Caroline Ellison, former chief executive officer of Alameda Research LLC, arrives to court in New York, US, on Thursday, Oct. 12, 2023. Ellison, ex-girlfriend of FTX co-founder Sam Bankman-Fried, outlined for a New York jury Wednesday how she worked with Sam Bankman-Fried to deceive lenders and customers to build his multi-billion dollar cryptocurrency empire, and their failed attempts to prevent a spectacular collapse. Photographer: Stephanie Keith/Bloomberg via Getty Images
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Caroline Ellison, the government’s star witness in its fraud case against FTX founder Sam Bankman-Fried, took the stand for cross-examination on Thursday morning as the trial continued in a courthouse in downtown Manhattan.
Ellison was CEO of Bankman-Fried’s hedge fund, Alameda Research, and also dated him on and off while working with him. She pleaded guilty in December to two counts of wire fraud, two counts of conspiracy to commit wire fraud, conspiracy to commit commodities fraud, conspiracy to commit securities fraud and conspiracy to commit money laundering. Part of the 28-year-old’s plea deal with the government has involved cooperating with the prosecution’s case against Bankman-Fried.
On Thursday morning, Ellison faced aggressive questioning from Bankman-Fried’s lawyer, Mark Cohen, who spoke over her several times as she tried to testify. But Judge Lewis Kaplan also appeared annoyed at the fact that Cohen requested two sidebar conferences early on to pursue lines of questioning.
Ellison mostly avoided eye contact with the defendant, as she has during the past two daysof testimony, staring down at her hands in between questions and frequently flipping her hair over her left shoulder.
Part of the cross-examination revolved around Sam Trabucco, who was Alameda’s co-CEO with Ellison from October 2021 until August 2022, months before both companies collapsed into bankruptcy as investors raced to withdraw funds from FTX amid allegations that it had used customer funds to help paper over losses at Alameda as the crypto market tanked.
Ellison testified that she and Trabucco began handling a lot of Alameda’s day-to-day business as early as 2020, well before officially taking over, and that there were periods of time where Bankman-Fried would not talk to them much. By 2021, she testified, Bankman-Fried had largely stopped coming into the Alameda office and had left more of the job to Ellison. She said that Trabucco was good under pressure and at handling extreme trading situations.
She also testified that the firm had attempted to hire several people to oversee Alameda’s accounting, but they all left and Ellison took on the role of preparing Alameda’s balance sheets from Ryan Salame, who had been the CEO of a subsidiary called FTX Digital Markets. In previous testimony, Ellison admitted that she had used FTX customer money to pay Alameda’s loans, and alleged she did so at Bankman-Fried’s suggestion.
Ellison also testified that Bankman-Fried had discussed adding a new co-CEO when Trabucco left, but she resisted.
When Cohen asked if she considered herself an ambitious person, Ellison said she didn’t think of herself as particularly ambitious, but became more so with Bankman-Fried’s encouragement as she worked for him.
Ellison’s cross-examination is likely to continue throughout Thursday morning.
Health-care software vendor Athenahealth on Tuesday said it will offer Abridge’s artificial intelligence scribing tool to its network of more than 160,000 clinicians.
Athenahealth has developed an electronic health record, revenue cycle management tools and patient engagement tools for ambulatory care providers, which include outpatient facilities like independent practices. The company introduced a solution called Ambient Notes in October that allows doctors to choose between various AI-powered documentation tools, and Abridge is the latest addition.
Abridge uses AI to draft clinical notes in real time as doctors consensually record their visits with patients. The startup is part of a red-hot market that has exploded as health-care executives search for solutions to help reduce staff burnout and daunting administrative workloads.
“The market is going to evolve rather rapidly, there are going to be winners and losers over time,” Athenahealth CEO Bob Segert told CNBC. “Different physicians will prefer different ways that notes are taken and that the information is delivered, and we want to be able to provide that flexibility.”
Athenahealth and Abridge declined to share the financial details of the partnership.
