On Dec. 9, OpenAI made its artificial intelligence video generation model Sora publicly available in the U.S. and other countries.
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The U.K. is drawing up measures to regulate the use of copyrighted content by tech companies to train their artificial intelligence models.
The British government on Tuesday kicked off a consultation which aims to increase clarity for both the creative industries and AI developers when it comes to both how intellectual property is obtained and then used by AI firms for training purposes.
Some artists and publishers are unhappy with the way their content is being scraped freely by companies like OpenAI and Google to train their large language models — AI models trained on huge quantities of data to generate humanlike responses.
Large language models are the foundational technology behind today’s generative AI systems, including the likes of OpenAI’s ChatGPT, Google’s Gemini and Anthropic’s Claude.
Last year, The New York Times brought a lawsuit against Microsoft and OpenAI accusing the companies of infringing its copyright and abusing intellectual property to train large language models.
In response, OpenAI disputed the NYT’s allegations, stating that the use of open web data for training AI models should be considered “fair use” and that it provides an “opt-out” for rights holders “because it’s the right thing to do.”
Separately, image distribution platform Getty Images sued another generative AI firm, Stability AI, in the U.K., accusing it of scraping millions of images from its websites without consent to train its Stable Diffusion AI model. Stability AI has disputed the suit, noting that the training and development of its model took place outside the U.K.
Proposals to be considered
First, the consultation will consider making an exception to copyright law for AI training when used in the context of commercial purposes but while still allowing rights holders to reserve their rights so they can control the use of their content.
Second, the consultation will put forward proposed measures to help creators license and be remunerated for the use of their content by AI model makers, as well as give AI developers clarity over what material can be used for training their models.
The government said more work needs to be done by both the creative industries and technology firms to ensure any standards and requirements for rights reservation and transparency are effective, accessible and widely adopted.
The government is also considering proposals that would require AI model makers to be more transparent about their model training datasets and how they’re obtained so that rights holders can understand when and how their content has been used to train AI.
That could prove controversial — technology firms aren’t especially forthcoming when it comes to the data that fuels their coveted algorithms or how they train them up, given the commercial sensitivities involved in revealing those secrets to potential competitors.
Previously, under former Prime Minister Rishi Sunak, the government attempted to agree a voluntary AI copyright code of practice.
AI copyright rules: U.K. versus U.S.
In a recent interview with CNBC, the boss of app development software firm Appian said he thinks the U.K. is well placed to be the “global leader on this issue.”
“The U.K. has put a stake in the ground declaring its prioritization of personal intellectual property rights,” Matt Calkins, Appian’s CEO, told CNBC. He cited 2018’s Data Protection Act as an example of how the U.K. is “closely associated with intellectual property rights.”
The U.K. is also not “subject to the same overwhelming lobbying blitz from domestic AI leaders that the U.S. is,” Calkins added — meaning it might not be as prone to bowing down to pressure from tech giants as politicians stateside.
“In the U.S., anybody who writes a law about AI is going to hear from Amazon, Oracle, Microsoft or Google before that bill even reaches the floor,” Calkins said.
“That’s a powerful force stopping anyone from writing sensible legislation or protecting the rights of individuals whose intellectual property is being taken wholesale by these major AI players.”
The issue of potential copyright infringement by AI firms is becoming more notable as tech firms are moving toward a more “multimodal” form of AI — that is, AI systems that can understand and generate content in the form of images and video as well as text.
Last week, OpenAI made its AI video generation model Sora publicly available in the U.S. and “most countries internationally.” The tool allows a user to type out a desired scene and produce a high-definition video clip.
Vlad Tenev, chief executive officer of Robinhood Markets Inc., during the Token2049 conference in Singapore, on Thursday, Oct. 2, 2025.
Bloomberg | Bloomberg | Getty Images
The tokenization of real-world assets, from stocks to real estate, will spread to financial markets around the world, according to Robinhood Markets Chief Executive Officer Vlad Tenev.
“Tokenization is like a freight train. It can’t be stopped, and eventually it’s going to eat the entire financial system,” Tenev told a panel at a crypto conference in Singapore on Wednesday.
“I think most major markets will have some framework in the next five years,” he said, though he added that reaching 100% could take more than a decade.
A tokenized asset is a digital representation of a real-world asset, like stocks, bonds, or commodities, that can be recorded and traded on a blockchain or distributed ledger.
In June, Robinhood began offering more than 200 tokenized U.S. stocks to customers in the European Union, giving them a new way to gain exposure to the underlying assets. The move sent its stock surging to a then-record high.
“I think it will become the default way to get exposure to U.S. stocks outside the U.S.,” Tenev said.
He expects the practice to gain traction once there is greater licensing and regulatory clarity in more jurisdictions.
“I think that will come, starting in Europe, but then expanding to the rest of the world,” he said.
On the other hand, Tenev expects the U.S. to be among the last economies to actually fully tokenize, due to what he calls the greater sticking power of the financial infrastructure.
The crypto industry has long predicted that a mass tokenization of assets on the blockchain was coming, promising greater market efficiency.
And, along with Robinhood’s launch of tokenized stocks, there’s been more signs this year that real implementation is coming, with institutional giants Morgan Stanley and BlackRock signaling interest.
