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.
OpenAI CEO Sam Altman said artificial general intelligence, or “AGI,” is losing its relevance as a term as rapid advances in the space make it harder to define the concept.
AGI refers to the concept of a form of artificial intelligence that can perform any intellectual task that a human can. For years, OpenAI has been working to research and develop AGI that is safe and benefits all humanity.
“I think it’s not a super useful term,” Altman told CNBC’s “Squawk Box” last week, when asked whether the company’s latest GPT-5 model moves the world any closer to achieving AGI. The AI entrepreneur has previously said he thinks AGI could be developed in the “reasonably close-ish future.”
The problem with AGI, Altman said, is that there are multiple definitions being used by different companies and individuals. One definition is an AI that can do “a significant amount of the work in the world,” according to Altman — however, that has its issues because the nature of work is constantly changing.
“I think the point of all of this is it doesn’t really matter and it’s just this continuing exponential of model capability that we’ll rely on for more and more things,” Altman said.
Altman isn’t alone in raising skepticism about “AGI” and how people use the term.
Difficult to define
Nick Patience, vice president and AI practice lead at The Futurum Group, told CNBC that though AGI is a “fantastic North Star for inspiration,” on the whole it’s not a helpful term.
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“It drives funding and captures the public imagination, but its vague, sci-fi definition often creates a fog of hype that obscures the real, tangible progress we’re making in more specialised AI,” he said via email.
OpenAI and other startups have raised billions of dollars and attained dizzyingly high valuations with the promise that they will eventually reach a form of AI powerful enough to be considered “AGI.” OpenAI was last valued by investors at $300 billion and it is said to be preparing a secondary share sale at a valuation of $500 billion.
Last week, the company released GPT-5, its latest large language model for all ChatGPT users. OpenAI said the new system is smarter, faster and “a lot more useful” — especially when it comes to writing, coding and providing assistance on health care queries.
But the launch led to criticisms from some online that the long-awaited model was an underwhelming upgrade, making only minor improvements on its predecessor.
“By all accounts it’s incremental, not revolutionary,” Wendy Hall, professor of computer science at the University of Southampton, told CNBC.
AI firms “should be forced to declare how they measure up to globally agreed metrics” when they launch new products, Hall added. “It’s the Wild West for snake oil salesmen at the moment.”
A distraction?
For his part, Altman has admitted OpenAI’s new model misses the mark of his own personal definition of AGI, as the system is not yet capable of continuously learning on its own.
While OpenAI still maintains artificial general intelligence as its ultimate goal, Altman has said it’s better to talk about levels of progress toward this state of general intelligence rather than asking if something is AGI or not.
“We try now to use these different levels … rather than the binary of, ‘is it AGI or is it not?’ I think that became too coarse as we get closer,” the OpenAI CEO said during a talk at the FinRegLab AI Symposium in November 2024.
Altman still expects AI to achieve some key breakthroughs in specific fields — such as new math theorems and scientific discoveries — in the next two years or so.
“There’s so much exciting real-world stuff happening, I feel AGI is a bit of a distraction, promoted by those that need to keep raising astonishing amounts of funding,” Futurum’s Patience told CNBC.
“It’s more useful to talk about specific capabilities than this nebulous concept of ‘general’ intelligence.”
Masayoshi Son, chairman and chief executive officer of SoftBank Group Corp., speaks at the SoftBank World event in Tokyo, Japan, on Wednesday, July 16, 2025.
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Masayoshi Son is making his biggest bet yet: that his brainchild SoftBank will be the center of a revolution driven by artificial intelligence.
Son says artificial superintelligence (ASI) — AI that is 10,000 times smarter than humans — will be here in 10 years. It’s a bold call — but perhaps not surprising. He’s made a career out of big plays; notably, one was a $20 million investment into Chinese e-commerce company Alibaba in 2000 that has made billions for SoftBank.
Now, the billionaire is hoping to replicate that success with a series of investments and acquisitions in AI firms that will put SoftBank at the center of a fundamental technological shift.
While Son has been outspoken about his vision over the last year, his thinking precedes much of his recent bullishness, according to two former executives at SoftBank.
“I vividly remember the first time he invited me to his home for dinner and sitting on his porch over a glass of wine, he started talking to me about singularity – the point at which machine intelligence overtakes human intelligence,” Alok Sama, a former finance chief at SoftBank until 2016 and and president until 2019, told CNBC.
SoftBank’s big AI plays
For Son, AI seems personal.
“SoftBank was founded for what purpose? For what purpose was Masa Son born? It may sound strange, but I think I was born to realize ASI,” Son said last year.
That may go some way to explain what has been an aggressive drive over the past few years — but especially the last two — to put SoftBank at the center of the AI story.
ChatGPT maker OpenAI is another marquee investment for SoftBank, with the Japanese giant saying recently that planned investments in the company will reach about 4.8 trillion Japanese yen ($32.7 billion).
SoftBank has also invested in a number of other companies related to AI across its portfolio.
“SoftBank’s AI strategy is comprehensive, spanning the entire AI stack from foundational semiconductors, software, infrastructure, and robotics to cutting-edge cloud services and end applications across critical verticals such as enterprise, education, health, and autonomous systems,” Neil Shah, co-founder at Counterpoint Research, told CNBC.
“Mr. Son’s vision is to cohesively connect and deeply integrate these components, thereby establishing a powerful AI ecosystem designed to maximize long-term value for our shareholders.”
