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Sundar Pichai, CEO of Google and Alphabet, speaks on artificial intelligence during a Bruegel think tank conference in Brussels, Belgium, on Jan. 20, 2020.

Yves Herman | Reuters

Google on Wednesday announced MedLM, a suite of new health-care-specific artificial intelligence models designed to help clinicians and researchers carry out complex studies, summarize doctor-patient interactions and more.

The move marks Google’s latest attempt to monetize health-care industry AI tools, as competition for market share remains fierce between competitors like Amazon and Microsoft. CNBC spoke with companies that have been testing Google’s technology, like HCA Healthcare, and experts say the potential for impact is real, though they are taking steps to implement it carefully.

The MedLM suite includes a large and a medium-sized AI model, both built on Med-PaLM 2, a large language model trained on medical data that Google first announced in March. It is generally available to eligible Google Cloud customers in the U.S. starting Wednesday, and Google said while the cost of the AI suite varies depending on how companies use the different models, the medium-sized model is less expensive to run. 

Google said it also plans to introduce health-care-specific versions of Gemini, the company’s newest and “most capable” AI model, to MedLM in the future.

Aashima Gupta, Google Cloud’s global director of health-care strategy and solutions, said the company found that different medically tuned AI models can carry out certain tasks better than others. That’s why Google decided to introduce a suite of models instead of trying to build a “one-size-fits-all” solution. 

For instance, Google said its larger MedLM model is better for carrying out complicated tasks that require deep knowledge and lots of compute power, such as conducting a study using data from a health-care organization’s entire patient population. But if companies need a more agile model that can be optimized for specific or real-time functions, such as summarizing an interaction between a doctor and patient, the medium-sized model should work better, according to Gupta.

Real-world use cases

A Google Cloud logo at the Hannover Messe industrial technology fair in Hanover, Germany, on Thursday, April 20, 2023.

Krisztian Bocsi | Bloomberg | Getty Images

When Google announced Med-PaLM 2 in March, the company initially said it could be used to answer questions like “What are the first warning signs of pneumonia?” and “Can incontinence be cured?” But as the company has tested the technology with customers, the use cases have changed, according to Greg Corrado, head of Google’s health AI. 

Corrado said clinicians don’t often need help with “accessible” questions about the nature of a disease, so Google hasn’t seen much demand for those capabilities from customers. Instead, health organizations often want AI to help solve more back-office or logistical problems, like managing paperwork.  

“They want something that’s helping them with the real pain points and slowdowns that are in their workflow, that only they know,” Corrado told CNBC. 

For instance, HCA Healthcare, one of the largest health systems in the U.S., has been testing Google’s AI technology since the spring. The company announced an official collaboration with Google Cloud in August that aims to use its generative AI to “improve workflows on time-consuming tasks.” 

Dr. Michael Schlosser, senior vice president of care transformation and innovation at HCA, said the company has been using MedLM to help emergency medicine physicians automatically document their interactions with patients. For instance, HCA uses an ambient speech documentation system from a company called Augmedix to transcribe doctor-patient meetings. Google’s MedLM suite can then take those transcripts and break them up into the components of an ER provider note.

Schlosser said HCA has been using MedLM within emergency rooms at four hospitals, and the company wants to expand use over the next year. By January, Schlosser added, he expects Google’s technology will be able to successfully generate more than half of a note without help from providers. For doctors who can spend up to four hours a day on clerical paperwork, Schlosser said saving that time and effort makes a meaningful difference. 

“That’s been a huge leap forward for us,” Schlosser told CNBC. “We now think we’re going to be at a point where the AI, by itself, can create 60-plus percent of the note correctly on its own before we have the human doing the review and the editing.” 

Schlosser said HCA is also working to use MedLM to develop a handoff tool for nurses. The tool can read through the electronic health record and identify relevant information for nurses to pass along to the next shift. 

Handoffs are “laborious” and a real pain point for nurses, so it would be “powerful” to automate the process, Schlosser said. Nurses across HCA’s hospitals carry out around 400,000 handoffs a week, and two HCA hospitals have been testing the nurse handoff tool. Schlosser said nurses conduct a side-by-side comparison of a traditional handoff and an AI-generated handoff and provide feedback.

With both use cases, though, HCA has found that MedLM is not foolproof.

Schlosser said the fact that AI models can spit out incorrect information is a big challenge, and HCA has been working with Google to come up with best practices to minimize those fabrications. He added that token limits, which restrict the amount of data that can be fed to the model, and managing the AI over time have been additional challenges for HCA. 

