Robert Hart | The Verge

Google hit with $1 billion fine for breaking EU antitrust rules

2026-07-23T07:16:50-04:00

The European Union has fined Google’s parent company Alphabet €890 million (about $1 billion) for two separate violations of the bloc’s Digital Markets Act (DMA). One penalty is for giving its own products preferential treatment in search results, while the other is for blocking Android developers from sending users to alternate payment options.

A €460 million fine has been issued to Google for giving preferential treatment to its own Shopping, Hotels, and Flights services in Google Search results. The second €430 million penalty is for Play Store rules preventing developers from freely steering consumers to alternative payment systems that may be cheaper.

As part of the ruling, Google has been given 60 days to make changes to its policies, or face further periodic penalty payments. In Search, it will be required to treat third-party services “in a fair and non-discriminatory manner,” while it will also have to allow Android developers to freely promote offers to users both inside and outside the Play Store.

The fines were announced by the European Commission today, more than two years after it first opened a non-compliance investigation, and follow a preliminary ruling in March 2025. Google was given time to address the EU’s concerns, with an extension granted in May 2026 after the Commission said a previous proposal from the company “is simply not strong enough.”

Google made and tested several changes to its Search services in an effort to comply with DMA rules, such as removing the Google Flights widget for Search users in the EU, and boosting links to third-party comparison websites via an updated search result layout. The company has previously fired back at the EU’s criticisms of its Search product, telling Reuters in May that changes it made in an attempt to achieve DMA compliance “represent the biggest downgrade in the product’s history, creating a second-rate experience ⁠for Europeans to the benefit of a few self-interested complainants.” These changes were made prior to Google introducing a reimagined AI-focused search box at its I/O conference in May, however, which has also rolled out to EU users.

Google was previously hit with a €2.42 billion fine in 2017 for a similar breach of the EU’s antitrust rules, after it was charged with giving its comparison shopping service an illegal advantage over competitors.

As for the Play Store, Google has repeatedly objected to rules requiring it to open up app distribution on Android systems, claiming doing so poses a security risk to users. The company repeated these objections following the Commission’s preliminary finding and in a blog posted last year, said “the DMA is making it difficult to protect users from scams and malicious links on Android by forcing us to remove our legitimate safeguards that protect users’ security and safety.” Nevertheless, it updated certain terms following consultations with the European Commission and other experts, revising fees and restrictions on Android developers. The Commission says these changes “constitute good progress towards compliance.”

Google is also facing a reckoning over its Play Store policies in the US after Fortnite publisher Epic Games successfully sued the company over in-app purchase fees, and it will be forced to carry rival Android app stores inside its own.

The DMA targets the largest “gatekeeper” companies that provide core digital services in Europe, and requires them to act in a fair manner — not stifle competition by abusing their market dominance. The maximum fine for breaching DMA rules is 10 percent of the company’s global annual revenue — $40 billion in Google’s case, based on the $400 billion it reported for 2025.

“The best products should succeed because they’re better, not because they’re owned by the company running the search engine,” says Teresa Ribera, the Commission’s executive vice-president for clean, just and competitive transition. “And European consumers have a right to be told by app developers where to sign up to the best offers, even when the app store owner does not get a cut. This is the promise of the DMA, protecting fairness, choice and innovation in digital markets for the benefit of all European citizens.”

America needs to stop getting shocked by Chinese AI

2026-07-21T07:43:25-04:00

People visit the booth of Kimi, an LLM developed by the Chinese startup Moonshot, during the World AI Conference in Shanghai, China, Monday, July 20, 2026. | Image: LONG WEI/ Feature China/Future Publishing via Getty Images

Last week, two Chinese AI companies unveiled models they say can credibly compete with the best systems from OpenAI and Anthropic. The response was swift and predictable. Markets wobbled, commentators declared Silicon Valley shooketh, and policymakers reached for the familiar language of arms races and wake-up calls.

