AI & Singularity

The State of AI is a collaboration between the Financial Times & MIT Technology Review examining the ways in which AI is reshaping global power. Every Monday for the next six weeks, writers from both publications will debate one aspect of the generative AI revolution reshaping global power. In this conversation, the FT’s tech columnist and Innovation Editor John Thornhill and MIT Technology Review’s Caiwei Chen consider the battle between Silicon Valley and Beijing for technological supremacy. John Thornhill writes: Viewed from abroad, it seems only a matter of time before China emerges as the AI superpower of the 21st century. 
Here in the West, our initial instinct is to focus on America’s significant lead in semiconductor expertise, its cutting-edge AI research, and its vast investments in data centers. The legendary investor Warren Buffett once warned: “Never bet against America.” He is right that for more than two centuries, no other “incubator for unleashing human potential” has matched the US. Today, however, China has the means, motive, and opportunity to commit the equivalent of technological murder. When it comes to mobilizing the whole-of-society resources needed to develop and deploy AI to maximum effect, it may be just as rash to bet against. 
The data highlights the trends. In AI publications and patents, China leads. By 2023, China accounted for 22.6% of all citations, compared with 20.9% from Europe and 13% from the US, according to Stanford University’s Artificial Intelligence Index Report 2025. As of 2023, China also accounted for 69.7% of all AI patents. True, the US maintains a strong lead in the top 100 most cited publications (50 versus 34 in 2023), but its share has been steadily declining.  Similarly, the US outdoes China in top AI research talent, but the gap is narrowing. According to a report from the US Council of Economic Advisers, 59% of the world’s top AI researchers worked in the US in 2019, compared with 11% in China. But by 2022 those figures were 42% and 28%.  The Trump administration’s tightening of restrictions for foreign H-1B visa holders may well lead more Chinese AI researchers in the US to return home. The talent ratio could move further in China’s favor. Regarding the technology itself, US-based institutions produced 40 of the world’s most notable AI models in 2024, compared with 15 from China. But Chinese researchers have learned to do more with less, and their strongest large language models—including the open-source DeepSeek-V3 and Alibaba’s Qwen 2.5-Max—surpass the best US models in terms of algorithmic efficiency. Where China is really likely to excel in future is in applying these open-source models. The latest report from Air Street Capital shows that China has now overtaken the US in terms of monthly downloads of AI models. In AI-enabled fintech, e-commerce, and logistics, China already outstrips the US.  Perhaps the most intriguing—and potentially the most productive—applications of AI may yet come in hardware, particularly in drones and industrial robotics. With the research field evolving toward embodied AI, China’s advantage in advanced manufacturing will shine through. Dan Wang, the tech analyst and author of Breakneck, has rightly highlighted the strengths of China’s engineering state in developing manufacturing process knowledge—even if he has also shown the damaging effects of applying that engineering mentality in the social sphere. “China has been growing technologically stronger and economically more dynamic in all sorts of ways,” he told me. “But repression is very real. And it is getting worse in all sorts of ways as well.” I’d be fascinated to hear from you, Caiwei, about your take on the strengths and weaknesses of China’s AI dream. To what extent will China’s engineered social control hamper its technological ambitions? 

