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Ether ETFs have finally come to life this year after some started to fear they may be becoming zombie funds.

Collectively, the funds tracking the price of spot ether are on pace for their sixth consecutive week of inflows and eight positive week in the last nine, according to SoSoValue.

The second largest cryptocurrency has become more attractive to institutions in recent weeks largely due to recent regulatory momentum in the U.S. around stablecoins – many of which run on the Ethereum network – the successful IPO of Circle, the issuer of the second-largest stablecoin; and new leadership at the Ethereum Foundation.

“What we’re seeing is institutional recalibration,” said Ben Kurland, CEO at crypto charting and research platform DYOR. “After the initial ETH ETF approval fizzled without a price pop, smart money started quietly building positions. They’re betting not on price momentum but on positioning ahead of utility unlocks like staking access, options listings, and eventually inflows from retirement platforms.”

The first year of ether ETFs, which launched in July 2024, has been characterized by weak demand. While the funds have had spikes in inflows, they’ve trailed far behind bitcoin ETFs in both inflows and investor attention – amassing about $3.9 billion in net inflows since listing versus bitcoin ETFs’ $36 billion in their first year of trading.

“With increasing acceptance of crypto on Wall Street, especially now as a means for payments and remittances, investors are being drawn to ETH ETFs,” said Chris Rhine, head of liquid active strategies at Galaxy Digital.

Additionally, he added, the CME basis on ether – or the price difference between ether futures and the spot price – is higher than that of bitcoin, giving arbitrageurs an opportunity to profit by going long on ether ETFs while shorting futures (a common trading strategy) and contributing to the uptrend in ether ETF inflows.

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Ether (ETH) 1 month

Despite the uptrend in inflows, the price of ether itself is negative for this month and flat over the past month.

For the year, it’s down 25% as it’s been suffering from an identity crisis fueled by uncertainty about Ethereum’s value proposition, weaker revenue since its last big technical upgrade and increasing competition from Solana. Market volatility driven by geopolitical uncertainty this year has not helped.

In March, Standard Chartered slashed its ether price target by more than half. However, the firm also said the coin could still see a turnaround this year.

Since last week’s big spike in inflows, they’ve “slowed but stayed net positive, suggesting conviction, not hype,” Kurland said. “The market looks like a heart monitor, but the buyers are treating it like a long-term infrastructure bet.”

Don’t miss these cryptocurrency insights from CNBC Pro:

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Chip stocks fall on report U.S. could terminate waivers for Taiwan Semi and others

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Chip stocks fall on report U.S. could terminate waivers for Taiwan Semi and others

A motorcycle is seen near a building of the Taiwan Semiconductor Manufacturing Company (TSMC), which is a Taiwanese multinational semiconductor contract manufacturing and design company, in Hsinchu, Taiwan, on April 16, 2025.

Daniel Ceng | Anadolu | Getty Images

Semiconductor stocks declined Friday following a report that the U.S. is weighing measures that would terminate waivers allowing some chipmakers to send American technology to China.

Commerce Department official Jeffrey Kessler told Samsung Electronics, SK Hynix and Taiwan Semiconductor this week that he wanted to cancel their waivers, which allow them to send U.S. chipmaking tech to their factories in China, the Wall Street Journal reported, citing people familiar with the matter.

The VanEck Semiconductor ETF declined about 1%. Nvidia, Qualcomm and Marvell Technology fell about 1%, while Taiwan Semiconductor slipped about 2%.

The latest reported move by the Commerce Department comes as the U.S. and China hold an unsteady truce over tariffs and trade, with chip controls a key sticking point.

Read more CNBC tech news

The countries agreed to the framework of a second trade agreement in London days ago after relations soured following the initial tariff pause in May.

The U.S. issued several chip export changes after the May pause that rattled relations, with China calling the rules “discriminatory.”

U.S. chipmakers have been hit with curbs over the last few years, limiting the ability to sell advanced artificial intelligence chips to China due to national security concerns.

During its earnings report last month, Nvidia said the recent export restriction on its China-bound H20 chips hindered sales by about $8 billion.

Nvidia CEO Jensen Huang told investors on an earnings call that the $50 billion market in China for AI chips is “effectively closed to U.S. industry.” During a CNBC interview in May, he called getting blocked from China’s AI market a “tremendous loss.”

Read the full WSJ report here.

WATCH: U.S. prepares action targeting allies’ ability to ship American chip-making equipment to China

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Meta tried to buy Ilya Sutskever’s $32 billion AI startup, but is now planning to hire its CEO

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Meta tried to buy Ilya Sutskever's  billion AI startup, but is now planning to hire its CEO

When Meta CEO Mark Zuckerberg poached Scale AI founder Alexandr Wang last week as part of a $14.3 billion investment in the artificial intelligence startup, he was apparently just getting started.

