America’s climate brain drain is real — and it’s just getting started

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America’s climate brain drain is real — and it’s just getting started

Joe Curtatone is president of the Alliance for Climate Transition. While China now leads the U.S. in the number of patents, the United States has long been the global leader in scientific innovation and technological breakthroughs. From launching the internet to decoding the human genome, our universities, national labs and startup ecosystems have powered progress […]

Joe Curtatone is president of the Alliance for Climate Transition.

While China now leads the U.S. in the number of patents, the United States has long been the global leader in scientific innovation and technological breakthroughs. From launching the internet to decoding the human genome, our universities, national labs and startup ecosystems have powered progress not just at home, but across the globe.

But that leadership is now at serious risk — especially in climate and tough tech sectors — thanks to a combination of short-sighted federal policies, tariffs, attacks on academic institutions and an increasingly hostile posture toward international students and researchers.

At the heart of this crisis is a growing brain drain — a phenomenon where top talent, including scientists, engineers and entrepreneurs, increasingly look outside the U.S. to study, work and build the technologies of the future.

The warning signs are everywhere. In recent months, we’ve seen sweeping attempts by the current administration to undermine the independence and integrity of university research, especially in areas tied to climate science, advanced energy and environmental policy. Key research grants have been frozen or redirected based on political ideology. Experts have been sidelined or dismissed. Federal agencies have been pressured to strip climate and environmental language from their reports. The message is clear: If your work doesn’t align with the administration’s narrative, you may be punished for it.

Simultaneously, international scholars and students — the lifeblood of many of our top science and engineering programs — are being pushed away. Visas are being revoked without due process, delays are mounting and the overall tone from federal leadership is one of suspicion and exclusion.

This isn’t just bad optics. It directly threatens our innovation economy and the recovery could take decades.

Engineering, environmental science and computer science international students don’t just study here — they launch startups, file patents, drive new discoveries and often stay to build companies that hire American workers. When we shut the door on them, we don’t just lose individuals; we lose the ripple effect of their ideas and impact.

At the same time, American students and researchers, including 75% of those polled in Nature Magazine, are beginning to look elsewhere for higher education, lab space and research dollars, especially those interested in climate and technology fields. Canada, the United Kingdom, the European Union, and even countries like Singapore and Australia are investing in university programs, visa pathways and research incentives designed to attract the very talent the U.S. is pushing away.

This trend is amplified by the fact that other nations are doubling down on venture capital and public investment in clean tech and tough tech sectors. While Washington debates the existence of climate change, countries like Germany, South Korea and the Netherlands are aggressively funding battery innovation, green hydrogen and next-gen energy storage. China has already outpaced the U.S. in solar manufacturing and is gaining ground in electric vehicles and grid-scale technologies. These nations see climate tech not just as a moral imperative but as a defining economic opportunity — one that will shape jobs, industries and global influence for decades.

Meanwhile, the U.S. risks losing its seat at the table.

Let’s be clear: The climate crisis isn’t going away. The demand for clean energy, carbon removal, climate adaptation and climate tech innovation will only grow, regardless of who sits in the White House. The question is whether the U.S. wants to lead this future or fall behind.

We need to reverse course. That means restoring integrity and independence to our research institutions, welcoming international talent instead of repelling it and investing boldly in the technologies that will define the next economy. It also means defending higher education — not undermining it — for its critical role in preparing the next generation of problem-solvers.

Because if we don’t, others will. And we may find that when we’re ready to catch up, the world has already moved on — without us.

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Charging Forward: Centrica flags Rough shutdown in blow to hydrogen storage hopes

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Transmission charging adds £1bn to Scottish offshore wind farm costs

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Petrofac restructuring approved by courts as it looks to ‘healthy pipeline of future opportunities’

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Tariff uncertainty weighs on networking vendors

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“Facility water loops sometimes have good water quality, sometimes bad,” says My Troung, CTO at ZutaCore, a liquid cooling company. “Sometimes you have organics you don’t want to have inside the technical loop.” So there’s one set of pipes that goes around the data center, collecting the heat from the server racks, and another set of smaller pipes that lives inside individual racks or servers. “That inner loop is some sort of technical fluid, and the two loops exchange heat across a heat exchanger,” says Troung. The most common approach today, he says, is to use a single-phase liquid — one that stays in liquid form and never evaporates into a gas — such as water or propylene glycol. But it’s not the most efficient option. Evaporation is a great way to dissipate heat. That’s what our bodies do when we sweat. When water goes from a liquid to a gas it’s called a phase change, and it uses up energy and makes everything around it slightly cooler. Of course, few servers run hot enough to boil water — but they can boil other liquids. “Two phase is the most efficient cooling technology,” says Xianming (Simon) Dai, a professor at University of Texas at Dallas. And it might be here sooner than you think. In a keynote address in March at Nvidia GTC, Nvidia CEO Jensen Huang unveiled the Rubin Ultra NVL576, due in the second half of 2027 — with 600 kilowatts per rack. “With the 600 kilowatt racks that Nvidia is announcing, the industry will have to shift very soon from single-phase approaches to two-phase,” says ZutaCore’s Troung. Another highly-efficient cooling approach is immersion cooling. According to a Castrol survey released in March, 90% of 600 data center industry leaders say that they are considering switching to immersion

