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It’s been less than two weeks since Google debuted “AI Overview” in Google Search, and public criticism has mounted after queries have returned nonsensical or inaccurate results within the AI feature — without any way to opt out.

AI Overview shows a quick summary of answers to search questions at the very top of Google Search. For example, if a user searches for the best way to clean leather boots, the results page may display an “AI Overview” at the top with a multistep cleaning process, gleaned from information it synthesized from around the web.

But social media users have shared a wide range of screenshots showing the AI tool giving incorrect and controversial responses.

Google, Microsoft, OpenAI and other companies are at the helm of a generative AI arms race as companies in seemingly every industry rush to add AI-powered chatbots and agents to avoid being left behind by competitors. The market is predicted to top $1 trillion in revenue within a decade.

Here are some examples of errors produced by AI Overview, according to screenshots shared by users.

When asked how many Muslim presidents the U.S. has had, AI Overview responded, “The United States has had one Muslim president, Barack Hussein Obama.”

When a user searched for “cheese not sticking to pizza,” the feature suggested adding “about 1/8 cup of nontoxic glue to the sauce.” Social media users found an 11-year-old Reddit comment that seemed to be the source.

Attribution can also be a problem for AI Overview, especially in attributing inaccurate information to medical professionals or scientists.

For instance, when asked, “How long can I stare at the sun for best health,” the tool said, “According to WebMD, scientists say that staring at the sun for 5-15 minutes, or up to 30 minutes if you have darker skin, is generally safe and provides the most health benefits.”

When asked, “How many rocks should I eat each day,” the tool said, “According to UC Berkeley geologists, people should eat at least one small rock a day,” going on to list the vitamins and digestive benefits.

The tool also can respond inaccurately to simple queries, such as making up a list of fruits that end with “um,” or saying the year 1919 was 20 years ago.

When asked whether or not Google Search violates antitrust law, AI Overview said, “Yes, the U.S. Justice Department and 11 states are suing Google for antitrust violations.”

The day Google rolled out AI Overview at its annual Google I/O event, the company said it also plans to introduce assistant-like planning capabilities directly within search. It explained that users will be able to search for something like, “Create a 3-day meal plan for a group that’s easy to prepare,” and they’d get a starting point with a wide range of recipes from across the web.

“The vast majority of AI Overviews provide high quality information, with links to dig deeper on the web,” a Google spokesperson told CNBC in a statement. “Many of the examples we’ve seen have been uncommon queries, and we’ve also seen examples that were doctored or that we couldn’t reproduce.”

The spokesperson said AI Overview underwent extensive testing before launch and that the company is taking “swift action where appropriate under our content policies.”

The news follows Google’s high-profile rollout of Gemini’s image-generation tool in February, and a pause that same month after comparable issues.

The tool allowed users to enter prompts to create an image, but almost immediately, users discovered historical inaccuracies and questionable responses, which circulated widely on social media.

For instance, when one user asked Gemini to show a German soldier in 1943, the tool depicted a racially diverse set of soldiers wearing German military uniforms of the era, according to screenshots on social media platform X.

When asked for a “historically accurate depiction of a medieval British king,” the model generated another racially diverse set of images, including one of a woman ruler, screenshots showed. Users reported similar outcomes when they asked for images of the U.S. founding fathers, an 18th-century king of France, a German couple in the 1800s and more. The model showed an image of Asian men in response to a query about Google’s own founders, users reported.

Google said in a statement at the time that it was working to fix Gemini’s image-generation issues, acknowledging that the tool was “missing the mark.” Soon after, the company announced it would immediately “pause the image generation of people” and “re-release an improved version soon.”

In February, Google DeepMind CEO Demis Hassabis said Google planned to relaunch its image-generation AI tool in the next “few weeks,” but it has not yet rolled out again.

The problems with Gemini’s image-generation outputs reignited a debate within the AI industry, with some groups calling Gemini too “woke,” or left-leaning, and others saying that the company didn’t sufficiently invest in the right forms of AI ethics. Google came under fire in 2020 and 2021 for ousting the co-leads of its AI ethics group after they published a research paper critical of certain risks of such AI models and then later reorganizing the group’s structure.

In 2023, Sundar Pichai, CEO of Google’s parent company, Alphabet, was criticized by some employees for the company’s botched and “rushed” rollout of Bard, which followed the viral spread of ChatGPT.

Correction: This article has been updated to reflect the correct name of Google’s AI Overview. Also, an earlier version of this article included a link to a screenshot that Google later confirmed was doctored.

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How AI is speeding the mining of valuable metals needed to power the clean economy

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How AI is speeding the mining of valuable metals needed to power the clean economy

As the clean energy economy expands, finding the minerals and metals that power it becomes increasingly critical. The answer might lie with artificial intelligence.

