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Jessica Guistolise, Megan Hurley and Molly Kelley talk with CNBC in Minneapolis, Minnesota, on July 11, 2025, about fake pornographic images and videos depicting their faces made by their mutual friend Ben using AI site DeepSwap.

Jordan Wyatt | CNBC

In the summer of 2024, a group of women in the Minneapolis area learned that a male friend used their Facebook photos mixed with artificial intelligence to create sexualized images and videos.   

Using an AI site called DeepSwap, the man secretly created deepfakes of the friends and over 80 women in the Twin Cities region. The discovery created emotional trauma and led the group to seek the help of a sympathetic state senator.

As a CNBC investigation shows, the rise of “nudify” apps and sites has made it easier than ever for people to create nonconsensual, explicit deepfakes. Experts said these services are all over the Internet, with many being promoted via Facebook ads, available for download on the Apple and Google app stores and easily accessed using simple web searches.

“That’s the reality of where the technology is right now, and that means that any person can really be victimized,” said Haley McNamara, senior vice president of strategic initiatives and programs at the National Center on Sexual Exploitation.

CNBC’s reporting shines a light on the legal quagmire surrounding AI, and how a group of friends became key figures in the fight against nonconsensual, AI-generated porn.

Here are five takeaways from the investigation.

The women lack legal recourse

Because the women weren’t underage and the man who created the deepfakes never distributed the content, there was no apparent crime.

“He did not break any laws that we’re aware of,” said Molly Kelley, one of the Minnesota victims and a law student. “And that is problematic.”

Now, Kelley and the women are advocating for a local bill in their state, proposed by Democratic state Senator Erin Maye Quade, intended to block nudify services in Minnesota. Should the bill become law, it would levy fines on the entities enabling the creation of the deepfakes.

Maye Quade said the bill is reminiscent of laws that prohibit peeping into windows to snap explicit photos without consent.

“We just haven’t grappled with the emergence of AI technology in the same way,” Maye Quade said in an interview with CNBC, referring to the speed of AI development.

The harm is real

Jessica Guistolise, one of the Minnesota victims, said she continues to suffer from panic and anxiety stemming from the incident last year.

Sometimes, she said, a simple click of a camera shutter can cause her to lose her breath and begin trembling, her eyes swelling with tears. That’s what happened at a conference she attended a month after first learning about the images.

“I heard that camera click, and I was quite literally in the darkest corners of the internet,” Guistolise said. “Because I’ve seen myself doing things that are not me doing things.”

Mary Anne Franks, professor at the George Washington University Law School, compared the experience to the feelings victims describe when talking about so-called revenge porn, or the posting of a person’s sexual photos and videos online, often by a former romantic partner.

“It makes you feel like you don’t own your own body, that you’ll never be able to take back your own identity,” said Franks, who is also president of the Cyber Civil Rights Initiative, a nonprofit organization dedicated to combating online abuse and discrimination.

Deepfakes are easier to create than ever

Less than a decade ago, a person would need to be an AI expert to make explicit deepfakes. Thanks to nudifier services, all that’s required is an internet connection and a Facebook photo.

Researchers said new AI models have helped usher in a wave of nudify services. The models are often bundled within easy-to-use apps, so that people lacking technical skills can create the content.

And while nudify services can contain disclaimers about obtaining consent, it’s unclear whether there is any enforcement mechanism. Additionally, many nudify sites market themselves simply as so-called face-swapping tools.

“There are apps that present as playful and they are actually primarily meant as pornographic in purpose,” said Alexios Mantzarlis, an AI security expert at Cornell Tech. “That’s another wrinkle in this space.”

Nudify service DeepSwap is hard to find

The site that was used to create the content is called DeepSwap, and there’s not much information about it online.

In a press release published in July, DeepSwap used a Hong Kong dateline and included a quote from Penyne Wu, who was identified in the release as CEO and co-founder. The media contact on the release was Shawn Banks, who was listed as marketing manager. 

CNBC was unable to find information online about Wu, and sent multiple emails to the address provided for Banks, but received no response.

DeepSwap’s website currently lists “MINDSPARK AI LIMITED” as its company name, provides an address in Dublin, and states that its terms of service are “governed by and construed in accordance with the laws of Ireland.”

However, in July, the same DeepSwap page had no mention of Mindspark, and references to Ireland instead said Hong Kong. 

