You’re out of free articles.
Log in
To continue reading, log in to your account.
Create a Free Account
To unlock more free articles, please create a free account.
Sign In or Create an Account.
By continuing, you agree to the Terms of Service and acknowledge our Privacy Policy
Welcome to Heatmap
Thank you for registering with Heatmap. Climate change is one of the greatest challenges of our lives, a force reshaping our economy, our politics, and our culture. We hope to be your trusted, friendly, and insightful guide to that transformation. Please enjoy your free articles. You can check your profile here .
subscribe to get Unlimited access
Offer for a Heatmap News Unlimited Access subscription; please note that your subscription will renew automatically unless you cancel prior to renewal. Cancellation takes effect at the end of your current billing period. We will let you know in advance of any price changes. Taxes may apply. Offer terms are subject to change.
Subscribe to get unlimited Access
Hey, you are out of free articles but you are only a few clicks away from full access. Subscribe below and take advantage of our introductory offer.
subscribe to get Unlimited access
Offer for a Heatmap News Unlimited Access subscription; please note that your subscription will renew automatically unless you cancel prior to renewal. Cancellation takes effect at the end of your current billing period. We will let you know in advance of any price changes. Taxes may apply. Offer terms are subject to change.
Create Your Account
Please Enter Your Password
Forgot your password?
Please enter the email address you use for your account so we can send you a link to reset your password:
Spoiler: None of them feels great.
“Delete, delete, delete,” Elon Musk reportedly told his biographer, Walter Isaacson, describing his approach to management. “Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn't delete enough.”
Musk has taken his own advice: He is slicing to the bone. Earlier this week, he dismissed the head of Tesla’s Supercharger network, Rebecca Tinucci, as well as her more than 500-person team. As of today, Tesla has only a barebones crew, at best, tasked with maintaining and expanding its high-speed car charging network. It has already pulled out of a planned expansion in New York City.
Musk also laid off what remained of the company’s policy and new vehicle teams. These severe cuts follow layoffs announced in March, when Musk dismissed about 10% of Tesla’s employees. According to Electrek, the two events may be related: Musk asked Tinucci to make deeper cuts in her team in April, she pushed back, and he fired her to set an example. The company has cut more than 14,000 employees worldwide since the beginning of the year.
The news is — and there is no way of sugarcoating this — either sort of stupid, bad, or very bad for the electric vehicle transition. Here are three ways of looking at it:
Over the past year, every other major automaker in the United States has switched to Tesla’s charging plug, the North American Charging Standard, or NACS. They have struck deals that will let them use much of Tesla’s existing Supercharger network; Ford is in the process of mailing its drivers a free NACs adapter plug. These agreements were meant to give consumers more certainty about the EV transition: No matter what car they bought, they would be able to use most of Tesla’s superior charging network.
Now, that certainty is gone. Which chargers will work in the future? How much more will the Tesla network expand? And what will happen to those deals with automakers now that the Supercharger team is gone? The employees laid off this week included those who worked closely with other companies.
At least publicly, Ford is keeping its cool. “Our plans for our customers do not change,” Marty Günsberg, communications director for Ford’s electric vehicle division, told Heatmap. And yet contractors and others with business in front of Tesla's charging team were left completely in the dark Tuesday, their emails bouncing back from addresses that no longer existed, according to E&E News. No other equivalent charging network exists in the U.S., meaning there's no other easy place for them to go.
Musk, for his part, has intimated that the company will begin to look into wireless charging. Although wireless charging may make slightly more sense for self-driving cars — the car could drive itself into a given spot, et voilà! — it is a puzzling decision from a man who has said the only real constraints are those imposed by the laws of physics. More than half of current and prospective EV owners say that they worry about charger availability and convenience, yet wireless charging is slower and less efficient than wired charging, meaning it will require more charging spots and each vehicle will have to stay there longer.
So again we must ask, why? The answer may lie in the animal spirits of the market — and Elon’s dependence on the market for his personal wealth. Tesla’s stock has more or less held steady since the cuts. As my colleague Matthew Zeitlin wrote, Musk has spun the layoffs as part of a corporate turn away from selling electric vehicles, chargers, and home batteries and toward achieving artificial intelligence and autonomous driving.