“What I would say right now, is that the hype around the current use of these AI models in health care is outstripping the reality,” Schlosser said. “Everyone’s contending with this problem, and no one has really let these models loose in a scaled way in the health-care systems because of that.”

Even so, Schlosser said providers’ initial response to MedLM has been positive, and they recognize that they are not working with the finished product yet. He said HCA is working hard to implement the technology in a responsible way to avoid putting patients at risk.

“We’re being very cautious with how we approach these AI models,” he said. “We’re not using those use cases where the model outputs can somehow affect someone’s diagnosis and treatment.”

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Google also plans to introduce health-care-specific versions of Gemini to MedLM in the future. Its shares popped 5% after Gemini’s launch earlier this month, but Google faced scrutiny over its demonstration video, which was not conducted in real time, the company confirmed to Bloomberg

In a statement, Google told CNBC: “The video is an illustrative depiction of the possibilities of interacting with Gemini, based on real multimodal prompts and outputs from testing. We look forward to seeing what people create when access to Gemini Pro opens on December 13.”

Corrado and Gupta of Google said Gemini is still in early stages, and it needs to be tested and evaluated with customers in controlled health-care settings before the model rolls out through MedLM more broadly. 

“We’ve been testing Med-PaLM 2 with our customers for months, and now we’re comfortable taking that as part of MedLM,” Gupta said. “Gemini will follow the same thing.” 

Schlosser said HCA is “very excited” about Gemini, and the company is already working out plans to test the technology, “We think that may give us an additional level of performance when we get that,” he said.

Another company that has been using MedLM is BenchSci, which aims to use AI to solve problems in drug discovery. Google is an investor in BenchSci, and the company has been testing its MedLM technology for a few months.  

Liran Belenzon, BenchSci’s co-founder and CEO, said the company has merged MedLM’s AI with BenchSci’s own technology to help scientists identify biomarkers, which are key to understanding how a disease progresses and how it can be cured. 

Belenzon said the company spent a lot of time testing and validating the model, including providing Google with feedback about necessary improvements. Now, Belenzon said BenchSci is in the process of bringing the technology to market more broadly.  

“[MedLM] doesn’t work out of the box, but it helps accelerate your specific efforts,” he told CNBC in an interview. 

Corrado said research around MedLM is ongoing, and he thinks Google Cloud’s health-care customers will be able to tune models for multiple different use cases within an organization. He added that Google will continue to develop domain-specific models that are “smaller, cheaper, faster, better.”  

Like BenchSci, Deloitte tested MedLM “over and over” before deploying the technology to health-care clients, said Dr. Kulleni Gebreyes, Deloitte’s U.S. life sciences and health-care consulting leader.

Deloitte is using Google’s technology to help health systems and health plans answer members’ questions about accessing care. If a patient needs a colonoscopy, for instance, they can use MedLM to look for providers based on gender, location or benefit coverage, as well as other qualifiers. 

Gebreyes said clients have found that MedLM is accurate and efficient, but it’s not always great at deciphering a user’s intent. It can be a challenge if patients don’t know the right word or spelling for colonoscopy, or use other colloquial terms, she said. 

“Ultimately, this does not substitute a diagnosis from a trained professional,” Gebreyes told CNBC. “It brings expertise closer and makes it more accessible.”

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Binance CEO dismisses claims the firm boosted a Trump crypto venture ahead of CZ pardon

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Binance CEO dismisses claims the firm boosted a Trump crypto venture ahead of CZ pardon

Richard Teng, chief executive officer of Binance, during the DC Blockchain Summit in Washington, DC, U.S., on Wednesday, March 26, 2025.

Bloomberg | Bloomberg | Getty Images

Binance CEO Richard Teng has dismissed claims that the cryptocurrency exchange helped boost a Trump-backed stablecoin before former CEO Changpeng Zhao received a presidential pardon.

The claims in question relate to a $2 billion investment Binance received from Abu Dhabi’s state-owned investment firm MGX. The deal was settled using USD1, a stablecoin created by the Trump family’s crypto venture, World Liberty Financial. 

MGX’s investment and Binance’s subsequent listing of USD1 on its exchange helped bolster the stablecoin’s usage and credibility, with some lawmakers and reports suggesting this may have influenced the pardon of Zhao, commonly known as CZ.

However, in a CNBC interview on Monday, Teng rejected the notion that Binance — the world’s largest cryptocurrency firm — had given USD1 any preferential treatment.

“First of all, the usage of USD1 [for the] transaction between MGX as a strategic investor into Binance, that was decided by MGX … We didn’t partake in that decision,” Teng said. 

He noted that USD1 had already been listed on other exchanges before Binance, adding that, as the “largest crypto ecosystem in the world,” the company regularly engages with promising new projects.

