The U.S. and China Are Pursuing Different AI Futures

More money has been invested in AI than it took to land on the moon. Spending on the technology this year is projected to reach up to $700 billion, almost double last year’s spending. Part of the impetus for this frantic outlay is a conviction among investors and policymakers in the United States that it needs to “beat China.” Indeed, headlines have long cast AI development as a zero-sum rivalry between the U.S. and China, framing the technology’s advance as an arms race with a defined finish line. The narrative implies speed, symmetry, and a common objective.

But a closer look at AI development in the two countries shows they’re not only not racing toward the same finish line: “The U.S. and China are running in very different lanes,” says Selina Xu, who leads China and AI policy research for Eric Schmidt, the tech investor, philanthropist and former Google chief, in New York City. “The U.S. is doubling down on scaling,” in pursuit of artificial general intelligence (AGI) Xu says, “while for China it’s more about boosting economic productivity and real-world impact.”

Lumping the U.S. and China onto a single AI scoreboard isn’t just inaccurate, it can impact policy and business decisions in a harmful way. “An arms race can become a self-fulfilling prophecy,” Xu says. “If companies and governments all embrace a ‘race to the bottom’ mentality, they will eschew necessary security and safety guardrails for the sake of being ahead. That increases the odds of AI-related crises.”

Where’s the Real Finish Line?

As machine learning advanced in the 2010s, prominent public figures such as Stephen Hawking and Elon Musk warned that it would be impossible to separate AI’s general-purpose potential from its military and economic implications, echoing Cold War–era frameworks for strategic competition. “An arms race is an easy way to think about this situation even if it’s not exactly right,” says Karson Elmgren, a China researcher at the Institute for AI Policy and Strategy, a think tank in San Francisco. Frontier labs, investors, and media benefit from simple, comparable progress metrics, like larger models, better benchmarks, and more computing power, so they favor and compound the arms race framing.

Artificial general intelligence is the implied “finish line” if AI is an arms race. But one of the many problems with an AGI finish line is that by its very nature, a machine superintelligence would be smarter than humans and therefore impossible to control. “If superintelligence were to emerge in a particular country, there’s no guarantee that that country’s interests are going to win,” says Graham Webster, a China researcher at Stanford University, in Palo Alto, California.

An AGI finish line also assumes the U.S. and China are both optimizing for this goal and putting the majority of their resources towards it. This isn’t the case, as the two countries have starkly different economic landscapes.

When Is the Payoff?

After decades of rapid growth, China is now facing a grimmer reality. “China has been suffering through an economic slowdown for a mixture of reasons, from real estate to credit to consumption and youth unemployment,” says Xu, adding that the country’s leaders have been “trying to figure out what is the next economic driver that can get China to sustain its growth.”

Enter AI. Rather than pouring resources into speculative frontier models, Beijing has a pressing incentive to use the technology as a more immediate productivity engine. “In China we define AI as an enabler to improve existing industry, like healthcare, energy, or agriculture,” says AI policy researcher Liang Zheng, of Tsinghua University in Beijing, China. “The first priority is to use it to benefit ordinary people.”

To that end, AI investment in China is focused on embedding the technology into manufacturing, logistics, energy, finance, and public services. “It’s a long-term structural change, and companies must invest more in machines, software, and digitalization,” Liang says. “Even very small and medium enterprises are exploring use of AI to improve their productivity.”

China’s AI Plus initiative encourages using AI to boost efficiency. “Having a frontier technology doesn’t really move China towards an innovation-led developed economy,” says Kristy Loke, a fellow at MATS Research who focuses on China’s AI innovation and governance strategies. Instead, she says, “It’s really important to make sure that [these tools] are able to meet the demands of the Chinese economy, which are to industrialize faster, to do more smart manufacturing, to make sure they’re producing things in competitive processes.”

Automakers have embraced intelligent robots in “dark factories” with minimal human intervention; as of 2024, China had around five times more factory robots in use than the U.S. “We used to use human eyes for quality control and it was very inefficient,” says Liang. Now, computer vision systems detect errors and software predicts equipment failures, pausing production and scheduling just-in-time maintenance. Agricultural models advise farmers on crop selection, planting schedules, and pest control.

In healthcare, AI tools triage patients, interpret medical images, and assist diagnoses; Tsinghua is even piloting an AI “Agent Hospital” where physicians work alongside virtual clinical assistants. “In hospitals you used to have to wait a long time, but now you can use your agent to make a precise appointment,” Liang says. Many such applications use simpler “narrow AI” designed for specific tasks.

AI is also increasingly embedded across industries in the U.S., but the focus tends toward service-oriented and data-driven applications, leveraging large language models (LLMs) to handle unstructured data and automate communication. For example, banks use LLM-based assistants to help users manage accounts, find transactions, and handle routine requests; LLMs help healthcare professionals extract information from medical notes and clinical documentation.

“LLMs as a technology naturally fit the U.S. service-sector-based economy more so than the Chinese manufacturing economy,” Elmgren says.

