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Google’s AI is the ‘worst’ for stealing content, says People CEO

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When Google became the dominant search engine around 2004, not everyone was happy. Everyone from book publishers to music studios blasted the company for helping itself to copyrighted content without paying. The search giant eventually smoothed things over but now, twenty years later, Google has become the media industry’s villain all over again—this time for gobbling that same content to train its AI tools.

Speaking at Fortune’s Brainstorm Tech conference on Wednesday, People Inc CEO Neil Vogel—whose firm’s titles include People and Food & Wine—said other big AI firms are paying for publishers to use the content they create, but that Google has so far refused.

“Some AI shops are good actors. Open AI is a good guy,” said Vogel. “The worst guy is Google.”

Vogel made his comments during an on-stage panel discussion about the future of digital media in the new AI-driven internet. The comments come as media and news publishers are squaring off with AI companies at the deal table and in the courtroom. The New York Times has sued OpenAI alleging that it trained its chatbots on its content without permission or payment. OpenAI has called the suit baseless.

Cloudflare CEO Matthew Prince, who was also on Wednesday’s Brainstorm panel, said it has become far harder for websites to attract traffic at a time when AI firms serve as “answer engines” that provide what people are looking for in quick snippets.

Prince observed that, in the past, Google served as a “great patron” to the Internet by ingesting the content of web pages in order to display links to those pages in response to people’s search queries. This arrangement directed traffic to companies’ websites, offering them a chance to make money from the visitors.

Today, that traffic is falling dramatically since AI-generated answers often provide all the information users need. Google is among those supplying AI answers based on information it has crawled from companies’ websites but, unlike its traditional search results, Google’s AI answers don’t deliver the same traffic to websites—leading the likes of Vogel to fret that publishers have already traded analog dollars for digital dimes, and are now trading those dimes for AI pennies.

In the case of other big AI companies, publishers have obtained some leverage by working with firms like Cloudflare to cut off the so-called crawlers that read and ingest their content. In the case of Google, though, that hasn’t proved a viable option since the company’s crawler for AI is the same as it uses for showing search results. A publisher intent on preventing Google’s AI machine from crawling its content would have to sacrifice its discoverability in search too.

Vogel noted that, while Google searches are bringing less traffic to People Inc websites than in the past, they still account for between 25-30% of visits, making it financially unviable to cut off the company’s crawlers. He added that some AI firms have already agreed to pay content creators—including Anthropic, which this month reached a $1.5 billion settlement with book publishers—and that others are actively working on similar arrangements. The exception is Google, which Vogel dubbed a “bad actor.”

Google declined to comment on Vogel’s remarks.

The YouTube model as a possible solution

The current controversy over Google and other big AI’s use of others’ content has strong echoes of the early internet era. That era—and Google—may also offer a solution. Bill Gross, an influential early Internet figure credited with pioneering the paid search advertising business model and who is now founder and publisher of ProRata.ai, points to what happened with YouTube, which Google acquired in 2006.

Stuart Isett/Fortune

In its early days, YouTube outraged content creators like musicians and movie studios by letting users blatantly pirate their content. This triggered a series of lawsuits but, in time, YouTube came up with a compromise: It would give creators the option to monetize their content through advertising. That solution has proved workable and mutually beneficial for more than a decade—Google says it has paid more than $12 billion in shared ad revenue to rights holders as of December 2024—and Gross says it can work equally well for the AI era.

“The right way to solve this is not with lawsuits but with royalties,” said Gross, whose firm offers AI-related monetization options. “It opens up incentives for lots of new content to be created.”

Prince sounded even more bullish, predicting a “golden age” where AI companies would provide annual payments to those who produced unique and valuable content. He cited recent deals in which OpenAI agreed to pay the New York Times, Reddit and others.

Not everyone, however, is optimistic that the AI era will be an improvement. Janice Min, the CEO of Ankler Media, says that the past two decades show that big tech platforms like Google and Facebook may temporarily create arrangements that benefit publishers—but that they will abruptly yank them away as soon as they get what they need.

“I don’t see any benefit to partnerships with AI,” said Min. “I see the tech story happening over and over again. They come in and offer you money and it’s hard not to say no to shiny things.”

Min says Ankler has blocked all AI crawlers and is sticking with its strategy of building a media business around paid newsletters and Substack content instead.

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Databricks CEO Ali Ghodsi says company will be worth $1 trillion by doing these three things

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December 9, 2025

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Ali Ghodsi, the CEO and cofounder of data intelligence company Databricks, is betting his privately held startup can be the latest addition to the trillion-dollar valuation club.

