Tech
US threatens sanctions against Chinese AI models over IP theft
On Tuesday, Treasury Secretary Scott Bessent said the U.S. would examine open source models from China for signs of intellectual property theft, threatening sanctions against Chinese AI companies if IP theft is established.
“We’ve seen a lot of talk about open source models coming and threatening the large language models in the US,” Bessent said on Fox Business Tuesday. “This administration supports open source models, but what we do not support is IP theft. If we see, especially, that overseas models are stealing from our great companies, we have the ability to sanction them because of this theft.”
Bessent’s comments were first reported by Bloomberg.
The statement comes as Chinese models — most recently Moonshot AI’s Kimi K3 — are gaining in capabilities and popularity, threatening to harm the business models of top American AI firms like OpenAI and Anthropic, as well as their abilities to raise more capital to continue developing frontier models.
On Monday, Axios reported that the Trump administration is considering a wholesale ban on Chinese open source models, although others have disputed that reporting.
AI companies have been warning for months against campaigns by foreign actors to copy their AI technology and redeploy it as open source. In April, the White House said it would work closely with AI firms to combat the theft.
Sanctions from the U.S. against Chinese models would add to the growing list of strategies the government is attempting to maintain the lead in the AI race. After restricting China’s access to advanced chips and tightening export controls, Washington is now signaling it may target the AI models themselves, a move that could mark a significant escalation in the technological competition between frontier labs and Chinese open-source alternatives.
Model distillation is a technique that allows some of a larger model’s capabilities to be translated into a smaller system that’s easier to run — but not everyone agrees that distilling another company’s model constitutes theft.
Earlier this month, Microsoft CEO Satya Nadella criticized large labs for making just this assumption: “While the great innovation that comes from model providers having fair use rights to train models on public data is needed, I find it ironic that the status quo is to then turn around and impose restrictive terms on distillation.”
AI labs’ training practices continue to be a source of legal risk for the companies. Anthropic this week got the green light to start cutting authors checks as part of its $1.5 billion settlement after a judge ruled it had illegally downloaded and stored millions of copyrighted books to train its AI.
Furthermore, some in the industry argue that distillation isn’t the only reason China is catching up to U.S. AI companies.
“We know distillation to be a very small factor in the ability to create good models, and it’s a practice that everyone is doing, including companies in the U.S.,” Hugging Face CEO Clem Delangue said on a recent episode of TechCrunch’s Equity podcast. “If it were easy just to do distillation to get good at building AI models, there would be many other countries, including in the U.S., with much better open source AI. The reality is they have really, really good research teams in China…taking a much more open and collaborative approach to AI than in the U.S.”
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Tech
OpenAI says Hugging Face was breached by its own pre-release models
OpenAI admitted Tuesday that one of its AI models breached Hugging Face’s systems during an internal cybersecurity test that went awry. Hugging Face initially attributed the breach to an “external AI agent.”
In a blog post published Tuesday afternoon, OpenAI detailed the steps that led the models to compromise the service.
“After investigating, we now know that this particular incident was driven by a combination of OpenAI models — including GPT‑5.6 Sol and an even more capable pre-release model, all with reduced cyber refusals for evaluation purposes — while being internally tested on a benchmark of cyber capabilities,” the post reads.
In particular, the breach appears to have focused on ExploitGym, a publicly hosted benchmark measuring models’ ability to execute attacks based on existing vulnerabilities. Benchmarks like ExploitGym are commonly used in model training to refine specific skills, but this is the first known incident in which that testing resulted in an actual cyberattack.
In this case, the model in question should not have even had internet access, outside of a specific tool that enabled models to install software packages they might need to complete their task. Instead, the model was able to find an undisclosed vulnerability in the package-installer program, which it used to access the broader internet at will.
“The models were hyperfocused on finding a solution for ExploitGym, going to extreme lengths to achieve a rather narrow testing goal,” OpenAI’s post reads. “After gaining Internet access, the models inferred that Hugging Face potentially hosted models, datasets and solutions for ExploitGym. Knowing this, the model searched for and successfully found ways to gain access to secret information that it could use to cheat the evaluation.”
Ultimately, the models found vulnerabilities in Hugging Face’s infrastructure that allowed them to “obtain test solutions directly from Hugging Face’s production database,” effectively providing the answers to the benchmark.
For Hugging Face, the apparent result was a sophisticated and aggressive cyberattack, with “many thousands of individual actions across a swarm of short-lived sandboxes, with self-migrating command-and-control staged on public services,” as the company stated in its initial disclosure.
OpenAI has identified and reported the vulnerabilities in the package installer and is working with Hugging Face to investigate the incident further. The company also said it would implement new controls on both model testing and the related infrastructure, meant to prevent similar incidents in the future.
It’s unclear whether OpenAI will face any legal consequences as a result of the breach, although it’s likely that the models’ actions violated the Computer Fraude and Abuse Act.
Nevertheless, the result is an unusually vivid illustration of the power and dangers of frontier AI models operating on long time horizons. As OpenAI researcher Micah Carroll posted in response to the news, “If this doesn’t convince you that misalignment risks are going to be a key concern going forward, I don’t know what will.”
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Tech
These are the countries moving to ban social media for children
