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Alex Spiro, attorney to Elon Musk, center, departs court in San Francisco, California, US, on Tuesday, Jan. 17, 2023.

Benjamin Fanjoy | Bloomberg | Getty Images

Tesla CEO Elon Musk appeared in a San Francisco federal court on Friday to defend tweets he posted to his tens of millions of followers in August 2018.

The tweets said he had “funding secured” to take his electric vehicle company private for $420 per share, and that “investor support” for such a deal was “confirmed.”

Tesla’s stock trading initially halted after the tweets, then shares were highly volatile for weeks. Musk later said that he had been in discussions with Saudi Arabia’s sovereign wealth fund and felt sure that funding would come through at his proposed price. A deal never materialized.

The SEC charged Musk and Tesla with civil securities fraud after the tweets. Musk and Tesla each paid $20 million fines to the agency, and struck a revised settlement agreement that required Musk to temporarily relinquish his role as chairman of the board at Tesla.

His 2018 tweets also triggered a shareholder class action lawsuit from Tesla investors. They alleged that Musk’s tweets misled them and said relying on his statements to make trades cost them significant amounts of money.

The shareholders’ trades in question took place during a 10-day period before Musk seemed to admit a take-private deal was not going to happen in 2018.

Musk said under oath on Friday that it’s difficult to link Tesla’s stock price to his tweets.

“There have been many cases where I thought that if I were to tweet something, the stock price would go down,” Musk said. “For example, at one point I tweeted that I thought that, in my opinion, the stock price was too high…and it went went higher, which was, which is, you know, counterintuitive.”

A big increase in trading volume after he tweeted

It’s rare for top executives at publicly traded companies to discuss their stock price because any commentary can influence price movements.

Daniel Taylor, director of the Wharton Forensics Analytics Lab and professor at the University of Pennsylvania, analyzed every trade in Tesla stock occurring on Aug. 7, 2018, the day that Musk tweeted. He calculated the total trading volume every minute from the time the market opened through the time of Musk’s tweets about a buyout. 

Taylor found that the trading volume the minute Musk tweeted, at 12:48 p.m. ET that day, was over $350 million, and the trading volume for Tesla shares the next minute was over $250 million. By comparison, the average volume five minutes before Musk tweeted was $32 million per minute. The minute before Musk tweeted, trading volume was $24 million.  

“It is generally true that correlation is not causation,” Taylor told CNBC on Friday, after Musk’s first day on the witness stand. “However, I am unaware of any alternative explanation for a 10-fold increase in trading volume the same minute that Elon Musk tweeted.”

Musk also testified about his low opinion of short sellers on Friday.

“I believe short selling should be made illegal,” Musk said, referring to short sellers as “bad people on Wall Street” who “steal” from other investors. He said they also plant stories in the media to “get the stock to go down” and will “do anything in their power to make a company die.”

Tesla was among the most heavily shorted stocks in August 2018, when Musk made the statements about taking Tesla private. Tesla’s share price surged about 10% during trading that day. Short sellers face enormous losses when shares in a given company climb higher.

Some of the plaintiffs in the trial that’s underway claim that Musk’s “funding secured” tweets were intended to put upward price pressure on Tesla’s stock driving a so-called “short squeeze.”

Musk’s testimony is not yet complete and the court plans to hear from him again on Monday.

WATCH: Musk testifies over tweets

Tesla CEO Elon Musk to testify over 2018 'funding secured' tweets

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Musk says he does not support a merger between Tesla and xAI but backs investment

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Musk says he does not support a merger between Tesla and xAI but backs investment

Elon musk and the xAI logo.

Vincent Feuray | Afp | Getty Images

Elon Musk on Monday said he does not support a merger between xAI and Tesla, as questions swirl over the future relationship of the electric automaker and artificial intelligence company.

X account @BullStreetBets_ posted an open question to Tesla investors on the social media site asking if they support a merger between Tesla and xAI. Musk responded with “No.”

The statement comes as the tech billionaire contemplates the future relationship between his multiple businesses.

Overnight, Musk suggested that Tesla will hold a shareholder vote at an unspecified time on whether the automaker should invest in xAI, the billionaire’s company that develops the controversial Grok AI chatbot.

Last year, Musk asked his followers in an poll on social media platform X whether Tesla should invest $5 billion into xAI. The majority voted “yes” at the time.