In August, Ghodsi told the Wall Street Journalthat he believed Databricks, which is reportedly in talks toraise funding at a $134 billion valuation, had “a shot to be a trillion-dollar company.” At Fortune’s Brainstorm AI conference in San Francisco on Tuesday, he explained how it would happen, laying out a “trifecta” of growth areas to ignite the company’s next leg of growth.

The first is entering the transactional database market, the traditional territory of large enterprise players like Oracle, which Ghodsi said has remained largely “the same for 40 years.” Earlier this year, Databricks launched a link-based offering called Lakehouse, which aims to combine the capabilities of traditional databases with modern data lake storage, in an attempt to capture some of this market.

The company is also seeing growth driven by the rise of AI-powered coding. “Over 80% of the databases that are being launched on Databricks are not being launched by humans, but by AI agents,” Ghodsi said. As developers use AI tools for “vibe coding”—rapidly building software with natural language commands—those applications automatically need databases, and Ghodsi they’re defaulting to Databricks’ platform.

“That’s just a huge growth factor for us. I think if we just did that, we could maybe get all the way to a trillion,” he said.

The second growth area is Agentbricks, Databricks’ platform for building AI agents that work with proprietary enterprise data.

“It’s a commodity now to have AI that has general knowledge,” Ghodsi said, but “it’s very elusive to get AI that really works and understands that proprietary data that’s inside enterprise.” He pointed to the Royal Bank of Canada, which built AI agents for equity research analysts, as an example. Ghodsi said these agents were able to automatically gather earnings calls and company information to assemble research reports, reducing “many days’ worth of work down to minutes.”

And finally, the third piece to Ghodsi’s puzzle involves building applications on top of this infrastructure, with developers using AI tools to quickly build applications that run on Lakehouse and which are then powered by AI agents. “To get the trifecta is also to have apps on top of this. Now you have apps that are vibe coded with the database, Lakehouse, and with agents,” Ghodsi said. “Those are three new vectors for us.”

Ghodsi did not provide a timeframe for attaining the trillion-dollar goal. Currently, only a handful of companies have achieved the milestone, all of them as publicly traded companies. In the tech industry, only big tech giants like Apple, Microsoft, Nvidia, Alphabet, Amazon, and Meta have managed to cross the trillion-dollar threshold.

To reach this level would require Databricks, which is widely expected to go public sometime in early 2026, to grow its valuation roughly sevenfold from its current reported level. Part of this journey will likely also include the expected IPO, Ghodsi said.

“There are huge advantages and pros and cons. That’s why we’re not super religious about it,” Ghodsi said when asked about a potential IPO. “We will go public at some point. But to us, it’s not a really big deal.”

Could the company IPO next year? Maybe, replied Ghodsi.



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New contract shows Palantir working on tech platform for another federal agency that works with ICE

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December 9, 2025

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Palantir, the artificial intelligence and data analytics company, has quietly started working on a tech platform for a federal immigration agency that has referred dozens of individuals to U.S. Immigration and Customs Enforcement for potential enforcement since September.

The U.S. Citizenship and Immigration Services agency—which handles services including citizenship applications, family immigration, adoptions, and work permits for non-citizens—started the contract with Palantir at the end of October, and is paying the data analytics company to implement “Phase 0” of a “vetting of wedding-based schemes,” or “VOWS” platform, according to the federal contract, which was posted to the U.S. government website and reviewed by Fortune.

The contract is small—less than $100,000—and details of what exactly the new platform entails are thin. The contract itself offers few details, apart from the general description of the platform (“vetting of wedding-based schemes”) and an estimate that the completion of the contract would be Dec. 9.Palantir declined to comment on the contract or nature of the work, and USCIS did not respond to requests for comment for this story.

But the contract is notable, nonetheless, as it marks the beginning of a new relationship between USCIS and Palantir, which has had longstanding contracts with ICE, another agency of the Department of Homeland Security, since at least 2011. The description of the contract suggests that the “VOWS” platform may very well be focused on marriage fraud and related to USCIS’ recent stated effort to drill down on duplicity in applications for marriage and family-based petitions, employment authorizations, and parole-related requests.

USCIS has been outspoken about its recent collaboration with ICE. Over nine days in September, USCIS announced that it worked with ICE and the Federal Bureau of Investigation to conduct what it called “Operation Twin Shield” in the Minneapolis-St. Paul area, where immigration officials investigated potential cases of fraud in immigration benefit applications the agency had received. The agency reported that its officers referred 42 cases to ICE over the period. In a statement published to the USCIS website shortly after the operation, USCIS director Joseph Edlow said his agency was “declaring an all-out war on immigration fraud” and that it would “relentlessly pursue everyone involved in undermining the integrity of our immigration system and laws.” 

