Humanoid robots are the blockchain of 2025

There are numerous reasons why a company will jump on a hype bubble. It tends to be good PR and projects an impression of forward thinking. Investors generally reward it and often punish companies that fail to jump on the bandwagon. Finally, CEOs are by no means immune to popular manias and fear of missing out; if anything, it's just the opposite.

The question that you need to keep asking yourself while reading any of these humanoid robot puff pieces (other than who stands to gain from another tech bubble) is: why bipedal? Wheels and treads are cheaper, simpler, more reliable, and generally more stable. If you do need to have a walking robot, it's generally best to go with: "Four legs good, two legs bad." Quadrupeds are simpler and more stable, which is probably why they have found their way into real-world applications while bipedal robots have not.

2025 Is the Year of the Humanoid Robot Factory Worker by Russell Brandom

Later this year, Boston Dynamics plans to put its all-electric humanoid Atlas robot to work in a Hyundai factory. The new version of the bot, evolved from the hydraulic Atlas model that’s been performing viral video demos since 2013, made its public debut last spring. But while the company’s dog-like Spot and warehouse robot Stretch are already deployed at industrial sites, the Hyundai pilot will be the first time Atlas is used in commercial manufacturing.

Boston Dynamics, which was acquired by Hyundai for $1.1 billion in 2021, is coy about how the robot will be used, but the general idea is that it’s designed to be stronger and more reliable than a human worker. “The robot is going to be able to do things that are difficult for humans,” Boston Dynamics spokesperson Kerri Neelon says. “Like pick up very heavy objects and carry things that are awkward for humans to carry.” [Doesn't the very fact that something is "awkward for humans to carry" suggest that a humanoid robot is not the way to go for that task? -- MP]

BD has great engineers and well-designed robots, but they (and Hyundai) have a huge incentive to see this hype bubble continue to inflate—both for the stock price and to promote their other, more useful robots.

 

Atlas will have friends: 2025 looks set to be the year that multipurpose humanoid robots, until now largely confined to research labs, go commercial. Some have already taken their first tentative robot steps into paid work, with Agility Robotics’ Digit moving items in a warehouse and Figure’s eponymous biped shipping out to commercial customers last year.

I'll try to comment on these in more detail later, but if you watch videos of Digit and Figure 02 working you'll notice three things:

1. There is no reason for them to be using legs rather than a cheaper and more efficient wheeled base.

2. They aren't doing anything all that impressive.

3. By comparison, the non-featured, non-humanoid robots seen in the background are really amazing.

Tech giants are also getting in on the trend: Both Apple and Meta are rumored to be working on some kind of consumer-facing humanoid robot. A 2024 Goldman Sachs report estimates that humanoid robots will represent a $38 billion market by 2035 —more than six times what the firm projected a year earlier.

Two things:

1. This is exactly what you'd expect in a bubble. Companies jumping on the bandwagon. Analysts suddenly pumping up their estimates in order to be part of the next big thing.

2.  Given the amounts being invested, that $38 billion market by 2035 (which is itself based on optimistic assumptions) doesn't seem like that big of a number, particularly with respect to Tesla, a company with a valuation of over one trillion dollars, much, possibly most of which is now based on the perceived potential of its robotics division.

The basic promise of humanoid robots is that they will be able to switch between multiple tasks, just like their human peers. It’s a fundamentally different approach from traditional assembly line automation, which builds an entire environment around the specific tasks required for manufacturing. Jonathan Hurst, cofounder and chief robot officer at Agility Robotics, expects its robots to sit alongside that process, not disrupt it.

For the 8,000th time... It has become embarrassingly commonplace to equate multipurpose robots with humanoids, despite the fact that there is absolutely no good reason— from an engineering or economic standpoint— to do so. In fact, it's just the opposite. There are any number of tasks that the human body is badly designed to tackle, including many—probably most—of those suggested for humanoid robots, such as the previously mentioned carrying of large, heavy packages.

“A purpose-built automation solution is always going to be higher performance and lower cost for that purpose,” Hurst says. “That’s great if you have 24/7 operations for that specific thing you want to do.” But for tasks that don’t need to run around the clock, a flexible robot could be more productive.

Hurst deserves credit for honesty here -- for a given task, purpose built will always be better and cheaper -- but he understates how small the segment of manufacturing labor is left, particularly once AI expands the number of tasks a purpose built robot can perform.

Coming to a vineyard near you...

When you get away from the humanoid personal robot bullshit, the real research is really cool.

Evan Ackerman writing for IEEE Spectrum:

 The robot itself is not that complicated, at least on the scale of how complicated robots usually are. It’s made up of a head with some sensors in it plus a handful of identical cable-connected segments, each with a couple of motors for leg actuation. On paper, this works out to be a lot of degrees of freedom, but you can get surprisingly good performance using relatively simple control techniques.

“Centipede robots, like snake robots, are basically swimmers,” Goldman says. The key difference is that adding legs expands the different kinds of environments through which swimming robots can move. The right pattern of lifting and lowering the legs generates a fluidlike thrust force that helps the robot to push off more stuff as it moves to make its motion more consistent and reliable. “We created a new kind of mechanism to take actuation away from the centerline of the robot to the sides, using cables back and forth,” says Goldman. “When you tune things properly, the robot goes from being stiff to unidirectionally compliant. And if you do that, what you find is almost like magic—this thing swims through arbitrarily complex environments with no brain power.” 