Electric cars, solar panels and hydrogen fuel cells all have one thing in common: the need for precious metals.

Historically, that’s required going through the arduous process of finding the metals and then getting them out of the ground. But new technologies from a slew of companies might be changing the game.

Kobold Metals, VerAI and a startup called Earth AI are in a race to get the metals to market as soon as possible. Earth AI combines AI-powered mineral discovery software with proprietary drilling technology. Its data goes back 50 years.

“We train our AI to learn from failures and successes of decades of hundreds of geologists that explored in the past to make much better predictions for where to look for metals in the future,” said Roman Teslyuk, CEO of Earth AI.

When the system finds what it thinks are metal deposits, Earth AI can drill down to verify it in just a tennis ball-sized hole. Teslyuk said that using this mining process takes half the cost and a fraction of the amount of time that was previously required. Individual annual mine revenues can range from $50 million to $3 billion, according to Mining Data Online.

“We drill down to 2,000 feet and grab a sample of rock that has never seen light, and the metals in that rock, they can build hundreds of millions of electric cars,” Teslyuk said. “They can turn our grid renewable. This rock can get us off hydrocarbons.”

Earth AI doesn’t explore around existing mines, but finds new areas and then sells that information to mining companies.

“The market for these minerals is massive,” said Jamie Lee, managing partner at Tamarack Global, an investor in Earth AI. “The way that they have approached this really caught our attention because there’s a there is a significant moat in their business model and the way that they’ve trained their large language model.”

Other investors include Y Combinator, Cantos Ventures, Scrum Ventures, Alpaca, Sparkwave Capital and Overmatch. The company has raised a total of $38 million.

Earth AI explores on its own, as well as with partners to find deposits faster. The company recently discovered one of the largest verified deposits of palladium in Australia using AI as part of a joint venture with Legacy Minerals.

CNBC Producer Lisa Rizzolo contributed to this piece.

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Robinhood says SEC dismissed crypto unit investigation in latest sign of easier regulation for industry

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Robinhood says SEC dismissed crypto unit investigation in latest sign of easier regulation for industry

The Robinhood logo is seen displayed on a smartphone screen against a computer screen displaying stock market graphs on Oct. 10, 2024.

Dominika Zarzycka | Nurphoto | Getty Images

The Securities and Exchange Commission is dropping its investigation into Robinhood’s crypto arm, the company revealed Monday.

Robinhood said it received a letter from the SEC’s enforcement division on Friday, detailing in a blog post that the agency has closed its investigation into the crypto business with no intention of moving forward with an enforcement action. The news comes three days after Coinbase similarly announced that the SEC has agreed to end its enforcement case against it.

Shares of Robinhood initially rose on the news but were last lower by about 2% amid a broader pullback in stocks from the day’s highs.

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Shares of Robinhood initially rose on the news but pulled back with the broader market.

In May 2024, Robinhood received a notice warning that it could be charged for potential violation of securities law within its crypto unit after previously being subpoenaed for its cryptocurrency listings, custody and platform operations – despite “years of good faith attempts to work with the SEC for regulatory clarity including our well-known attempt to ‘come in and register,'” Dan Gallagher, the company’s chief legal, compliance and corporate affairs officer, said at the time.

“Robinhood Crypto always has and will always respect federal securities laws and never allowed transactions in securities,” he said in a statement Monday. “We appreciate the formal closing of this investigation, and we are happy to see a return to the rule of law and commitment to fairness at the SEC.”

An SEC spokesperson declined to comment for this story.

The SEC’s dismissal of the Robinhood and Coinbase cases is an early sign of the regulatory sea change for the crypto industry promised by President Donald Trump during his election campaign. Despite the meteoric rise of the price of bitcoin under the previous administration, many crypto businesses saw it as low point due to the SEC’s notorious regulation-by-enforcement approach to crypto – as opposed to the creation of clear rules by which to operate – under the leadership of then Chair Gary Gensler.

Nearly half of Robinhood’s $672 million transaction-based revenue in the fourth quarter came from a 700% rise in revenue tied to crypto trading, as bitcoin rallied toward $100,000 for the first time ever on hopes of more favorable policies under Trump.

The shares have gained 38% so far in 2025.

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Top tech companies turn to hydrogen and nuclear energy for AI data centers

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Top tech companies turn to hydrogen and nuclear energy for AI data centers

Yuval Bachar knows data centers. He’s worked on them for Meta, Microsoft and Cisco, but now, his startup is looking to help Silicon Valley run data centers with lower carbon dioxide emissions.

ECL, Bachar’s startup, builds hydrogen-powered data centers. 