“Under President Trump, we will leave no stone unturned,” he said.

Earlier this year, USCIS rolled out updates to its policy requirements for marriage-based green cards, which have included more details of relationship evidence and stricter interview requirements.

While Palantir has always been a controversial company—and one that tends to lean into that reputation no less—the new contract with USCIS is likely to lead to more public scrutiny. Backlash over Palantir’s contracts with ICE have intensified this year amid the Trump Administration’s crackdown on immigration and aggressive tactics used by ICE to detain immigrants that have gone viral on social media. Not to mention, Palantir inked a $30 million contract with ICE earlier this year to pilot a system that will track individuals who have elected to self-deport and help ICE with targeting and enforcement prioritization. There has been pushback from current and former employees of the company alike over contracts the company has with ICE and Israel.

In a recent interview at the New York Times DealBook Summit, Karp was asked on stage about Palantir’s work with ICE and later what Karp thought, from a moral standpoint, about families getting separated by ICE. “Of course I don’t like that, right? No one likes that. No American. This is the fairest, least bigoted, most open-minded culture in the world,” Karp said. But he said he cared about two issues politically: immigration and “re-establishing the deterrent capacity of America without being a colonialist neocon view. On those two issues, this president has performed.”



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CoreWeave CEO: Despite see-sawing stock, IPO was ‘incredibly successful’ amid challenges of tariff timing

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December 9, 2025

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CoreWeave has been rocked by dizzying stock swings—with its stock currently trading 52% below its post-IPO high—and a frequent target of market commentators, but CEO Michael Intrator says the company’s move to the public markets has been “incredibly successful. And he takes the public’s mixed reaction in stride, given the novelty of CoreWeave’s “neocloud” business which competes with established cloud providers like Amazon AWS and Google Cloud.

“When you introduce new models, introduce a new way of doing business, disrupt what has been a static environment, it’s going to take some people some time,” Intrator said Tuesday at Fortune’s Brainstorm AI conference in San Francisco. But, he added, more people are beginning to understand the CoreWeave’s business model.

“We came out into one of the most challenging environments,” Intrator said of CoreWeave’s March IPO, which occurred very close to President Trump’s “Liberation Day” tariffs in April. “In spite of the incredible headwinds, we’re able to launch a successful IPO.”

CoreWeave, which priced its IPO at $40 per share, has experienced frequent severe up-and-down price swings in the eight months since its public market debut. At its closing price of $90.66 on Tuesday, the stock remains well above its IPO price.

As Fortune reported last month, CoreWeave’s rapid rise has been fueled by an aggressive, debt-heavy strategy to stand up data centers at unprecedented speed for AI customers. And for now, the bet is still paying off. In its third-quarter results released in November, the company said its revenue backlog nearly doubled in a single quarter—to $55.6 billion from $30 billion—reflecting long-term commitments from marquee clients including Meta, OpenAI, and French AI startup Poolside. Both earnings and revenue came in ahead of Wall Street expectations.

But the numbers were not all celebratory. CoreWeave disclosed a further increase in the debt it has taken on to finance its expansion, and it revised its full-year revenue outlook downward—suggesting that, even with historic demand in the pipeline.

With media headlines calling CoreWeave a “ticking time bomb,” with critics calling out insider stock sales, circular financing accusations and an overreliance on Nvidia, Intrator was asked whether he felt CoreWeave was misunderstood.

“Look, we built a company that is challenging one of the most stable businesses that exist—that cloud business, these three massive players,” he said, referring to AWS, Microsoft Azure and Google Cloud.  I feel like it’s incumbent on CoreWeave to introduce a new business model on how the cloud is going to be built and run. And that’s what we’re doing.” 

He repeatedly framed CoreWeave not as a GPU reseller or traditional data-center operator but as a company purpose-built from scratch to deliver high-performance, parallelized computing for AI workloads. That focus, he said, means designing proprietary software that orchestrates GPUs, building and colocating its own infrastructure, and moving “up the stack” through acquisitions such as Weights & Biases and OpenPipe.

Intrator also defended the company’s debt strategy, saying CoreWeave is effectively inventing a new financing model for AI infrastructure. He pointed to the company’s ability to repurpose power sources, rapidly deploy capacity, and finance large-scale clusters as proof it is solving problems incumbents never had to face.

“When I look back at history of the company, it took us a year with with a company investor like Fidelity, before they were like, ‘Oh, I get it,’” he said. “So look, we’ve been public for eight months. I couldn’t be prouder of what the company has accomplished.” 



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