For real engineers, getting the same functionality with less complexity is a good thing.

The complex environments that the robot is designed for are agricultural. Think sensing and weed control in fields, but don’t think about gentle rolling hills lined with neat rows of crops. That kind of farming is very amenable to automation at scale, and there are plenty of robotics companies in that space already. Not all plants grow in well-kept rows on mostly flat ground, however: Perennial crops, where the plant itself sticks around and you harvest stuff off of it every year, can be much more complicated to manage. This is especially true for crops like wine grapes, which can grow on very steep and often rocky slopes. Those kinds of environments are an opportunity for GCR’s robots, offering an initial use case that brings the robot from academic curiosity to something with unique commercial potential.

...

According to GCR, there is currently no automated solution for weed control around scraggly bushy or vinelike plants (like blueberries or strawberries or grapes), and farmers can spend an enormous amount of money having humans crawl around under the plants to check health and pull weeds. GCR estimates that weed control for blueberries in California can run US $300 per acre or more, and strawberries are even worse, sometimes more than $1,000 per acre. It’s not a fun job, and it’s getting increasingly difficult to find humans willing to do it. For farmers who don’t want to spray pesticides, there aren’t a lot of good options, and GCR thinks that its robotic centipedes could fill that niche.

An obvious question with any novel robotic mobility system is whether you could accomplish basically the same thing with a system that’s much less novel. Like, quadrupeds are getting pretty good these days, why not just use one of them? Or a wheeled robot, for that matter? “We want to send the robot as close to the crops as possible,” says Goldman. “And we don’t want a bigger, clunkier machine to destroy those fields.” This gets back to the clutter problem: A robot large enough to ignore clutter could cause damage, and most robots small enough not to damage clutter become a nightmare of a control problem.

When most of the obstacles that robots encounter are at a comparable scale to themselves, control becomes very difficult. “The terrain reaction forces are almost impossible to predict,” explains Goldman, which means that the robot’s mobility regime gets dominated by environmental noise. One approach would be to try to model all of this noise and the resulting dynamics and implement some kind of control policy, but it turns out that there’s a much simpler strategy: more legs. “It’s possible to generate reliable motion without any sensing at all,” says Goldman, “if we have a lot of legs.” 

This strikes me as an example of what a robotics story should be. An intelligent discussion of engineering principles and challenges applied to a real world business problems. I ran it by some actual roboticists on BlueSky and they were all in agreement. Here's what one had to say. 

Exactly.

Build and optimize the automation against requirements that bring immediate wins.

Then, and only then, once perfected, perhaps look to expand the domain of that automation or build new automation structures around it.

Understand the SYSTEMS problem as you go along.

Best possible way.

And they're fun to watch (though the weed pulling mechanism still needs some work).

 

It's almost as if, bear with me here, it's more cost efficient to reduce the amount of carbon you're putting into the atmosphere than it is to try to capture it after the fact.

I keep being drawn toward the idea of using biochar to simultaneously dispose of forest waste in the West while also creating a carbon sink. Then I convinced myself it could never be scalable or cost effective. Then I read something like this and find myself coming back to it.

Bjartmar Oddur Þeyr Alexandersson and Valur Grettisson writing for Heimildin:

Climeworks in Iceland has only captured just over 2,400 carbon units since it began operations in the country in 2021, out of the twelve thousand units that company officials have repeatedly claimed the company’s machines can capture. This is confirmed by figures from the Finnish company Puro.Earth on the one hand and from the company’s annual accounts on the other. Climeworks has made international news for capturing carbon directly from the atmosphere. For this, the company uses large machines located in Hellisheiði, in South Iceland. They are said to have the capacity to collect four thousand tons of CO2 each year directly from the atmosphere.

According to data available to Heimildin, it is clear that this goal has never been achieved and that Climeworks does not capture enough carbon units to offset its own operations, emissions amounting to 1,700 tons of CO2 in 2023. The emissions that occur due to Climeworks' activities are therefore more than it captures. Since the company began capturing in Iceland, it has captured a maximum of one thousand tons of CO2 in one year.

...

 The Swiss founders of Climeworks were ambitious when they started in 2009. In a 2017 interview, they said that by 2025 they planned to capture one percent of all global emissions. That amounts to 400 million tons of CO2. Those plans have not been realised, and the company has never come close to achieving that. They also planned to reduce the cost of capturing each ton of CO2 from the atmosphere to about $100. Today, a ton of CO2 costs about $1,000, according to the Climeworks website – ten times more than the target this year.

Despite not achieving those goals, the company’s executives have set new, more ambitious goals. The company now says it plans to capture 1 billion tons of CO2 by 2050. Climeworks’ operations and ambitious goals have garnered worldwide attention, and the company recently ranked second on Time Magazine’s list of the 100 top green tech companies in the world. This is the first time Climeworks has made the list, but another unrelated company, which has operated in Iceland, made the list last year, Running Tide. [Completely fail to come anywhere close to your absurdly unrealistic goal. Deflect criticism by proposing an even less realistic one. (These guys haven't just been watching Elon; they've been taking notes.) -- MP]

...