Caiwei Chen responds: Hi, John! You’re right that the US still holds a clear lead in frontier research and infrastructure. But “winning” AI can mean many different things. Jeffrey Ding, in his book Technology and the Rise of Great Powers, makes a counterintuitive point: For a general-purpose technology like AI, long-term advantage often comes down to how widely and deeply technologies spread across society. And China is in a good position to win that race (although “murder” might be pushing it a bit!). Chips will remain China’s biggest bottleneck. Export restrictions have throttled access to top GPUs, pushing buyers into gray markets and forcing labs to recycle or repair banned Nvidia stock. Even as domestic chip programs expand, the performance gap at the very top still stands. Yet those same constraints have pushed Chinese companies toward a different playbook: pooling compute, optimizing efficiency, and releasing open-weight models. DeepSeek-V3’s training run, for example, used just 2.6 million GPU-hours—far below the scale of US counterparts. But Alibaba’s Qwen models now rank among the most downloaded open-weights globally, and companies like Zhipu and MiniMax are building competitive multimodal and video models.  China’s industrial policy means new models can move from lab to implementation fast. Local governments and major enterprises are already rolling out reasoning models in administration, logistics, and finance.  Education is another advantage. Major Chinese universities are implementing AI literacy programs in their curricula, embedding skills before the labor market demands them. The Ministry of Education has also announced plans to integrate AI training for children of all school ages. I’m not sure the phrase “engineering state” fully captures China’s relationship with new technologies, but decades of infrastructure building and top-down coordination have made the system unusually effective at pushing large-scale adoption, often with far less social resistance than you’d see elsewhere. The use at scale, naturally, allows for faster iterative improvements. Meanwhile, Stanford HAI’s 2025 AI Index found Chinese respondents to be the most optimistic in the world about AI’s future—far more optimistic than populations in the US or the UK. It’s striking, given that China’s economy has slowed since the pandemic for the first time in over two decades. Many in government and industry now see AI as a much-needed spark. Optimism can be powerful fuel, but whether it can persist through slower growth is still an open question.
Social control remains part of the picture, but a different kind of ambition is taking shape. The Chinese AI founders in this new generation are the most globally minded I’ve seen, moving fluidly between Silicon Valley hackathons and pitch meetings in Dubai. Many are fluent in English and in the rhythms of global venture capital. Having watched the last generation wrestle with the burden of a Chinese label, they now build companies that are quietly transnational from the start. The US may still lead in speed and experimentation, but China could shape how AI becomes part of daily life, both at home and abroad. Speed matters, but speed isn’t the same thing as supremacy.
John Thornhill replies: You’re right, Caiwei, that speed is not the same as supremacy (and “murder” may be too strong a word). And you’re also right to amplify the point about China’s strength in open-weight models and the US preference for proprietary models. This is not just a struggle between two different countries’ economic models but also between two different ways of deploying technology.   Even OpenAI’s chief executive, Sam Altman, admitted earlier this year: “We have been on the wrong side of history here and need to figure out a different open-source strategy.” That’s going to be a very interesting subplot to follow. Who’s called that one right? Further reading on the US-China competition There’s been a lot of talk about how people may be using generative AI in their daily lives. This story from the FT’s visual story team explores the reality  From China, FT reporters ask how long Nvidia can maintain its dominance over Chinese rivals When it comes to real-world uses, toys and companions devices are a novel but emergent application of AI that is gaining traction in China—but is also heading to the US. This MIT Technology Review story explored it. The once-frantic data center buildout in China has hit walls, and as the sanctions and AI demands shift, this MIT Technology Review story took an on-the-ground look at how stakeholders are figuring it out.

Demand for copper is surging, as is pollution from its dirty production processes. The founders of one startup, Still Bright, think they have a better, cleaner way to generate the copper the world needs.  The company uses water-based reactions, based on battery chemistry technology, to purify copper in a process that could be less polluting than traditional smelting. The hope is that this alternative will also help ease growing strain on the copper supply chain. “We’re really focused on addressing the copper supply crisis that’s looming ahead of us,” says Randy Allen, Still Bright’s cofounder and CEO. Copper is a crucial ingredient in everything from electrical wiring to cookware today. And clean energy technologies like solar panels and electric vehicles are introducing even more demand for the metal. Global copper demand is expected to grow by 40% between now and 2040. 