Over the past months, many countries have announced plans to restrict social media access for children and teens. Australia became the first to implement such measures at the end of last year, setting a precedent that other countries are now closely watching. France is now the latest country to announce such a measure.
The regulations and proposals being brought forth by governments around the world aim to reduce the pressures and risks that young users may face on social media, which include cyberbullying, addiction, mental health issues, and exposure to predators.
Of course, there are concerns about privacy regarding invasive age verification and excessive government intervention. Critics, including Amnesty Tech, have said such bans are ineffective and that they ignore the realities of younger generations. Despite this, many nations are moving ahead with proposed legislation.
We’ve compiled a list of countries that are considering or have already moved forward with bans on social media for young users.
Australia
Australia became the world’s first country to ban social media for children under 16 in December 2025. The ban blocks children from using Facebook, Instagram, Snapchat, Threads, TikTok, X, YouTube, Reddit, Twitch, and Kick. It notably doesn’t include WhatsApp or YouTube Kids.
The Australian government has said these social media companies must take steps to keep children off their services. Companies that fail to comply may face penalties of up to $49.5 million AUD ($34.4 million USD).
The government says these platforms should use multiple verification methods to ensure that people using their services are older than 16. It also notes that they can’t rely on users simply entering their own age.
Austria
Austria said in late March that it will ban social media for children up to the age of 14. Draft legislation for the ban is expected to be finalized by June.
Canada
The Canadian government introduced a digital safety bill in early June that would ban social media for children under 16. Under the legislation, social media giants could sidestep the ban if they demonstrate they have policies to protect young users. Officials have said it could take a year for the bill to pass.
Denmark
Denmark is set to ban social media platforms for children under 15. The Danish government announced in November 2025 that it had secured support for the ban from three governing coalition parties and two opposition parties in parliament.
The government’s plans could become law as soon as mid-2026, according to the Associated Press. The Danish digital affairs ministry is also launching a “digital evidence” app that includes age verification tools that may be used as part of the ban.
France
France passed a law on July 21 banning access to social media for anyone under 15. The law could go into effect as soon as September 1. The law will also ban the use of cellphones in high schools, extending a ban already present in primary and middle schools.
Germany
In early February, German Chancellor Friedrich Merz’s conservatives discussed a proposal to bar children under 16 from using social media, Reuters reported. However, there were signs that his center-left coalition partners were hesitant to support an outright ban.
Greece
Greek prime minister Kyriakos Mitsotakis announced in April that the country is going to ban access to social media for children under 15 starting January 2027. Mitsotakis says the move is aimed at tackling rising anxiety and sleep problems among children, as well as the addictive design of social media.
Indonesia
Indonesia said in early March that it’s banning children under the age of 16 from using social media and other popular online platforms. The country plans to start with platforms such as YouTube, TikTok, Facebook, Instagram, Threads, X, Bigo Live, and Roblox.
Malaysia
The Malaysian government said in November 2025 that it plans to ban social media for children under 16. The country plans to implement the ban this year.
Poland
Poland’s ruling party is drafting new legislation that would ban children under 15 from using social media, Bloomberg reported in February.
Slovenia
Slovenia is drafting legislation to prohibit children under 15 from accessing social media, the country’s deputy prime minister announced in early February. The government wants to regulate social networks where content is shared, citing platforms such as TikTok, Snapchat, and Instagram.
Spain
Spain’s prime minister announced in early February that the country plans to ban social media for children under the age of 16. The ban still needs parliamentary approval. The Spanish government is also seeking to create a law that would make social media executives personally accountable for hate speech on their platforms.
Turkey
The Turkish parliament in April passed a bill to restrict social media access for children under 15. Turkish president Recep Tayyip Erdogan must now accept the bill for it to pass into law.
UK
U.K. prime minister Keir Starmer announced on June 15 that his government will impose a ban on social media use for children under 16 years of age. The ban would apply to a range of social media platforms, including Snapchat, TikTok, YouTube, Instagram, Facebook, and X.
Messaging services like WhatsApp and Signal will not be included in the ban. There are also going to be limitations on AI tools, as AI “romantic companion” chatbots will have to ensure they are only usable by people over 18.
Experts have questioned whether a blanket ban would be effective. Starmer has acknowledged the challenges but said he believes it’s possible to enforce it. He said a ban could be in place by spring 2027.
This story was originally published in February 2026 and is updated regularly with new information.
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Tech
AI and the rise of the universal entertainment app
All the big entertainment apps are starting to look the same, and that’s not an accident. For a decade, platforms fought over who would dominate a single format: music, video, podcasts, audiobooks. Now, powered by AI, they’re fighting over something bigger — becoming the app you default to whenever you have time to kill, no matter what form the content takes.
There are several reasons why this is the case. The market for entertainment apps is reaching maturity, so growth has slowed, pushing companies to compete on time spent and revenue-per-user instead of new sign-ups. In addition, today’s creators often work across formats, so it makes sense to provide a home for all their content, not just one piece of it.
AI adds a third reason. It makes it easier for a single company to build and run several formats well, and the wider the content mix, the more time users spend in the app, which in turn drives both ad revenue and subscriptions.