Competition and cooperation

The U.S. and China do compete more or less head-to-head in some AI-related areas, such as the underlying chips. The two have grappled to gain enough control over their supply chains to ensure national security, as recent tariff and export control fights have shown. “I think the main competitive element from a top level [for China] is to wriggle their way out of U.S. coercion over semiconductors. They want to have an independent capability to design, build, and package advanced semiconductors,” Webster says.

Military applications of AI are also a significant arena of U.S.–China competition, with both governments aiming to speed decision-making, improve intelligence, and increase autonomy in weapons systems. The U.S. Department of Defense launched its AI Acceleration Strategy last month, and China has explicitly integrated AI into its military modernization strategy under its policy of military-civil fusion. “From the perspective of specific military systems, there are incremental advantages that one side or the other can gain,” Webster says.

Despite China’s commitment to military and industrial applications, it has not yet picked an AI national champion. “After Deepseek in early 2025 the government could have easily said, ‘You guys are the winners, I’ll give you all the money, please build AGI,’ but they didn’t. They see being ‘close enough’ to the technological frontier as important, but putting all eggs in the AGI basket as a gamble,” Loke says.

American companies are also still working with Chinese technology and workers, despite a slow uncoupling of the two economies. Though it may seem counterintuitive, more cooperation—and less emphasis on cutthroat competition—could yield better results for all. “For building more secure, trustworthy AI, you need both U.S. and Chinese labs and policymakers to talk to each other, to reach consensus on what’s off limits, then compete within those boundaries,” Xu says. “The arms race narrative also just misses the actual on-the-ground reality of companies co-opting each other’s approaches, the amount of research that gets exchanged in academic communities, the supply chains and talent that permeates across borders, and just how intertwined the two ecosystems are.”

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IEEE Course Improves Engineers’ Writing Skills

In the rapidly evolving world of engineering technology, professionals devote enormous energy to such tasks as mastering the latest frameworks, optimizing architectures, and refining machine learning models. It’s easy to let technical expertise become the sole measure of professional value. However, one of the most important skills an engineer can develop is the capacity to write and communicate effectively.

Whether you’re conducting research at a university or leading systems development projects at a global firm, your expertise can become impactful only when you share it in a way that others can understand and act upon. Without a clear narrative, even groundbreaking data or innovative designs can fail to gain traction, limiting their reach among colleagues and stakeholders, and in peer‑reviewed journals.

The cost of the “soft skill” misnomer

Writing is often labeled a “soft skill”—which can diminish its importance. In reality, communication is a core engineering competency. It lets us document methods, articulate research findings, and persuade decision-makers who determine whether projects move forward.

If your writing is dense, disorganized, or overloaded with technical jargon, the value of the underlying work can become obscured. A strong proposal might be dismissed not because the idea lacks merit but because the justification is difficult to follow.

Clear writing can strengthen the impact of your work. Poor writing can distract from the points you’re trying to make, as readers might not understand what you’re saying.

The architecture of authority

Technical writing differs from other forms of prose because readers expect information to follow predictable, logical patterns. Unclear writing can leave readers unsure of the author’s intent.

One of the most enduring frameworks for writing about technology in an understandable manner is the IMRaD structure: introduction, methods, results, and discussion.

• Introduction: Define the problem and its relevance.
• Methods: Detail the approach and justify the choices.
• Results: Present the empirical findings.
• Discussion: Interpret the outcomes and their implications.

More than just a template for academic papers, IMRaD is a road map for logical reasoning. Mastering the structure can help engineers communicate in a way that aligns with professional writing standards used in technical journals, so their work is better understood and more respected.

Bridging the training gap

Despite technical communication’s importance, engineering curricula often limit or lack formal instruction in it.

Recognizing that gap, IEEE has expanded its role as a global knowledge leader by offering From Research to Publication: A Step-by-Step Guide to Technical Writing. The course is led by Traci Nathans-Kelly, director of the engineering communications program at Cornell.

Developed by IEEE Educational Activities and the IEEE Professional Communication Society, the learning opportunity goes beyond foundational writing skills. It addresses today’s challenges, such as the ethical use of generative AI in the writing workflow, the complexities of team-based authorship, and publishing strategies.

The program centers on core skill areas that can influence an engineer’s ability to communicate. Participants learn to master the IMRaD structure and learn advanced editing techniques to help strip away jargon, making complex ideas more accessible. In addition, the course covers strategic approaches to publishing work in high‑impact journals and improving a writer’s visibility within the technical community.

The course is available on the IEEE Learning Network. Participants earn professional development credit and a shareable digital badge. IEEE members receive a US $100 discount. Organizations can connect with an IEEE content specialist to offer the training to their teams.

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Tomorrow’s Smart Pills Will Deliver Drugs and Take Biopsies

One day soon, a doctor might prescribe a pill that doesn’t just deliver medicine but also reports back on what it finds inside you—and then takes actions based on its findings.

