Exxon predicted global warming with remarkable accuracy years ago, study shows
Gas prices are displayed at an Exxon gas station on July 29, 2022 in Houston, Texas.
Brandon Bell | Getty Images
Three academics from Harvard and the University of Potsdam in Germany published a study in the journal Science on Thursday providing evidence that Exxon Mobil, the oil and gas behemoth with a current market capitalization of $466 billion, predicted global warming with incredible accuracy in a series of internal reports and messages starting in the 1970s.
“Specifically, what’s new here is that we put a number on – and paint a picture of – what Exxon knew and when,” said study co-author Geoffrey Supran, who worked as a research associate at Harvard when he did this work.
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“We now have airtight, unimpeachable evidence that ExxonMobil accurately predicted global warming years before it turned around and publicly attacked climate science and scientists. Our findings show that ExxonMobil’s public denial of climate science contradicted its own scientists’ data,” Supran told CNBC. “This corroborates and adds statistical precision to the prior conclusions of scholars, journalists, lawyers, and politicians.”
The phrase and hashtag “ExxonKnew” have become a rallying cry after previous reporting from Inside Climate News and others showing that Exxon publicly contradicted its own understanding of climate science.
Exxon Mobil says the “ExxonKnew” movement is a “coordinated campaign” working to “stigmatize” the oil company, “creating the false appearance that ExxonMobil has misrepresented its company research and investor disclosures on climate change to the public.”
Climate activists protest on the first day of the Exxon Mobil trial outside the New York State Supreme Court building on October 22, 2019 in New York City.
Angela Weiss | AFP | Getty Images
It all started with a tweet
The catalyst for the research was a viral tweet, Supran told CNBC.
Stefan Rahmstorf, a physics professor at the University of Potsdam, saw a global warming predictive chart from Exxon Mobil that Supran and Harvard professor Naomi Oreskes had previously discovered, and overlaid actual historical data on top of Exxon’s.
“The overlap was startling,” Supran said and when Rahmstorf blogged and tweeted about it, the results got a lot of attention, “by the standards of climate science on Twitter anyway,” Supran told CNBC.
The three academics then realized that the accuracy of Exxon’s climate’s projections hadn’t been formally studied, and teamed up to write this report. They were surprised to discover is the extent and accuracy of Exxon’s knowledge of climate science.
“It was startling to plot all of the company’s projections onto one graph and find them all line up so tightly around the real-world temperature rise that has ensued since their reports. That gave me pause, seeing quantitatively that Exxon didn’t just know some climate science, they helped advance it,” Supran told CNBC. “They didn’t just vaguely know ‘something’ about global warming decades ago, they knew as much as independent academic and government scientists did. Arguably, they knew all they needed to know.”
According to their research, the academics found that between 63% and 83% of the climate projections Exxon made were accurate in predicting future climate change and global warming. Exxon predicted that climate change would cause global warming of 0.20° ± 0.04 degrees Celsius per decade, which is the same as academic and governmental predictions that came out between 1970 and 2007.
The study in Science builds on work done by investigative journalists at Inside Climate News back in 2015 and Democratic lawmakers at the House Committee on Oversight and Reform, among many others.
Exxon continues to deny its wrongdoing.
“This issue has come up several times in recent years and, in each case, our answer is the same: those who talk about how ‘Exxon Knew’ are wrong in their conclusions,” Todd Spitler, spokesperson for Exxon Mobil, told CNBC.
Spitler pointed to the results of a 2019 case heard before the New York State Supreme Court by Judge Barry Ostrager which did not find the oil and gas company guilty of fraud in its climate change regulation accounting.
“What the evidence at trial revealed is that ExxonMobil executives and employees were uniformly committed to rigorously discharging their duties in the most comprehensive and meticulous manner possible,” Ostrager wrote, and Spitler passed along to CNBC. “The testimony of these witnesses demonstrated that ExxonMobil has a culture of disciplined analysis, planning, accounting, and reporting.”
Tesla has officially launched the Model YL, a new, larger Model Y with 6 seats, in China, and it starts at 339,000 Chinese Yuan, the equivalent of about $47,000 USD.
After a few weeks of teasing, Tesla has officially launched the new version of the Model Y on its online configurator in China:
The main things we didn’t know about the vehicle yet were the price and range. Those questions are now answered.