That is partly because Musk must keep justifying — or, if we really want to be blunt, propping up — Tesla’s astronomical share price, which itself is premised on the idea that Tesla is a technology company, not a car company. In order to do that, he must continually steer his sometimes-profitable company toward the buzziest, most hyped-up phenomenon in the economy. Never mind his actually existing EV charger business; that can’t justify the fantasy of the share price. He needs to find something new.
One of the more useful ways of understanding Elon Musk is that he seeks to create and control private infrastructure. SpaceX creates privatized access to rocket launches. Starlink allows for privatized access to the global, satellite-provided internet. The Hyperloop — to the degree that it existed at all — sought to create a privatized and individualized form of mass transit. (Musk, fittingly, hates public transit.) Even Musk’s purchase of Twitter, now rechristened X, reflected a desire to enclose the public sphere.
And for the past year, you could understand Tesla in the same light. Sure, Tesla was an electric vehicle company. But it was rapidly becoming an infrastructure company. Through its deals with other automakers, it was cementing itself as the premier provider of electric vehicle charging in the United States. It was also the part of the company that elicited the least suspicion from Tesla’s many critics. Drivers might not always be able to rely on a third-party charger, but a Tesla Supercharger? It worked.
It hasn’t always been this way. For years, the Supercharger network seemed like Tesla’s key competitive advantage, its Warren Buffett-style moat. If you wanted access to America’s most famous and reliable fast-charging network, you had to buy a Tesla. But starting with Ford a year ago, Musk struck deals with other automakers allowing their cars to use some of its charger network. At the same time, Tesla also bowed to federal pressure and standardized its NACS charger with SAE International. That helped it win more than $17 million in grants from the Bipartisan Infrastructure Law to build even more chargers.
Why pull back now? None of the options is very encouraging. The most hopeful answer is Tesla-specific: Maybe demand for the automaker’s vehicles is sinking so quickly that Musk is, in essence, reaching for things he can throw overboard. Tesla has historically relied on Chinese consumers to buoy its sales, but it has hemorrhaged market share in China as the country’s home-grown automakers have come out with newer and often superior EVs. But things there took a turn for the better earlier this week as Musk won approval (albeit conditional) to use Tesla’s so-called Full Self-Driving software on Chinese roads. And even if a sales slump were the explanation, why also ditch the team working on new vehicles at Tesla?
The other possibilities are bleaker. BloombergNEF has ballparked that Tesla’s charging business could generate $740 million in annual profits by 2030. But that relies on Musk’s estimate that the Supercharging business has a 10% margin. If that margin has since shrunk — or if its chargers just aren’t getting used as much as Tesla once anticipated — then further investment right now might not make sense.
That’s a problem, though, as most prospective buyers say that there need to be even more public chargers before they would consider buying an EV. If the economics don’t justify a further investment in chargers, however, even with all that apparently pent up demand, then the country is in a pickle. In that case, Musk’s decision looks self-defeating, a panicky and downturn-averse reaction that will ultimately undercut the market for Tesla’s cars.
About the only bright spot here is that Musk has surrendered hundreds of the most talented charging employees to the market. Tesla excelled at using a mix of policy and engineering prowess to integrate their chargers into local utilities’ systems and rate structures; other automakers can now snap up the people with those skills.
Log in
To continue reading, log in to your account.
Create a Free Account
To unlock more free articles, please create a free account.
Why the new “reasoning” models might gobble up more electricity — at least in the short term
What happens when artificial intelligence takes some time to think?
The newest set of models from OpenAI, o1-mini and o1-preview, exhibit more “reasoning” than existing large language models and associated interfaces, which spit out answers to prompts almost instantaneously.
Instead, the new model will sometimes “think” for as long as a minute or two. “Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes,” OpenAI announced in a blog post last week. The company said these models perform better than their existing ones on some tasks, especially related to math and science. “This is a significant advancement and represents a new level of AI capability,” the company said.