Climeworks has sold a significant amount of carbon credits. They are not only credits that have already been certified and captured, but also a large amount of credits that Climeworks plans to capture in the future. According to the company, one third of all the credits that the Mammoth capture plant is expected to capture from the atmosphere over the next 25 years have already been sold. About 21 thousand people have a subscription with the company, where they pay monthly for the capture and disposal of carbon credits. The waiting time to receive these carbon credits can be up to six years, according to the company's terms. If Climeworks' capture figures do not improve, the wait could extend from years to decades.

...

Not only investors have financed the operation of Climeworks. Since the company was founded, it has received approval for over one hundred billion krónur in grants from public sources, as stated on the Climeworks website, including from Swiss and American taxpayers. The Swiss handed over $5 million to the company, while the US government has promised the company $625 million.

 

This all goes back to our ongoing techno-optimism thread. We have been fed the dogma of putting our faith into tech entrepreneurs, leaping off the cliff and trusting that a new innovation will miraculously appear to catch us. It has made us easy marks for con artists and charlatans.

 

Criticism vs. Reviews vs. Meta-Reviews vs. Non-reviews

As part of our ongoing thread on critics and reviewers, here are a couple of relevant and enjoyable videos from Bob Chipman. The first is a thoughtful video essay that uses the reaction to Marvel's The Eternals as a springboard to discuss the role of the critic and the economic realities of the job in the age of Rotten Tomatoes.




The second takes a slightly meta, but completely appropriate, approach to reviewing Morbius. I haven't seen Sony's notorious box office bomb, but I am still almost certain that this video is more entertaining.

More on humanoid robots -- who ya gonna believe?

According to Elon Musk (whose fortune now largely rests on the perceived earnings potential of robots and AI), humanoid robots that can immediately replace anyone doing manual labor is just around the proverbial corner. Emphasis added throughout.]

Speaking on Tuesday at the US-Saudi Investment Forum in Riyadh, the Tesla CEO predicted that humanoid robots could eventually number in the tens of billions, transforming the global economy.

"Everyone will want their personal robot," Musk said. "You can think of it like having your own personal C-3PO or R2-D2 — but even better," he said, referring to "Star Wars" characters.

With that scale of automation, Musk said productivity could soar and usher in what he called a "universal high income," where goods and services become so abundant that "no one wants for anything."

Musk has skin in the robot game. He called Tesla's humanoid Optimus potentially the "biggest product ever of any kind" during a launch event for its robotaxi last October.

 Musk has been making this sales pitch for months now.

"You can produce any product, provide any service," Musk said of humanoid robots. "There's really no limit to the economy at that point. You can make anything."

The billionaire said that money may not carry much value by then.

"Will money even be meaningful? I don't know; it might not be," he said, adding that robots could create a "universal high-income situation" because anyone will have the ability to make as many goods and services as they want.

Musk's bullishness on humanoid robots comes as no surprise. The CEO said during an earnings call on January 29 that Tesla will begin production of "several thousand" Optimus robots by the end of 2025.

"It's one of those things where I think, long term, Optimus has the potential to be north of $10 trillion in revenue," he said during the call. "Like, it's really bananas."

 

He also suggested his robots could provide "quasi-infinite products and services."

 On the other side, we have actual researchers (from NPR):

BRUMFIEL: I spoke to Ken Goldberg, a professor at the University of California at Berkeley. And he is pretty emphatic that AI-powered robots weren't here yet.

[AUDIO PLAYBACK]

KEN GOLDBERG: Robots are not going to suddenly become the science fiction dream overnight.

[END PLAYBACK]

BARBER: OK, so, like, tell me why because, like, AI chatbots have gotten, like, way better, super fast. So why are these robots getting stuck?

BRUMFIEL: Chatbots have a huge amount of data to learn from. They've taken basically the entire internet to train themselves how to write sentences and draw pictures. But Ken says--

[AUDIO PLAYBACK]

GOLDBERG: For robotics, there's nothing, right? There's no examples online of robot commands being generated in response to robot inputs.

[END PLAYBACK]

BRUMFIEL: And if robots really need as much training data as their virtual chatbot friends, then having humans teach them one task at a time is going to take a really long time.

BARBER: Oof.

GOLDBERG: You know, at this current rate, we're going to take 100,000 years to get that much data.

BARBER: What? OK, that's so long.

BRUMFIEL: [LAUGHS]

BARBER: Like, are there any alternatives? There must be.

BRUMFIEL: One might be to let the AI brain of the robot learn in a simulation. A researcher who's trying this is a guy named Pulkit Agrawal. He's at the Massachusetts Institute of Technology.

[AUDIO PLAYBACK]

PULKIT AGRAWAL: The power of simulation is that you can collect, you know, very large amounts of data. For example, in three hours', you know, worth of simulation, we can collect 100 days' worth of data.

[END PLAYBACK]

BARBER: Hm.