“I actually think cryptocurrency and traditional finance have been living in two separate worlds for a while, but they’re going to fully merge,” Tenev said at the event.
He cited stablecoins — digital currencies designed not to fluctuate wildly, and pegged to a commodity or a fiat currency like the U.S. dollar — as an early example of a tokenized real-world asset.
“I think that crypto technology has so many advantages over the traditional way we’re doing things that in the future there’s going to be no distinction,” Tenev said.
Co-founder and Chief Science Officer at Hugging Face, Thomas Wolf, speaks at the opening ceremony of the Web Summit, in Lisbon, Portugal, November 11, 2024.
Pedro Nunes | Reuters
Current artificial intelligence models from labs like OpenAI are unlikely to lead to major scientific breakthroughs, a tech co-founder said, pouring cold water on some of the hype around the technology and claims by major figures in the field.
The comments by Thomas Wolf, co-founder of $4.5 billion AI startup Hugging Face, are in stake contrast to those by major names in AI including OpenAI boss Sam Altman and Anthropic CEO Dario Amodei.
When Wolf talks about scientific breakthroughs, he means novel ideas like those at a Nobel Prize level. Examples including Nicolaus Copernicus who theorized the sun was at the center of the universe and other planets move round it.
Wolf explained a couple of issues with chatbots right now. The first is that these products like ChatGPT and others often agree or align with the person prompting it. Think back to if you’ve asked a chatbot a prompt and it will tell you how interesting or great that question is.
The second is that the models underpinning these chatbots are designed to “predict the most likely next token” or “word” in a sentence.
However, he noted two key traits of scientists. The first is that scientists who make major breakthroughs are often contrarian and question what others are saying.
“The scientist is not trying to predict the most likely next word. He’s trying to predict this very novel thing that’s actually surprisingly unlikely, but actually is true,” Wolf said.
The Hugging Face co-founder has been thinking about this topic for the last few months. His interest was sparked after he read an essay penned by Anthropic’s Amodei, who posited that “AI-enabled biology and medicine will allow us to compress the progress that human biologists would have achieved over the next 50-100 years into 5-10 years.”
That got Wolf thinking about the state of AI and how this won’t be possible, in his view, with the current crop of models.
Wolf said that these chatbots and tools will likely be used as a sort of “co-pilot for a scientist” where they are used for research to help the human generate new ideas.
To some extent, this has been happening already. Google DeepMind’s AlphaFold product has helped to analyze protein structures which the company has promised could aid scientists in discovering new drugs.
But there are some new startups that are hoping to take AI one step further into being able to make scientific breakthroughs, including Lila Sciences and FutureHouse.
Taiwan Semiconductor Manufacturing Company, Limited at Hsinchu Science Park.
Annabelle Chih | Getty Images News | Getty Images
Taiwan will not accept Washington’s proposal to locally manufacture half the chips it currently supplies to the U.S., the island’s top trade negotiator said.
Speaking to reporters, Cheng Li-chiun, also the country’s vice premier, said on Wednesday that the proposal for a “50-50” split in semiconductor production was not even discussed, as she returned from trade talks in the U.S., according to Taiwan’s Central News Agency.
Cheng said the talks were focused on lowering tariff rates, securing exemptions from tariff stacking — additional duties — and reducing levies on Taiwanese exports. Taiwan currently faces a “reciprocal” tariff rate of 20%.
Washington has held discussions with Taipei about the “50-50” split in semiconductor production, which would cut American reliance on Taiwan, Commerce Secretary Howard Lutnick said last weekend in an interview to NewsNation, adding that currently 95% of the U.S. demand was met via chips produced within Taiwan.
“My objective, and this administration’s objective, is to get chip manufacturing significantly onshored — we need to make our own chips,” Lutnick said. “The idea that I pitched [Taiwan] was, let’s get to 50-50. We’re producing half, and you’re producing half.”
U.S. President Donald Trump had also taken aim at the island’s dominance in chips earlier this year, accusing it of “stealing” the U.S.’ chip business.
The Office of the U.S. Trade Representative and Taiwan’s Ministry of Economic Affairs did not immediately respond to CNBC’s request for comments.
Lutnick’s proposal has been condemned by Taiwan’s politicians, with Eric Chu, chairman of the island’s principal opposition party Kuomintang, calling it “an act of exploitation and plunder,” according to the Central News Agency report.
“No one can sell out Taiwan or TSMC, and no one can undermine Taiwan’s silicon shield,” Chu said, referring to Taiwan Semiconductor Manufacturing Company, the world’s leader in advanced chip manufacturing.
Taiwan’s critical position in global chips production is believed to have assured the island nation’s defense against direct military action from China, often referred to as the “Silicon Shield” theory.
In his NewsNation interview, Lutnick downplayed the “Silicon Shield,” arguing that Taiwan would be safer with more balanced chip production between Washington and Taipei. Beijing views the democratically governed island of Taiwan as its own territory and has vowed to reclaim it by force if necessary, while Taipei rejects those claims.
Taiwan People’s Party Chairman Huang Kuo-chang reportedly called Lutnick’s proposal an attempt to “hollow out the foundations of Taiwan’s technology sector.”