But is it also a significant advancement in energy usage?
In the short run at least, almost certainly, as spending more time “thinking” and generating more text will require more computing power. As Erik Johannes Husom, a researcher at SINTEF Digital, a Norwegian research organization, told me, “It looks like we’re going to get another acceleration of generative AI’s carbon footprint.”
Discussion of energy use and large language models has been dominated by the gargantuan requirements for “training,” essentially running a massive set of equations through a corpus of text from the internet. This requires hardware on the scale of tens of thousands of graphical processing units and an estimated 50 gigawatt-hours of electricity to run.
Training GPT-4 cost “more than” $100 million OpenAI chief executive Sam Altman has said; the next generation models will likely cost around $1 billion, according to Anthropic chief executive Dario Amodei, a figure that might balloon to $100 billion for further generation models, according to Oracle founder Larry Ellison.
While a huge portion of these costs are hardware, the energy consumption is considerable as well. (Meta reported that when training its Llama 3 models, power would sometimes fluctuate by “tens of megawatts,” enough to power thousands of homes). It’s no wonder that OpenAI’s chief executive Sam Altman has put hundreds of millions of dollars into a fusion company.
But the models are not simply trained, they're used out in the world, generating outputs (think of what ChatGPT spits back at you). This process tends to be comparable to other common activities like streaming Netflix or using a lightbulb. This can be done with different hardware and the process is more distributed and less energy intensive.
As large language models are being developed, most computational power — and therefore most electricity — is used on training, Charlie Snell, a PhD student at University of California at Berkeley who studies artificial intelligence, told me. “For a long time training was the dominant term in computing because people weren’t using models much.” But as these models become more popular, that balance could shift.
“There will be a tipping point depending on the user load, when the total energy consumed by the inference requests is larger than the training,” said Jovan Stojkovic, a graduate student at the University of Illinois who has written about optimizing inference in large language models.
And these new reasoning models could bring that tipping point forward because of how computationally intensive they are.
“The more output a model produces, the more computations it has performed. So, long chain-of-thoughts leads to more energy consumption,” Husom of SINTEF Digital told me.
OpenAI staffers have been downright enthusiastic about the possibilities of having more time to think, seeing it as another breakthrough in artificial intelligence that could lead to subsequent breakthroughs on a range of scientific and mathematical problems. “o1 thinks for seconds, but we aim for future versions to think for hours, days, even weeks. Inference costs will be higher, but what cost would you pay for a new cancer drug? For breakthrough batteries? For a proof of the Riemann Hypothesis? AI can be more than chatbots,” OpenAI researcher Noam Brown tweeted.
But those “hours, days, even weeks” will mean more computation and “there is no doubt that the increased performance requires a lot of computation,” Husom said, along with more carbon emissions.
But Snell told me that might not be the end of the story. It’s possible that over the long term, the overall computing demands for constructing and operating large language models will remain fixed or possibly even decline.
While “the default is that as capabilities increase, demand will increase and there will be more inference,” Snell told me, “maybe we can squeeze reasoning capability into a small model ... Maybe we spend more on inference but it’s a much smaller model.”
OpenAI hints at this possibility, describing their o1-mini as “a smaller model optimized for STEM reasoning,” in contrast to other, larger models that “are pre-trained on vast datasets” and “have broad world knowledge,” which can make them “expensive and slow for real-world applications.” OpenAI is suggesting that a model can know less but think more and deliver comparable or better results to larger models — which might mean more efficient and less energy hungry large language models.
In short, thinking might use less brain power than remembering, even if you think for a very long time.
On Azerbaijan’s plans, offshore wind auctions, and solar jobs
Current conditions: Thousands of firefighters are battling raging blazes in Portugal • Shanghai could be hit by another typhoon this week • More than 18 inches of rain fell in less than 24 hours in Carolina Beach, which forecasters say is a one-in-a-thousand-year event.