The Model YL starts at ¥339,000, equivalent to approximately $47,000 USD. It’s about $3,600 USD more expensive than the Model Y Long Range AWD in China.
It is rated with a range of 751 km (466 miles) based on the CLTC driving cycle, which typically yields a longer range than the WLTP and EPA standards.
For comparison, the larger version achieves roughly the same range as the smaller Model Y Long Range AWD, thanks to its larger battery pack.
Tesla has released new images of the new version of the Model Y:
Last month, the first specifications and dimensions were released, confirming a length of approximately 180mm (7 inches) longer, a height of about 24mm (1 inch) taller, and a wheelbase that is also 150mm (or approximately 6 inches) longer.
Now, Tesla has confirmed a few more features, including up to 2,539 liters of storage space and electric armrests in the second-row seats.
The automaker is guiding deliveries in September.
Electrek’s Take
The price is reasonable in comparison to Tesla’s current lineup, making the upgrade relatively affordable.
However, it is a lot more expensive than other 6-seater all-electric SUV options in China, such as the Onvo L90, which is about $8,000 cheaper.
I’m curious to see how it will be priced in North America, where I think it would be much more popular than in China.
Tesla needs to go downmarket to access a bigger market in China – not upmarket, but the new option is still a positive for the automaker.
If the pricing matches the one in China, it shouldn’t be much more than $51,000 in the US, which I think would make it a popular option.
However, I think it would be the end of the Model X.
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Environment
Analysts downplay AI bubble worries as Altman says some investors will be left ‘very burnt’
The artificial intelligence boom that Sam Altman helped ignite with ChatGPT in late 2022 is starting to make even him uneasy.
Startups with little more than a pitch deck are raising hundreds of millions. Valuations have become “insane.” Capital is chasing a “kernel of truth” with feverish speed.
The OpenAI CEO still believes the long-term societal upside of AI will outweigh the froth, and he’s ready to keep spending in pursuit of that goal.
“Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes,” he said at a recent dinner with reporters. “Is AI the most important thing to happen in a very long time? My opinion is also yes.”
He repeated the word ‘bubble‘ three times in 15 seconds, then half-joked, “I’m sure someone’s gonna write some sensational headline about that. I wish you wouldn’t, but that’s fine.”
While Altman warned that valuations are now out of control, he’s ready to shell out on more infrastructure.
“You should expect OpenAI to spend trillions of dollars on datacenter construction in the not very distant future,” Altman said. “And you should expect a bunch of economists wringing their hands, saying, ‘This is so crazy, it’s so reckless,’ and we’ll just be like, ‘You know what? Let us do our thing.'”
OpenAI is already looking beyond Microsoft Azure’s cloud capacity, and is shopping around for more.
The company signed a deal with Google Cloud this spring and, according to Altman, OpenAI is “beyond the compute demand” of what any one hyperscaler can offer.
“You should expect us to take as much compute as we can,” he added. “Our bet is, our demand is going to keep growing, our training needs are going to keep going, and we will spend maybe more aggressively than any company who’s ever spent on anything ahead of progress, because we just have this very deep belief in what we’re seeing.”
It’s not just OpenAI. All the megacaps are trying to keep up.
In their most recent earnings, tech’s biggest names all raised capital expenditure guidance to keep pace with AI demand: Microsoft is now targeting $120 billion in full-year capital expenditures, Amazon is topping $100 billion, Alphabet raised its forecast to $85 billion, and Meta lifted the high end of its capex range to $72 billion.
Wedbush’s Dan Ives said Monday on CNBC’s “Closing Bell” that demand for AI infrastructure has grown 30% to 40% in the last months, calling the capex surge a validation moment for the sector.
Ives acknowledged “some froth” in parts of the market, but said the AI revolution with autonomous is only starting to play out and we are in the “second inning of a nine-inning game.”
“The actual impact over the medium and long term is actually being underestimated,” he said.
Citi’s Rob Rowe, speaking Monday on CNBC’s “Money Movers,” pushed back on comparisons between today’s AI boom and the dotcom bubble.
“Back then, you had a lot of over-leveraged situations. You didn’t have a lot of companies that had earnings,” Rowe said. “Here you’re talking about companies that have very solid earnings, very strong cash flow, and they’re funding a lot of this growth through that cash flow. So in many respects, it’s a little different than that.”