“Sometimes it works out. Sometimes it doesn’t. In the case of USD1, I’m glad that both parties worked it out.” 

Accusations of corruption 

Teng’s denials come after the Wall Street Journal reported last week that Binance not only facilitated the settlement of MGX’s investment using USD1, but also assisted in building the technology behind the stablecoin, citing anonymous sources familiar with the matter.

The Journal also previously noted that World Liberty Financial benefited greatly from the listing of its USD1 token on Binance and a partnership with Pancake Swap — an online marketplace for cryptocurrencies said to be associated with Binance. 

Meanwhile, scrutiny of CZ’s pardon and Binance’s ties to the Trump-linked World Liberty Financial has continued to mount from opposition leaders on Capitol Hill.

Among the most prominent voices has been Sen. Elizabeth Warren, ranking member of the Senate Banking, Housing, and Urban Affairs Committee, who has accused Binance and the Trump administration of corruption.

In a statement last month, the vocal critic of the crypto industry said: “First, Changpeng Zhao pleaded guilty to a criminal money laundering charge. Then he boosted one of Donald Trump’s crypto ventures and lobbied for a pardon,” with the President later doing “his part.”

Binance did not respond immediately to a request for comment.

Binance CEO Richard Teng on crypto regulation and Trump's pardon for founder CZ

Critics have long questioned World Liberty Financial’s open connections to the Trump administration as it seeks new partnerships and investors overseas.

According to World Liberty Financial’s website, a Trump-affiliated firm called DT Marks DEFI LLC, along with members of the Trump family, receives a major share of the platform’s revenue and holds digital tokens backing the company, known as WLFI. The firm has reportedly netted the Trump family hundreds of millions to billions in profits.

However, it also states that Trump, his family or any members of the Trump Organization or DT Marks DEFI LLC are not an “officer, director, founder, or employee of, or manager, owner or operator of World Liberty Financial or its affiliates.”

MGX’s purchase of $2 billion in USD1 tokens has also raised eyebrows after a New York Times report in September noted that it occurred two weeks before the White House signed a major agreement with the U.A.E. on access to hundreds of thousands of American microchips.

In a conversation with CNBC last month, Donald Trump Jr., the U.S. president’s eldest son and a co-founder of World Liberty Financial, dismissed the reports and broader concerns about potential conflicts of interest.

He was joined by the firm’s CEO, Zach Witkoff, son of U.S. Special Envoy to the Middle East Steve Witkoff, who said their fathers were not focused on nor directly involved in the business. 

Trump’s crypto embrace

Zhao was forced to step down from his role at Binance in 2023 after pleading guilty to enabling money laundering through the cryptocurrency exchange.

White House press secretary Karoline Leavitt said in a statement on Oct. 23 that Zhao had been prosecuted under the Biden administration “despite no allegations of fraud or identifiable victims.”

Trump later said he pardoned Zhao “at the request of a lot of very good people” and that he knew nothing about him.

Since returning to office, Trump has embraced the crypto sector, proposing new crypto legislation while rolling back enforcement actions that targeted crypto exchanges such as Coinbase and Ripple during the prior administration.

Speaking Monday, Teng said that Binance and the crypto industry “were very thankful” to the president for CZ’s pardon and for signaling that the U.S. will be the “global crypto capital of the world.”

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HSBC, General Atlantic CEOs flag AI capex-revenue mismatch, ‘irrational exuberance’

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HSBC, General Atlantic CEOs flag AI capex-revenue mismatch, 'irrational exuberance'

HONG KONG, CHINA – 2025/03/01: In this photo illustration, Artificial intelligence (AI) apps of perplexity, DeepSeek and ChatGPT are seen on a smartphone screen.

Sopa Images | Lightrocket | Getty Images

As companies pour billions into artificial intelligence, HSBC CEO Georges Elhedery on Tuesday warned of a mismatch between investments and revenues.

Speaking at the Global Financial Leaders’ Investment Summit in Hong Kong, Elhedery said the scale of investment poses a conundrum for companies: while the computing power for AI is essential, current revenue profiles may not justify such massive spending.

Morgan Stanley in July estimated that over the next five years, global data center capacity would grow six times, with data centers and their hardware alone costing $3 trillion by the end of 2028.

McKinsey said in a report in April that by 2030, data centers equipped to handle AI processing loads would require $5.2 trillion in capital expenditure to keep up with compute demand, while the capex for those powering traditional IT applications is forecast at $1.5 trillion.

Elhedery said that consumers were not ready to pay for it, and businesses will be cautious as productivity benefits will not materialize in a year or two.