BRUMFIEL: So this is a really promising approach for some things, but it's much more of a challenge for others. So, for example, let's talk about walking. When you're just dealing with the Earth and your body, the physics of walking around, it's actually kind of simple. But if you want your robot to, say, try and pick up a mug off a desk or something, that's a lot more complicated.

BARBER: Mm, more forces.

[AUDIO PLAYBACK]

AGRAWAL: If you apply the wrong forces, these objects can fly away very quickly.

[END PLAYBACK]

BRUMFIEL: Basically, your robot will fling things across the room if it doesn't understand the weight and the size of what it's carrying. And there's more. You know, if your robot encounters anything that you haven't simulated 100% perfectly, then it won't know what to do. It'll just break.

BARBER: OK, so, Geoff, you've taken me from, like, optimist to pessimist. It's the you know, the road I take every day.

BRUMFIEL: [LAUGHS]

BARBER: I'm starting to think that AI is, like, never going to work that well in robots. Or, like, it's going to be a really long time.

BRUMFIEL: I'm sorry if I've, like, turned you into a pessimist here, Gina. And then I'm going to--

BARBER: It happens.

BRUMFIEL: --and then I'm going to have to sort of whipsaw you back. Because AI is already finding its way into robotics in ways that are really interesting. So, for example, Ken Goldberg has co-founded a package sorting company. And just this year, they started using AI image recognition to pick the best points for their robots to grab the packages.

BARBER: Ooh.

BRUMFIEL: And I think we're going to see a lot of that, AI being used for parts of the robotic problem, you know, walking, or vision, or whatever. It just may not arrive everywhere all at once.

Robotics is the future but in the foreseeable future, it's not going to be the kind of bipedal humanoid Swiss Army knife Tesla is supposed about to unveil. If there's a major breakthrough it could speed things up, but even under the best case scenario, serious people working in the field will tell you we're years, possibly decades away from the kind of functionality Elon is promising will be coming off the assembly line in six months.

 So who ya gonna believe? Well, if you're an investor...

 

 

 

 

 

 

 

Possible Papal Posts

 

 

 Anti-papal Catholics

I've been talking about this for years now, and I was sure that I had written numerous posts on the subject, but it turns out that, other than one unfinished piece in the draft folder, apparently I never wrote anything down, which is a shame because it's a topic worth talking about.

Everyone knows about Catholic leaders in the far right...

"I mean it's kind of jaw-dropping," Trump's former chief strategist Steve Bannon told the BBC on Friday, speaking of Leo's election.

"It is shocking to me that a guy could be selected to be the Pope that had had the Twitter feed and the statements he's had against American senior politicians," said Bannon, a hard-right Trump loyalist, practising Catholic and former altar boy.

... but I'm mainly interested in those at the bottom.
   
 If you were paying close attention, you might have spotted them before, but these anti-papal Catholics really became a thing during the first Trump Administration. They almost always had the same backstory. They got sucked into right-wing media's indoctrination process, initially attracted to what seemed a pro-Church message. Much as with secular evangelicals (whom we have discussed before), they came to define their faith on less and less spiritual terms. Under John Paul II, and even more importantly Benedict, there was little danger of cognitive dissonance. Opus Dei and Fox News are not at all strange bedfellows, but when the Jesuit-affiliated Francis took the office, the disconnect became obvious. And when the cult of personality formed around Trump, it became fairly common to see people who weren't just Catholic but who had built their entire identities around their religion openly choosing a purely secular (and often profane) political figure over their own Pope.

The "Trump effect"?

    It is unwise to draw inferences from an unequal data set of three, but in the course of a few days, we saw three striking examples of candidates perceived as anti-Trump figures winning elections they were favored to lose (or, in the case of Prevost, not even supposed to be in the running). In Canada and Australia, the ministers from the relatively pro-Trump parties who were expected to be the new prime ministers actually lost their seats. In the case of the conclave, this was a historically fast decision, suggesting that this was not a difficult choice for the College of Cardinals.

They did not see that coming

    One conclave story, mainly of interest to political scientists and statistics nerds (in other words, our readership), was how badly the prediction markets missed this. Prevost was a well-known figure in the Church, something of a protégé of Pope Francis, and a likely beneficiary of the previously mentioned pattern we’d seen in Canada and Australia. Though certainly a long shot, it was difficult to explain why he was showing up at less than half a percent in the betting markets, particularly given their historical tendency to greatly overvalue other long-shot candidates.

    This miss raises all sorts of interesting questions. One of the big arguments for wisdom-of-the-crowd-type approaches is that they can supposedly accurately assign weights to a range of information that would be difficult to incorporate into a traditional model. They should be able to do a reasonably good job even without having polling data. That doesn't seem to be the case here (they missed Francis too). How have prediction markets fared in other low-data, high-information situations?

Allison Morrow writing for CNN:

The conclave markets’ big miss this week reflects the limits of their predictive powers.

In sports betting, you’ve got thousands of data points about individual athletes, team stats going back decades and any number of informed opinions from professional commentators. Political winds can be volatile, but polling and voter data are practically endless at the national level.

In pope betting, the data are far more scarce.