In one headline, The Associated Press said a Chinese model had taken the “US tech industry by surprise.” Bloomberg described it as a “surprise breakthrough” that is “roiling markets” and sending global tech stocks tumbling over concerns it could force US firms to rethink their gargantuan spending on data centers, chips, and other AI infrastructure. Business Insider questioned whether the launch is “The next DeepSeek?”, referring to the Chinese model that blindsided the US AI industry last year. Xprize founder Peter Diamandis went as far to call the release America’s “AI Sputnik moment,” referring to the Soviet satellite launch at the height of the Cold War that encouraged significant US investment in its science and space programs. Of course, DeepSeek was also widely described as America’s AI Sputnik moment, a comparison that felt less gratuitous then as DeepSeek appeared to arrive with little warning, challenged the prevailing assumptions about the costs of frontier AI, and prompted immediate reactions across the technology and financial sectors.

What is actually surprising is that the model announcements were a surprise at all. For years, we have been warned that China was catching up in AI. Yet the world is shocked when it starts to look like the moment may have arrived.

US and Chinese companies train almost all of the world’s most-used AI models, and six of the top 10 AI tools on OpenRouter’s leaderboard tracking token consumption and benchmarks were Chinese. The performance gap has been narrowing for some time, with recent models from companies like Z.ai and DeepSeek seen as highly competitive with top-tier offerings from US labs like Anthropic and OpenAI. Chinese models are also significantly cheaper to use, and reports suggest US companies are increasingly turning to Chinese tools as the cost of using domestic providers surge.

Beijing has also been keen to support homegrown AI efforts, including incentivizing and funding innovation and cracking down on firms trying to shed their ties to China. Meanwhile, Washington’s AI strategy has often veered between heavy-handed intervention that has left allies questioning America’s reliability and a laissez-faire assumption that markets will see things right. It is a difficult approach to maintain against a competitor prepared to mobilize the full force of the state behind a single technological goal.

Beijing-based startup Moonshot AI, one of China’s leading AI model developers, unveiled a new flagship model on Friday, claiming it outperforms nearly every US model, trailing only OpenAI’s GPT-5.6 Sol and Anthropic’s Claude Fable 5. Moonshot is also pricing Kimi K3 aggressively, charging $15 per million output tokens, compared with roughly $30 for GPT-5.6 Sol and $50 for Fable 5. Demand was so strong after the launch that Moonshot, the company claimed, that it temporarily paused new subscriptions after the service was overwhelmed. The majority of responses mainly focus on this release.

Days later, Chinese tech titan Alibaba followed with a preview of Qwen3.8. It described the new model as “one of the most powerful model[s] available today” and “second only to Fable 5.” This only added to the uproar Kimi K3 had caused.

Crucially, both companies plan to make their new flagship models publicly available. Both Moonshot and Alibaba say they plan to release their models as open weight, which would allow developers to download, use, and modify the core values created during the AI’s training that shape its responses. It stands in stark contrast to the closed, proprietary approach to frontier models taken by most leading US AI labs, including OpenAI, Anthropic, and Google.

The economics deserve particularly close scrutiny. There’s the whole unsettled debate over whether, and to what degree, Chinese companies are — as American firms accuse — using US models to train their own, which could improve performance at a fraction of the cost. Tokens are not directly comparable between models, and token prices alone give an incomplete picture of how much it costs to use an AI system. A more expensive model may, for example, generate better responses with fewer tokens. Companies also routinely subsidize inference costs to win over customers. Cheaper, in other words, does not automatically mean better, or even less expensive overall.

Still, the possibility remains that Chinese labs may eventually produce models that are not merely cheap substitutes, but systems that could genuinely match or outperform their US rivals. Even companies that trail the frontier slightly could still have an enormous impact if their models are good enough, easier or cheaper to deploy, or available on more attractive terms. This could have direct consequences for US companies, the wider economy, and national security.

Anthropic and OpenAI are both gearing up for what could potentially be trillion dollar IPOs, valuations that in part depend on the expectation that they will dominate the global AI market. Capable Chinese models challenge that assumption, and could potentially draw away customers, squeeze margins, and weaken growth assumptions underpinning those valuations. Given how expensive American AI has become, some US startups are already reportedly turning to cheaper Chinese models. There is a wider market risk, too, reaching far beyond a handful of AI players. Tech stocks make up an outsized share of US markets, and much of that recent growth has been tied to expectations that AI demand will continue to soar. Companies have piled hundreds of billions of dollars into data centers, chips, energy, and other infrastructure that relies on the assumption American firms will continue to dominate. If Chinese labs can capture some of that demand, or show models that can be produced and operated for less, investors would inevitably question whether those costs are justified. Given the money involved, any reassessment on their part would have ripple effects throughout all of these industries, as well as the millions of people with savings or pensions exposed to them.

