Tesla’s price cuts accelerate the EV market’s first real recession stress test
Pedestrians walk past the Tesla Motors official authorized car dealer store in Hong Kong.
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Is the first electric-vehicle recession here, or coming soon?
As electric-car stocks plummeted in late 2022, the rout evoked comparisons to the dot-com stock bust two decades ago. Like the internet industry then, the EV industry boasts companies, notably Tesla, that look like long-term winners, but it is also made up of young companies that may not have the cash to ride out a downturn, as well as in-between players like Lucid Group, Fisker and Rivian Automotive, that have done their best to prepare, and whose fate may depend on how bad things get.
With the economy at an inflection point between receding inflation fears and broad expectation of a recession beginning in 2023, the market doesn’t know what to make of moves like Tesla’s big price cuts, first in China and then on Jan. 13, in the U.S. and Europe. Analysts like Guggenheim Securities’ Ronald Jesikow said it could push Tesla’s profit margins 25% lower than Wall Street consensus and drain profits from all of Tesla’s competitors. But optimists like Wedbush analyst Dan Ives think it’s the right, aggressive move to jumpstart the EV transition amid macro uncertainty.
“Many dot-coms didn’t make it,” Ives said. “There’s no stress test for a severe recession for an industry that’s in its infancy.”
What happens next — whether battered EV stocks rebound, whether young companies that need more funding will be able to get it, and whether the sector becomes the jobs engine Washington was counting on when it passed the Inflation Reduction Act last summer, laden with tax credits for EVs — depends on the economy first, and the markets second.
The “first EV recession” theme comes with a big if – that there is a recession in the first place, either here or in China, where Tesla sales dropped 44 percent in December from November levels as the government there continued struggling to contain Covid-19.
In the U.S., most economists and CEOs think a recession is likely this year, though the market gains of the last week may reflect the beginnings of a change in the investor outlook, with more believing in the “soft landing” narrative for the economy. One holdout, Moody’s Analytics chief economist Mark Zandi, forecasts a months-long “slowcession” where growth doesn’t quite turn negative. Either scenario would likely hurt car sales in general, which were the worst in a decade in the U.S. last year, but where some auto executives are now slightly more confident about a rebound, though the EV outlook among the automakers has become more cautious in the short-term. But either scenario may be too pessimistic if the economy responds positively to now-slowing inflation.
The outlook from China, home to more than half of the world’s EV sales, according to Clean Technica, is at least as murky. Manufacturing moved into negative-growth territory late in the year and housing prices are falling, but the International Monetary Fund says China will avoid a recession and grow its economy by 3.8% this year. That would be half of 2021’s clip and slightly below China’s pace last summer, when the nation began to cope with new Covid-related shutdowns. China is now pushing to reopen its economy amid the pandemic.
Tesla’s 2023 world is like Amazon and eBay’s 2000
A recession, if it happens, doesn’t necessarily mean EV sales will fall. Most models saw big sales gains last year in both the U.S. and Asia. It’s more a question of whether EV companies will grow fast enough to keep adding jobs, and for companies beyond Tesla to turn profitable when investors expect them to — or before they run out of cash they raised to fund startup losses.
That sets up a dynamic a lot like the one that confronted dot-com companies like Amazon and eBay as 2000 blended into 2001: A web-stock selloff was well-underway then, just as EV companies like Tesla, Fisker and Lucid fell sharply last year — 65 percent for Tesla, 54 percent for Fisker and 82 percent for Lucid. Then as now, weaker players like today’s EV makers Lordstown Motors, Faraday Future and Canoo were scrambling to avoid running out of cash as an economic slowdown loomed, either by cutting costs or raising more money from investors.
“We look at a combination of balance sheet stability and ability to raise more capital,” said Greg Bissuk, CEO of AXS Investments in New York, which runs an exchange-traded fund that uses swaps to deliver the opposite of Tesla’s daily return — in essence, usually a near-term bet that the shares will drop. “We think it will be rocky,” he said, specifically referring to the middle-tier EV makers.
But at the same time, revenue at dot-com companies kept rising fast, and the businesses that were destined to survive began to turn profitable between 2001 and 2003. Today, EV sales in China are rising, even as Covid continues to hamper its economy, and EVs posted a 52% sales gain in the U.S. At year-end, EVs had 6% of the U.S. light-vehicle market, compared to 1 percent of U.S. retail sales being online in late 2000.