Musk has looked to bring his various businesses closer together. In March, Musk merged xAI and X together in a deal that valued the artificial intelligence company at $80 billion and the social media company at $33 billion.

Musk also said last week that xAI’s chatbot Grok will be available in Tesla vehicles. The chatbot has come under criticism recently, after praising Adolf Hitler and posting a barrage of antisemitic comments.

CNBC’s Samantha Subin contributed to this report.

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Alibaba-backed Moonshot releases new Kimi AI model that beats ChatGPT, Claude in coding — and it costs less

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Alibaba-backed Moonshot releases new Kimi AI model that beats ChatGPT, Claude in coding — and it costs less

An AI sign at the MWC Shanghai tech show on June 19, 2025.

Bloomberg | Bloomberg | Getty Images

BEIJING — The latest Chinese generative artificial intelligence model to take on OpenAI’s ChatGPT is offering coding capabilities — at a lower price.

Alibaba-backed startup Moonshot released on late Friday night its Kimi K2 model: a low-cost, open source large language model — the two factors that underpinned China-based DeepSeek’s industry disruption in January. Open-source technology provides source code access for free, an approach that few U.S. tech giants have taken, other than Meta and Google to some extent.

Coincidentally, OpenAI CEO Sam Altman announced early Saturday that there would be an indefinite delay of its first open-source model yet again due to safety concerns. OpenAI did not immediately respond to a CNBC request for comment on Kimi K2.

Rethinking the AI coding payoff

One of Kimi K2’s strengths is in writing computer code for applications, an area in which businesses see potential to reduce or replace staff with generative AI. OpenAI’s U.S. rival Anthropic focused on coding with its Claude Opus 4 model released in late May.

In its release announcement on social media platforms X and GitHub, Moonshot claimed Kimi K2 surpassed Claude Opus 4 on two benchmarks, and had better overall performance than OpenAI’s coding-focused GPT-4.1 model, based on several industry metrics.

“No doubt [Kimi K2 is] a globally competitive model, and it’s open sourced,” Wei Sun, principal analyst in artificial intelligence at Counterpoint, said in an email Monday.

Cheaper option

“On top of that, it has lower token costs, making it attractive for large-scale or budget-sensitive deployments,” she said.

The new K2 model is available via Kimi’s app and browser interface for free unlike ChatGPT or Claude, which charge monthly subscriptions for their latest AI models.

Kimi is also only charging 15 cents for every 1 million input tokens, and $2.50 per 1 million output tokens, according to its website. Tokens are a way of measuring data for AI model processing.

In contrast, Claude Opus 4 charges 100 times more for input — $15 per million tokens — and 30 times more for output — $75 per million tokens. Meanwhile, for every one million tokens, GPT-4.1 charges $2 for input and $8 for output.

Moonshot AI said on GitHub that developers can use K2 however they wish, with the only requirement that they display “Kimi K2” on the user interface if the commercial product or service has more than 100 million monthly active users, or makes the equivalent of $20 million in monthly revenue.

Hot AI market

Initial reviews of K2 on both English and Chinese social media have largely been positive, although there are some reports of hallucinations, a prevalent issue in generative AI, in which the models make up information.

Still, K2 is “the first model I feel comfortable using in production since Claude 3.5 Sonnet,” Pietro Schirano, founder of startup MagicPath that offers AI tools for design, said in a post on X.

Moonshot has open sourced some of its prior AI models. The company’s chatbot surged in popularity early last year as China’s alternative to ChatGPT, which isn’t officially available in the country. But similar chatbots from ByteDance and Tencent have since crowded the market, while tech giant Baidu has revamped its core search engine with AI tools.

Kimi’s latest AI release comes as investors eye Chinese alternatives to U.S. tech in the global AI competition.

Still, despite the excitement about DeepSeek, the privately-held company has yet to announce a major upgrade to its R1 and V3 model. Meanwhile, Manus AI, a Chinese startup that emerged earlier this year as another DeepSeek-type upstart, has relocated its headquarters to Singapore.

Over in the U.S., OpenAI also has yet to reveal GPT-5.

Work on GPT-5 may be taking up engineering resources, preventing OpenAI from progressing on its open-source model, Counterpoint’s Sun said, adding that it’s challenging to release a powerful open-source model without undermining the competitive advantage of a proprietary model.

Grok 4 competitor

Kimi K2 is not the company’s only recent release. Moonshot launched a Kimi research model last month and claimed it matched Google’s Gemini Deep Research ‘s 26.9 score and beat OpenAI’s version on a benchmark called “Humanity’s Last Exam.”