Zuckerberg’s multibillion-dollar AI hiring spree has now turned to Daniel Gross, the CEO of Ilya Sutskever’s startup Safe Superintelligence, and former GitHub CEO Nat Friedman, according to sources with knowledge of the matter.

It’s not how Zuckerberg planned for a deal to go down.

Earlier this year, sources said, Meta tried to acquire Safe Superintelligence, which was reportedly valued at $32 billion in a fundraising round in April. Sutskever, who just launched the startup a year ago, shortly after leaving OpenAI, rebuffed Meta’s efforts, as well as the company’s attempt to hire him, said the sources, who asked not to be named because the information is confidential.

Soon after those talks ended, Zuckerberg started negotiating with Gross, the sources said. In addition to his role at Safe Superintelligence, Gross runs a venture capital firm with Friedman called NFDG, their combined initials.

Both men are joining Meta as part of the transaction, and will work on products under Wang, one source said. Meta, meanwhile, will get a stake in NFDG, according to multiple sources.

The Information was first to report on Meta’s plans to hire Gross and Friedman.

Gross, Friedman and Sutskever didn’t respond to CNBC’s requests for comment.

A Meta spokesperson said the company “will share more about our superintelligence effort and the great people joining this team in the coming weeks.”

Zuckerberg’s aggressive hiring tactics escalate an AI talent war that’s reached new heights of late. Meta, Google and OpenAI, along with a host of other big companies and high-valued startups, are racing to develop the most powerful large language models, and pushing towards artificial general intelligence (AGI), or AI that’s considered equal to or greater than human intelligence.

Last week, Meta agreed to pump $14.3 billion into Scale AI to bring on Wang and a few other top engineers while getting a 49% stake in the startup.

Altman said on the latest episode of the “Uncapped” podcast, which is hosted by his brother, that Meta has tried to lure OpenAI employees by offering signing bonuses as high as $100 million, with even larger annual compensation packages. Altman said “none of our best people have decided to take them up on that.”

“I’ve heard that Meta thinks of us as their biggest competitor,” Altman said on the podcast. “Their current AI efforts have not worked as well as they have hoped and I respect being aggressive and continuing to try new things.”

Meta didn’t respond to a request for comment on Altman’s remarks.

OpenAI, for its part, has gone to similar lengths, paying about $6.5 billion to hire iPhone designer Jony Ive and to acquire his nascent devices startup io.

Elsewhere, the founders of AI startup Character.AI were recruited back to Google last year in a multibillion-dollar deal, while DeepMind co-founder Mustafa Suleyman was brought on by Microsoft in a $650 million purchase of talent from Inflection AI.

In Gross, Zuckerberg is getting a longtime entrepreneur and AI investor. Gross founded the search engine Cue, which was acquired by Apple in 2013. He was a top executive at Apple and helped lead machine learning efforts and the development of Siri. He was later a partner at startup accelerator Y Combinator, before co‑founding Safe Superintelligence alongside Sutskever.

Friedman co-founded two startups before becoming the CEO of GitHub following Microsoft’s acquisition of the code-sharing platform in 2018.

NFDG has backed Coinbase, Figma, CoreWeave, Perplexity and Character.ai over the years, according to Pitchbook. It’s unclear what happens to its investment portfolio in a Meta deal, a source said.

WATCH: Zuckerberg, Altman feud for top AI talent

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Creators say they didn’t know Google uses YouTube to train AI

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Creators say they didn't know Google uses YouTube to train AI

Silhouettes of laptop and mobile device users are seen next to a screen projection of the YouTube logo.

Dado Ruvic | Reuters

Google is using its expansive library of YouTube videos to train its artificial intelligence models, including Gemini and the Veo 3 video and audio generator, CNBC has learned.

The tech company is turning to its catalog of 20 billion YouTube videos to train these new-age AI tools, according to a person who was not authorized to speak publicly about the matter. Google confirmed to CNBC that it relies on its vault of YouTube videos to train its AI models, but the company said it only uses a subset of its videos for the training and that it honors specific agreements with creators and media companies.

“We’ve always used YouTube content to make our products better, and this hasn’t changed with the advent of AI,” said a YouTube spokesperson in a statement. “We also recognize the need for guardrails, which is why we’ve invested in robust protections that allow creators to protect their image and likeness in the AI era — something we’re committed to continuing.”

Such use of YouTube videos has the potential to lead to an intellectual property crisis for creators and media companies, experts said.

While YouTube says it has shared this information previously, experts who spoke with CNBC said it’s not widely understood by creators and media organizations that Google is training its AI models using its video library.

