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Five years ago, the world met the Model Y. Tesla officially unveiled its smaller crossover in March 2019 and, the next year, began to sell the car in staggering numbers. The Model Y helped Tesla tighten its grip on the electric vehicle market. By 2023 it had displaced the Toyota Corolla as the world’s best-selling car of any kind.
It’s not easy to follow up a massive success. What’s worse is having no plan at all — or being chronically unable to stick to one. That’s where Tesla seems to be amid yet another shakeup at the company.
This week, Tesla announced it would lay off 10% of its worldwide staff, while some influential leaders are leaving of their own accord. The news comes as Tesla has just announced a sales dip and prognosticators wonder whether we’re entering an “EV winter” where more buyers choose hybrids instead. Now, this is neither the first time Tesla has run into difficulty nor the first time the EV maker has commenced mass layoffs to cut costs. Somehow, though, this time feels different.
During the Model’s Y’s ascendance over the past half-decade, Tesla’s path forward to the next thing has turned into a mess of distractions and left turns. Musk became obsessed with and then purchased Twitter, a boondoggle of a deal that clearly distracted him from his car company. The oft-touted Roadster supercar has yet to materialize.
More importantly, the long-promised $25,000 car appears to be dead (or at least tabled indefinitely). Musk had initially indicated the affordable Tesla would finally arrive next year, leaving the company to endure a single gap year without a new vehicle. But Reuters reported that Tesla has killed the idea in part because of competition overseas from ultra-cheap Chinese EVs, and while Musk responded to the report by saying Reuters was “lying,” he’s done nothing to indicate the “Model 2” is anything but dead.
Meanwhile, the only new-ish vehicle in the Tesla lineup, the Cybertruck, is stuck. Tesla stopped deliveries of the steel beast for an unknown issue, rumored to be related to sticky accelerator problems, and shortened production shifts at the factory. And while it’s possible to squint and see a case for the Cybertruck, I’ve written here numerous times that Tesla’s big mistake wasn’t putting that eyesore on the road. Instead, it was focusing the company’s attention on something so adolescent and absurd at a moment when it could have tightened its grip on the EV market, and given American EV drivers some interesting new options, by rolling out new cars that look more like something the average American would want to buy.
So what is Tesla up to? In a follow-up tweet after he attacked Reuters, Musk suddenly announced that he would reveal the company’s “robotaxi” on August 8. This would be Tesla’s completely self-driven vehicle. Musk’s favorite claim about the car is that it would earn its owners passive income by driving itself around, picking up and dropping off passengers as a kind of dystopian Uber.
The dream certainly fits in with Musk’s oeuvre. The CEO clearly still sees Tesla as a lean startup that moves fast and breaks things, not an established car company that would do something so expected and bland as building a perfectly acceptable three-row family crossover to compete with the Kia EV9. Compare that to the way other companies born of Silicon Valley began to act once they got big. Apple may have engaged in a long, fruitless dalliance with the self-driving car, but ultimately, it knows its bread is buttered by iterating on everything in the iPhone ecosystem. Facebook may have changed its name to Meta to highlight its mission to create the metaverse, but it still leaned into the revenue engines it built or acquired, like Instagram or Whatsapp.
It’s fine to tell yourself a story about who you want to be. And to give Tesla the benefit of the doubt for a moment: sure, maybe it will be the one to crack full autonomous driving. But in practical terms, that tech is not close to reality, and Tesla’s version of it has encountered its fair share of bugs and been sued over crashes.
(In the spirit of “robotaxi,” the company just offered a month-long free trial of Full Self Driving to Tesla drivers. I will certainly not be using it with a young child in the car. The brand has also mandated that potential drivers be given a demo of FSD during test-drives, seemingly to hammer home the idea that Tesla is just a few steps away from having the car drive you home while you take a nap.)
In the meantime, you have to wonder just what Tesla is going to sell to humans who want a plain old electric car. It recently completed a refresh for the Model 3, and while the new one looks a little like next year’s iPhone — the same product with a facelift and a couple new features — you’d expect to see a similar update coming to the Model Y.
It’s important to remember: Despite the ill wishes from his online haters, Musk isn’t exactly dead in the water. Tesla sold 220,000 Model 3s in America last year and nearly 400,000 Model Ys, a huge lead over competitor EV from legacy car brands. Those companies are hitting the same EV headwinds as Tesla this year, while golden child Rivian is still at least a couple of years away from selling its exciting smaller SUVs. Tesla is the established giant in electric cars, even as it looks in the mirror and sees an upstart.