Instead of scheduling an endoscopy or CT scan, you’d swallow an electronic capsule smaller than a multivitamin. As it travels through your digestive system, it could check tissue health, look for cancerous changes, and send data to your doctor. It could even release drugs exactly where they’re needed or snip a tiny biopsy sample before passing harmlessly out of your body.

This dream of a do-it-all pill is driving a surge of research into ingestible electronics: smart capsules designed to monitor and even treat disease from inside the gastrointestinal (GI) tract. The stakes are high. GI diseases affect tens of millions of people worldwide, including such ailments as inflammatory bowel disease, celiac disease, and small intestinal bacterial overgrowth. Diagnosis often involves a frustrating maze of blood tests, imaging, and invasive endoscopy. Treatments, meanwhile, can bring serious side effects because drugs affect the whole body, not just the troubled gut.

If capsules could handle much of that work—streamlining diagnosis, delivering targeted therapies, and sparing patients repeated invasive procedures—they could transform care. Over the past 20 years, researchers have built a growing tool kit of ingestible devices, some already in clinical use. These capsule-shaped devices typically contain sensors, circuitry, a power source, and sometimes a communication module, all enclosed in a biocompatible shell. But the next leap forward is still in development: autonomous capsules that can both sense and act, releasing a drug or taking a tissue sample.

That’s the challenge that our lab—the MEMS Sensors and Actuators Laboratory (MSAL) at the University of Maryland, College Park—is tackling. Drawing on decades of advances in microelectromechanical systems (MEMS), we’re building swallowable devices that integrate sensors, actuators, and wireless links in packages that are small and safe enough for patients. The hurdles are considerable: power, miniaturization, biocompatibility, and reliability, to name a few. But the potential payoff will be a new era of personalized and minimally invasive medicine, delivered by something as simple as a pill you can swallow at home.

The Origin of Ingestible Devices

The idea of a smart capsule has been around since the late 1950s, when researchers first experimented with swallowable devices to record temperature, gastric pH, or pressure inside the digestive tract. At the time, it seemed closer to science fiction than clinical reality, bolstered by pop-culture visions like the 1966 film Fantastic Voyage, where miniaturized doctors travel inside the human body to treat a blood clot.

One of the authors (Ghodssi) holds a miniaturized drug-delivery capsule that’s designed to release medication at specific sites in the gastrointestinal tract.Maximilian Franz/Engineering at Maryland Magazine

For decades, though, the mainstay of GI diagnostics was endoscopy: a camera on a flexible tube, threaded down the throat or up through the colon. These procedures are quite invasive and require patients to be sedated, which increases both the risk of complications and procedural costs. What’s more, it’s difficult for endoscopes to safely traverse the circuitous pathway of the small intestine. The situation changed in the early 2000s, when video-capsule endoscopy arrived. The best-known product, PillCam, looks like a large vitamin but contains a camera, LEDs, and a transmitter. As it passes through the gut, it beams images and videos to a wearable device.

Today, capsule endoscopy is a routine tool in gastroenterology; ingestible devices can measure acidity, temperature, or gas concentrations. And researchers are pushing further, with experimental prototypes that deliver drugs or analyze the microbiome. For example, teams from Tufts University, in Massachusetts, and Purdue University, in Indiana, are working on devices with dissolvable coatings and mechanisms to collect samples of liquid for studies of the intestinal microbiome.

Still, all those devices are passive. They activate on a timer or by exposure to the neutral pH of the intestines, but they don’t adapt to conditions in real time. The next step requires capsules that can sense biomarkers, make decisions, and trigger specific actions—moving from clever hardware to truly autonomous “smart pills.” That’s where our work comes in.

Building on MEMS technology

Since 2017, MSAL has been pushing ingestible devices forward with the goal of making an immediate impact in health care. The group built on the MEMS community’s legacy in microfabrication, sensors, and system integration, while taking advantage of new tools like 3D printing and materials like biocompatible polymers. Those advances have made it possible to prototype faster and shrink devices smaller, sparking a wave of innovation in wearables, implants, and now ingestibles. Today, MSAL is collaborating with engineers, physicians, and data scientists to move these capsules from lab benches to pharmaceutical trials.

As a first step, back in 2017, we set out to design sensor-carrying capsules that could reliably reach the small intestine and indicate when they reached it. Another challenge was that sensors that work well on the benchtop can falter inside the gut, where shifting pH, moisture, digestive enzymes, and low-oxygen conditions can degrade typical sensing components.

Our earliest prototype adapted MEMS sensing technology to detect abnormal enzyme levels in the duodenum that are linked to pancreatic function. The sensor and its associated electronics were enclosed in a biocompatible, 3D-printed shell coated with polymers that dissolved only at certain pH levels. This strategy could one day be used to detect biomarkers in secretions from the pancreas to detect early-stage cancer.