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“If you want to ask Codex a question about your codebase, click “Ask”. Each task is processed independently in a separate, isolated environment preloaded with your codebase. Codex can read and edit files, as well as run commands including test harnesses, linters, and type checkers. Task completion typically takes between 1 and 30 minutes, depending on complexity, and you can monitor Codex’s progress in real time,” according to OpenAI. “Once Codex completes a task, it commits its changes in its environment. Codex provides verifiable evidence of its actions through citations of terminal logs and test outputs, allowing you to trace each step taken during task completion,” OpenAI wrote. “You can then review the results, request further revisions, open a GitHub pull request, or directly integrate the changes into your local environment. In the product, you can configure the Codex environment to match your real development environment as closely as possible.” OpenAI is releasing Codex as a research preview: “We prioritized security and transparency when designing Codex so users can verify its outputs – a safeguard that grows increasingly more important as AI models handle more complex coding tasks independently and safety considerations evolve. Users can check Codex’s work through citations, terminal logs and test results,” OpenAI wrote. Internally, technical teams at OpenAI have started using Codex. “It is most often used by OpenAI engineers to offload repetitive, well-scoped tasks, like refactoring, renaming, and writing tests, that would otherwise break focus. It’s equally useful for scaffolding new features, wiring components, fixing bugs, and drafting documentation,” OpenAI stated. Cisco’s view of agentic AI Patel stated that Codex is part of the developing AI agent world, where Cisco envisions billions of AI agents will work together to transform and redefine the architectural assumptions the industry has relied on. Agents will communicate within and

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AMD announced a five-year, $10 billion collaboration with Humain to deploy up to 500 megawatts of AI compute in Saudi Arabia and the US, aiming to deploy “multi-exaflop capacity by early 2026.” AWS, too, is expanding its data centers in Saudi Arabia to bolster Humain’s cloud infrastructure. Saudi Arabia has abundant oil and gas to power those data centers, and is growing its renewable energy resources with the goal of supplying 50% of the country’s power by 2030. “Commercial electricity rates, nearly 50% lower than in the US, offer potential cost savings for AI model training, though high local hosting costs due to land, talent, and infrastructure limit total savings,” said Eric Samuel, Associate Director at IDC. Located near Middle Eastern population centers and fiber optic cables to Asia, these data centers will offer enterprises low-latency cloud computing for real-time AI applications. Late is great There’s an advantage to being a relative latecomer to the technology industry, said Eric Samuel, associate director, research at IDC. “Saudi Arabia’s greenfield tech landscape offers a unique opportunity for rapid, ground-up AI integration, unburdened by legacy systems,” he said.

AMD, Nvidia partner with Saudi startup to build multi-billion dollar AI service centers

Humain will deploy the Nvidia Omniverse platform as a multi-tenant system to drive acceleration of the new era of physical AI and robotics through simulation, optimization and operation of physical environments by new human-AI-led solutions. The AMD deal did not discuss the number of chips involved in the deal, but it is valued at $10 billion. AMD and Humain plan to develop a comprehensive AI infrastructure through a network of AMD-based AI data centers that will extend from Saudi Arabia to the US and support a wide range of AI workloads across corporate, start-up, and government markets. Think of it as AWS but only offering AI as a service. AMD will provide its AI compute portfolio – Epyc, Instinct, and FPGA networking — and the AMD ROCm open software ecosystem, while Humain will manage the delivery of the hyperscale data center, sustainable power systems, and global fiber interconnects. The partners expect to activate a multi-exaflop network by early 2026, supported by next-generation AI silicon, modular data center zones, and a software platform stack focused on developer enablement, open standards, and interoperability. Amazon Web Services also got a piece of the action, announcing a more than $5 billion investment to build an “AI zone” in the Kingdom. The zone is the first of its kind and will bring together multiple capabilities, including dedicated AWS AI infrastructure and servers, UltraCluster networks for faster AI training and inference, AWS services like SageMaker and Bedrock, and AI application services such as Amazon Q. Like the AMD project, the zone will be available in 2026. Humain only emerged this month, so little is known about it. But given that it is backed by Crown Prince Salman and has the full weight of the Kingdom’s Public Investment Fund (PIF), which ranks among the world’s largest and

Check Point CISO: Network segregation can prevent blackouts, disruptions

Fischbein agrees 100% with his colleague’s analysis and adds that education and training can help prevent such incidents from occurring. “Simulating such a blackout is impossible, it has never been done,” he acknowledges, but he is committed to strengthening personal and team training and risk awareness. Increased defense and cybersecurity budgets In 2025, industry watchers expect there will be an increase in the public budget allocated to defense. In Spain, one-third of the budget will be allocated to increasing cybersecurity. But for Fischbein, training teams is much more important than the budget. “The challenge is to distribute the budget in a way that can be managed,” he notes, and to leverage intuitive and easy-to-use platforms, so that organizations don’t have to invest all the money in training. “When you have information, management, users, devices, mobiles, data centers, clouds, cameras, printers… the security challenge is very complex. You have to look for a security platform that makes things easier, faster, and simpler,” he says. ” Today there are excellent tools that can stop all kinds of attacks.” “Since 2010, there have been cybersecurity systems, also from Check Point, that help prevent this type of incident from happening, but I’m not sure that [Spain’s electricity blackout] was a cyberattack.” Leading the way in email security According to Gartner’s Magic Quadrant, Check Point is the leader in email security platforms. Today email is still responsible for 88% of all malicious file distributions. Attacks that, as Fischbein explains, enter through phishing, spam, SMS, or QR codes. “There are two challenges: to stop the threats and not to disturb, because if the security tool is a nuisance it causes more harm than good. It is very important that the solution does not annoy [users],” he stresses. “As almost all attacks enter via e-mail, it is

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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

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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

Google just leapfrogged every competitor with mind-blowing AI that can think deeper, shop smarter, and create videos with dialogue

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google announced a sweeping set of

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