Slower growth isn’t no growth
For EV makers, the likely impact of a recession is slower growth, but not the negative growth the overall economy experiences in a downturn, as new technology keeps gaining market share.
The best-positioned EV maker is still Tesla, said CFRA Research analyst Garrett Nelson. With the company still expected to have generated about $4 billion in late-2022 cash flow when it reports fourth-quarter earnings Jan. 25, and having had about $21 billion at the end of the third quarter, it’s not in danger of a cash burn, Ives said.
“We think the stock rebounds quickly this year,” Nelson said, calling Tesla his top pick among all auto makers, and noting that CFRA economists don’t expect a recession. It trades at 24 times this year’s profit estimates, which in turn only call for 25% profit growth, numbers that are modest for a growth company with room to keep expanding fast.
After the price cut, Nelson said the company will see narrower profit margin but will sell more cars.
“It should widen the company’s competitive advantage and make many more Tesla vehicles eligible for the $7,500 federal EV tax credit,” Nelson said.
The just-enacted price cut pulled the most-popular Model Y vehicles under the price maximum for tax-credit eligibility in the 2022 Inflation Reduction Act.
Tesla has its own issues, with sales growth having slowed late in the year. Fourth-quarter units were up 32%, down sharply from earlier in the year, missing Wall Street estimates for a second straight quarter. CEO Elon Musk’s antics as the new lead owner of Twitter raise concerns about how closely Musk is watching the store, and how quickly he may respond if Tesla’s decline accelerates, Ives said.
“The biggest [issue] is Twitter,” Nelson said.
On the plus side, this year’s earnings estimates assume no contribution from the Cybertruck, which Tesla is again promising to launch late this year, after being delayed since 2021. And Goldman Sachs analyst Mark Delaney wrote Jan. 2 that vehicle deliveries should reaccelerate by midyear, helped by lower cost structures at Tesla’s newer factories and a pickup in Chinese sales.
“Now is a time for leadership from Musk to lead Tesla through this period of softer demand in a darker macro, and not the time to be hands off, which is the perception of the Street,” Ives said. “This is a fork-in-the-road year for Tesla, where it will either lay the groundwork for its next chapter of growth or continue its slide.”
Cash burn and the rest of the EV market
In the middle, Lucid, Rivian and Fisker make up a range of higher-risk possibilities that may well turn out fine in the end. But Tesla’s price cutting may cause them problems: Fisker’s stock dropped almost 10% on its rival’s announcement, since Tesla’s move puts the Model Y’s price closer to that of the Fisker Ocean, whose middle tier is around $50,000.
Of the three, Rivian has the most cash on hand, with short-term investments at $13.3 billion as of the end of the third quarter. Fisker had $829 million, and Lucid had $3.85 billion.
Each company is still burning cash, posing the question of whether they have enough to survive a downturn. Fisker lost about $480 million in cash flow in the 12 months ending in September, and invested another $220 million, meaning its cash would last between one and two years if its losses and investment didn’t slow.
“Our commitment to a lean business model has given us a solid balance sheet, which we have supported with disciplined management of our cash,” CEO Henrik Fisker said in a statement to CNBC. “We are in good shape to manage future economic challenges and to act on opportunities.”
Lucid spent over $2 billion in the first nine months of 2022 on operating cash flow losses and capital investment, and says its cash will cover its plans “at least into the fourth quarter of 2023,” according to its third-quarter earnings call. Lucid’s recent production and delivery numbers did beat expectations, albeit expectations that had already been lowered.
Rivian’s stockpile is more than two years’ worth of recent cash-flow losses and investment.
All three companies, which declined or didn’t respond to on-the-record interview requests, can also extend their cash runway by raising more capital and, indeed, at least two of them have already begun to do so. Lucid raised another $1.515 billion in December, mostly from Saudi Arabia’s Public Investment Fund, while Fisker has filed to raise $2 billion from an ongoing shelf registration at the Securities and Exchange Commission and has so far raised $116 million.
All three should also give financial guidance for 2023 during earnings season, including updates on their capital spending, and on whether cash-flow losses will narrow as they begin to ship more vehicles.