A high-speed video shows how a capsule deploys microneedles to deliver drugs into intestinal tissue.University of Maryland/Elsevier

That first effort with a passive device taught us the fundamentals of capsule design and opened the door to new applications. Since then, we’ve developed sensors that can track biomarkers such as the gas hydrogen sulfide, neurotransmitters such as serotonin and dopamine, and bioimpedance—a measure of how easily ions pass through intestinal tissue—to shed light on the gut microbiome, inflammation, and disease progression. In parallel, we’ve worked on more-active devices: capsule-based tools for controlled drug release and tissue biopsy, using low-power actuators to trigger precise mechanical movements inside the gut.

Like all new medical devices and treatments, ingestible electronics face many hurdles before they reach patients—from earning physician trust and insurance approval to demonstrating clear benefits, safety, and reliability. Packaging is a particular focus, as the capsules must be easy to swallow yet durable enough to survive stomach acid. The field is steadily proving safety and reliability, progressing from proof of concept in tissue, through the different stages of animal studies, and eventually to human trials. Every stage provides evidence that reassures doctors and patients—for example, showing that ingesting a properly packaged tiny battery is safe, and that a capsule’s wireless signals, far weaker than those of a cellphone, pose no health risk as they pass through the gut.

Engineering a Pill-Size Diagnostic Lab

The gastrointestinal tract is packed with clues about health and disease, but much of it remains out of reach of standard diagnostic tools. Ingestible capsules offer a way in, providing direct access to the small intestine and colon. Yet in many cases, the concentrations of chemical biomarkers can be too low to detect reliably in early stages of a disease, which makes the engineering challenge formidable. What’s more, the gut’s corrosive, enzyme-rich environment can foul sensors in multiple ways, interfering with measurements and adding noise to the data.

Microneedle designs for drug-delivery capsules have evolved over the years. An early prototype [top] used microneedle anchors to hold a capsule in place. Later designs adopted molded microneedle arrays [center] for more uniform fabrication. The most recent version [bottom] integrates hollow microinjector needles, allowing more precise and controllable drug delivery.From top: University of Maryland/Wiley;University of Maryland/Elsevier;University of Maryland/ACS

Take, for example, inflammatory bowel disease, for which there is no standard clinical test. Rather than searching for a scarce biomarker molecule, our team focused on a physical change: the permeability of the gut lining, which is a key factor in the disease. We designed capsules that measure the intestinal tissue’s bioimpedance by sending tiny currents across electrodes and recording how the tissue resists or conducts those currents at different frequencies (a technique called impedance spectroscopy). To make the electrodes suitable for in vivo use, we coated them with a thin, conductive, biocompatible polymer that reduces electrical noise and keeps stable contact with the gut wall. The capsule finishes its job by transmitting its data wirelessly to our computers.

In our lab tests, the capsule performed impressively, delivering clean impedance readouts from excised pig tissue even when the sample was in motion. In our animal studies, it detected shifts in permeability triggered by calcium chelators, compounds that pry open the tight junctions between intestinal cells. These results suggest that ingestible bioimpedance capsules could one day give clinicians a direct, minimally invasive window into gut-barrier function and inflammation. We believe that ingestible diagnostics can serve as powerful tools—catching disease earlier, confirming whether treatments are working, and establishing a baseline for gut health.

Drug Delivery at the Right Place, Right Time

Targeted drug delivery is one of the most compelling applications for ingestible capsules. Many drugs for GI conditions—such as biologics for inflammatory bowel disease—can cause serious side effects that limit both dosage and duration of treatment. A promising alternative is delivering a drug directly to the diseased tissue. This localized approach boosts the drug’s concentration at the target site while reducing its spread throughout the body, which improves effectiveness and minimizes side effects. The challenge is engineering a device that can both recognize diseased tissue and deliver medication quickly and precisely.

With other labs making great progress on the sensing side, we’ve devoted our energy to designing devices that can deliver the medicine. We’ve developed miniature actuators—tiny moving parts—that meet strict criteria for use inside the body: low power, small size, biocompatibility, and long shelf life.

Some of our designs use soft and flexible polymer “cantilevers” with attached microneedle systems that pop out from the capsule with enough force to release a drug, but without harming the intestinal tissue. While hollow microneedles can directly inject drugs into the intestinal lining, we’ve also demonstrated prototypes that use the microneedles for anchoring drug payloads, allowing the capsule to release a larger dose of medication that dissolves at an exact location over time.

In other experimental designs, we had the microneedles themselves dissolve after injecting a drug. In still others, we used microscale 3D printing to tailor the structure of the microneedles and control how quickly a drug is released—providing either a slow and sustained dose or a fast delivery. With this 3D printing, we created rigid microneedles that penetrate the mucosal lining and gradually diffuse the drug into the tissue, and soft microneedles that compress when the cantilever pushes them against the tissue, forcing the drug out all at once.

Tissue Biopsy via Capsule

What Smart Capsules Can Do

Ingestible electronic capsules use miniaturized sensors and actuators to monitor the gut, deliver medication, and collect biological samples.