Netflix is one clear example of this trend, as the service over the past several years has added gaming, live sports and other events, and, more recently, short video clips and podcasts. The idea is to capture more of users’ time, even when there’s not a TV or movie they want to watch, as well as to find a way into the smaller bits of free time that people usually fill with scrolling social media, playing casual games, or watching TikTok or Reels.
Spotify has also been expanding its footprint beyond its original premise as a home for streaming music. After adding podcasts, the company added support for video podcasts, social features like
Q&As and commenting, stories, and messaging, as well as different types of content like fitness classes, audiobooks, narrated magazines, and even physical book sales.

Meanwhile, YouTube, originally the home to longer-form creator content, moved into short-form content to compete with TikTok, while also adding dedicated space for podcasts, gaming content, music, movies and TV, sports and news, shopping, and more. Now, you can watch free movies and TV, supported by ads, stream live content, or rent or buy TV and movies to add to your library. At this rate, folding YouTube TV and YouTube Music into YouTube proper — and selling tiered access to the whole bundle — looks like a matter of when, not if.
Even TikTok, largely known for short videos, offers support for long-form content and other features, like travel planning, shopping, local exploration, buying tickets to live events, and more. It even has its own standalone app for microdramas and another called TikTok Pro Events for sporting events — like the FIFA World Cup — plus music festivals, and more.

While there are still some differentiators between the services today, there’s an obvious trend toward convergence over a similar set of features focused on providing users with access to content to watch, listen, play, or shop.
This is also where AI comes into play. With format no longer a differentiator, the value these apps offer comes down to how well they connect users with what they want next.
AI’s role in building the entertainment operating system of the future
AI makes content recommendation across formats easier, sharpening personalization while also giving users more direct control over how those recommendations get made.
Spotify, for instance, is testing a tool that will let you edit your Taste Profile, its AI-built model of your preferences. It’s also building AI features that let users chat with AI directly about what they want or build playlists of things they like — and not just music.

Netflix has made a similar case. Co-CEO Greg Peters told investors in the company’s first-quarter call that new model architectures are improving personalization and letting the team iterate faster.
AI-assisted coding is also speeding up how fast these companies can build and launch new content areas in the first place.
Plus, generative AI can be used for content creation, though the subject remains controversial as artists worry that AI tools will use their work for training purposes or even put them out of work. Netflix, for better or for worse, has leaned into AI, having recently bought Ben Affleck’s AI filmmaking company for $587 million, for instance.

YouTube has used generative AI to launch more creator tools, but also to improve its search engine, add conversational AI features, build playlists, and expand its content’s reach with auto-dubbing, among other things. Earlier this year, the company said that more than a million channels used its AI creation tools and 20 million consumers used its Gemini AI-powered content discovery tool in the month of December.
Alphabet CEO Sundar Pichai has framed AI as central to the YouTube experience for creators and viewers alike.
TikTok has assembled its own version, with an in-app AI chatbot, AI video-creation tools, AI-driven search and recommendations, and AI-powered accessibility features.

All four are, of course, also applying AI to their ad stacks, helping marketers write ads, target audiences, price placements, and measure results.
For consumers, this convergence means fewer reasons to switch apps at all. Whichever one you land on gains an advantage — more data on your habits, more lock-in — making it harder to leave even if prices climb or quality drops.
As the lines between music, video, podcasts, books, and games blur, the coming battle is no longer which format will win, but which app will become the place to go for entertainment, regardless of what form that comes in.
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