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SoftBank’s stock performance since 2017, the year that its first Vision Fund was founded.
There is a common theme behind SoftBank’s investments in AI companies that comes directly from Son — namely, that these firms should be using advanced intelligence to be more competitive, successful, to make their product better and their customers happy, a person familiar with the company told CNBC. They could only comment anonymously because of the sensitivity of the matter.
It started with and brain computers and robots
As SoftBank launched “SoftBank’s Next 30-Year Vision” in 2010, Son spoke about “brain computers” during a presentation. He described these computers as systems that could learn and program themselves eventually.
And then came robots. Major tech figures like Nvidia CEO Jensen Huang and Tesla boss Elon Musk are now talking about robotics as a key application of AI — but Son was thinkingabout this more than a decade ago.
In 2012, SoftBank took a majority stake in a French company called Aldebaran. Two years later, the two companies launched a humanoid robot called Pepper, which they billed as “the world’s first personal robot that can read emotions.”
Later, Son said: “In 30 years, I hope robots will become one of the core businesses in generating profits for the SoftBank group.”
SoftBank’s bet on Pepper ultimately flopped for the company. SoftBank slashed jobs at its robotics unit and stopped producing Pepper in 2020.In 2022, German firm United Robotics Group agreed to acquire Aldebaran from SoftBank.
But Son’s very early interest in robots underscored his curiosity for AI applications of the future.
“He was in very early and he has been thinking about this obsessively for a long time,” Sama, who is author of “The Money Trap,” said.
In the background, Son was cooking up something bigger: a tech fund that would make waves in the investing world. He founded the Vision Fund in 2017 with a massive $100 billion in deployable capital.
SoftBank aggressively invested in companies across the world with some of the biggest bets on ride hailing players like Uber and Chinese firm Didi.
The market questioned some of Son’s investments in companies like Uber and Didi, which were burning through cash at the time and had unclear unit economics.
But even those investments spoke to Son’s AI view, according to the former partner at the SoftBank Vision Fund.
“His thought back then was the first advent of AI would be self-driving cars,” the source told CNBC.
Again this could be seen as a case of being too early. Uber created a driverless car unit only to sell it off. Instead, the company has focused on other self-driving car companies to bring them onto the Uber platform. Even now, driverless cars are not widespread on roads, though commercial services like those of Waymo are available.
SoftBank still has investments in driverless car companies, such as British startup Wayve.
Timing clearly wasn’t on Son’s side. After record losses at the Vision Fund in 2022, Son declared SoftBank would go into “defense” mode, significantly reducing investments and being more prudent. It was at this time that companies like OpenAI were beginning to gain steam, but still before the launch of ChatGPT that would put the company on the map.
“When those companies came to head in 2021, 2022, Masa would have been in a perfect place but he had used all his ammunition on other companies,” the former Vision Fund exec said.
“When they came to age in 21, 22, the Vision Fund had invested in five or six hundred different companies and he was not in a position to invest in AI and he missed that.”
Son himself said this year that SoftBank wanted to invest in OpenAI as early as 2019, but it was Microsoft that ended up becoming the key investor. Fast forward to 2025, the Vision Fund — of which there are now two — has a portfolio stacked full of AI focused companies.
But that period was tough for investors across the board. The Covid-19 pandemic, booming inflation and rising rates hit public and private markets across the board after years of loose monetary policy and a tech bull run.
SoftBank didn’t see that time as a missed opportunity to invest in AI, a person familiar with the company said.
Instead, the the company is of the view that it is still very early in the AI investing cycle, the source added.
Risk and reward
AI technology is fast-moving, from the chips that run the software to the models that underpin popular applications.
Tech giants in the U.S. and China are battling it out to produce ever-advancing AI models with the aim of reaching artificial general intelligence (AGI) — a term with different definitions depending on who you speak to, but one that broadly refers to AI that is smarter than humans. With billions of dollars of investment going into the technology, the risk is high, and the rewards could be even higher.
While markets have since recovered, the potential of surprise advances in technology at such an early stage in AI remains a big risk for the likes of SoftBank.
“As with most technology investments the key challenge is to invest in the winning technologies. Many of the investments SoftBank has made are in the current leaders but AI is still in its relative infancy so other challengers could still rear up from nowhere,” Dan Baker, senior equity analyst at Morningstar, told CNBC.
Still, Son has made it clear he wants to set SoftBank up with DNA that will see it survive and thrive for 300 years, according to the company’s website.
That may go some way to explain the big risks that Son takes, and his conviction when it comes to particular themes and companies — and the valuations he’s willing to pay.
“He (Son) made some mistakes, but directionally he is going in the same driection, which is — he wants to be sure that he is a real player in AI and he is making it happen,” the former Vision Fund exec said.
In exchange for 15% of revenues from the chip sales, the two chipmakers will receive export licenses to sell Nvidia’s H20 and AMD’s MI308 chips in China, according to the FT.
The arrangement comes as President Donald Trump’s tariffs continue to reverberate through the global economy, underscoring the White House’s willingness to carve out exceptions as a bargaining tool.
Nvidia CEO Jensen Huang met with Trump last week, according to the FT.
In a statement, Nvidia told the Financial Times: “We follow rules the U.S. government sets for our participation in worldwide markets.”
Last week, Trump had said he would implement a 100% tariff on imports of semiconductors and chips, unless a company was “building in the United States.”