Sensing

Embedded sensors can probe the gut—for example, measuring the bioimpedance of the intestinal lining to detect disease—and transmit the data wirelessly.All illustrations: Chris Philpot

Drug delivery

Miniature actuators can trigger drug release at specific sites in the gut, boosting effectiveness while limiting side effects.

Biopsy

A spring-loaded mechanism can collect a tiny biopsy sample from the gut wall and store it during the capsule’s passage through the digestive system.

Tissue sampling remains the gold standard diagnostic tool in gastroenterology, offering insights far beyond what doctors can glean from visual inspection or blood tests. Capsules hold unique promise here: They can travel the full length of the GI tract, potentially enabling more frequent and affordable biopsies than traditional procedures. But the engineering hurdles are substantial. To collect a sample, a device must generate significant mechanical force to cut through the tough, elastic muscle of the intestines—while staying small enough to swallow.

Different strategies have been explored to solve this problem. Torsion springs can store large amounts of energy but are difficult to fit inside a tiny capsule. Electrically driven mechanisms may demand more power than current capsule batteries can provide. Magnetic actuation is another option, but it requires bulky external equipment and precise tracking of the capsule inside the body.

Our group has developed a low-power biopsy system that builds on the torsion-spring approach. We compress a spring and use adhesive to “latch” it closed within the capsule, then attach a microheater to the latch. When we wirelessly send current to the device, the microheater melts the adhesive on the latch, triggering the spring. We’ve experimented with tissue-collection tools, integrating a bladed scraper or a biopsy punch (a cylindrical cutting tool) with our spring-activated mechanisms; either of those tools can cut and collect tissue from the intestinal lining. With advanced 3D printing methods like direct laser writing, we can put fine, microscale edges on these miniature cutting tools that make it easier for them to penetrate the intestinal lining.

Storing and protecting the sample until the capsule naturally passes through the body is a major challenge, requiring both preservation of the sample and resealing the capsule to prevent contamination. In one of our designs, residual tension in the spring keeps the bladed scraper rotating, pulling the sample into the capsule and effectively closing a hatch that seals it inside.

The Road to Clinical Use for Ingestibles

Looking ahead, we expect to see the first clinical applications emerge in early-stage screening. Capsules that can detect electrochemical, bioimpedance, or visual signals could help doctors make sense of symptoms like vague abdominal pain by revealing inflammation, gut permeability, tumors, or bacterial overgrowth. They could also be adapted to screen for GI cancers. This need is pressing: The American Cancer Society reports that as of 2021, 41 percent of eligible U.S. adults were not up to date on colorectal cancer screening. What’s more, effective screening tools don’t yet exist for some diseases, such as small bowel adenocarcinoma. Capsule technology could make screening less invasive and more accessible.

Of course, ingestible capsules carry risks. The standard hazards of endoscopy still apply, such as the possibility of bleeding and perforation, and capsules introduce new complications. For example, if a capsule gets stuck in its passage through the GI tract, it could cause bowel obstruction and require endoscopic retrieval or even surgery. And concerns that are specific to ingestibles, including the biocompatibility of materials, reliable encapsulation of electronics, and safe battery operation, all demand rigorous testing before clinical use.

A microbe-powered biobattery designed for ingestible devices dissolves in water within an hour. Seokheun Choi/Binghamton University

Powering these capsules is a key challenge that must be solved on the path to the clinic. Most capsule endoscopes today rely on coin-cell batteries, typically silver oxide, which offer a safe and energy-dense source but often occupy 30 to 50 percent of the capsule’s volume. So researchers have investigated alternatives, from wireless power transfer to energy-harvesting systems. At the State University of New York at Binghamton, one team is exploring microbial fuel cells that generate electricity from probiotic bacteria interacting with nutrients in the gut. At MIT, researchers used the gastric fluids of a pig’s stomach to power a simple battery. In our own lab, we are exploring piezoelectric and electrochemical approaches to harvesting energy throughout the GI tract.

The next steps for our team are pragmatic ones: working with gastroenterologists and animal-science experts to put capsule prototypes through rigorous in vivo studies, then refining them for real-world use. That means shrinking the electronics, cutting power consumption, and integrating multiple functions into a single multimodal device that can sense, sample, and deliver treatments in one pass. Ultimately, any candidate capsule will require regulatory approval for clinical use, which in turn demands rigorous proof of safety and clinical effectiveness for a specific medical application.

The broader vision is transformative. Swallowable capsules could bring diagnostics and treatment out of the hospital and into patients’ homes. Whereas procedures with endoscopes require anesthesia, patients could take ingestible electronics easily and routinely. Consider, for example, patients with inflammatory bowel disease who live with an elevated risk of cancer; a smart capsule could perform yearly cancer checks, while also delivering medication directly wherever necessary.

Over time, we expect these systems to evolve into semiautonomous tools: identifying lesions, performing targeted biopsies, and perhaps even analyzing samples and applying treatment in place. Achieving that vision will require advances at the very edge of microelectronics, materials science, and biomedical engineering, bringing together capabilities that once seemed impossible to combine in something the size of a pill. These devices hint at a future in which the boundary between biology and technology dissolves, and where miniature machines travel inside the body to heal us from within.