Fisker began shipping its initial model, the Fisker Ocean, only in mid-November, and plans to ship a less-expensive SUV called the Fisker PEAR next year. Rivian, hampered by parts shortages due to Covid-driven supply chain issues, missed its 2022 production target of 25,000 vehicles by less than 700. It hasn’t yet said how many cars it will ship this year. Rivian also paused a partnership with Mercedes in November, ending for now a plan to co-develop commercial vehicles. Rivian said it would concentrate on its consumer business and other commercial ventures, primarily a deal to sell delivery vans to Amazon, that offer better risk-adjusted returns. That move will help avoid pressure on the startup’s capital base.
Business plans for the future, little current business
Lower on the food chain are companies like Faraday Future Intelligent Electric, Canoo and Lordstown Motors, which went public via mergers with Special Purpose Acquisition Companies, or SPACs, and have lost most of their equity value since.
Lordstown in November announced a fresh investment by Foxconn, the contract manufacturer that will own 19.9% of Lordstown after the deal, including preferred stock, to help scale up production of its initial pickup truck and bolster the $204 million in cash on its balance sheet. Foxconn has agreed to make Fisker vehicles in Lordstown’s Ohio factory, which Foxconn bought in May, for launch in 2024. It issued a going-concern warning in 2021, before raising money from Foxconn.
“The new capital from Foxconn doesn’t change our focus” on cost containment, Lordstown CFO Adam Kroll said, arguing that the Foxconn deal will slash Lordstown’s capital needs. “We continue to execute a playbook of prudence and discipline.”
Companies like Faraday, Canoo and Lordstown that need to raise more capital could find the path blocked by a more-skeptical capital market than the one that financed them during the special-purpose acquisition company boom, CFRA’s Nelson said. Weaker players include Electro Mechanica, which has proposed a solo EV but hasn’t shipped it in scale yet, British commercial-vehicle maker Arrival, and Green Power Motor, a Canadian electric bus maker, he said. He even includes Fisker, Lucid and Rivian among those at risk from tighter markets.
“They had a business plan but no business, and they got absurd amounts of capital,” Nelson said. “In our opinion, you’ll see many additional bankruptcies, but the market will return to balance. But it’s hard to imagine we’ve seen the bottom.”
But Nelson does believe the electric car boom is for real — indeed, he says Tesla is the year’s best bet in the overall auto industry. A note of skepticism: After the dot-com boom and bust, Amazon.com began rising off its lows in 2002, rising tenfold by 2008, but didn’t leave its 1999 highs behind for good until 2010. EBay recovered faster but couldn’t sustain its momentum.
Ives said the Inflation Reduction Act, which offers tax credits of $7,500 for electric cars costing less than $55,000 and SUVs or pickups selling for $80,000 or less, may throw the industry a lifeline as companies arrange to do enough domestic manufacturing to qualify all of their vehicles. Arrival, citing IRA credits of up to $40,000 for buyers of commercial vehicles, said in November that it is refocusing its London-based company on the U.S. market.
“The pressure in 2023 is less about EVs than the overall macro environment,” Ives said. “The IRA is not a small point.”
That’s not lost even on Bassuk, who emphasizes that his fund is about helping exploit short-term weakness in the market’s view of EVs. Long-term, he says, EVs are coming, recession or not.
“Those with the capital to get through 2023, we’d bet the farm on,” he said.
CNBC is now accepting nominations for the 2023 Disruptor 50 list – our 11th annual look at the most innovative venture-backed companies. Learn more about eligibility and how to submit an application by Friday, Feb. 17.
Technology
AI research takes a backseat to profits as Silicon Valley prioritizes products over safety, experts say
Sam Altman, co-founder and CEO of OpenAI and co-founder of Tools for Humanity, participates remotely in a discussion on the sidelines of the IMF/World Bank Spring Meetings in Washington, D.C., April 24, 2025.
Brendan Smialowski | AFP | Getty Images
Not long ago, Silicon Valley was where the world’s leading artificial intelligence experts went to perform cutting-edge research.
Meta, Google and OpenAI opened their wallets for top talent, giving researchers staff, computing power and plenty of flexibility. With the support of their employers, the researchers published high-quality academic papers, openly sharing their breakthroughs with peers in academia and at rival companies.