There are security considerations, too. Highly capable open Chinese models, even if trailing the US frontier, could make advanced AI systems available to a much wider range of users, notably in cases where US companies restrict access or impose stronger safeguards. When the US government demanded Anthropic limit access to its latest models, cybersecurity leaders warned that doing so would make it harder for defenders to find and fix vulnerabilities. Those restrictions are harder to justify if comparable models are available elsewhere. Organizations denied access to US models may feel compelled to rely on Chinese alternatives to secure their networks, or else accept the greater exposure to attackers able to use the same tools. Already, reports are starting to emerge where Kimi K3 identified and fixed cyber vulnerabilities that OpenAI’s Codex and Anthropic’s Fable would not touch due to safety guardrails. Even less broadly capable models can still pose a threat and some already appear to be doing so. In June, China’s Z.ai claimed its GLM-5.2 model could match Anthropic’s Mythos on cybersecurity tasks, even though it trailed in more general tasks.

As neither model has yet been fully released, it is still difficult to independently assess how capable either actually is, and companies’ benchmark claims should be treated with caution. Even so, there has been little public suggestion that the companies are fundamentally misrepresenting their results when it comes to performance.

But the exact ranking is almost beside the point. Whether Kimi K3 and Qwen3.8 ultimately prove to rank among the world’s top five models or merely the top 10, the broader conclusion remains the same: China’s leading AI companies are now producing systems that could plausibly rival those emerging from top US labs. And they are doing so with enough regularity that each new release should no longer be treated as a shock, let alone something as singularly galvanizing as another “DeepSeek” or “Sputnik moment.” If this really is a race, it’s time to accept that someone else might actually win, or at least get close enough that they might as well have.

China delivers a one-two punch to America’s AI dominance

2026-07-20T08:47:44-04:00

China’s leading AI companies are ramping up the pressure on Silicon Valley, as Moonshot and Alibaba unveiled models they claim can go toe-to-toe with the best from OpenAI and Anthropic at a fraction of the cost. The rapid-fire releases suggest America’s lead at the AI frontier is increasingly tight, just as the technology is becoming central to national security, economic power, and geopolitical influence.

The opening salvo came from Beijing-based Moonshot AI, one of China’s leading AI model developers, which unveiled Kimi K3 on Friday. Moonshot claims its own testing ranks it consistently above nearly every US system, trailing only OpenAI’s GPT-5.6 Sol and Anthropic’s Claude Fable 5, though it came out ahead on certain benchmarks.

Over the weekend, Chinese tech behemoth Alibaba followed with a preview of Qwen3.8, a new model it says is “one of the most powerful model[s] available today” and “second only to Fable 5,” Anthropic’s flagship model.

Both companies are emphasizing a key difference from the leading US labs: Rather than locking their most advanced models behind closed doors, they are making them publicly available. While some US companies, most notably Meta, have taken a similar approach, releasing models that developers can freely download, modify, and build upon has become a growing point of differentiation for China’s AI industry.

Moonshot describes Kimi K3 as the world’s largest open-source AI system, with 2.8 trillion parameters. Parameter counts are measures of a model’s complexity during training and offer a rough indication of its scale and performance, though bigger does not always mean better. Alibaba says Qwen3.8 is a 2.4 trillion parameter model and “continuously evolving.” Neither OpenAI nor Anthropic disclose exact parameter counts for their leading systems.

It remains difficult to assess how capable either Chinese model is until they are fully released and independently tested. Moonshot says it will release full model weights — the internal numerical learned during an AI model’s training period — a week from now on July 27th. Alibaba says Qwen3.8 is “going open-weight soon.”

Even so, the releases have already sharpened competition between the US and China in what has been repeatedly characterized as the defining technological race of our time. They have shaken up the industry in a way not seen since DeepSeek unveiled a low-cost model last year that rivaled leading US systems. The models also raise questions about whether the vast sums of money US companies are pouring into chips, data centers, and model training can secure a durable advantage, particularly if Chinese rivals can approach — or surpass — that frontier with fewer resources.