Clinicians spend nearly nine hours a week on documentation, according to an October study from Google Cloud. And more than 90% of physicians report feeling burned out on a “regular basis,” according to a survey commissioned by Athenahealth last February.
Companies including Abridge, Microsoft’s Nuance Communications, Suki and others say their AI scribing tools can help. Suki and iScribeHealth already offer their tools through Athenahealth’s Ambient Notes solution.
“It’ll be incumbent upon us to make sure that we’re able to demonstrate differentiation,” Abridge CEO Dr. Shiv Rao told CNBC. “So far, we’ve had good luck these last few years doing that.”
Abridge has deployed its technology across more than 100 health systems in the U.S., including organizations like the Mayo Clinic, Duke Health and Johns Hopkins Medicine.
The company announced a $250 million funding round earlier this month. It also unveiled a new Contextual Reasoning Engine that can pull information that’s relevant to a specific clinician and their clinic’s best practices. Abridge’s Rao said that technology will be available to Athenahealth clinicians.
Athenahealth’s Ambient Notes solution is currently available in a limited capacity, but the company said it plans to widen availability for clinicians through 2025.
“The more they try it, the more they like it, and I think we’re going to see a pretty steep adoption curve as this continues to move forward,” Segert said.
Nvidia is scheduled to report fourth-quarter financial results on Wednesday after the bell.
It’s expected to put the finishing touches on one of the most remarkable years from a large company ever. Analysts polled by FactSet expect $38 billion in sales for the quarter ended in January, which would be a 72% increase on an annual basis.
The January quarter will cap off the second fiscal year where Nvidia’s sales more than doubled. It’s a breathtaking streak driven by the fact that Nvidia’s data center graphics processing units, or GPUs, are essential hardware for building and deploying artificial intelligence services like OpenAI’s ChatGPT. In the past two years, Nvidia stock has risen 478%, making it the most valuable U.S. company at times with a market cap over $3 trillion.
But Nvidia’s stock has slowed in recent months as investors question where the chip company can go from here.
It’s trading at the same price as it did last October, and investors are wary of any signs that Nvidia’s most important customers might be tightening their belts after years of big capital expenditures. This is particularly concerning in the wake of recent breakthroughs in AI out of China.
Much of Nvidia’s sales go to a handful of companies building massive server farms, usually to rent out to other companies. These cloud companies are typically called “hyperscalers.” Last February, Nvidia said a single customer accounted for 19% of its total revenue in fiscal 2024.
Morgan Stanley analysts estimated this month that Microsoft will account for nearly 35% of spending in 2025 on Blackwell, Nvidia’s latest AI chip. Google is at 32.2%, Oracle at 7.4% and Amazon at 6.2%.
This is why any sign that Microsoft or its rivals might pull back spending plans can shake Nvidia stock.
Last week, TD Cowen analysts said that they’d learned that Microsoft had canceled leases with private data center operators, slowed its process of negotiating to enter into new leases and adjusted plans to spend on international data centers in favor of U.S. facilities.
The report raised fears about the sustainability of AI infrastructure growth. That could mean less demand for Nvidia’s chips. TD Cowen’s Michael Elias said his team’s finding points to “a potential oversupply position” for Microsoft. Shares of Nvidia fell 4% on Friday.
Microsoft pushed back Monday, saying it still planned to spend $80 billion on infrastructure in 2025.
“While we may strategically pace or adjust our infrastructure in some areas, we will continue to grow strongly in all regions. This allows us to invest and allocate resources to growth areas for our future,” a spokesperson told CNBC.
Over the last month, most of Nvidia’s key customers touted large investments. Alphabet is targeting $75 billion in capital expenditures this year, Meta will spend as much as $65 billion and Amazon is aiming to spend $100 billion.
Analysts say about half of AI infrastructure capital expenditures ends up with Nvidia. Many hyperscalers dabble in AMD’s GPUs and are developing their own AI chips to lessen their dependence on Nvidia, but the company holds the majority of the market for cutting-edge AI chips.