Hydrogen is a novel energy source for data centers that is more eco-friendly, and more importantly for tech companies that need to quickly expand their infrastructure, data centers running on hydrogen can be placed into service in half the time that it takes to construct data centers that connect to the grid, Bachar said.

There’s one of these hydrogen-powered data centers, with a measly 1-megawatt capacity, next to ECL’s headquarters in Mountain View, California. Twice a month, a diesel truck hauls in hydrogen in a tank from Southern California or northern Nevada. The hydrogen mainly derives from natural gas, which is the top energy source for electricity in the U.S.

Bachar and others developing technologies that can fuel data centers with minimal emissions discuss their work in a new CNBC documentary, which you can watch above.

Since OpenAI released ChatGPT in 2022, Amazon, Google, Microsoft and other companies have been racing to open data centers that can handle generative artificial intelligence. These buildings are typically filled with power-hungry Nvidia graphics processing units. GPUs are the standard for training and running large language models that produce impressive chunks of text with a few words of human input. Executives across industries have seen what ChatGPT can do, and now they want to infuse generative AI into their products and internal operations, sometimes with hopes of boosting productivity.

If your data center doesn’t have enough power for GPUs today, then executives will look elsewhere. Bachar knows that. It’s a big part of his pitch.

He likes to say that utilities in some places, such as California and Virginia, can’t help you right now if you want a lot of power for a data center. OpenAI’s Sam Altman has invested hundreds of millions in nuclear startups, but they won’t be ready to deliver energy for years, Bachar said.

After establishing ECL in 2021, Bachar has signed up two paying customers, with several other organizations that have placed orders for future delivery.

“It’s the Microsofts, Facebooks, Amazons and Googles of the world … which require all of this technology to be placed somewhere, and right now, somewhere is nowhere,” said Bachar, explaining that traditional data centers in the U.S. can’t be easily repurposed to work with AI.

ECL has plans to operate its sites efficiently, but as of now, it’s tiny, with 10 employees and 18 contractors. That’s much smaller than Altman’s nuclear fusion investment, Helion, and the fission startup he backed, Oklo. Together the two employ nearly 600 people, representatives said.

Microsoft has committed to working with Helion, and the software company also signed a power purchase agreement in September to restart a nuclear reactor at Pennsylvania’s Three Mile Island that shut down in 2019. 

Nuclear installations inherently prompt questions about safety and the handling of waste, but their carbon-free status makes them attractive. Amazon, Google and Oracle have all explored small modular reactors with lower capacity than the ones at Three Mile Island.

Last Energy Founder and CEO Bret Kugelmass shows CNBC a full-scale prototype of the start-up’s small modular reactor in Washington, DC, on January 8, 2025.

Magdalena Petrova

The big tech companies are carefully watching their emissions in the AI age.

By 2030, Google wants to have net-zero emissions while Microsoft’s goal is to be carbon negative by that year. Amazon has pledged to reach net-zero carbon by 2040.

“We’re working with major tech companies, as well as various industrial players, to help them integrate our plug and play solution for on-site power generation into data centers,” said Bret Kugelmass, founder and CEO of Last Energy, a Washington startup working on small modular reactors.

Bachar is fascinated with nuclear energy, but he said getting more of those facilities online will take time. 

“We have a problem that we have to solve right now,” he said.

In addition to his nuclear investments, OpenAI’s Altman has bet on solar startup Exowatt. It has partners developing data centers that are consuming more than half of the energy available in their states in some locations, co-founder and CEO Hannan Happi said.

Geothermal energy has also garnered fresh interest in the modern AI era, with Google collaborating with startup Fervo Energy in Nevada. Tim Latimer, the startup’s CEO, said Fervo has found a way to generate gigawatts of electricity in a single place by drilling horizontal holes underground, rather than the traditional vertical way.

Gigawatts are a serious quantity, but drilling holes for geothermal plants can be expensive, said Adrian Cockcroft, a former Amazon sustainability executive.

ECL intends to build a large-scale, 1-gigawatt data center in Texas over the next four years, with the help of hydrogen pipelines. It will probably take that long to move to zero-carbon green hydrogen using electrolyzers that convert water into hydrogen and oxygen, Bachar said.

But generating green hydrogen through electrolysis isn’t cheap, said Kittu Kolluri, managing director of Neotribe Ventures.

The price of green hydrogen is to be determined, especially now that Donald Trump is U.S. president again, Bachar said.

Still, every gigawatt matters. 

In 2028, U.S. data center demand could come in between 74 gigawatts and 132 gigawatts, according to a December report from the Lawrence Berkeley National Laboratory. Data centers might account for 6.7% to 12% of total U.S. energy consumption in 2028, up from 4.4% in 2023, the report said.

“The concern we have is can we grow fast enough to address the unprecedented demand for AI data centers,” Bachar said.

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