The prospect of two highly capable Chinese models being released for others to download and adapt also contrasts starkly with the more guarded approach of US labs, whose most advanced systems remain proprietary. That openness emerges even as Washington moves rapidly to restrict global access to the underlying technology. The government has used export controls to restrict China’s access to the most advanced chips, as well as to force Anthropic to pull its most capable system from the market over concerns it could help foreign competitors catch up.

Whether the new Chinese models live up to their creator’s claims remains to be seen. But, like DeepSeek before them, they are likely to sharpen the technological rivalry between the US and China, influence economic and national security policy, and show that America’s lead is far narrower than it once appeared.

Google is better than Apple at playing the AI regulations game

2026-07-16T15:41:51-04:00

Google CEO Sundar Pichai | Bloomberg via Getty Images

Today, the European Union ordered Google to give its AI rivals greater access to Android, the open-source operating system that powers billions of devices worldwide. The demand is hardly surprising. It may look like a defeat on paper for Google, which has spent years resisting exactly this kind of access, but it is a regulatory win. It’s also a sign that Google may have outmaneuvered Apple by playing Brussels’ regulatory game far more shrewdly.

In one of two decisions handed down on Thursday, the European Commission — the EU’s executive arm and the principal enforcer of the bloc’s competition rules — said Google must give rival AI assistants the same kind of system features and data access it grants Google’s Gemini. The order stems from Europe’s Digital Markets Act (DMA), which requires dominant platforms designated as “gatekeepers” to give competitors access to certain systems and data comparable to what is available to their own services.

Crucially, Google has until July 2027 to make those changes, giving it roughly a year to continue expanding Gemini, negotiate technical details with the EU, and shape how its rivals will eventually plug into Android. The company could also challenge the decision in court, though it has not commented publicly whether it plans to do so and declined to comment on the record when The Verge inquired.

While Google has made it clear it would rather not open its systems at all — arguing it risks compromising users’ safety, security, and privacy — that yearlong runway compounds an already significant advantage. Gemini is already deeply integrated into Android and often ships preinstalled as the default AI assistant on many devices, giving Google more time to strengthen its position before rivals like OpenAI and Anthropic gain comparable levels of access.

Google’s strategy of shipping first and negotiating with regulators later stands in stark contrast to Apple’s. When Apple announced its long-awaited Siri AI assistant last month, it made a big point of saying the feature would not launch in Europe because of the DMA.

As with Android, the Commission said Apple would need to give third-party assistants comparable access to key systems, features, and data to those of Siri AI. Apple argued that doing so “would be irresponsible” and create unacceptable privacy and security risks. The company said it asked the Commission for 18 months to build a compliant version and introduce the required interoperability on a “gradually rolling” basis. The Commission rejected that proposal.

Apple still has no public timeline for when, or even whether, it plans to bring Siri AI to the EU and did not respond to The Verge’s request for comment. Google, meanwhile, just secured the very grace period for Gemini that Apple wanted for Siri AI: time to comply with the DMA while its AI assistant stays on the market.

The contrast may partly reflect where each company’s AI assistant stood when the DMA began shaping product decisions. Gemini has been the central pillar of Google’s AI strategy for years and has been widely distributed across the company’s product ecosystem, giving Google a strong incentive to stay in the market and figure out compliance with any laws later. Apple, meanwhile, unveiled its new Siri AI very recently and chose to withhold it from the EU, despite having had years to anticipate the DMA’s requirements during the product’s design.

Apple also chose to turn Siri AI’s absence into a political weapon, evidently hoping the court of public opinion would find in its favor and pressure Brussels to relax interoperability requirements. It did so publicly and repeatedly, taking the unusual step of dedicating part of its WWDC 2026 keynote to explaining why Siri AI won’t be coming to Europe, publishing a pointed blog post titled “Due to DMA, Siri AI delayed in EU for iOS 27 and iPadOS 27,” and holding media briefings on the issue. It relayed news that China was missing out on Siri AI through a one-sentence footnote. All of this served to cast Brussels, not Apple’s product choices, as the reason for the delay.