AI’s collateral damage

The alarming rise of AI ‘nudify’ apps that create explicit images of real people

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China’s DeepSeek launches next-gen AI model. Here’s what makes it different

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China's DeepSeek launches next-gen AI model. Here's what makes it different

Anna Barclay | Getty Images News | Getty Images

Chinese startup DeepSeek’s latest experimental model promises to increase efficiency and improve AI’s ability to handle a lot of information at a fraction of the cost, but questions remain over how effective and safe the architecture is.  

DeepSeek sent Silicon Valley into a frenzy when it launched its first model R1 out of nowhere last year, showing that it’s possible to train large language models (LLMs) quickly, on less powerful chips, using fewer resources.

The company released DeepSeek-V3.2-Exp on Monday, an experimental version of its current model DeepSeek-V3.1-Terminus, which builds further on its mission to increase efficiency in AI systems, according to a post on the AI forum Hugging Face.

“DeepSeek V3.2 continues the focus on efficiency, cost reduction, and open-source sharing,” Adina Yakefu, Chinese community lead at Hugging Face, told CNBC. “The big improvement is a new feature called DSA (DeepSeek Sparse Attention), which makes the AI better at handling long documents and conversations. It also cuts the cost of running the AI in half compared to the previous version.”

“It’s significant because it should make the model faster and more cost-effective to use without a noticeable drop in performance,” said Nick Patience, vice president and practice lead for AI at The Futurum Group. “This makes powerful AI more accessible to developers, researchers, and smaller companies, potentially leading to a wave of new and innovative applications.”

The pros and cons of sparse attention 

An AI model makes decisions based on its training data and new information, such as a prompt. Say an airline wants to find the best route from A to B, while there are many options, not all are feasible. By filtering out the less viable routes, you dramatically reduce the amount of time, fuel and, ultimately, money, needed to make the journey. That is exactly sparse attention does, it only factors in data that it thinks is important given the task at hand, as opposed to other models thus far which have crunched all data in the model.

“So basically, you cut out things that you think are not important,” said Ekaterina Almasque, the cofounder and managing partner of new venture capital fund BlankPage Capital.

Sparse attention is a boon for efficiency and the ability to scale AI given fewer resources are needed, but one concern is that it could lead to a drop in how reliable models are due to the lack of oversight in how and why it discounts information.

“The reality is, they [sparse attention models] have lost a lot of nuances,” said Almasque, who was an early supporter of Dataiku and Darktrace, and an investor in Graphcore. “And then the real question is, did they have the right mechanism to exclude not important data, or is there a mechanism excluding really important data, and then the outcome will be much less relevant?”

This could be particularly problematic for AI safety and inclusivity, the investor noted, adding that it may not be “the optimal one or the safest” AI model to use compared with competitors or traditional architectures. 

DeepSeek, however, says the experimental model works on par with its V3.1-Terminus. Despite speculation of a bubble forming, AI remains at the centre of geopolitical competition with the U.S. and China vying for the winning spot. Yakefu noted that DeepSeek’s models work “right out of the box” with Chinese-made AI chips, such as Ascend and Cambricon, meaning they can run locally on domestic hardware without any extra setup.

Deepseek trains breakthrough R1 model at a fraction of US costs

DeepSeek also shared the actual programming code and tools needed to use the experimental model, she said. “This means other people can learn from it and build their own improvements.”

But for Almasque, the very nature of this means the tech may not be defensible. “The approach is not super new,” she said, noting the industry has been “talking about sparse models since 2015” and that DeepSeek is not able to patent its technology due to being open source. DeepSeek’s competitive edge, therefore, must lie in how it decides what information to include, she added.

The company itself acknowledges V3.2-Exp is an “intermediate step toward our next-generation architecture,” per the Hugging Face post.

As Patience pointed out, “this is DeepSeek’s value prop all over: efficiency is becoming as important as raw power.”

“DeepSeek is playing the long game to keep the community invested in their progress,” Yakefu added. “People will always go for what is cheap, reliable, and effective.”

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U.S. Commerce head Lutnick wants Taiwan to help America make 50% of its chips locally

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U.S. Commerce head Lutnick wants Taiwan to help America make 50% of its chips locally

A logo of the Taiwan Semiconductor Manufacturing Company (TSMC) displayed on a smartphone screen

Vcg | Visual China Group | Getty Images

The Trump administration is pushing Taipei to shift investment and chip production to the U.S. so that half of America’s chips are manufactured domestically, in a move that could have implications for Taiwan’s national defense. 