“These are like five year trends, and therefore the ramp up means that we will start seeing real revenue benefits and real readiness to pay for it, probably later than than the expectations of investors,” he said.

William Ford, chairman and CEO of General Atlantic, speaking at the same panel, agreed: “In the long term, you’re going to create a whole new set of industries and applications, and there will be a productivity payoff, but that’s a 10-, 20-year play.”

Big Tech firms AlphabetMetaMicrosoft and Amazon have all lifted their guidance for capital expenditures and now collectively expect that number to reach more than $380 billion this year.

OpenAI, which set off the AI frenzy with the launch of ChatGPT in November 2022, has announced roughly $1 trillion worth of infrastructure deals with partners including NvidiaOracle and Broadcom.

Ford said that the huge expenditure that is going into the sector shows that people recognize the long-term impact of AI. This sector, however, will be capital-intensive initially, he said adding that “you need to, sort of, pay up front for the opportunity that’s going to come down the road.”

Ford warned there could be “misallocation of capital, destruction, overvaluation… [and] irrational exuberance” in the initial stages, and also added that it can be difficult to pick winners and losers at the moment.

“You’re really betting on this being a broad based technology, more like railroads or electricity, that had profound impacts over over time, and reshaped the economy, but were very hard to predict exactly how in the first few years.”

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AI is not in a bubble, says VC founder. Why he says it’s different to the dotcom boom

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AI is not in a bubble, says VC founder. Why he says it's different to the dotcom boom

VC founder: AI isn't a bubble — but its founders need to start thinking globally

Whether or not markets are getting ahead of themselves over artificial intelligence is a hot topic for investors right now.

Last week, billionaire investor Ray Dalio said his personal “bubble indicator” was relatively high, while Federal Reserve Chair Jerome Powell described the AI boom as “different” from the dotcom bubble.

For Magnus Grimeland, founder of Singapore-based venture capital firm Antler, it’s clear the market is not overheating. “I definitely don’t think we’re in a bubble,” he told CNBC’s “Beyond the Valley” podcast, listing several reasons.

The speed at which AI is being adopted by businesses is notable compared to other tech shifts, Grimeland said, such as the move from physical servers to cloud computing, which he said took a decade. Added to this, AI is “top of the agenda” for leaders today, he said, whether they’re running a healthcare provider in India or a U.S. Fortune 500 company.

“There’s a willingness to invest into using that technology … and that’s happened immediately,” Grimeland said.

He described the rapid shift to AI as being substantially different from the dotcom bubble of the late 1990s and early 2000s, when unprofitable internet startups eventually collapsed and the tech-heavy Nasdaq lost almost 80% of its value between March 2000 and October 2002.

“What makes this a little bit different from a bubble and makes it very different from dotcom is that there’s really real revenues behind a lot of this growth,” Grimeland said.

OpenAI, the company behind ChatGPT, said it reached $10 billion in annual recurring revenue in June. Annual recurring revenue (ARR) is the amount of money a company expects to make from customers over 12 months.

Antler is an investor in Lovable, a company that enables people to build apps and websites using AI. In July, Lovable said it had passed $100 million ARR in eight months.

Another reason that the rapid adoption of AI is different from the dotcom boom is the speed at which consumers are taking to the technology, Grimeland said. “Think about how quickly our behavior online has changed, right? … 100% of my searches a year ago [were on] Google. Now it’s probably 20%,” he said.

Earlier this month, OpenAI launched its ChatGPT Atlas browser for Mac OS, with shares of Google’s parent company Alphabet falling on the news.

Smaller AI players

While Grimeland said there was a “tremendous” amount of money going to AI-related companies at the “wrong” valuation, these trends happen at the beginning of an investment cycle, he said. “But in the end … The opportunity in this space is so much bigger than the investments being put there,” Grimeland added.

Asked whether there are opportunities for AI startups when large U.S. and Chinese companies currently dominate the sector, Grimeland said the big firms were “being challenged in the way they haven’t for a very long time.” He gave the example of DeepSeek, the Chinese startup that has produced AI models comparable to those from OpenAI.

Tencent is building great AI, Baidu is building great AI, but that’s not where DeepSeek came from, right?” Grimeland said. “The AI winners of this current platform shift [are] not necessarily those big incumbents.”

As such, there are significant opportunities for smaller AI companies to become big businesses, Grimeland said, flagging firms that have “positive signals,” such as a good founding team, growth in the lifetime value of a customer and a reduction in the cost of delivering a product.

– CNBC’s Dylan Butts, Ashley Capoot, Alex Harring and Jaures Yip contributed to this report.

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