It’s also possible that the split is less significant behind the scenes than it appears in public. Google and Apple both vehemently oppose the DMA’s interoperability demands, framing them as threats to privacy, security, and product integrity. The two companies have also worked together on integrating Gemini into Apple’s AI products, including Siri AI, making it plausible that they have remained in contact while exploring different ways to fight the same set of restrictions.

For now, though, the difference is stark. Google has a year to bring Android into compliance while continuing to expand Gemini. Brussels denied Apple this kind of runway, and who knows when Siri AI will reach the EU.

Google ordered to open Android and Search to rivals in Europe

2026-07-16T08:42:27-04:00

Google must give rival AI assistants and search engines greater access to key parts of Android and Google Search after the European Union ordered the company to comply with the bloc’s digital antitrust rules.

The two decisions, handed down Thursday, could weaken Google’s control over two of the tech industry’s most important platforms and have far-reaching consequences for the company, shape the future of its AI tool Gemini, and open up new opportunities for rivals to gain ground. Google has until January 2027 to begin sharing search data and July 2027 to implement changes to Android.

The rulings stem from technical regulatory proceedings under the EU’s Digital Markets Act (DMA), which requires dominant platforms — designated “gatekeepers” — to give competitors comparable access to systems and data as they themselves enjoy. Unlike a financial penalty, the procedures require Google to change how it operates in order to bring its services in line with the DMA and are developed through extensive engagement between the company and regulators. If Google does not comply, the European Commission could impose fines of up to 10 percent of its annual worldwide turnover, potentially tens of billions of dollars.

The two proceedings focus on separate but thematically similar parts of Google’s business: How rival AI assistants can operate on Android, and how competing search engines and other AI chatbots can access data generated by Google Search.

The Android decision sets out how Google must give rival AI assistants the same kind of system features and data access as it gives Gemini. In practical terms, it requires greater interoperability, allowing users — rather than Google — to decide whether competing tools can access their data and device hardware. That could include the ability to interact with apps, respond to voice commands like “Hey Google,” and make fuller use of the phone’s hardware. That means Android users could eventually choose ChatGPT, Claude, Perplexity, or other assistants as deeply integrated system assistants instead of Gemini, with comparable access to device capabilities.

The second proceeding focuses on Google Search and the data it generates, setting out how competing search engines and AI services can gain access to information historically kept by Google. Notably, the EU said this includes AI chatbots, which effectively function as search engines in some cases. The data-sharing measure broadly echoes remedies ordered in the US search antitrust case, where Google was instructed to share valuable search information with rivals that could help boost their ability to compete.

Google has pushed back against both of these measures, arguing the requirements pose an unacceptable risk to user privacy and security, as well as compromise its products. The EU said there will be limits on how search data can be used and that Google will be able to vet which services get deeper access to Android to ensure safety and security aren’t compromised.

Today’s rulings may also offer an indication into how Brussels will approach similar questions involving other tech giants. This includes Apple, which declined to release Siri AI in Europe, explicitly blaming the DMA and arguing its interoperability requirements compromise user safety.

“With today’s measures, we want to support innovation and diversity in the European Union, enabling fair competition in the markets of AI assistant for Android devices and search engines,” said European Commission executive vice president for tech sovereignty, security, and democracy Henna Virkkunen. “Thanks to these measures we hope to see emerging alternatives to Google Search and Google’s AI services, such as Gemini, and that users in the EU can enjoy greater choice of services. All developers, large and small, are welcome to explore these new opportunities, which will certainly benefit users too.”

In a blog post published after the decisions, Google’s president of global affairs Kent Walker said: “Today’s decisions risk undermining vital privacy and security guardrails for millions of Europeans. We have repeatedly offered solutions to safeguard users while satisfying the DMA’s goals, but these rulings discount extensive evidence of user harm.”

OpenAI finally launches hardware… for Codex

2026-07-15T09:30:33-04:00

OpenAI is finally releasing some hardware. No, it isn’t the mysterious AI-powered device the company is developing with former Apple designer Jony Ive, a project already tangled up in a messy lawsuit. Instead, it’s a product designed to be used with its coding platform, Codex.