He added that the current wave of AI investment is being driven by structural shifts in the global economy, particularly the rapid growth of digital services, which now account for a large share of global exports. Also unlike the dotcom cycle of the late 90s, companies today are funding their infrastructure spending with strong cash flow rather than relying on debt.
Still, concerns about overheating have been mounting.
Alibaba co-founder Joe Tsai pointed to worrying signs in the AI sector well before the hyperscalers raised their annual capex guidance during the latest earnings prints.
In March, he warned of a brewing AI bubble in the U.S.
Speaking at HSBC’s Global Investment Summit in Hong Kong, Tsai said he was astounded by the scale of datacenter spending under discussion. Tsai questioned whether hundreds of billions in spending is necessary, and flagged concern about companies starting to build datacenters “on spec,” without clear demand.
Altman, for his part, sees these cycles as part of the natural rhythm of technological progress.
The dotcom crash wiped out scores of companies, but still gave rise to the modern internet. He expects AI to follow a similar path: a few high-profile wipeouts, followed by a lasting transformation.
“I do think some investors are likely to get very burnt here, and that sucks. And I don’t want to minimize that,” he said. “But on the whole, it is my belief that… the value created by AI for society will be tremendous.”
WATCH: OpenAI staffer reportedly to sell $6 billion in stock to SoftBank and other investors
Waymo founder and former CEO John Krafcik is a critic of Tesla’s approach to self-driving, and he has so far accurately predicted the rollout of the “Robotaxi” service.
He is now taking another dig at Tesla.
Krafcik is a highly respected leader in the auto industry. He began his career as a mechanical engineer at the NUMMI plant, which was then a joint GM-Toyota factory, but is now owned by Tesla.
He spent 14 years at Ford, where he was chief engineer of the Ford Expedition and Lincoln Navigator, a very successful vehicle program. He then moved to Hyundai America, where he served as President for five years.
However, Krafcik is best known for leading Waymo from 2015 to 2021, helping it become the consensus leader in self-driving technology.
Ahead of Tesla’s rollout of its so-called “Robotaxi” service in Austin in June, Krafcik suggested that Tesla could fake the service:
“There are many ways to fake a robotaxi service.”
He wasn’t exactly wrong.
There’s a Tesla employee in the front seat of every “Robotaxi” in the fleet, which is only about a dozen vehicles, based on crowdsource data, which is the only data available, as Tesla doesn’t release any.
Those supervisors in the front seat have their fingers on a kill switch ready to stop the vehicle at all times, and there are many examples of them intervening to prevent accidents or traffic violations.
In new comments (via Business Insider), Krafcik makes it clear that he doesn’t consider this to be a “robotaxi” service:
“Please let me know when Tesla launches a robotaxi — I’m still waiting. It’s (rather obviously) not a robotaxi if there’s an employee inside the car.”
More recently, Tesla expanded its “Robotaxi” service area to the Bay Area in California, but it again has an employee in the car, this time in the driver’s seat.
Krafcik commented:
“If they were striving to re-create today’s Bay Area Uber experience, looks like they’ve absolutely nailed it.”
He continued:
“I think the AV industry would be delighted if Tesla followed Waymo’s approach to launch a robotaxi service, but they are not doing that.”
Furthermore, Tesla has been limiting access to “invite-only” and the invites have been primarily going to Tesla influencers and investors who are rarely critical of the company.
CEO Elon Musk has been discussing “opening up” the service in Austin to the public next month, but it appears that Tesla will need to retain the in-car supervisor for the foreseeable future.
Electrek’s Take
It must be a bit frustrating for Waymo, which has deployed an actual robotaxi service for years, to see Tesla calling this a robotaxi.
When Waymo was using in-car “safety drivers’, it didn’t call its service “robotaxi.” It was obviously in the testing phase.
If Tesla were to remove the safety drivers, which I suggest they don’t, based on the current disengagement rate of FSD and the interventions we have seen from supervisors in the currently minimal “Robotaxi” service in Austin, it would officially be about 5 years behind Waymo.
The argument that Tesla will magically scale faster because they don’t use lidar should be retired, as the goal should be the safest, not the fastest, at scaling.
And when it comes to scaling, Tesla’s current bottleneck is safety. It needs to be safe enough to remove the safety supervisor, and it’s clearly not there yet.
I really don’t like Tesla’s approach. It seems to be more about optics than adopting a safe and transparent approach.
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