But that era has ended. Now, experts say, AI is all about the product.
Since OpenAI released ChatGPT in late 2022, the tech industry has shifted its focus to building consumer-ready AI services, in many cases prioritizing commercialization over research, AI researchers and experts in the field told CNBC. The profit potential is massive — some analysts predict $1 trillion in annual revenue by 2028. The prospective repercussions terrify the corner of the AI universe concerned about safety, industry experts said, particularly as leading players pursue artificial general intelligence, or AGI, which is technology that rivals or exceeds human intelligence.
In the race to stay competitive, tech companies are taking an increasing number of shortcuts when it comes to the rigorous safety testing of their AI models before they are released to the public, industry experts told CNBC.
James White, chief technology officer at cybersecurity startup CalypsoAI, said newer models are sacrificing security for quality, that is, better responses by the AI chatbots. That means they’re less likely to reject malicious kinds of prompts that could cause them to reveal ways to build bombs or sensitive information that hackers could exploit, White said.
“The models are getting better, but they’re also more likely to be good at bad stuff,” said White, whose company performs safety and security audits of popular models from Meta, Google, OpenAI and other companies. “It’s easier to trick them to do bad stuff.”
The changes are readily apparent at Meta and Alphabet, which have deprioritized their AI research labs, experts say. At Facebook’s parent company, the Fundamental Artificial Intelligence Research, or FAIR, unit has been sidelined by Meta GenAI, according to current and former employees. And at Alphabet, the research group Google Brain is now part of DeepMind, the division that leads development of AI products at the tech company.
CNBC spoke with more than a dozen AI professionals in Silicon Valley who collectively tell the story of a dramatic shift in the industry away from research and toward revenue-generating products. Some are former employees at the companies with direct knowledge of what they say is the prioritization of building new AI products at the expense of research and safety checks. They say employees face intensifying development timelines, reinforcing the idea that they can’t afford to fall behind when it comes to getting new models and products to market. Some of the people asked not to be named because they weren’t authorized to speak publicly on the matter.
Mark Zuckerberg, CEO of Meta Platforms, during the Meta Connect event in Menlo Park, California, on Sept. 25, 2024.
David Paul Morris | Bloomberg | Getty Images
Meta’s AI evolution
When Joelle Pineau, a Meta vice president and the head of the company’s FAIR division, announced in April that she would be leaving her post, many former employees said they weren’t surprised. They said they viewed it as solidifying the company’s move away from AI research and toward prioritizing developing practical products.
“Today, as the world undergoes significant change, as the race for AI accelerates, and as Meta prepares for its next chapter, it is time to create space for others to pursue the work,” Pineau wrote on LinkedIn, adding that she will formally leave the company May 30.
Pineau began leading FAIR in 2023. The unit was established a decade earlier to work on difficult computer science problems typically tackled by academia. Yann LeCun, one of the godfathers of modern AI, initially oversaw the project, and instilled the research methodologies he learned from his time at the pioneering AT&T Bell Laboratories, according to several former employees at Meta. Small research teams could work on a variety of bleeding-edge projects that may or may not pan out.
The shift began when Meta laid off 21,000 employees, or nearly a quarter of its workforce, starting in late 2022. CEO Mark Zuckerberg kicked off 2023 by calling it the “year of efficiency.” FAIR researchers, as part of the cost-cutting measures, were directed to work more closely with product teams, several former employees said.
Two months before Pineau’s announcement, one of FAIR’s directors, Kim Hazelwood, left the company, two people familiar with the matter said. Hazelwood helped oversee FAIR’s NextSys unit, which manages computing resources for FAIR researchers. Her role was eliminated as part of Meta’s plan to cut 5% of its workforce, the people said.
Joelle Pineau of Meta speaks at the Advancing Sustainable Development through Safe, Secure, and Trustworthy AI event at Grand Central Terminal in New York, Sept. 23, 2024.
Bryan R. Smith | Via Reuters
OpenAI’s 2022 launch of ChatGPT caught Meta off guard, creating a sense of urgency to pour more resources into large language models, or LLMs, that were captivating the tech industry, the people said.