As demand swells, so do the climate and environmental impacts of copper extraction, the process of refining ore into a pure metal. There’s also growing concern about the geographic concentration of the copper supply chain. Copper is mined all over the world, and historically, many of those mines had smelters on-site to process what they extracted. (Smelters form pure copper metal by essentially burning concentrated copper ore at high temperatures.) But today, the smelting industry has consolidated, with many mines shipping copper concentrates to smelters in Asia, particularly China. That’s partly because smelting uses a lot of energy and chemicals, and it can produce sulfur-containing emissions that can harm air quality. “They shipped the environmental and social problems elsewhere,” says Simon Jowitt, a professor at the University of Nevada, Reno, and director of the Nevada Bureau of Mines and Geology.
It’s possible to scrub pollution out of a smelter’s emissions, and smelters are much cleaner than they used to be, Jowitt says. But overall, smelting centers aren’t exactly known for environmental responsibility.  So even countries like the US, which have plenty of copper reserves and operational mines, largely ship copper concentrates, which contain up to around 30% copper, to China or other countries for smelting. (There are just two operational ore smelters in the US today.) Still Bright avoids the pyrometallurgic process that smelters use in favor of a chemical approach, partially inspired by devices called vanadium flow batteries. In the startup’s reactor, vanadium reacts with the copper compounds in copper concentrates. The copper metal remains a solid, leaving many of the impurities behind in the liquid phase. The whole thing takes between 30 and 90 minutes. The solid, which contains roughly 70% copper after this reaction, can then be fed into another, established process in the mining industry, called solvent extraction and electrowinning, to make copper that’s over 99% pure.  This is far from the first attempt to use a water-based, chemical approach to processing copper. Today, some copper ore is processed with acid, for example, and Ceibo, a startup based in Chile, is trying to use a version of that process on the type of copper that’s traditionally smelted. The difference here is the particular chemistry, particularly the choice to use vanadium. One of Still Bright’s founders, Jon Vardner, was researching copper reactions and vanadium flow batteries when he came up with the idea to marry a copper extraction reaction with an electrical charging step that could recycle the vanadium. COURTESY OF STILL BRIGHT After the vanadium reacts with the copper, the liquid soup can be fed into an electrolyzer, which uses electricity to turn the vanadium back into a form that can react with copper again. It’s basically the same process that vanadium flow batteries use to charge up.  While other chemical processes for copper refining require high temperatures or extremely acidic conditions to get the copper into solution and force the reaction to proceed quickly and ensure all the copper gets reacted, Still Bright’s process can run at ambient temperatures.

One of the major benefits to this approach is cutting the pollution from copper refining.  Traditional smelting heats the target material to over 1,200 °C (2,000 °F), forming sulfur-containing gases that are released into the atmosphere.  Still Bright’s process produces hydrogen sulfide gas as a by-product instead. It’s still a dangerous material, but one that can be effectively captured and converted into useful side products, Allen says. Another source of potential pollution is the sulfide minerals left over after the refining process, which can form sulfuric acid when exposed to air and water (this is called acid mine drainage, common in mining waste). Still Bright’s process will also produce that material, and the company plans to carefully track it, ensuring that it doesn’t leak into groundwater.  The company is currently testing its process in the lab in New Jersey and designing a pilot facility in Colorado, which will have the capacity to make about two tons of copper per year. Next will be a demonstration-scale reactor, which will have a 500-ton annual capacity and should come online in 2027 or 2028 at a mine site, Allen says. Still Bright recently raised an $18.7 million seed round to help with the scale-up process. How scale up goes will be a crucial test of the technology and whether the typically conservative mining industry will jump on board, UNR’s Jowitt says: “You want to see what happens on an industrial scale. And I think until that happens, people might be a little reluctant to get into this.”