“The papal conclave markets are one of the ones that you’d expect to be the least well-calibrated since they only get a data point every decade or two,” Eric Zitzewitz, professor of economics at Dartmouth College, told CNN. “And the process is much more opaque than almost any other political selection process… No tell-all memoirs, even well after the fact.”

Plenty of academics and journalists offered insights into who might be among the favorites based on their various CVs and reputations in the church. Pietro Parolin and Luis Antonio Tagle were among the favorites heading into the conclave on Wednesday. And, as election forecaster Nate Silver noted Friday, Parolin’s chances shot up as the white smoke emerged, “presumably on the assumption that the quick decision was good news for the frontrunners.”

Of course, the dynamics inside the Sistine Chapel were impossible for market participants to gauge from the outside. All any of us regular people could do was watch “Conclave” and, based on the movie, assume there’s plenty of drama and shifting allegiances.

Bottom line: Even in a highly liquid market, which crowd-wisdom theory holds should be more accurate, there are simply no tools to measure what Catholics believe is the spirit of God guiding the cardinals’ choice.

“The Holy Spirit is indeed a wily one,” Zitzewitz said.

“How come I can’t breathe at home and y’all get to breathe at home?”

Ariel Wittenberg writing for Politico. 

MEMPHIS, Tennessee — Elon Musk’s artificial intelligence company is belching smog-forming pollution into an area of South Memphis that already leads the state in emergency department visits for asthma.

None of the 35 methane gas turbines that help power xAI’s massive supercomputer is equipped with pollution controls typically required by federal rules.

The company has no Clean Air Act permits.

In just 11 months since the company arrived in Memphis, xAI has become one of Shelby County’s largest emitters of smog-producing nitrogen oxides, according to calculations by environmental groups whose data has been reviewed by POLITICO’s E&E News. The plant is in an area whose air is already considered unhealthy due to smog.

The turbines spew nitrogen oxides, also known as NOx, at an estimated rate of 1,200 to 2,000 tons a year — far more than the gas-fired power plant across the street or the oil refinery down the road. That’s according to calculations by the Southern Environmental Law Center, a nonpartisan legal advocacy group that focuses on the South, which used turbine manufacturer spec sheets to estimate xAI’s annual emissions and compare them with pollution that other South Memphis plants have reported to the Environmental Protection Agency’s National Emissions Inventory.

The turbines were necessary to get the third version of the company’s AI chatbot up and running in time, Musk said at the product’s launch in February, adding: “We have generators on one side of the building, just trailer after trailer of generators until we can get the utility power to come in.” He has not publicly addressed the pollution concerns and did not respond to requests for comment about the turbines powering the plant and their lack of pollution controls.

“In time,” in this case, means meeting an entirely arbitrary deadline which Elon Musk set because he's desperately trying to overcome his last-mover disadvantage in what has turned out to be a huge hype bubble. Musk needs to be seen as a major player in AI if he wants to maintain the obscenely inflated values of his companies. As mentioned before, if Tesla and SpaceX were to suddenly be valued on any kind of rational basis, his net worth would drop by one to two orders of magnitude, and there are a number of margin calls lurking between here and there.

Just three miles away is Boxtown, a secluded neighborhood that officially became part of the city of Memphis in 1968, the year that the Rev. Martin Luther King Jr. was assassinated at the Lorraine Motel downtown. While the annexation had come with the promise of connecting Boxtown to municipal utilities, many homes still had no running water or sewage service as late as the 1970s.

Today, more than 90 percent of residents living in Boxtown’s ZIP code are Black, with a median household income of $36,000, according to the Census Bureau. It’s also home to more than 17 industrial facilities — some of which share an industrial park with xAI — that release enough toxic pollution to require registration with EPA’s Toxics Release Inventory.

“I can’t breathe at home, it smells like gas outside,” Boxtown resident Alexis Humphreys said through tears, holding up her asthma inhaler during a public hearing about the turbines on April 25. “How come I can’t breathe at home and y’all get to breathe at home?”

Together the turbines produce enough energy to power 280,000 homes. XAI has been relying on them because the data processing center’s voracious appetite for energy has outpaced electric utilities’ ability to serve it.

...

XAI’s main product is Musk’s chatbot, Grok, which also generates images. It has become known for having fewer user guardrails than other artificial intelligence programs, like ChatGPT, which often prevent users from requesting images that violate copyright standards or are deemed insensitive. Grok allows users to make deepfakes depicting things like Mickey Mouse wearing a Nazi uniform. Musk has called it “the most fun AI in the world.”

 Grok is also notable for allowing users to upload images of fully clothed women and showing what they would supposedly look like in sexy lingerie. Say what you will about Elon Musk—he certainly does know his fan base.

 Boxtown residents say they have been paying for the images with their health.

At a public hearing on the xAI permits at Fairley High School on April 25, multiple residents described cases of asthma and cancer in their families they attribute to air pollution, asking for the Shelby County Department of Health to deny xAI’s permit and shut down all the turbines. Many have health conditions, such as asthma and chronic obstructive pulmonary disease, that predate xAI’s arrival in South Memphis. But NOx emissions are known to worsen lung conditions, and residents fear that the sheer volume released by xAI will further harm their health. Some, like Humphreys, showed their inhalers and portable oxygen tanks as proof of the damage.