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Most VMware users still "actively reducing their VMware footprint," survey finds

More than two years after Broadcom took over VMware, the virtualization company’s customers are still grappling with higher prices, uncertainty, and the challenges of reducing vendor lock-in.

Today, CloudBolt Software released a report, "The Mass Exodus That Never Was: The Squeeze Is Just Beginning," that provides insight into those struggles. CloudBolt is a hybrid cloud management platform provider that aims to identify VMware customers’ pain points so it can sell them relevant solutions. In the report, CloudBolt said it surveyed 302 IT decision-makers (director-level or higher) at North American companies with at least 1,000 employees in January. The survey is far from comprehensive, but it offers a look at the obstacles these users face.

Broadcom closed its VMware acquisition in November 2023, and last month, 88 percent of survey respondents still described the change as “disruptive.” Per the survey, the most cited drivers of disruption were price increases (named by 89 percent of respondents), followed by uncertainty about Broadcom’s plans (85 percent), support quality concerns (78 percent), Broadcom shifting VMware from perpetual licenses to subscriptions (72 percent), changes to VMware’s partner program (68 percent), and the forced bundling of products (65 percent).

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Estimating Surface Heating of an Atmospheric Reentry Vehicle with Simulation

Here is the current HED: Estimating Surface Heating of an Atmospheric Reentry Vehicle with Simulation Here are 5 DEK suggestions: 1. Dive into thermal data from the LOFTID aeroshell mission 2. Validate heat flux gauges with inverse analysis techniques 3. Enhance thermal models for future HIAD missions 4. Discover how COMSOL Multiphysics® aids CFD predictions 5. Gain insights from NASA Ames expert Hannah AlpertJoin Hannah Alpert (NASA Ames) to explore thermal data from the record-breaking 6-meter LOFTID inflatable aeroshell. Learn how COMSOL Multiphysics® was used to perform inverse analysis on flight thermocouple data, validating heat flux gauges and preflight CFD predictions. Attendees will gain technical insights into improving thermal models for future HIAD missions, making this essential for engineers seeking to advance atmospheric reentry design. The session concludes with a live Q&A.

Register now for this free webinar!

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We’re Measuring Data Center Sustainability Wrong

In 2024, Google claimed that their data centers are 1.5x more energy efficient than industry average. In 2025, Microsoft committed billions to nuclear power for AI workloads. The data center industry tracks power usage effectiveness to three decimal places and optimizes water usage intensity with machine precision. We report direct emissions and energy emissions with religious fervor.

These are laudable advances, but these metrics account for only 30 percent of total emissions from the IT sector. The majority of the emissions are not directly from data centers or the energy they use, but from the end-user devices that actually access the data centers, emissions due to manufacturing the hardware, and software inefficiencies. We are frantically optimizing less than a third of the IT sector’s environmental impact, while the bulk of the problem goes unmeasured.

Incomplete regulatory frameworks are part of the problem. In Europe, the Corporate Sustainability Reporting Directive (CSRD) now requires 11,700 companies to report emissions using these incomplete frameworks. The next phase of the directive, covering 40,000+ additional companies, was originally scheduled for 2026 (but is likely delayed to 2028). In the United States, the standards body responsible for IT sustainability metrics (ISO/IEC JTC 1/SC 39) is conducting active revision of its standards through 2026, with a key plenary meeting in May 2026.

The time to act is now. If we don’t fix the measurement frameworks, we risk locking in incomplete data collection and optimizing a fraction of what matters for the next 5 to 10 years, before the next major standards revision.

The limited metrics

Walk into any modern data center and you’ll see sustainability instrumentation everywhere. Power usage efficiency (PUE) monitors track every watt. Water usage efficiency (WUE) systems measure water consumption down to the gallon. Sophisticated monitoring captures everything from server utilization to cooling efficiency to renewable energy percentages.

But here’s what those measurements miss: End-user devices globally emit 1.5 to 2 times more carbon than all data centers combined, according to McKinsey’s 2022 report. The smartphones, laptops, and tablets we use to access those ultra-efficient data centers are the bigger problem.

Data center operations, as measured by power usage efficiency, account for only 24 percent of the total emissions.

On the conservative end of the range from McKinsey’s report, devices emit 1.5 times as much as data centers. That means that data centers make up 40 percent of total IT emissions, while devices make up 60 percent.

On top of that, approximately 75 percent of device emissions occur not during use, but during manufacturing—this is so-called embodied carbon. For data centers, only 40 percent is embodied carbon, and 60 percent comes from operations (as measured by PUE).

Putting this together, data center operations, as measured by PUE, account for only 24 percent of the total emissions. Data center embodied carbon is 16 percent, device embodied carbon is 45 percent, and device operation is 15 percent.