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Why do so many people think the Fruit of the Loom logo had a cornucopia? Quick question: Does the Fruit of the Loom logo feature a cornucopia?Many of us have been wearing the company’s T-shirts for decades, and yet the question of whether there is a woven brown horn of plenty on the logo is surprisingly contentious.According to a 2022 poll, 55% of Americans believe the logo does include a cornucopia, 25% are unsure, and only 21% are confident that it doesn’t, even though this last group is correct.There’s a name for what’s happening here: the “Mandela effect,” or collective false memory, so called because a number of people misremember that Nelson Mandela died in prison. Yet while many find it easy to let their unconfirmable beliefs go, some spend years seeking answers—and vindication. Read the full story. —Amelia Tait
This story is part of MIT Technology Review’s series “The New Conspiracy Age,” on how the present boom in conspiracy theories is reshaping science and technology.
Here’s why we don’t have a cold vaccine. Yet. For those of us in the Northern Hemisphere, it’s the season of the sniffles. As the weather turns, we’re all spending more time indoors. The kids have been back at school for a couple of months. And cold germs are everywhere. So why can’t we get a vaccine to protect us against the common cold? Scientists have been working on this for decades, but it turns out that creating a cold vaccine is hard. Really hard. But not impossible. There’s still hope. Read the full story. —Jessica Hamzelou This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here. Inside the archives of the NASA Ames Research Center At the southern tip of San Francisco Bay, surrounded by the tech giants Google, Apple, and Microsoft, sits the historic NASA Ames Research Center. Its rich history includes a grab bag of fascinating scientific research involving massive wind tunnels, experimental aircraft, supercomputing, astrobiology, and more.A collection of 5,000 images from NASA Ames’s archives paints a vivid picture of bleeding-edge work at the heart of America’s technology hub. Read the full story.—Jon Keegan

This story is from the latest print issue of MIT Technology Review magazine, which is full of stories about the body. If you haven’t already, subscribe now to receive future issues once they land. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 The US government is considering banning TP-Link routersAn investigation has raised concerns over the company’s links to China. (WP $)+ Lawmakers are worried its equipment is vulnerable to hacking. (Bloomberg $)2 ICE has proposed building a deportation network in TexasThe 24/7 operation would transfer detained immigrants into holding facilities. (Wired $)+ But US citizens keep being detained, too. (NY Mag $)+ Inside the operation giving ICE a run for its money. (Slate $)+ Another effort to track ICE raids was just taken offline. (MIT Technology Review) 3 Ukrainian drone teams are gamifying their war effortsOfficials say rewarding soldiers for successful attacks keeps them motivated. (NYT $)+ A Peter Thiel-backed drone startup crashed and burned during military trials. (FT $)+ Meet the radio-obsessed civilian shaping Ukraine’s drone defense. (MIT Technology Review) 4 Meta has denied torrenting porn to train its AI modelsInstead, it claims, the downloads were for someone’s “private personal use.” (Ars Technica) 5 Bird flu is getting harder to keep tabs onThe virus has wreaked havoc on the US poultry industry for close to four years. (Vox)+ A new biosensor can detect bird flu in five minutes. (MIT Technology Review)
6 AI browsers are a cybersecurity nightmareThey’re a hotbed of known—and unknown—risks. (The Verge)+ I tried OpenAI’s new Atlas browser but I still don’t know what it’s for. (MIT Technology Review) 7 Robots are starting to do more jobs across AmericaBut they’re still proving buggy and expensive to run. (WSJ $)+ When you might start speaking to robots. (MIT Technology Review)
8 These are the jobs that AI builtFrom conversation designer to adoption strategist. (WP $)+ if you fancy landing a job in quantum computing, here’s how to do it. (IEEE Spectrum) 9 Computer vision is getting much, much better 👀Their blind spots are rapidly being eliminated. (Knowable Magazine) 10 A lock-cracking YouTuber is being sued by a lockmaking company 🔓 It’s arguing he defamed the company, even though he didn’t say a word during the clip. (Ars Technica) Quote of the day “Yes, we’ve been to the Moon before… six times!”