...

Memphis Light, Gas and Water and chamber officials initially suggested last summer there were 18 turbines of varying sizes. But then, when xAI filed a permit application in January, it listed 15 machines, at 16 MW each. Then, at the end of March, environmental groups flew over the facility and came back with aerial photos showing 35 turbines onsite. Memphis Mayor Paul Young defended the company, saying only 15 were actually running and that the rest were for backup.

But in late April, environmental groups sent a plane with thermal cameras to fly over the facility and found 33 turbines giving off significant amounts of heat — a sign they were also generating electricity and pollution.

“The way they have come into the city, it’s like, oh, you think we are unintelligent, you think that the people in these communities aren’t able to comprehend what you are doing and will take this assault on our health lying down,” 15-year-old Boxtown resident Jasmine Bernard said.

 Musk’s companies have always had horrific environmental records, to the point of setting up the launch site for his frequently exploding rockets in the middle of a nature preserve harboring numerous endangered species. What we're seeing in Memphis is simply par for the course.

I plan to get back to the larger question of large language models and energy consumption. It's a tremendously complex issue where I don't have any relevant experience, so I need to proceed cautiously and frequently check my assumptions with whatever authorities I can find.

I do have some relevant experience critiquing statistical analyses, and, having looked at some of the most widely circulated arguments that AI power usage is no big deal, I can tell you that while they may not be wrong (that's a question for the experts), they are bad—filled with the kind of red flags that we've been pointing out here at the blog for over a decade now.

I'll be spelling those out in an upcoming post.

 

A leftist filmmaker is interviewed in a leftist magazine about his recent pro-nuclear documentary

Another one that got somehow left behind in the queue.

 I'm not going to go into the merits of the arguments or of the film itself, other than to say it was fairly well-reviewed, with a 75% Tomatometer, where even the negative reviews seem to be mostly complimentary of the content—just not of the uncharacteristically low-key filming style.

If I get a chance to see it, I may have more to say on that subject, but what's interesting here is the way that climate change is realigning the left in unexpected ways.

I mean, seriously. Who out there would have predicted that Oliver Stone would go pro-nuke, and that Jacobin would give him a friendly reception when he did?

Oliver Stone Goes Nuclear

Ed Rampell:

So how did Nuclear Now come about?

 

Oliver Stone:

I was scared. In the 2006 movie [An Inconvenient Truth by] Al Gore, I was obviously conscious that he was giving solutions to the problems of clime change. But I was confused by the many different sides I was hearing. It was confusing — and I wanted to straighten it out for myself. I saw a book in 2019 that was well reviewed in the New York Times by Richard Rhodes: it was called A Bright Future. It was written by Josh Goldstein, an emeritus professor of international relations, and by a nuclear scientist named Staffan A. Qvist, from Sweden. It was a small little book, but it was simple and commonsensical. Common sense is important. It was very different in the sense that it was saying: “What’s wrong with nuclear power?”

Because that’s all you had heard for many years. I didn’t know; I just went along with the consensus that nuclear power was a bad thing. But when you read the book, you begin to understand that it is not a bad thing — it has been confounded with nuclear war; war and power are not the same thing — and that we have lost, bypassed a great opportunity, in America anyway, [compared to] if we had followed through on “Atoms for Peace,” what presidents Dwight Eisenhower and John Kennedy had started in the 1950s and ’60s.

Nuclear power was working. It worked for many years with the Navy, with Hyman Rickover, and then he transferred his acumen to building civilian power stations. Shippingport, Pennsylvania, was the first one in the United States; in 1958 and 1959 it came online. Many of those same reactors are still going; they’re called “legacy reactors,” but they’re almost finished now. But they worked seventy years [laughs], and nobody complained.

Except there was a scare at Three Mile Island, where no one died, and in fact, the containment structure worked. But a lot of hysteria and brouhaha — as you know, I’m not a guy who believes in passion, necessarily, when it’s wrong. You’ve got to call it out; I wanted the truth, and this is the truth.

I’ve been talking to many scientists. I went to Idaho National Laboratory; I went to France, and I went to Russia and talked to a lot of people. It’s all a lot of hooey from a lot of scared types who love to tell you what’s wrong with everything. You’ve got to scale it down and say, “Relative to what?” Relative to climate change — coal, oil, and gas?

Ed Rampell

In Nuclear Now, you criticize the fossil fuel energy industry for spreading disinformation regarding climate change. Did the nuclear industry have anything to do with the funding of Nuclear Now?

Oliver Stone

No, no, no. This was done with private investors. And the nuclear industry [laughs] has not done a very good job defending itself, if you look at the history. It has had no sense of fighting back. When Jane Fonda and Ralph Nader started their attacks, there was no really interesting response from the industry. It kind of folded up. Which was a shame, because I think when history is written, if we presume the planet will survive, and there’ll be a civilization, and I’d very much like. . . . I am an optimist. When this is written, they’ll say: “This was a huge mistake in the 1970s to stop building nuclear reactors in the United States.” Thank God they did not stop in Russia or China or France, which has kept it going.

