Once a dystopian fantasy, manipulating sunlight to cool the earth is now on the White House research agenda
Full frame sun, Climate change, Heatwave hot sun, Global warming from the sun and burning
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The White House is coordinating a five-year research plan to study ways of modifying the amount of sunlight that reaches the earth to temper the effects of global warming, a process sometimes called solar geoengineering or sunlight reflection.
The research plan will assess climate interventions, including spraying aerosols into the stratosphere to reflect sunlight back into space, and should include goals for research, what’s necessary to analyze the atmosphere, and what impact these kinds of climate interventions may have on the Earth, according to the White House‘s Office of Science and Technology Policy. Congress directed the research plan be produced in its spending plan for 2022, which President Joe Biden signed in March.
Some of the techniques, such as spraying sulfur dioxide into the atmosphere, are known to have harmful effects on the environment and human health. But scientists and climate leaders who are concerned humanity will overshoot its emissions targets say research is important to figure out how to balance these risks against a possibly catastrophic rise in the earth’s temperature.
Getting ready to research a topic is a very preliminary step, but it’s notable the White House is formally engaging with what has largely been seen as the stuff of dystopian fantasy. In Kim Stanley Robinson’s science fiction novel, “The Ministry for the Future,” a heatwave in India kills 20 million people and out of desperation, India decides to implement its own strategy of limiting the sunlight that gets to earth.
Chris Sacca, the founder of climate tech investment fund Lowercarbon Capital, says it’s prudent for the White House to be spearheading the research effort.
“Sunlight reflection has the potential to safeguard the livelihoods of billions of people, and it’s a sign of the White House’s leadership that they’re advancing the research so that any future decisions can be rooted in science not geopolitical brinkmanship,” Sacca told CNBC. (Sacca has donated to support research in the area, but has “zero financial interests beyond philanthropy” in the idea and does not think there should be private business models in the space, he told CNBC.)
Harvard professor David Keith first worked on the topic in 1989, and says it’s being taken much more seriously now. He points to a formal statement of support for research from a group he advises called the Overshoot Commission. The Environmental Defense Fund, the Union of Concerned Scientists, and the Natural Resources Defense Council have also indicated support for research into the topic.
To be clear, nobody is saying sunlight reflection modification is the solution to climate change. Reducing emissions remains the priority.
“You cannot judge what the country does on solar radiation modification without looking at what it is doing in emission reductions, because the priority is emission reductions,” said Janos Pasztor, the executive director of the Carnegie Climate Governance Initiative. “Solar radiation modification will never be a solution to the climate crisis.”
Three ways to reduce sunlight
The idea of sunlight reflection first appeared prominently in a 1965 report to President Lyndon B. Johnson entitled “Restoring the Quality of Our Environment,” Keith told CNBC. The report floated the idea of spreading particles over the ocean at a cost of $100 per square mile. A one percent change in the reflectivity of the earth would cost $500 million per year, which does “not seem excessive,” the report says, “considering the extraordinary economic and human importance of climate.”
The estimated price tag has gone up since then. The current estimate is that it would cost $10 billion per year to run a program that cools the earth by one degree Celsius, said Edward A. Parson, a professor of environmental law at UCLA’s law school. But that is remarkably cheap compared to other climate change mitigation efforts.
A landmark report released in March 2021 from the National Academies of Sciences, Engineering, and Medicine addressed three kinds of solar geoengineering: stratospheric aerosol injection, marine cloud brightening, and cirrus cloud thinning.
Stratospheric aerosol injection would involve flying aircraft into the stratosphere, which is between 10 and 30 miles up, and spraying a fine mist that would hang in the air, reflecting some of the sun’s radiation back into space.
“The stratosphere is calm, and things stay up there for a long time,” Parson told CNBC. “The atmospheric life of stuff that’s injected in the stratosphere is between six months and two years.”
Stratospheric aerosol injection “would immediately take the high end off hot extremes,” Parson said. And also it would “pretty much immediately” slow extreme precipitation events too, he said.
“The top line slogan about stratospheric aerosol injection, which I wrote in a paper more than 10 years ago — but it’s still apt — is fast, cheap, and imperfect. Fast is crucial. Nothing else that we do for climate change is fast. Cheap, it’s so cheap,” Parson told CNBC.
“And it’s not imperfect because we haven’t got it right yet. It’s imperfect because the imperfection is embedded in the way it works. The same reason it’s fast is the reason that it’s imperfect, and there’s no way to get around that.”
One option for an aerosol is sulfur dioxide, the cooling effects of which are well known from volcanic eruptions. The 1991 eruption of Mount Pinatubo, for instance, spewed thousands of tons of sulfur dioxide into the stratosphere, causing global temperatures to drop temporarily by about 1 degree Fahrenheit, according to the U.S. Geological Survey.
A giant volcanic mushroom cloud explodes some 20 kilometers high from Mount Pinatubo above almost deserted US Clark Air Base, on June 12, 1991 followed by another more powerful explosion. The eruption of Mount Pinatubo on June 15, 1991 was the second largest volcanic eruption of the twentieth century.
Arlan Naeg | Afp | Getty Images
There’s also a precedent in factories that burn fossil fuels, especially coal. Coal has some sulfur that oxidizes when burns, creating sulfur dioxide. That sulfur dioxide goes through other chemical reactions and eventually falls to the earth as sulfuric acid in rain. But, during the time that the sulfur pollution sits in the air, it does serve as a kind of insulation from the heat of the sun.
Ironically, as the world reduces coal burning to curb the carbon dioxide emissions that cause global warming, we’ll also be eliminating the sulfur dioxide emissions that mask some of that warming.