Under the EU’s current CSRD framework, companies must report their emissions in three categories: direct emissions from owned sources, indirect emissions from purchased energy, and a third category for everything else.

This “everything else” category does include device emissions and embodied carbon. However, those emissions are reported as aggregate totals broken down by accounting category—Capital Goods, Purchased Goods and Services, Use of Sold Products—but not by product type. How much comes from end-user devices versus datacenter infrastructure, or employee laptops versus network equipment, remains murky, and therefore, unoptimized.

Embodied carbon and hardware reuse

Manufacturing a single smartphone generates approximately 50 kg CO₂ equivalent (CO₂e). For a laptop, it’s 200 kg CO₂e. With 1 billion smartphones replaced annually, that’s 50 million tonnes of CO₂e per year just from smartphone manufacturing, before anyone even turns them on. On average, smartphones are replaced every 2 years, laptops every 3 to 4 years, and printers every 5 years. Data center servers are replaced approximately every 5 years.

Extending smartphone lifecycles to 3 years instead of 2 would reduce annual manufacturing emissions by 33 percent. At scale, this dwarfs data center optimization gains.

There are programs geared towards reusing old components that are still functional and integrating them into new servers. GreenSKUs and similar initiatives show 8 percent reductions in embodied carbon are achievable. But these remain pilot programs, not systematic approaches. And critically, they’re measured only in data center context, not across the entire IT stack.

Imagine applying the same circular economy principles to devices. With over 2 billion laptops in existence globally and 2-3-year replacement cycles, even modest lifespan extensions create massive emission reductions. Extending smartphone lifecycles to 3 years instead of 2 would reduce annual manufacturing emissions by 33 percent. At scale, this dwarfs data center optimization gains.

Yet data center reuse gets measured, reported, and optimized. Device reuse doesn’t, because the frameworks don’t require it.

The invisible role of software

Leading load balancer infrastructure across IBM Cloud, I see how software architecture decisions ripple through energy consumption. Inefficient code doesn’t just slow things down—it drives up both data center power consumption and device battery drain.

For example, University of Waterloo researchers showed that they can reduce 30 percent of energy use in data centers by changing just 30 lines of code. From my perspective, this result is not an anomaly—it’s typical. Bad software architecture forces unnecessary data transfers, redundant computations, and excessive resource use. But unlike data center efficiency, there’s no commonly accepted metric for software efficiency.

This matters more now than ever. With AI workloads driving massive data center expansion—projected to consume 6.7-12 percent of total U.S. electricity by 2028, according to Lawrence Berkeley National Laboratory—software efficiency becomes critical.

What needs to change

The solution isn’t to stop measuring data center efficiency. It’s to measure device sustainability with the same rigor. Specifically, standards bodies (particularly ISO/IEC JTC 1/SC 39 WG4: Holistic Sustainability Metrics) should extend frameworks to include device lifecycle tracking, software efficiency metrics, and hardware reuse standards.

To track device lifecycles, we need standardized reporting of device embodied carbon, broken out separately by device. One aggregate number in an “everything else” category is insufficient. We need specific device categories with manufacturing emissions and replacement cycles visible.

To include software efficiency, I advocate developing a PUE-equivalent for software, such as energy per transaction, per API call, or per user session. This needs to be a reportable metric under sustainability frameworks so companies can demonstrate software optimization gains.

To encourage hardware reuse, we need to systematize reuse metrics across the full IT stack—servers and devices. This includes tracking repair rates, developing large-scale refurbishment programs, and tracking component reuse with the same detail currently applied to data center hardware.

To put it all together, we need a unified IT emission-tracking dashboard. CSRD reporting should show device embodied carbon alongside data center operational emissions, making the full IT sustainability picture visible at a glance.

These aren’t radical changes—they’re extensions of measurement principles already proven in data center context. The first step is acknowledging what we’re not measuring. The second is building the frameworks to measure it. And the third is demanding that companies report the complete picture—data centers and devices, servers and smartphones, infrastructure and software.

Because you can’t fix what you can’t see. And right now, we’re not seeing 70 percent of the problem.

Reference: https://ift.tt/s0w5lJz

This Former Physicist Helps Keep the Internet Secure

When Alan DeKok began a side project in network security, he didn’t expect to start a 27-year career. In fact, he didn’t initially set out to work in computing at all.

DeKok studied nuclear physics before making the switch to a part of network computing that is foundational but—like nuclear physics—largely invisible to those not directly involved in the field. Eventually, a project he started as a hobby became a full-time job: maintaining one of the primary systems that helps keep the internet secure.

Alan DeKok

Employer

InkBridge Networks

Occupation

CEO

Education

Bachelor’s degree in physics, Carleton University; master’s degree in physics, Carleton University

Today, he leads the FreeRADIUS Project, which he cofounded in the late 1990s to develop what is now the most widely used Remote Authentication Dial-In User Service (RADIUS) software. FreeRADIUS is an open-source server that provides back-end authentication for most major internet service providers. It’s used by global financial institutions, Wi-Fi services like Eduroam, and Fortune 50 companies. DeKok is also CEO of InkBridge Networks, which maintains the server and provides support for the companies that use it.