So far, these chips have been used primarily to train cutting-edge AI models, a process that can cost hundreds of millions dollars. After the AI is developed by companies like OpenAI, Google and Anthropic, warehouses full of Nvidia GPUs are required to serve those models to customers. That’s why Nvidia projects its revenue to continue growing.
Another challenge for Nvidia is last month’s emergence of Chinese startup DeepSeek, which released an efficient and “distilled” AI model. It had high enough performance that suggested billions of dollars of Nvidia GPUs aren’t needed to train and use cutting-edge AI. That temporarily sunk Nvidia’s stock, causing the company to lose almost $600 billion in market cap.
Nvidia CEO Jensen Huang will have an opportunity on Wednesday to explain why AI will continue to need even more GPU capacity even after last year’s massive build-out.
Recently, Huang has spoken about the “scaling law,” an observation from OpenAI in 2020 that AI models get better the more data and compute are used when creating them.
Huang said that DeepSeek’s R1 model points to a new wrinkle in the scaling law that Nvidia calls “Test Time Scaling.” Huang has contended that the next major path to AI improvement is by applying more GPUs to the process of deploying AI, or inference. That allows chatbots to “reason,” or generate a lot of data in the process of thinking through a problem.
AI models are trained only a few times to create and fine-tune them. But AI models can be called millions of times per month, so using more compute at inference will require more Nvidia chips deployed to customers.
“The market responded to R1 as in, ‘oh my gosh, AI is finished,’ that AI doesn’t need to do any more computing anymore,” Huang said in a pretaped interview last week. “It’s exactly the opposite.”
A worsening macroeconomic climate and the collapse of industry giants such as FTX and Terra have weighed on bitcoin’s price this year.
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Bitcoin fell through the $90,000 level overnight, weakened by sell pressure in equities as the crypto market awaits its next catalyst.
The price of bitcoin fell 6% to $88,519, according to Coin Metrics. Earlier, it fell as low as $87,736.
The decline puts the blue chip coin almost 20% off its all-time high reached on President Donald Trump’s inauguration day.
“Equities have faced a few difficult sessions over the last week, with top-performing stocks down many times the index, as markets grapple with increased uncertainty under the new administration,” said Steven Lubka, head of private clients and family offices at Swan Bitcoin. “This pressure has spilled over into bitcoin and crypto markets.”
The S&P 500 on Monday posted a three-day losing streak as it failed to recover from last week’s sell-off, driven by concern over a slowing economy and sticky inflation.
“Ultimately, the lack of visible short-term catalysts and pressure from equities creates an environment for profit-taking and pressure from shorts,” Lubka added.
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Bitcoin falls below the key $90,000 level Monday
Bitcoin kicked off the year in rally mode, fueled by optimism about the positive changes the new Trump administration was expected to make for the crypto industry. However, since the President issued his widely anticipated executive order on crypto at the end of January – the contents of which were well received by the industry despite its tamer than hoped for language on a strategic bitcoin reserve – the market has had little to look forward to.
While optimism about the long-term positive impact Trump’s policies could have for crypto remains high, its movements have been and may continue to be dictated by macroeconomic trends.
“From November through January, the market was very enthusiastic about pricing in a crypto-friendly U.S. administration,” said Joel Kruger, market strategist at LMAX Group. “Now it’s a question of waiting for that next catalyst. We know that all of this is in place, and the market is in a bit of a sell-the-fact consolidation sell as it kind of waits.”
The $90,000 level marks the bottom of the narrow range bitcoin has been trading in since the end of November. Analysts have warned that if bitcoin were to meaningfully break below the level, it could see a deeper pullback toward $80,000.
“There is room for bitcoin still to go back down towards the $70,000 to $75,000 area without doing anything to compromise the outlook,” Kruger said, “and we suspect that there will be plenty of demand as we head down towards those levels.”
Lubka said he believes bitcoin will finish digesting this move and resume its long-term move higher by mid-March.
Other cryptocurrencies fared worse on Monday. Ether and Solana’s sol token each tumbled 9%. The broader market of cryptocurrencies, as measured by the CoinDesk 20 index, lost more than 8%.
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