The device, a square-shaped block of buttons called Codex Micro, is a collaboration between the AI company and keyboard maker Work Louder. OpenAI said it is a limited-run collaboration that will give users more ways to monitor and manage their agents.

The pad closely resembles Work Louder’s Creator Micro 2, and marketing images show what appears to be an identical array of 13 mechanical switches alongside a joystick, dial, and touch sensor. The device also looks broadly similar to a separate pad Work Louder produced with Figma back in 2023.

OpenAI said Codex Micro will cost $230 and be available on Supply Co while supplies last. It did not specify how many units were available as part of the partnership.

Key lights show the status of Codex agents. | Image: OpenAI" data-portal-copyright="Image: OpenAI" />

In a video explaining the device, Work Louder cofounder Mike Di Genova said Micro has six frosted keys that provide a “live view of your Codex threads,” using different colors to indicate the status of a task, such as whether it is complete, needs feedback, is running, or has encountered an error. There are also command keys that can be assigned to common actions, like push-to-talk, accept or reject changes, and send, and the device comes with 32 additional keycaps of Codex icons. The joystick and dial can also be used to start common workflows and adjust reasoning level, respectively, and OpenAI says all controls are configurable from the ChatGPT desktop app.

The pad comes with an array of Codex keycaps. | Image: OpenAI" data-portal-copyright="Image: OpenAI" />

The device is separate from OpenAI’s primary hardware project in development with Ive. Details on that device are slim, but reports suggest it will be some kind of smart speaker that lets you talk with ChatGPT. It’s rumored to launch at some point next year. The product has come under renewed scrutiny this week after Apple filed a lawsuit accusing OpenAI of stealing hardware secrets, allegations it said are without merit.

Spotify’s Daniel Ek is bringing his body-scanning clinics to the US

2026-07-15T07:31:54-04:00

Health startup Neko Health was founded by Hjalmar Nilsonne, left, and Daniel Ek, right. | Image: Neko Health

Spotify founder Daniel Ek’s body-scanning startup, Neko Health, is setting its sights on the United States after raising $700 million from a star-studded group of celebrities, entrepreneurs, and investment firms. It plans to open its first clinic in New York this year before expanding rapidly across the country.

Neko operates private clinics offering full-body scans and blood tests using AI and custom-built medical equipment. Scans are designed to proactively screen customers for conditions including skin cancer, heart disease, and diabetes. The company says its goal is to catch problems early, prevent disease, and help people live longer.

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In a press release, cofounder and CEO Hjalmar Nilsonne said the new funding will help Neko take “that mission to the US for the first time,” starting with New York and other cities this year. The company did not specify where else it plans to open clinics or provide a more detailed timeline, though a waitlist for the New York location is now open on its website. The money will also fund further research and development into technology Nilsonne said could “make prevention possible at scale.”

Neko, which was founded in 2018 but operated quietly until launching in 2023, is part of a growing cohort of companies focused on preventive care and private screening, a market driven in part by rising interest in longevity and biohacking and gaps in traditional healthcare systems that are often more reactive, intervening only after symptoms appear.

According to its website, Neko currently operates eight clinics in the UK and Sweden, including four in London and two in Stockholm. Scans cost £299 in the UK and 2,750 Swedish kronor in Sweden — roughly $400 and $285, respectively. The company has not disclosed pricing for its US clinics.

Neko has attracted strong demand at its existing clinics, but has struggled to keep pace as it scales. The company says more than 350,000 people have joined scan waitlists or registered for one, with 100,000 having been scanned so far.

New investors in the latest round include musician will.i.am, tennis player Maria Sharapova, Meta chief Mark Zuckerberg and his wife, Priscilla Chan, and former footballer Thierry Henry. Existing backers include Reddit cofounder Alexis Ohanian and actor Zoë Saldaña. Neko did not share its new valuation, though according to unnamed sources cited by the Financial Times, it now sits at around $7 billion. The company last raised $260 million in early 2025.

Google’s Demis Hassabis says it’s time for a global AI watchdog — led by the US

2026-07-14T07:56:44-04:00

Demis Hassabis, during a panel session at the World Economic Forum in Davos, Switzerland. | Image: Bloomberg via Getty Images

Demis Hassabis thinks the world needs an AI watchdog with the power to hit the brakes if frontier models become too dangerous.