But as we said in the film, “It’s too good to die. You cannot kill it off.” The United States is now slowly getting back into, of course, smaller reactors and more modern, new-generation reactors. There’s a lot promise. But the big building is still going on in China, Indonesia, Eurasia, India and so on.

How can we say that Flow is a bad idea if Andreessen Horowitz invested a third of a billion dollars in it?

“Here’s my idea for a new business.”

“That’s the stupidest thing I’ve ever heard. The business model is crap. The potential market is tiny. And it’s not even original.”

“It’s a tech company.”

“Can I invest $350 million?”

Though it never had the straight out punchline business model of MoviePass and it never approached the eye-watering overvaluation of Tesla ($1.5 trillion at its peak), there was a certain purity about WeWork that made it perhaps the definitive dumb money enterprise of its time. 

God knows, we've said our share of mean things about Uber and Lyft and Netflix and Tesla, but for all of the confusion and myth-making that drove those valuations to their current sky high values, even I have to admit that there was at least the possibility of the promise of something big behind each of those companies. The rise of the smartphone made new models of personal transportation possible. We can argue whether the dominant business model will be all-you-can-stream or a la carte or heavily tiered or advertiser-driven, but there is little question that more and more video viewing will be done online. The future of cars is both electric and autonomous.

By comparison, you almost have to admire the pure distilled bullshit of WeWork. There is nothing to ground this business model, no recent or even promised technological advance, no big innovation, nothing but the CEO babble and Ted Talk happy speak so in vogue in Silicon Valley these days.

But perhaps the most impressive thing about this con is that Adam Neumann pulled it again.

WeWork co-founder lines up $350 million A16Z investment for a new billion-dollar real estate venture

If there were ever a story that demanded the talents of Patrick Boyle...

The Inevitable Decline of WeWork





Adam's Back!

Josh Marshal's understating how dysfunctional the titans of Silicon Valley have become

 I find myself in the odd position of disagreeing rather strongly with a recent post by Josh Marshall. Not about any major conclusion, and certainly not about his political analyses (you don't tug on Superman's cape), but we've spent more than a decade here at the blog criticizing tech messiahs in general, and Elon Musk in particular, so I feel fairly comfortable raising some points about these three paragraphs, specifically about how the Tech right is attacking biomedical research for reasons that go far beyond a fixation with artificial intelligence.

 First, you have Elon Musk, the belief that AI can and will essentially replace research scientists and the related belief that AI-backed tech has essentially achieved a kind of escape velocity from government-supported science. So AI will soon replace research scientists. I, Elon (or tech generally) own the AI. So there’s no big harm shutting down this research apparatus. And since I own the AI, not only will we cure all the diseases but I’ll own all the cures! What’s not to like? This may seem like hyperbole but it is at most only a hyped up version of what these people think. This informs A LOT of the thinking behind the cuts. The aim of knocking the eggheads off their perch is easy to understand. If there’s also no downside (in terms of lost cures, lost leads in the sciences) why not?

Related to this is something I’ve picked up in discussions with a friend who is a very close and shrewd observer of the tech world. That’s the Silicon Valley class war between the folks with tens or hundreds of millions or more and the working stiffs on salaries of $400,000 or $500,000 a year. That tech “working class” salary point may sound absurd. But it really captures a big part of this. The dynamic is intensified by the ossification of tech. It used to be that the half-a-million-a-year folks might be one great start-up move away from hitting super wealth themselves. That’s not happening anymore. Meanwhile, the Elons and sub-Elons have super wealth and it’s annoying to have to listen to the gripes, the borderline-woke thinking and everything else, from the guys who fuel your wealth. A Thorstein Veblen type could explain it better than I can, but, for present purposes, we’ll settle for this thumbnail version.

Needless to say, government scientists don’t make half a million a year and neither do all but maybe a tiny elite of science grant superstars. But when the tech oligarchs in Elon’s world see these folks with their PhDs and their peer reviews and their long-ass study timelines, they see the uppity salaried techs who run their companies. And they act accordingly.

Rather than being surprising and unexpected, the tech right’s hostility toward biomedical research is a logical consequence of foundational beliefs that have, in some cases, been around for more than 20 years.

 The point about the class struggles of the Valley is true but not particularly relevant here. More importantly, I'd argue AI plays a secondary role here. It's true that if you asked Musk et al. today why they are cracking down, their answers would almost certainly include artificial intelligence—because in 2025, any question you ask these people will be answered by some combination of LLMs and humanoid robots (here and here for more details on the latter)—but while AI has always been a favorite subject for techno-optimists, it really only became top of mind after the implosions of the previous “next big things,” the metaverse and Web3. The antipathy toward this kind of research goes back way further than that.

Arguably, the defining trait of this crowd is an extraordinary—often straying into delusional—faith in their own ability and rightness. One consequence of this is a general disdain for expertise. They know more about medicine than doctors, more about banking than bankers, more about manufacturing than industrialists,* more about mechanical engineering than actual engineers. We saw an early indication of this with the rise of biohacking and various flaky life-extension theories—the latter also reflecting the reluctance of these men, who saw themselves as all-powerful, to submit to death at some point.