Azerbaijan, the host of this year’s COP29, today put forward a list of “non-negotiated” initiatives for the November climate summit that will “supplement” the official mandated program. The action plan includes the creation of a new “Climate Finance Action Fun” that will take (voluntary) contributions from fossil fuel producing countries, a call for increasing battery storage capacity, an appeal for a global “truce” during the event, and a declaration aimed at curbing methane emissions from waste (which the Financial Times noted is “only the third most common man-made source of methane, after the energy and agricultural sectors”). The plan makes no mention of furthering efforts to phase out fossil fuels in the energy system.
The Interior Department set a date for an offshore wind energy lease sale in the Gulf of Maine, an area which the government sees as suitable for developing floating offshore wind technology. The auction will take place on October 29 and cover eight areas on the Outer Continental Shelf off Massachusetts, New Hampshire, and Maine. The area could provide 13 gigawatts of offshore wind energy, if fully developed. The Biden administration has a goal of installing 30 GW of offshore wind by 2030, and has approved about half that amount so far. The DOI’s terms and conditions for the October lease sale include “stipulations designed to promote the development of a robust domestic U.S. supply chain for floating wind.” Floating offshore wind turbines can be deployed in much deeper waters than traditional offshore projects, and could therefore unlock large areas for clean power generation. Last month the government gave the green light for researchers to study floating turbines in the Gulf of Maine.
In other wind news, BP is selling its U.S. onshore wind business, bp Wind Energy. The firm’s 10 wind farm projects have a total generating capacity of 1.3 gigawatts and analysts think they could be worth $2 billion. When it comes to renewables, the fossil fuel giant said it is focusing on investing in solar growth, and onshore wind is “not aligned” with those plans.
The number of jobs in the U.S. solar industry last year grew to 279,447, up 6% from 2022, according to a new report from the nonprofit Interstate Renewable Energy Council. Utility-scale solar added 1,888 jobs in 2023, a 6.8% increase and a nice rebound from 2022, when the utility-scale solar market recorded a loss in jobs. The report warns that we might not see the same kind of growth for solar jobs in 2024, though. Residential installations have dropped, and large utility-scale projects are struggling with grid connection. The report’s authors also note that as the industry grows, it faces a shortage of skilled workers.
Interstate Renewable Energy Council
Most employers reported that hiring qualified solar workers was difficult, especially in installation and project development. “It’s difficult because our projects are built in very rural areas where there just aren't a lot of people,” one interviewee who works at a utility-scale solar firm said. “We strive to hire as many local people as possible because we want local communities to feel the economic impact or benefit from our projects. So in some communities where we go, it is difficult to find local people that are skilled and can perform the work.”
The torrential rain that has battered central Europe is tapering off a bit, but the danger of rising water remains. “The massive amounts of rain that fell is now working its way through the river systems and we are starting to see flooding in areas that avoided the worst of the rain,” BBC meteorologist Matt Taylor explained. The Polish city of Nysa told its 44,000 residents to leave yesterday as water rose. In the Czech Republic, 70% of the town of Litovel was submerged in 3 feet of flooding. The death toll from the disaster has risen to 18. Now the forecast is calling for heavy rain in Italy. “The catastrophic rainfall hitting central Europe is exactly what scientists expect with climate change,” Joyce Kimutai, a climate scientist with Imperial College London’s Grantham Institute, toldThe Guardian.
A recent study examining the effects of London’s ultra-low emissions zone on how students get to school found that a year after the rules came into effect, many students had switched to walking, biking, or taking public transport instead of being driven in private vehicles.
Welcome to Decarbonize Your Life, Heatmap’s special report that aims to help you make decisions in your own life that are better for the climate, better for you, and better for the world we all live in. This is our attempt, in other words, to assist you in living something like a normal life while also making progress in the fight against climate change.
That means making smarter and more informed decisions about how climate change affects your life — and about how your life affects climate change. The point is not what you shouldn’t do (although there is some of that). It’s about what you should do to exert the most leverage on the global economic system and, hopefully, nudge things toward decarbonization just a little bit faster.
We certainly think we’ve hit upon a better way to think about climate action, but you don’t have to take our word for it. Keep reading here for more on how (and why) we think about decarbonizing your life — or just skip ahead to our recommendations, below.