Writing in a blog post, the Google DeepMind CEO and cofounder said the US should lead the initiative, arguing that the country is the best place to set global standards “given its economic and technical standing.” The organization, which could resemble existing regulators like the Financial Industry Regulatory Authority, would be made up of leading independent experts and representatives from open-source communities and would have the authority to evaluate frontier models before they are released and coordinate an industry-wide slowdown if they were judged too risky to deploy.

The blog, titled “A Framework for Frontier AI and the Dawning of a New Age,” argued that the need for global regulation is becoming more urgent as AI systems grow in sophistication. Artificial general intelligence (AGI) “is probably only a few short years away,” he said. “When we look back on this time in the decades to come, I think we will realise we were standing in the foothills of the singularity – nothing less than the dawning of a new age for humanity.”

According to Axios, Hassabis has spent months quietly building support for his proposal, including briefing the Trump administration, other AI labs, and European officials, and hopes to have the new organization up and running before the end of the year. He told Axios that “the noises I’ve been hearing [from the Trump administration] are very positive.”

The proposal is the latest effort by Hassabis and other industry leaders to establish a coherent framework for governing increasingly powerful AI systems, as well as mitigate the risks they may pose. As of yet, there is no global set of rules governing AI specifically, nor a comprehensive set of rules nationally in the US. Hassabis, the joint winner of the 2024 Nobel Prize in Chemistry for his work on AI-based protein prediction, also signed his name to a statement calling for tougher protections against AI-aided bioweapons production last month.

Hassabis’ most recent comments follow a statement from top economists and tech titans — including Anthropic cofounder Jack Clark and former Google CEO Eric Schmidt — urging world leaders to take the looming economic impacts of AI seriously.

Social media limits are coming for teens across Europe

2026-07-13T05:22:52-04:00

The European Union is weighing sweeping new restrictions on children’s and teenagers’ access to social media, including age limits, an outright ban, and phased access. Social media platforms could also be forced to prove their services are not harmful before young people are allowed to use them.

European Commission President Ursula von der Leyen said the bloc’s executive arm could propose new legislation within months, after reviewing recommendations from a panel of experts released today. “This is not about whether children can access social media. It is about when social media can access our children,” von der Leyen said.

The panel recommended using a phased approach, including “no screens at all” for children under 3, supervised internet use for those under 13, and some limits for older teens. It also said social media platforms should have to prove their services are safe to younger users, an approach von der Leyen said she supports.

We need age-appropriate restrictions on platforms.

This is not about whether children can access social media.

It is about when social media can access our children.

For a safer start online for every child ↓ https://t.co/QheuC3gFzx
— Ursula von der Leyen (@vonderleyen) July 13, 2026

Von der Leyen said the Commission will consider the report and return with proposals “after the summer.” Any legislation would still need approval from the European Parliament and the EU’s 27 member countries before becoming law across the bloc. A formal proposal would add significant momentum to global efforts to curb children’s use of social media, joining a growing list of proposals or active regulations in countries including the UK and Australia.

New rules would also add significant pressure on platforms to demonstrate their services are safe to younger users. A preliminary investigation in the EU already found Meta to be in breach of its Digital Services Act last week over the “addictive” design of Facebook and Instagram. A similar finding was also issued against TikTok earlier this year.

Anthropic wants to develop its own drugs

2026-07-03T09:56:52-04:00

At the event “The Briefing: AI for Science” earlier this week, Anthropic announced Claude Science, a new “AI workbench for scientists” that pulls fragmented tools and datasets into one environment, and generates figures and visuals. Anthropic, already dominating the industry with its popular coding tools and powerful AI models, framed the launch around what it says is AI’s potential to “dramatically accelerate the pace of scientific discovery and the development of healthcare interventions,” and touted a long list of biotech and pharma customers already using Claude.

Anthropic also went a step further, saying it would develop drugs of its own. Head of life sciences Eric Kauderer-Abrams said the company will focus on discovering treatments for “neglected” diseases.