Yet with Cybertruck landing with a thud, and no obvious follow-up in the works, Tesla is in danger of blowing that huge lead. It may want to transform into a software company, and to earn back some of Musk’s Iron Man sci-fi cred by realizing the self-driving car. But at this moment, it feels a little like an electric car company that forgot it makes cars.
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The data center boom is everywhere you look in U.S. economic and emissions data.
This is an edition of Heatmap Daily, an evening review of the day’s news written by our executive editor. Sign up for it here.
It isn’t exactly a new thought, but I’ve been struck recently by how many trends in America’s economic and environmental data are fundamentally about the data center boom and the return of electricity demand:
First, the Energy Information Administration reported this week that U.S. emissions grew by more than 2% last year, driven by surging electricity demand and an increase in coal-fired generation. What caused that higher power demand? New factories and data centers — as well as record summertime cooling demand.
Second, many of the new factories driving that higher power demand are themselves producing goods that are … let’s say … data center-adjacent. There are the enormous new semiconductor fabs, of course. But Ford and General Motors have also set up new production lines (or repurposed old ones) to manufacture grid-scale batteries to meet power demand.
Third, take a look at the recent U.S. spending on private non-residential construction — in other words, everything American companies are building that is not houses, condos, or apartments.
The construction industry’s spent almost $60 billion on data centers over the past year, which is more than it spent on all other office buildings combined (and more than it spent building warehouses, too). Just a handful of categories — data centers, power plants, electricity infrastructure, and certain kinds of electronics manufacturing — now make up a third of all U.S. private non-residential construction investment. They’ve never made up such a large share of construction spending since data collection began in 2014.
As The New York Times recently noted, the American economy is unusually dependent on the American stock market right now — and the stock market is unusually dependent on artificial intelligence. This week, investors started to balk at the enormous spending hyperscalers are planning to keep building out the AI boom; Alphabet’s shares dropped 8% this week after it boosted its planned 2026 capital expenditure and signaled 2027 will be even bigger. If the data center boom started to slow down in earnest, then more than just that budget will change.
Speaking of which, my colleague Emily Pontecorvo wrote earlier this week about how many businesses are struggling to even estimate their carbon emissions from artificial intelligence. The carbon accounting startup Watershed recently unveiled a new formula to help companies get a sense of their AI-related emissions.
But even that formula is still limited by the amount of data hyperscalers publish — and they don’t publish that much. Google, for instance, is the only AI company that has (laudably) provided estimates of its emissions on a per-prompt basis. Yet no company has published its per-token emissions, or how emissions sync up with particular models or regions.
So Emily asked Google: Why aren’t you — or any other model provider — disclosing this kind of data yet?
The tech company didn’t get back to us until after we’d published Emily’s story. But its response was interesting enough that I wanted to quote some of it here.
The problem is “industry consensus,” Cooper Elsworth, a Google spokesperson, told us. “There is currently very little consensus on how to comprehensively and fairly measure the serving environmental impact of generative AI (such as text generation),” he wrote. “Without standardized, ‘apples-to-apples’ frameworks, it is difficult to compare different providers accurately.”
That’s partly because energy use — and emissions data — can vary from site to site and depend on “custom-built hardware, software compilers, and advanced inference techniques.” And he claimed Google doesn’t always have the measurement hardware in place to provide such specific estimates: “Providing precise, repeatable data requires highly advanced measurement infrastructure,” he said. “For example, software-based energy monitoring tools often suffer from sampling biases. For our study, we had to step away from top-down averages and directly measure actual energy at the physical power supply unit (PSU) level across our deployed fleet. Not all providers have the telemetry or data sets required to benchmark their operations at this level of granularity.”
Read Emily’s story to understand the other reasons why estimating — or even “guesstimating” — AI-related carbon emissions is so challenging.
A conversation with Emma Uridge of the Kansas Health Institute.
This week’s conversation is with Emma Uridge, analyst with the Kansas Health Institute. Uridge spent copious hours analyzing state and local laws on data center development to best understand how policymakers are responding to the potential environmental public health impacts of large AI infrastructure, including power and water. The report, which came out this week, also goes in depth into those health impacts. I reached out to her to discuss what she sees as must-watch territory for our readers on this emerging policy arena.