Reflecting on nearly three decades of experience leading FreeRADIUS, DeKok says he became an expert in remote authentication “almost by accident,” and the key to his career has largely been luck. “I really believe that it’s preparing yourself for luck, being open to it, and having the skills to capitalize on it.”

From Farming to Physics

DeKok grew up on a farm outside of Ottawa growing strawberries and raspberries. “Sitting on a tractor in the heat is not particularly interesting,” says DeKok, who was more interested in working with 8-bit computers than crops. As a student at Carleton University, in Ottawa, he found his way to physics because he was interested in math but preferred the practicality of science.

While pursuing a master’s degree in physics, also at Carleton, he worked on a water-purification system for the Sudbury Neutrino Observatory, an underground observatory then being built at the bottom of a nickel mine. He would wake up at 4:30 in the morning to drive up to the site, descend 2 kilometers, then enter one of the world’s deepest clean-room facilities to work on the project. The system managed to achieve one atom of impurity per cubic meter of water, “which is pretty insane,” DeKok says.

But after his master’s degree, DeKok decided to take a different route. Although he found nuclear physics interesting, he says he didn’t see it as his life’s work. Meanwhile, the Ph.D. students he knew were “fanatical about physics.” He had kept up his computing skills through his education, which involved plenty of programming, and decided to look for jobs at computing companies. “I was out of physics. That was it.”

Still, physics taught him valuable lessons. For one, “You have to understand the big picture,” DeKok says. “The ability to tell the big-picture story in standards, for example, is extremely important.” This skill helps DeKok explain to standards bodies how a protocol acts as one link in the entire chain of events that needs to occur when a user wants to access the internet.

He also learned that “methods are more important than knowledge.” It’s easy to look up information, but physics taught DeKok how to break down a problem into manageable pieces to come up with a solution. “When I was eventually working in the industry, the techniques that came naturally to me, coming out of physics, didn’t seem to be taught as well to the people I knew in engineering,” he says. “I could catch up very quickly.”

Founding FreeRADIUS

In 1996, DeKok was hired as a software developer at a company called Gandalf, which made equipment for ISDN, a precursor to broadband that enabled digital transmission of data over telephone lines. Gandalf went under about a year later, and he joined CryptoCard, a company providing hardware devices for two-factor authentication.

While at CryptoCard, DeKok began spending more time working with a RADIUS server. When users want to connect to a network, RADIUS acts as a gatekeeper and verifies their identity and password, determines what they can access, and tracks sessions. DeKok moved on to a new company in 1999, but he didn’t want to lose the networking skills he had developed. No other open-source RADIUS servers were being actively developed at the time, and he saw a gap in the market.

The same year, he started FreeRADIUS in his free time and it “gradually took over my life,” DeKok says. He continued to work on the open-source software as a hobby for several years while bouncing around companies in California and France. “Almost by accident, I became one of the more senior people in the space. Then I doubled down on that and started the business.” He founded NetworkRADIUS (now called InkBridge Networks) in 2008.

By that point, FreeRADIUS was already being used by 100 million people daily. The company now employs experts in Canada, France, and the United Kingdom who work together to support FreeRADIUS. “I’d say at least half of the people in the world get on the internet by being authenticated through my software,” DeKok estimates. He attributes that growth largely to the software being open source. Initially a way to enter the market with little funding, going open source has allowed FreeRADIUS to compete with bigger companies as an industry-leading product.

Although the software is critical for maintaining secure networks, most people aren’t aware of it because it works behind the scenes. DeKok is often met with surprise that it’s still in use. He compares RADIUS to a building foundation: “You need it, but you never think about it until there’s a crack in it.”

27 Years of Fixes

Over the years, DeKok has maintained FreeRADIUS by continually making small fixes. Like using a ratcheting tool to make a change inch by inch, “you shouldn’t underestimate that ratchet effect of tiny little fixes that add up over time,” he says.

He’s seen the project through minor patches and more significant fixes, like when researchers exposed a widespread vulnerability DeKok had been trying to fix since 1998. He also watched a would-be successor to the network protocol, Diameter, rise and fall in popularity in the 2000s and 2010s. (Diameter gained traction in mobile applications but has gradually been phased out in the shift to 5G.) Though Diameter offers improvements, RADIUS is far simpler and already widely implemented, giving it an edge, DeKok explains.

And he remains confident about its future. “People ask me, ‘What’s next for RADIUS?’ I don’t see it dying.” Estimating that billions of dollars of equipment run RADIUS, he says, “It’s never going to go away.”

About his own career, DeKok says he plans to keep working on FreeRADIUS, exploring new markets and products. “I never expected to have a company and a lot of people working for me, my name on all kinds of standards, and customers all over the world. But it worked out that way.”

This article appears in the March 2026 print issue as “Alan DeKok.”

Reference: https://ift.tt/wVCcBGU