Washington has held discussions with Taipei about the “50-50” split in semiconductor production, which would significantly reduce American dependence on Taiwan, U.S. Secretary of Commerce Howard Lutnick told News Nation in an interview released over the weekend. 

Taiwan is said to produce over 90% of the world’s advanced semiconductors, which, according to Lutnick, is cause for concern due to the island nation’s distance from the U.S. and proximity to China. 

“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.” 

Lutnick’s goal is to reach about 40% domestic semiconductor production by the end of U.S. President Donald Trump’s current term, which would take northwards of $500 billion in local investments, he said. 

Taiwan’s stronghold on chip production is thanks to Taiwan Semiconductor Manufacturing Co., the world’s largest and most advanced contract chipmaker, which handles production for American tech heavyweights like Nvidia and Apple. 

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.

However, in his News Nation interview, Lutnick downplayed the “Silicon Shield,” and argued that Taiwan would be safer with more balanced chip production between the U.S. and Taiwan.

“My argument to them was, well, if you have 95% [chip production], how am I going to get it to protect you? You’re going to put it on a plane? You’re going to put it on a boat?” Lutnick said. 

Under the 50-50 plan, the U.S. would still be “fundamentally reliant” on Taiwan, but would have the capacity to “do what we need to do, if we need to do it,” he added.

Beijing views the democratically governed island of Taiwan as its own territory and has vowed to reclaim it by force if necessary. Taipei’s current ruling party has rejected and pushed back against such claims. 

This year, the Chinese military has held a number of large-scale exercises off the coast of Taiwan as it tests its military capabilities. During one of China’s military drills in April, Washington reaffirmed its commitment to supporting Taiwan. 

More in return for defense

Lutnick’s statements on the News Nation interview aligned with past comments from Trump, suggesting that the U.S. should get more in return for its defense of the island nation against China. 

Last year, then-presidential candidate Trump had said in an interview that Taiwan should pay the U.S. for defense, and accused the country of “stealing” the United States’ chip business. 

The U.S. was once a leader in the global semiconductor market, but has lost market share due to industry shifts and the emergence of Asian juggernauts like TSMC and Samsung

However, Washington has been working to reverse that trend across multiple administrations. 

TSMC has been building manufacturing facilities in the U.S. since 2020 and has continued to ramp up its investments in the country. It announced intentions to invest an additional $100 billion in March, bringing its total planned investment to $165 billion. 

The Trump administration recently proposed 100% tariffs on semiconductors, but said that companies investing in the U.S. would be exempt. The U.S. and Taiwan also remain in trade negotiations that are likely to impact tariff rates for Taiwanese businesses. 

US still considered a 'check on China' for Taiwan: Former defense minister

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YouTube agrees to pay Trump $24.5 Million to settle lawsuit over suspended account

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YouTube agrees to pay Trump .5 Million to settle lawsuit over suspended account

U.S. President Donald Trump reacts, as he arrives at Joint Base Andrews, Maryland, U.S., September 26, 2025.

Elizabeth Frantz | Reuters

YouTube has agreed to pay $24.5 million to settle a lawsuit involving the suspension of President Donald Trump’s account following the U.S. Capitol riots on Jan. 6, 2021.

The settlement “shall not constitute an admission of liability or fault,” on behalf of the defendants or related parties, according to a filing on Monday from the U.S. District Court for the Northern District of California.

Trump sued YouTube, Facebook and Twitter in mid-2021, after the companies suspended his accounts on their platforms over concerns related to the incitement of violence.

Since Trump won a second term in November and returned to the White House in January, the tech companies have been settling their disputes with the president. Facebook-parent Meta said in January that it would pay $25 million to settle its lawsuit with Trump. The following month, Elon Musk’s X, formerly Twitter, agreed to settle its Trump-related case for roughly $10 million.

In August, several Democratic senators, including Elizabeth Warren of Massachusetts, sent a letter to Google CEO Sundar Pichai and YouTube CEO Neal Mohan expressing their concern over a possible settlement with the president.

The senators said in the letter that they worried such an action would be part of a “quid-pro-quo arrangement to avoid full accountability for violating federal competition, consumer protection, and labor laws, circumstances that could result in the company running afoul of federal bribery laws.”

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