Our conversation was lightly edited for clarity.
What is actually being done on policy when it comes to data centers — beyond moratoria of course?
So first I’d like to just talk about the point of moratoria. It’s helpful to talk about how these policies emerge in the first place. One area where moratoria are helpful is when a data center is proposed but the county has no approach for how they’d like to potentially regulate them. That’s temporary, most of the time. It lets local governments conduct research on the various impacts and also negotiate community benefits, ones that can mitigate any potential negative impacts — like Lancaster Pennsylvania, which instituted a community benefit agreement that maximized the potential benefits of development while mitigating what large data centers can do. That agreement looked at capping municipal water use at 20,000 gallons per day and requiring 100% clean energy. It had financial penalties for non-compliance. The company also committed $20 million to their local economic development and clean energy fund. There are ways to negotiate with developers.
We also see amendments to existing zoning. Data center proposals are increasingly popping up in rural areas, many of which are unzoned, so there’s no way a county can negotiate unless there’s a moratorium in place.
Other policy solutions include different performance standards or requiring on-site renewable energy, like what Jefferson County, Missouri, looked at. Also setback requirements, mandatory noise buffers, ending by-right zoning.
Where are local governments getting ideas for regulating data centers?
A lot of the technical information comes from developers. That can in cases be seen as a biased source of information. I wouldn’t say there’s a dedicated group providing assistance to local governments when a project is proposed — which is a similar story to wind industry development, where we have only a handful of consultants who provide technical advice. It can be really helpful to get a multi-disciplinary approach to hearing information. It can be helpful to have the utility commission, public health folks, those in academia, as well as the developer.
As of right now, especially in rural areas, local governments have a hard task of balancing pushback while getting the most accurate, evidence-based, neutral information to make decisions. That balance can be contentious.
What is the federal government doing on data center policy? How is the Trump administration approaching it?
A few things there. In the early days, the drive was for AI expansion and to be competitive with foreign adversaries. Now due to the amount of public pushback in red and blue localities and a more cautious approach.
I’m not seeing a lot of actual policy movement at this time.
I know the EPA is looking at the chemicals used in cooling data centers because when that water is cycled through the system, some of it is discharged into the water system, so they’re looking at the Toxic Substances and Control Act for monitoring that.
How much of an impact does this minimal federal role have on industry behavior?
Y’know, this isn’t specific to data centers. This is true for all kinds of large-scale development: there’s a need to require some sort of federal monitoring and regulation.
That’s where I see an emerging role for public health. At the federal level, there could be policy movement towards requiring some sort of environmental monitoring at data centers to make sure they’re operating responsibility. Looking at specific water use relative to water availability and what happens when there’s a time of severe, persistent drought. With air quality too — we’ve seen areas where the grid isn’t as reliable so their diesel generators are kicking on more and affecting air quality for residents.
We’re just not seeing all of that right now. We need corporate disclosure.
What do you see as the most important public health impacts from data center development?
It varies by localities. The most discussed obviously is water usage. One thing I’d note about my conversations with folks enthusiastic around emerging tech is, there are still questions that need to be asked about the capacity of localities to support a data center. Like a small town in Kansas may only be using 40% of their water for their utility needs. If a data center came online, how much of that water goes to the data center?
One area underexplored within the public health discipline is energy poverty and energy security. The ability of a household to meet the needs of everything energy provides in our lives. It’s known we have an aging electric grid but we’re not talking enough about large-scale blackouts when the grid is not sufficient to support some of these new data centers.
Plus more of the week’s big development fights.
1. Laramie County, Wyoming — Meta is fighting the fine it received in the Cheyenne data center water pollution controversy, and the conflict between the tech giant and the city’s small board of public utilities is continuing to spill out into the public.
2. Niagara County, New York — This county just rejected a solar project’s highway work permits in a show of retaliation against the state’s Office of Renewable Energy Siting.
3. Barron County, Wisconsin — The anti-solar protest is the new campaign stop in deep red Wisconsin.
4. Chesapeake, Virginia — A large battery storage project on the Virginia coastline is on the rocks amidst rampant local opposition.
5. Lewis County, West Virginia — West Virginia is now a key battleground in the fight over transmission, as a line spanning all of West Virginia and Maryland — and cutting through Data Center Alley in Virginia — causes compounding consternation.