AI companies have been eager to court science and pharma customers — OpenAI, Amazon, Google, and others have their own life sciences tools and platforms. But Anthropic’s planned move is one of the most direct public attempts by a major frontier AI company to actually develop drugs itself. It puts it in the unusual position of selling software to other, potentially competing drugmakers. Anthropic joins a broader race that includes AI-first drug companies like Insilico, Google DeepMind spinout Isomorphic Labs, biotech startups, and Big Pharma companies building or buying AI tools of their own.

Anthropic has provided very few specific details about what it hopes to accomplish in the drug development space. At the event, Kauderer-Abrams didn’t say what the company would do if it finds any promising drug candidates. Anthropic did not respond to The Verge’s requests for comment seeking more details, including what diseases it plans to target first and whether it would partner up with other companies for lab work, animal testing, clinical trials, or manufacturing.

AI is applied at “every single stage of drug discovery.”

Experts told The Verge that the uncertainty surrounding Anthropic’s plans reflects a broader uncertainty around the AI drug boom itself. “AI drug discovery” can mean many things. It “is a really broad term,” explained Namshik Han, a professor at the University of Cambridge and cofounder of AI biotech startup CardiaTec. AI is applied at “every single stage of drug discovery,” he said, from finding new compounds and improving them to supporting research, data analysis, clinical trials, and even manufacturing. Every major drug company will be using AI in some way, he said. Matthew Todd, a professor of drug discovery at University College London, echoed the sentiment that AI already pervades drug discovery and research, calling it a “catchall phrase” given its broad array of uses.

AI is undoubtedly changing drug development. Han pointed to the numerous initiatives by pharma giants like AstraZeneca, Novo Nordisk, and GSK, and said AI can already help generate possible drug ideas, such as by suggesting new molecules that could interact with parts of the body like cell receptors that are already known to be involved with a particular disease or are targets of existing drugs. Todd said it’s immensely useful for speeding up research and helping “road test” new drug ideas. Given Anthropic’s work on frontier models, the company would presumably use generative AI to search across vast chemical and biological possibilities and help researchers make connections that would be difficult or slow to find otherwise, potentially suggesting new drug ideas, identifying new disease targets, or finding new uses for existing drugs.

But that is still a long way from an AI-designed drug reaching patients. Todd said the field is “a long way off” from an AI-designed drug being approved by regulators for human use. He added that the drug discovery process would not run autonomously, with human input and supervision required throughout. Todd and Han both noted the lack of publicly available, high-quality experimental data, such as how various chemicals behave in the body, could slow drug development efforts as well, stressing that even for well-studied areas of biology there are still large gaps in our understanding of how things work.

AI models “haven’t yet come close to making experiments unnecessary.”

AI is not positioned to fix many of the slowest parts of drug discovery. Frank von Delft, a professor of structural chemical biology at the University of Oxford and head of protein crystallography at the Oxford Centre for Medicines Discovery, said people are right to get excited about advancing AI models, but they “haven’t yet come close to making experiments unnecessary.” Drug candidates still have to be tested in the real world for efficacy, toxicity, and whether they have practical properties allowing them to be prepared, stored, and delivered safely as medicines. All of that requires skilled workers, a lot of money, and time, especially clinical work in humans — a point when many promising drug candidates fail. If Anthropic wants to develop a drug, von Delft said, it is “going to have to spend a lot on experiments.”

It’s possible Anthropic is willing to try. In the last year, the company has been actively hiring biologists and building its own wet labs, and as of writing it has several live applications hiring for life sciences roles. Han said Anthropic has been “actively recruiting” in the area too, adding that several of his academic colleagues had been approached by the company. Without naming names, Han said he thinks Anthropic has successfully hired a few candidates away from Big Pharma and prestigious academic institutions.

With all of this complexity, whatever disease Anthropic picks, any payoff is likely a long way away — at the very least, the better part of a decade, given how long it typically takes a new drug to go through clinical trials. There’s “always a big lag time” with testing medicine, Todd said. “It takes time to show experimentally that something’s safe.” No AI-designed drug has yet made it through clinical trials and FDA approval to reach market. Some AI-developed candidates have entered clinical trials, but it’s hard to know how much AI contributed, where in the process it was used, or whether those candidates outperform conventional drugs. AI can speed up part of the search, but drugs still need to prove themselves the old-fashioned way: in slow, methodical experiments that take place in the real world.