The Kimi research model even got a mention last week during Elon Musk’s xAI release of Grok 4 — which scored 25.4 on its own on the “Humanity’s Last Exam” benchmark, but attained a 44.4 score when allowed to use a variety of AI tools and web search.

“Kimi-Researcher represents a paradigm shift in agentic AI,” said Winston Ma, adjunct professor at NYU School of Law. He was referring to AI’s capability of simultaneously making several decisions on its own to complete a complex task.

“Instead of merely generating fluent responses, it demonstrates autonomous reasoning at an expert level — the kind of complex cognitive work previously missing from LLMs,” Ma said. He is also author of “The Digital War: How China’s Tech Power Shapes the Future of AI, Blockchain and Cyberspace.”

— CNBC’s Victoria Yeo contributed to this report.

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Nvidia CEO downplays U.S. fears that China’s military will use his firm’s chips

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Nvidia CEO downplays U.S. fears that China's military will use his firm's chips

Co-founder and chief executive officer of Nvidia Corp., Jensen Huang attends the 9th edition of the VivaTech trade show in Paris on June 11, 2025.

Chesnot | Getty Images Entertainment | Getty Images

Nvidia CEO Jensen Huang has downplayed U.S. fears that his firm’s chips will aid the Chinese military, days ahead of another trip to the country as he attempts to walk a tightrope between Washington and Beijing. 

In an interview with CNN aired Sunday, Huang said “we don’t have to worry about” China’s military using U.S.-made technology because “they simply can’t rely on it.”

“It could be limited at any time; not to mention, there’s plenty of computing capacity in China already,” Huang said. “They don’t need Nvidia’s chips, certainly, or American tech stacks in order to build their military,” he added.

The comments were made in reference to years of bipartisan U.S. policy that placed restrictions on semiconductor companies, prohibiting them from selling their most advanced artificial intelligence chips to clients in China. 

Huang also repeated past criticisms of the policies, arguing that the tactic of export controls has been counterproductive to the ultimate goal of U.S. tech leadership. 

“We want the American tech stack to be the global standard … in order for us to do that, we have to be in search of all the AI developers in the world,” Huang said, adding that half of the world’s AI developers are in China. 

‘The Nvidia Way’ author Tae Kim: Jensen Huang always positions Nvidia ahead of the next big trend

That means for America to be an AI leader, U.S. technology has to be available to all markets, including China, he added.

Washington’s latest restrictions on Nvidia’s sales to China were implemented in April and are expected to result in billions in losses for the company. In May, Huang said chip restrictions had already cut Nvidia’s China market share nearly in half.

Huang’s CNN interview came just days before he travels to China for his second trip to the country this year, and as Nvidia is reportedly working on another chip that is compliant with the latest export controls.

Last week, the Nvidia CEO met with U.S. President Donald Trump, and was warned by U.S. lawmakers not to meet with companies connected to China’s military or intelligence bodies, or entities named on America’s restricted export list.

According to Daniel Newman, CEO of tech advisory firm The Futurum Group, Huang’s CNN interview exemplifies how Huang has been threading a needle between Washington and Beijing as it tries to maintain maximum market access.

“He needs to walk a proverbial tightrope to make sure that he doesn’t rattle the Trump administration,” Newman said, adding that he also wants to be in a position for China to invest in Nvidia technology if and when the policy provides a better climate to do so.

But that’s not to say that his downplaying of Washington’s concerns is valid, according to Newman. “I think it’s hard to completely accept the idea that China couldn’t use Nvidia’s most advanced technologies for military use.”

He added that he would expect Nvidia’s technology to be at the core of any country’s AI training, including for use in the development of advanced weaponry. 

A U.S. official told Reuters last month that China’s large language model startup DeepSeek — which says it used Nvidia chips to train its models — was supporting China’s military and intelligence operations. 

On Sunday, Huang acknowledged there were concerns about DeepSeek’s open-source R1 reasoning model being trained in China but said that there was no evidence that it presents dangers for that reason alone.

Huang complimented the R1 reasoning model, calling it “revolutionary,” and said its open-source nature has empowered startup companies, new industries, and countries to be able to engage in AI. 

“The fact of the matter is, [China and the U.S.] are competitors, but we are highly interdependent, and to the extent that we can compete and both aspire to win, it is fine to respect our competitors,” he concluded. 

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