—NASA’s acting administrator Sean Duffy reacts to Kim Kardashian’s belief that man has never set foot on the moon, the Guardian reports. One more thing What happens when you donate your body to science
Rebecca George doesn’t mind the vultures that complain from the trees that surround the Western Carolina University body farm. Her arrival has interrupted their breakfast. George studies human decomposition, and part of decomposing is becoming food. Scavengers are welcome. In the US, about 20,000 people or their families donate their bodies to scientific research and education each year. Whatever the reason, the decision becomes a gift. Western Carolina’s FOREST is among the places where watchful caretakers know that the dead and the living are deeply connected, and the way you treat the first reflects how you treat the second. Read the full story. —Abby Ohlheiser We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)+ Zoo animals across the world are getting into the Halloween spirit with some tasty pumpkins.+ If you’re stuck for something suitably spooky to watch tonight, this list is a great place to start.+ New York’s historic Morris-Jumel Mansion is seriously beautiful—and seriously haunted.+ Salem’s Lucipurr is on the prowl!

The acquisition of a legacy platform like AOL by Bending Spoons shows the latent value of long-standing digital ecosystems. AOL’s 30 million monthly active users represent an enduring brand and a data-rich resource that can be used in AI-driven services. That statement is true only if the data is properly governed and integrated. Such deals may blend nostalgia with business advantage, but present new compliance and cybersecurity risks that enterprises need to address.By acquiring AOL from Yahoo, Bending Spoons moves to consolidate high-retention consumer technologies in its expanding digital portfolio. As companies turn increasingly to synthetic data to feed their AI’s learning corpus, the deal shows a different tactic, one of using established data assets and user bases to accelerate AI personalisation, advertising efficiency, and digital identity information gathering. It illustrates how older platforms – perhaps written off as legacy – can become profitable fuel for innovation when combined with cloud-native architectures and machine learning models.Bending Spoons has financed its expansion strategy with a $2.8 billion debt package from major global banks that include J.P. Morgan, BNP Paribas, and HSBC. There’s clearly growing lender confidence in the long-term monetisation of data, unlike during the ‘dot.com’ boom and bust, where the emphasis and interest was in purely software products. The acquisition, expected to close by year-end, follows Bending Spoons’ planned purchase of Vimeo. The two deals, if they go through, position the company as a major consolidator of internet assets.Implementation and operational challengesIntegrating decades-old infrastructure like AOL’s presents technical challenges. Data migration from legacy email systems in line with current-day security protocols and compliance requirements needs careful stewardship. There’s also the not-insignificant issue of retraining staff for AI data stewardship on data that comes with significant buy-in from trusting service users. As with any digital acquisition, therefore, Bending Spoons’ success will depend on managing the technical and cultural dimensions of integration. Without strong governance, promising legacy platforms risk becoming compliance liabilities.Early in any acquisition cycle, there will have been preparatory work in mapping data lineage, running integration and interoperability audits, and significant governance discussions. It’s worth noting that many integration pilots stall without shared accountability between technology and business functions: It’s easier to covet data than to work out how it can be put to business use, especially when the best an acquirer can hope for are limited examples of what they might get, once the ink has dried on the cheque.Vendor and ecosystem contextAlthough Bending Spoons operates independently of major enterprise AI ecosystems, the logic of its acquisition aligns with Microsoft’s integration of LinkedIn data into Azure AI Foundry, and IBM’s efforts to reinvigorate legacy data with watsonx. AOL’s customer base and behavioural data could feasibly hold value with cloud analytics, customer profiling, and identity management frameworks, on even off-the-shelf platforms like AWS Bedrock, Azure, or Google Vertex AI.Executive takeawayLegacy platforms are not obsolete but they are often underused and undervalued. The differentiator lies in how organisations integrate historical data into modern AI governance and value delivery. Executives may see the AOL acquisition as a nostalgia play, but it’s a more hard-nosed imagining of a pure data asset. Perhaps the next wave of competitive advantage may come not from building new systems, but from reinterpreting older software and information that’s sometimes disregarded, simply because it’s not the latest-and-greatest ‘thing.’(Image source: “Spoon” by felixtsao is licensed under CC BY 2.0.)Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and co-located with other leading technology events. Click here for more information.AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.

