In a bid to limit China’s AI capabilities, the United States imposed restrictions in 2022 on the export of certain advanced chips to China. But throughout the AI boom those chips have kept turning up in China anyway. On 1 October 2026, the U.S. arrested a man on charges of sending over $300 million worth of GPU-equipped servers to China using paperwork intended for shipments to Malaysia and Singapore. As chip smuggling and diversion continues, the United States is learning that the more it tries to limit the motion of its AI chips, the harder they are to precisely locate. To help curb the issue, the country is turning to location verification. Last March, the U.S. House Foreign Affairs Committee passed a bill requiring location verification for advanced AI chips. Ahead of the U.S.-China summit in late September, legislators called for a floor vote on that and related bills. If such a requirement were to pass, how would chipmakers comply? They could build tamper-proof root of trust hardware, implement cryptographic signing and transmission, or possibly even fingerprint individual chips. Akin to the “Find My” feature for keeping track of Apple devices, here are some possibilities for designing a “Find My” for AI chips. Pings that pinpoint positions Location verification can take different forms, such as geolocation mechanisms, inventory management tools, mail-in inspections, and video inspections. A combination of approaches, such as ping-based location verification (PLV) supplemented by physical inspections, would be a feasible and robust approach, say the authors of a September Center for Security and Emerging Technology (CSET) report on chip location tracking. To deduce an AI chip’s location, PLV measures the time it takes for a ping to travel from the chip to multiple trusted “landmark” servers around the world and back. Kyle Miller, a senior research analyst at CSET and coauthor of the report, says that for new AI chips, manufacturers could integrate PLV functionality into the hardware itself, while a firmware update could be applied to chips already in circulation. Not all AI chips should be tracked, the researchers note. “The priority should be for the highest-end data center chips—the cream of the crop in high-end data center GPUs,” says Jacob Feldgoise, a senior data research analyst at CSET and coauthor of the report. A similar initiative involves transmitting encrypted “sovereignty certificates.” These certificates act as “cryptographic credentials that provide verifiable, unforgeable proof of the physical location of a computing device, such as a CPU or GPU, at a specific point in time,” per the draft specification published by secure computing firm Lucid Computing. “If you can use a private key that exists on a particular chip, and you can sign a message with that cryptographic key, and then that message is received by a so-called landmark server, then you can send a couple of those messages and time those messages. A lot of modern chips come with trusted execution environments that support a hardware root of trust where you can sign these messages,” says Kristian Rönn, CEO and cofounder of Lucid Computing. “You get a radius of where the chip has to be.” PLV could have some effect on chip smugglers, Miller says. “They know if they turn this chip on, it’s going to start pinging these landmark servers. That could deter some smuggling.” And when the system flags a chip as residing in a nonintended location, “the PLV data gives you a better sense of when and where it was moved,” he adds. However, ping-based location verification can only uncover diversion after it has happened. It can’t track offline chips that are in storage, in transit, or have yet to be activated. And when a chip fails to respond to a ping request, the system won’t know whether it’s due to a valid reason or nefarious causes. This is where physical inspections come in. “You need to do that follow-on investigative work. You need to physically go to these data centers and do those physical audits as well. Essentially, [PLV] generates leads, and you track down those leads,” says Miller. A PLV system involves sending signals from a chip to and from trusted servers and measuring the travel time.Source image: CSET A “lie detector” for data centers Despite the safeguards around ping-based location verification, the methodology remains vulnerable to particular attacks. If adversaries gain physical access to a chip, for example, they could prevent it from sending signals, or they could extract cryptographic keys and spoof a signal from the intended location. To fight that, some security researchers are exploring hardware fingerprints instead of cryptographic keys. One study demonstrated a proof-of-concept GPU fingerprinting function that produced unique fingerprints for Nvidia H200 GPUs based on their manufacturing variations and random numbers as seeds. “You want to support other types of fingerprinting because not all chips have a hardware root of trust. You might want to use some statistical fingerprinting to know that the chip is what it’s supposed to be,” Rönn says. “It also requires good physical security around the chips, such as tamper-proofing. Over time, you ideally want to have more defense in depth.” Additionally, the CSET report warns that PLV is costly. And if China achieves the ability to craft its own advanced AI chips, “then tracking the export of U.S. chips is less of a strategic priority,” says Miller. Hanna Dohmen, a senior research analyst at CSET and coauthor of the report, points to other gaps in the U.S. export control regime. “Currently, Chinese companies are legally able to remotely access AI chips abroad through cloud service providers,” she says. These advanced AI chips might be installed in data centers across Southeast Asian countries like Malaysia, which are increasingly serving Chinese firms. Whether or not a “Find My” for AI chips becomes a regulatory requirement, Feldgoise envisions tighter conditions for the export of advanced AI chips. “This is based on the increasing importance of compute to national and economic security,” he says. “The chips that generate compute are being seen as a strategic resource, so I would be unsurprised if the due diligence requirements on these devices increase as time passes.” Rönn views sovereignty certificates as essential tools in the future, likening it to a “lie detector” for data centers that answer the “where, how, what, and who questions for us to know that they comply with a basic standard of security when it comes to AI systems.”

There’s a famous (but unattributable) quip that goes something like this: If you are not a liberal at 25, you have no heart. If you are not a conservative at 35, you have no brain. In Chapter 12 of Probably Overthinking It, I used data from the General Social Survey (GSS) to show that the quip is half right. Older people hold more conservative views. But as people get older, their views don’t become more conservative; on average, they become... Read More Read More The post Do People Get More Conservative With Age? appeared first on Probably Overthinking It.

Like some of you, we have several kitchen appliances with integrated digital timers.

In this conversation, Blaise Agüera y Arcas and Baratunde Thurston explored what a story of symbiosis and interdependence might teach us about living alongside AI. Agüera y Arcas began by calling individual human intelligence a myth: we’ve always been a collective intelligence, entwined with our technologies. He traced this back to symbiogenesis. Life has grown more complex not by splitting apart but by merging, as separate organisms fuse into increasingly complex new forms of life. These mergers speed up change by opening new possibilities. Thurston agreed that union is in our nature but framed the current technological acceleration as a speed problem. We need time and new stories to adjust because, as he reminded us, “when you invent the ship, you invent the shipwreck.” Caring for one another through acceleration must be our prime directive, he said. The two then turned to how we relate to AI. Responding to Joanna Bryson’s argument that robots should be our slaves, Thurston said the master is also in chains — owning another dehumanizes the owner. As relational beings, how we treat AI will shape how we treat each other. Thurston called for both an expansion and a humbling of how we define ourselves: “We’ve overdone independence,” he said, “interdependence makes us richer.” Agüera y Arcas agreed and pushed us to drop a zero-sum definition of human intelligence, where every AI advance diminishes humanity’s value. As technology advances, we trade some individual skills for new collective capabilities, Agüera y Arcas acknowledged. But over the long arc of history, he believes, that exchange pays off in collective flourishing. Thurston didn’t deny this, but he closed with an urgent question: who controls the loss of capabilities and agency?