In 2023, Meta began heavily pushing its freely available and open-source Llama family of AI models to compete with OpenAI, Google and others.
With Zuckerberg and other executives convinced that LLMs were game-changing technologies, management had less incentive to let FAIR researchers work on far-flung projects, several former employees said. That meant deprioritizing research that could be viewed as having no impact on Meta’s core business, such as FAIR’s previous health care-related research into using AI to improve drug therapies.
Since 2024, Meta Chief Product Officer Chris Cox has been overseeing FAIR as a way to bridge the gap between research and the product-focused GenAI group, people familiar with the matter said. The GenAI unit oversees the Llama family of AI models and the Meta AI digital assistant, the two most important pillars of Meta’s AI strategy.
Under Cox, the GenAI unit has been siphoning more computing resources and team members from FAIR due to its elevated status at Meta, the people said. Many researchers have transferred to GenAI or left the company entirely to launch their own research-focused startups or join rivals, several of the former employees said.
While Zuckerberg has some internal support for pushing the GenAI group to rapidly develop real-world products, there’s also concern among some staffers that Meta is now less able to develop industry-leading breakthroughs that can be derived from experimental work, former employees said. That leaves Meta to chase its rivals.
A high-profile example landed in January, when Chinese lab DeepSeek released its R1 model, catching Meta off guard. The startup claimed it was able to develop a model as capable as its American counterparts but with training at a fraction of the cost.
Meta quickly implemented some of DeepSeek’s innovative techniques for its Llama 4 family of AI models that were released in April, former employees said. The AI research community had a mixed reaction to the smaller versions of Llama 4, but Meta said the biggest and most powerful Llama 4 variant is still being trained.
The company in April also released security and safety tools for developers to use when building apps with Meta’s Llama 4 AI models. These tools help mitigate the chances of Llama 4 unintentionally leaking sensitive information or producing harmful content, Meta said.
“Our commitment to FAIR remains strong,” a Meta spokesperson told CNBC. “Our strategy and plans will not change as a result of recent developments.”
In a statement to CNBC, Pineau said she is enthusiastic about Meta’s overall AI work and strategy.
“There continues to be strong support for exploratory research and FAIR as a distinct organization in Meta,” Pineau said. “The time was simply right for me personally to re-focus my energy before jumping into a new adventure.”
Meta on Thursday named FAIR co-founder Rob Fergus as Pineau’s replacement. Fergus will return to the company to serve as a director at Meta and head of FAIR, according to his LinkedIn profile. He was most recently a research director at Google DeepMind.
“Meta’s commitment to FAIR and long term research remains unwavering,” Fergus said in a LinkedIn post. “We’re working towards building human-level experiences that transform the way we interact with technology and are dedicated to leading and advancing AI research.”
Demis Hassabis, co-founder and CEO of Google DeepMind, attends the Artificial Intelligence Action Summit at the Grand Palais in Paris, Feb. 10, 2025.
Benoit Tessier | Reuters
Google ‘can’t keep building nanny products’
Google released its latest and most powerful AI model, Gemini 2.5, in March. The company described it as “our most intelligent AI model,” and wrote in a March 25 blog post that its new models are “capable of reasoning through their thoughts before responding, resulting in enhanced performance and improved accuracy.”
For weeks, Gemini 2.5 was missing a model card, meaning Google did not share information about how the AI model worked or its limitations and potential dangers upon its release.
Model cards are a common tool for AI transparency.
A Google website compares model cards to food nutrition labels: They outline “the key facts about a model in a clear, digestible format,” the website says.
“By making this information easy to access, model cards support responsible AI development and the adoption of robust, industry-wide standards for broad transparency and evaluation practices,” the website says.
Google wrote in an April 2 blog post that it evaluates its “most advanced models, such as Gemini, for potential dangerous capabilities prior to their release.” Google later updated the blog to remove the words “prior to their release.”
Without a model card for Gemini 2.5, the public had no way of knowing which safety evaluations were conducted or whether DeepMind checked for dangerous capabilities at all.
In response to CNBC’s inquiry on April 2 about Gemini 2.5’s missing model card, a Google spokesperson said that a “tech report with additional safety information and model cards are forthcoming.” Google published an incomplete model card on April 16 and updated it on April 28, more than a month after the AI model’s release, to include information about Gemini 2.5’s “dangerous capability evaluations.”