“Sulfur pollution that’s coming out of smokestacks right now is masking between a third and a half of the heating signal from the greenhouse gases humans have already emitted into the atmosphere,” Parson said.
In other words, we’ve been doing one form of sunlight reflection for decades already, but in an uncontrolled fashion with terrible warming effects, explains Kelly Wanser, the executive director of SilverLining, an organization promoting research and governance of climate interventions.
“This isn’t something totally new and Frankenstein — we’re already doing it; we’re doing it in the most dirty, unplanned way you could possibly do it, and we don’t understand what we’re doing,” Wanser told CNBC.
Spraying sulfur in the stratosphere is not the only way of manipulating the amount of sunlight that gets to the earth, and some say it’s not the best option.
“Sulfur dioxide is likely not the best aerosol and is by no means the only technique for this. Cloud brightening is a very promising technique as well, for example,” Sacca told CNBC.
Marine cloud brightening involves increasing the reflectivity of clouds that are relatively close to the surface of the ocean with techniques like spraying sea salt crystals into the air. Marine cloud brightening generally gets less attention than stratospheric aerosol injection because it affects a half dozen to a few dozen miles and would potentially only last hours to days, Parson told CNBC.
Cirrus cloud thinning, the third category addressed in the 2021 report from the National Academies, involves thinning mid-level clouds, between 3.7 and 8.1 miles high, to allow heat to escape from the surface of the earth. It is not technically part of the “solar geoengineering” umbrella category because it does not involve reflecting sunlight, but instead involves increasing the release of thermal radiation.
Known risks to people and the environment
There are significant and well-known risks to some of these techniques — sulfur dioxide aerosol injection in particular.
First, spraying sulfur into the atmosphere will “mess with the ozone chemistry in a way that might delay the recovery of the ozone layer,” Parson told CNBC.
The Montreal Protocol adopted on September 16, 1987, regulates and phases out the use of ozone depleting substances, such as hydrochlorofluorocarbons (HCFCs) which were commonly used in refrigeration and air conditioners, but that healing process is still ongoing.
Also, sulfates injected into the atmosphere eventually come down as acid rain, which affects soil, water reservoirs, and local ecosystems.
Thirdly, the sulfur in the atmosphere forms very fine particulates that cause respiratory illness.
The question, then, is whether these known effects are more or less harmful than the warming they would offset.
“Yes, damaging the ozone is bad, acid deposition is bad, respiratory illness is bad, absolutely. And spraying sulfur in the stratosphere would contribute in the bad direction to all of those effects,” Parson told CNBC. “But you also have to ask, how much and relative to what?”
The sulfur already being emitted from the burning of fossil fuels is already causing environmental damage and is already killing between 10 and 20 million people a year due to respiratory illness, said Parson. “So that’s the way we live already,” he said.
Meanwhile, “the world is getting hotter, and there will be catastrophic impacts for many people in the world,” said Pasztor.
“There’s already too much carbon out there. And even if you stop all emissions today, the global temperature will still be high and will remain high for hundreds of years. So that’s why scientists are saying maybe we need something else, in addition — not instead of — but maybe in addition to everything else that is being done,” he said. “The current action/non action of countries collectively — we are committing millions of people to death. That’s what we’re doing.”
For sunlight reflection technology to become a tool in the climate change mitigation toolbox, awareness among the public and lawmakers has to grow slowly and steadily, according to Tyler Felgenhauer, a researcher at Duke University who studies public policy and risk.
“If it is to rise onto the agenda, it’ll be kind of an evolutionary development where more and more environmental groups are willing to state publicly that they’re for research,” Felgenhauer told CNBC. “We’re arguing it’s not going to be some sort of one big, bad climate event that makes us all suddenly adopt or be open to solar geoengineering — there will be more of a gradual process.”
A man waits for customers displaying fans at his store amid rising temperatures in New Delhi on May 27, 2020. – India is wilting under a heatwave, with the temperature in places reaching 50 degrees Celsius (122 degrees Fahrenheit) and the capital enduring its hottest May day in nearly two decades.
Jewel Samad | Afp | Getty Images
Research it now or be caught off guard later?
Some environmentalists consider sunlight relfection a “moral hazard,” because it offers a relatively easy and inexpensive alternative to doing the work of reducing emissions.
One experiment to study stratospheric aerosols by the Keutsch Group at Harvard was called off in 2021 due to opposition. The experiment would have “threaten the reputation and credibility of the climate leadership Sweden wants and must pursue as the only way to deal effectively with the climate crisis: powerful measures for a rapid and just transition to zero emission societies, 100% renewable energy and shutdown of the fossil fuel industry,” an open letter from opponents said.
But proponents insist that researching sunlight modification technologies should not preclude emissions reduction work.
“Even the people like me who think it’s very important to do research on these things and to develop the capabilities all agree that the urgent top priority for managing climate change is cutting emissions,” Parson told CNBC.
Keith of Harvard agrees. His goal is “simply that we learn more and develop better mechanism[s] for governance,” he told CNBC.
Doing research is also important because many onlookers expect that some country, facing an unprecedented climate disaster, will act unilaterally to will try some version of sunlight modification anyway — even if it hasn’t been carefully studied.
“In my opinion, it’s more than 90 percent likely that within the next 20 years, some major nation wants to do this,” Parson said.
Sacca put the odds even higher.
“The odds are 100 percent that some country pursues sunlight reflection, particularly in the wake of seeing millions of their citizens die from extreme weather,” Sacca told CNBC. “The world will not stand idly by and leaders will feel compelled to take action. Our only hope is that by doing the research now, and in public, the world can collaboratively understand the upsides and best methods for any future project.”
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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