherent optics to converge functions that historically

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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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