YouTube didn’t say how many of the 20 billion videos on its platform or which ones are used for AI training. But given the platform’s scale, training on just 1% of the catalog would amount to 2.3 billion minutes of content, which experts say is more than 40 times the training data used by competing AI models.

The company shared in a blog post published in September that YouTube content could be used to “improve the product experience … including through machine learning and AI applications.” Users who have uploaded content to the service have no way of opting out of letting Google train on their videos. 

“It’s plausible that they’re taking data from a lot of creators that have spent a lot of time and energy and their own thought to put into these videos,” said Luke Arrigoni, CEO of Loti, a company that works to protect digital identity for creators. “It’s helping the Veo 3 model make a synthetic version, a poor facsimile, of these creators. That’s not necessarily fair to them.”

CNBC spoke with multiple leading creators and IP professionals, none were aware or had been informed by YouTube that their content could be used to train Google’s AI models.

Google DeepMind Veo 3.

Courtesy: Google DeepMind

The revelation that YouTube is training on its users’ videos is noteworthy after Google in May announced Veo 3, one of the most advanced AI video generators on the market. In its unveiling, Google showcased cinematic-level video sequences, including a scene of an old man on a boat and another showing Pixar-like animals talking with one another. The entirety of the scenes, both the visual and the audio, were entirely AI generated. 

According to YouTube, an average of 20 million videos are uploaded to the platform each day by independent creators by nearly every major media company. Many creators say they are now concerned they may be unknowingly helping to train a system that could eventually compete with or replace them.

“It doesn’t hurt their competitive advantage at all to tell people what kind of videos they train on and how many they trained on,” Arrigoni said. “The only thing that it would really impact would be their relationship to creators.”

Even if Veo 3’s final output does not directly replicate existing work, the generated content fuels commercial tools that could compete with the creators who made the training data possible, all without credit, consent or compensation, experts said.

When uploading a video to the platform, the user is agreeing that YouTube has a broad license to the content.

“By providing Content to the Service, you grant to YouTube a worldwide, non-exclusive, royalty-free, sublicensable and transferable license to use that Content,” the terms of service read.

“We’ve seen a growing number of creators discover fake versions of themselves circulating across platforms — new tools like Veo 3 are only going to accelerate the trend,” said Dan Neely, CEO of Vermillio, which helps individuals protect their likeness from being misused and also facilitates secure licensing of authorized content.

Neely’s company has challenged AI platforms for generating content that allegedly infringes on its clients’ intellectual property, both individual and corporate. Neely says that although YouTube has the right to use this content, many of the content creators who post on the platform are unaware that their videos are being used to train video-generating AI software.

Vermillio uses a proprietary tool called Trace ID to asses whether an AI-generated video has significant overlap with a human-created video. Trace ID assigns scores on a scale of zero to 100. Any score over 10 for a video with audio is considered meaningful, Neely said.

A video from YouTube creator Brodie Moss closely matched content generated by Veo 3. Using Vermillio’s Trace ID tool, the system attributed a score of 71 to the original video with the audio alone scoring over 90.

Vermillio

In one example cited by Neely, a video from YouTube creator Brodie Moss closely matched content generated by Veo 3. Trace ID attributed a score of 71 to the original video with the audio alone scoring over 90.

Some creators told CNBC they welcome the opportunity to use Veo 3, even if it may have been trained on their content.

“I try to treat it as friendly competition more so than these are adversaries,” said Sam Beres, a creator with 10 million subscribers on YouTube. “I’m trying to do things positively because it is the inevitable —but it’s kind of an exciting inevitable.”

Google includes an indemnification clause for its generative AI products, including Veo, which means that if a user faces a copyright challenge over AI-generated content, Google will take on legal responsibility and cover the associated costs.

YouTube announced a partnership with Creative Artists Agency in December to develop access for top talent to identify and manage AI-generated content that features their likeness. YouTube also has a tool for creators to request a video to be taken down if they believe it abuses their likeness.

However, Arrigoni said that the tool hasn’t been reliable for his clients.

YouTube also allows creators to opt out of third party training from select AI companies including Amazon, Apple and Nvidia, but users are not able to stop Google from training for its own models.

The Walt Disney Company and Universal filed a joint lawsuit last Wednesday against the AI image generator Midjourney, alleging copyright infringement, the first lawsuit of its kind out of Hollywood.

“The people who are losing are the artists and the creators and the teenagers whose lives are upended,” said Sen. Josh Hawley, R-Mo., in May at a Senate hearing about the use of AI to replicate the likeness of humans. “We’ve got to give individuals powerful enforceable rights and their images in their property in their lives back again or this is just never going to stop.”

Disclosure: Universal is part of NBCUniversal, the parent company of CNBC.

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