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Bill Gates doesn’t shy away or pretend modesty when it comes to his stature in the climate world today. “Well, who’s the biggest funder of climate innovation companies?” he asked a handful of journalists at a media roundtable event last week. “If there’s someone else, I’ve never met them.” The former Microsoft CEO has spent the last decade investing in climate technology through Breakthrough Energy, which he founded in 2015. Ahead of the UN climate meetings kicking off next week, Gates published a memo outlining what he thinks activists and negotiators should focus on and how he’s thinking about the state of climate tech right now. Let’s get into it.  Are we too focused on near-term climate goals? One of the central points Gates made in his new memo is that he thinks the world is too focused on near-term emissions goals and national emissions reporting. So in parallel with the national accounting structure for emissions, Gates argues, we should have high-level climate discussions at events like the UN climate conference. Those discussions should take a global view on how to reduce emissions in key sectors like energy and heavy industry.
“The way everybody makes steel, it’s the same. The way everybody makes cement, it’s the same. The way we make fertilizer, it’s all the same,” he says. As he noted in one recent essay for MIT Technology Review, he sees innovation as the key to cutting the cost of clean versions of energy, cement, vehicles, and so on. And once products get cheaper, they can see wider adoption.
What’s most likely to power our grid in the future? “In the long run, probably either fission or fusion will be the cheapest way to make electricity,” he says. (It should be noted that, as with most climate technologies, Gates has investments in both fission and fusion companies through Breakthrough Energy Ventures, so he has a vested interest here.) He acknowledges, though, that reactors likely won’t come online quickly enough to meet rising electricity demand in the US: “I wish I could deliver nuclear fusion, like, three years earlier than I can.” He also spoke to China’s leadership in both nuclear fission and fusion energy. “The amount of money they’re putting [into] fusion is more than the rest of the world put together times two. I mean, it’s not guaranteed to work. But name your favorite fusion approach here in the US—there’s a Chinese project.” Can carbon removal be part of the solution? I had my colleague James Temple’s recent story on what’s next for carbon removal at the top of my mind, so I asked Gates if he saw carbon credits or carbon removal as part of the problematic near-term thinking he wrote about in the memo. Gates buys offsets to cancel out his own personal emissions, to the tune of about $9 million a year, he said at the roundtable, but doesn’t expect many of those offsets to make a significant dent in climate progress on a broader scale: “That stuff, most of those technologies, are a complete dead end. They don’t get you cheap enough to be meaningful. “Carbon sequestration at $400, $200, $100, can never be a meaningful part of this game. If you have a technology that starts at $400 and can get to $4, then hallelujah, let’s go. I haven’t seen that one. There are some now that look like they can get to $40 or $50, and that can play somewhat of a role.”  Will AI be good news for innovation?  During the discussion, I started a tally in the corner of my notebook, adding a tick every time Gates mentioned AI. Over the course of about an hour, I got to six tally marks, and I definitely missed making a few. Gates acknowledged that AI is going to add electricity demand, a challenge for a US grid that hasn’t seen net demand go up for decades. But so too will electric cars and heat pumps. 

I was surprised at just how positively he spoke about AI’s potential, though: “AI will accelerate every innovation pipeline you can name: cancer, Alzheimer’s, catalysts in material science, you name it. And we’re all trying to figure out what that means. That is the biggest change agent in the world today, moving at a pace that is very, very rapid … every breakthrough energy company will be able to move faster because of using those tools, some very dramatically.” I’ll add that, as I’ve noted here before, I’m skeptical of big claims about AI’s potential to be a silver bullet across industries, including climate tech. (If you missed it, check out this story about AI and the grid from earlier this year.)  This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.