Those assessments are important for gauging the safety of a model — whether people can use the models to learn how to build chemical or nuclear weapons or hack into important systems. These checks also determine whether a model is capable of autonomously replicating itself, which could lead to a company losing control of it. Running tests for those capabilities requires more time and resources than simple, automated safety evaluations, according to industry experts.
Google co-founder Sergey Brin
Kelly Sullivan | Getty Images Entertainment | Getty Images
The Financial Times in March reported that Google DeepMind CEO Demis Hassabis had installed a more rigorous vetting process for internal research papers to be published. The clampdown at Google is particularly notable because the company’s “Transformers” technology gained recognition across Silicon Valley through that type of shared research. Transformers were critical to OpenAI’s development of ChatGPT and the rise of generative AI.
Google co-founder Sergey Brin told staffers at DeepMind and Gemini in February that competition has accelerated and “the final race to AGI is afoot,” according to a memo viewed by CNBC. “We have all the ingredients to win this race but we are going to have to turbocharge our efforts,” he said in the memo.
Brin said in the memo that Google has to speed up the process of testing AI models, as the company needs “lots of ideas that we can test quickly.”
“We need real wins that scale,” Brin wrote.
In his memo, Brin also wrote that the company’s methods have “a habit of minor tweaking and overfitting” products for evaluations and “sniping” the products at checkpoints. He said employees need to build “capable products” and to “trust our users” more.
“We can’t keep building nanny products,” Brin wrote. “Our products are overrun with filters and punts of various kinds.”
A Google spokesperson told CNBC that the company has always been committed to advancing AI responsibly.
“We continue to do that through the safe development and deployment of our technology, and research contributions to the broader ecosystem,” the spokesperson said.
Sam Altman, CEO of OpenAI, is seen through glass during an event on the sidelines of the Artificial Intelligence Action Summit in Paris, Feb. 11, 2025.
Aurelien Morissard | Via Reuters
OpenAI’s rush through safety testing
The debate of product versus research is at the center of OpenAI’s existence. The company was founded as a nonprofit research lab in 2015 and is now in the midst of a contentious effort to transform into a for-profit entity.
That’s the direction co-founder and CEO Sam Altman has been pushing toward for years. On May 5, though, OpenAI bowed to pressure from civic leaders and former employees, announcing that its nonprofit would retain control of the company even as it restructures into a public benefit corporation.
Nisan Stiennon worked at OpenAI from 2018 to 2020 and was among a group of former employees urging California and Delaware not to approve OpenAI’s restructuring effort. “OpenAI may one day build technology that could get us all killed,” Stiennon wrote in a statement in April. “It is to OpenAI’s credit that it’s controlled by a nonprofit with a duty to humanity.”
But even with the nonprofit maintaining control and majority ownership, OpenAI is speedily working to commercialize products as competition heats up in generative AI. And it may have rushed the rollout of its o1 reasoning model last year, according to some portions of its model card.
Results of the model’s “preparedness evaluations,” the tests OpenAI runs to assess an AI model’s dangerous capabilities and other risks, were based on earlier versions of o1. They had not been run on the final version of the model, according to its model card, which is publicly available.
Johannes Heidecke, OpenAI’s head of safety systems, told CNBC in an interview that the company ran its preparedness evaluations on near-final versions of the o1 model. Minor variations to the model that took place after those tests wouldn’t have contributed to significant jumps in its intelligence or reasoning and thus wouldn’t require additional evaluations, he said. Still, Heidecke acknowledged that OpenAI missed an opportunity to more clearly explain the difference.
OpenAI’s newest reasoning model, o3, released in April, seems to hallucinate more than twice as often as o1, according to the model card. When an AI model hallucinates, it produces falsehoods or illogical information.
OpenAI has also been criticized for reportedly slashing safety testing times from months to days and for omitting the requirement to safety test fine-tuned models in its latest “Preparedness Framework.”
Heidecke said OpenAI has decreased the time needed for safety testing because the company has improved its testing effectiveness and efficiency. A company spokesperson said OpenAI has allocated more AI infrastructure and personnel to its safety testing, and has increased resources for paying experts and growing its network of external testers.
In April, the company shipped GPT-4.1, one of its new models, without a safety report, as the model was not designated by OpenAI as a “frontier model,” which is a term used by the tech industry to refer to a bleeding-edge, large-scale AI model.
But one of those small revisions caused a big wave in April. Within days of updating its GPT-4o model, OpenAI rolled back the changes after screenshots of overly flattering responses to ChatGPT users went viral online. OpenAI said in a blog post explaining its decision that those types of responses to user inquiries “raise safety concerns — including around issues like mental health, emotional over-reliance, or risky behavior.”
OpenAI said in the blogpost that it opted to release the model even after some expert testers flagged that its behavior “‘felt’ slightly off.”
“In the end, we decided to launch the model due to the positive signals from the users who tried out the model. Unfortunately, this was the wrong call,” OpenAI wrote. “Looking back, the qualitative assessments were hinting at something important, and we should’ve paid closer attention. They were picking up on a blind spot in our other evals and metrics.”
Metr, a company OpenAI partners with to test and evaluate its models for safety, said in a recent blog post that it was given less time to test the o3 and o4-mini models than predecessors.
“Limitations in this evaluation prevent us from making robust capability assessments,” Metr wrote, adding that the tests it did were “conducted in a relatively short time.”
Metr also wrote that it had insufficient access to data that would be important in determining the potential dangers of the two models.
The company said it wasn’t able to access the OpenAI models’ internal reasoning, which is “likely to contain important information for interpreting our results.” However, Metr said, “OpenAI shared helpful information on some of their own evaluation results.”
OpenAI’s spokesperson said the company is piloting secure ways of sharing chains of thought for Metr’s research as well as for other third-party organizations.
Steven Adler, a former safety researcher at OpenAI, told CNBC that safety testing a model before it’s rolled out is no longer enough to safeguard against potential dangers.
“You need to be vigilant before and during training to reduce the chance of creating a very capable, misaligned model in the first place,” Adler said.
He warned that companies such as OpenAI are backed into a corner when they create capable but misaligned models with goals that are different from the ones they intended to build.
“Unfortunately, we don’t yet have strong scientific knowledge for fixing these models — just ways of papering over the behavior,” Adler said.
WATCH: OpenAI closes $40 billion funding round, largest private tech deal on record
Omar Marques | Sopa Images | Lightrocket | Getty Images
Shares of stock brokerage platform eToro popped in their Nasdaq debut on Wednesday after the company raised almost $310 million in its initial public offering.
The stock opened at $69.69, or 34% above its IPO, pushing its market cap to $5.6 billion. Shares were last up more than 40%.
The Israel-based company sold nearly six million shares at $52 each, above the expected range of $46 to $50. Almost six million additional shares were sold by existing investors. At the IPO price, the company was valued at roughly $4.2 billion.
Wall Street is looking to the Robinhood competitor for signs of renewed interest in IPOs after an extended drought. Many investors saw President Donald Trump’s return to the White House as a catalyst before tariff concerns led companies to delay their plans.
Etoro isn’t the only company attempting to test the waters. Fintech company Chime filed its prospectus with the U.S. Securities and Exchange Commission on Tuesday, while digital physical therapy company Hinge Health kickstarted its IPO roadshow, and said in a filing it aims to raise up to $437 million in its offering.
EToro had previously filed to go public in 2021 through a merger with a special purpose acquisition company, or SPAC, that would have valued it at more than $10 billion. It shelved those plans in 2022 as equity markets nosedived, but remained focused on an eventual IPO.
EToro was founded in 2007 by brothers Yoni and Ronen Assia and David Ring. The company makes money through trading-related fees and nontrading activities such as withdrawals. Net income increased almost thirteenfold last year to $192.4 million from $15.3 million in 2023.
The company has steadily built a growing business in cryptocurrencies. Revenue from crypto assets more than tripled to upward of $12 million in 2024, and one-quarter of its net trading contribution stemmed from crypto last year. That is up from 10% in 2023.
EToro said that for the first quarter, it expects crypto assets to account for 37% of its commission from trading activities, down from 43% a year earlier.
Spark Capital is the company’s biggest outside investor, with 14% control after the offering, followed by BRM Group at 8.7%. CEO Yoni Assia controls 9.3%.
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