Inevitably, this combination of absolute faith in their own opinions, combined with the tendency to dismiss those of people who knew what they were talking about, led to all manner of flaky ideas and junk science getting a foothold. This came to a head during the pandemic, when Silicon Valley effectively became ground zero for COVID denial and quack cures.

It has been noted elsewhere that COVID was when numerous tech-world figures either became radicalized to the far right or simply decided it was safe to come out with their extreme opinions.

Another related core belief among this group is the idea that these successful tech visionaries are omnicompetent. The term first showed up on our radar when Alon Levy used it to describe Elon Musk, but there are lots of examples to pick from. Perhaps my favorite is when Zuckerberg promised to cure all disease in his child’s lifetime by pledging to match around 1% of the NIH budget.

For a long time, it was part of the popular mythology that whenever these titans decided to disrupt a new field, they would inevitably crush the old, slow-moving competition. If you dug into any of the famous examples, you would find that either the success was greatly exaggerated and/or based on the work of those same experts Silicon Valley so disdains. Possibly the best example is SpaceX, where the accomplishments have been somewhat overstated, and—more to the point—were produced by TRW rocket scientists basically continuing the research they'd been doing for their previous employer.

The idea that an Elon Musk or a Marc Andreessen could step in with no relevant experience and effortlessly fix all of our problems has been around for years, and no matter how many times they fail, their confidence—and that of their followers—is unperturbed. As recently as this year, a writer as intelligent as Noah Smith continued to depict Elon Musk as super-competent, though those arguments have been trailing off as of late.

Musk, in particular, is now entirely in the thrall of the worst of the far right, more likely than not to agree with a Laura Loomer. It's not surprising to see him going after traditional targets like stem-cell researchers, but the idea that the messiahs of Silicon Valley could burn all this down and easily replace it with something far better is a notion we have seen countless times from all of these people and it long preceded the current hype bubble around artificial intelligence.

* "I Think I Know More About Manufacturing Than Anyone Currently Alive On Earth." ElonMusk

Another one for the lexicon: deerstalker

 

A deerstalker is a belief which is:

1. Held by the general public;
2. Discounted by the moderately well-informed;
3. Known to be true by experts.

The name comes from the hunting cap worn by Sherlock Holmes in the stories of Arthur Conan Doyle.

While it is true that Sherlock Holmes, a generally well-dressed upper-class English gentleman, would not go about the streets of London wearing a deerstalker any more than an American outdoorsman would wear his Elmer Fudd hunting cap to a fine restaurant, he would wear one when appropriate, such as when out in the country and at least once on what we would call a stakeout in London. He was routinely depicted as wearing a deerstalker in the original illustrations, and at least once, Doyle included a description of the hat in the stories. He did not use the specific term but that was the type of apparel he was clearly describing.

What brought this to mind was the deep dive I've been doing into the technological revolution of the late 19th and early 20th centuries, particularly the impact of Thomas Alva Edison.

While the popular conception is that Edison was the greatest inventor of his time, it has become fashionable to be dismissive of this view. Bring up Edison's huge and hugely influential list of patents, and you will probably have someone inform you that he actually invented very little—if anything. He was just an administrator who took credit for the work of other researchers, much in the way that Walt Disney's signature used to appear on every piece of art involving characters owned by the studio.

I was always a bit skeptical of the "Edison didn't really do anything" school of thought—after all, he was only able to put together a team because of early inventions like the quadruplex telegraph—but it wasn't until I did some serious reading that I realized how completely wrong this take was.

Because of the way Edison worked, and because of the enormous scrutiny he was under both during his life and posthumously, we have a remarkably detailed and accurate picture of the process behind all of his patents and behind those innovations—like his improvements on X-ray equipment—that he refused to patent to make them more widely available. We can go from the initial sketches in his notebooks, follow along through the detailed records of each iteration and refinement of an idea, and read the contemporary accounts and the memoirs of the researchers who were working alongside him.

With very few exceptions, Edison had the original idea, set up the research project to develop it, and supervised—and frequently personally conducted—the experiments needed for each iteration. With the caveat that, given the fever pitch of research at the time, there were almost always so many brilliant researchers pursuing any promising notion that it was generally impossible to say exactly who truly invented what, Edison's body of work is very probably unequaled. And even that is dwarfed by the impact his model for organized, large-scale research has had. 

1. Edison was the greatest inventor of the 19th Century

2. Edison was just an administrator and promoter

3. Edison was the greatest inventor of the 19th Century

A few years ago Morgan Stanley released an analysis promising that the metaverse would soon be worth more than $5 trillion dollars. Their latest one on humanoid robots may not rise to that level of prescience.

Guys, we've been pointing out bubbles here at the blog for well over a decade now and, trust me, this is a bubble

Just as it did in response to the metaverse hype of a few years ago, Morgan Stanley has jumped on the humanoid robot bandwagon with a report predicting:

Based on our analysis, we believe ~75% of occupations and ~40% of employees in the US have some degree of "humanoidability." This amounts to an estimated addressable market of ~$3 trillion, or ~63 million humanoid units in the US alone. While this estimate considers only the US, we note that a TAM based on the global labor market could be greater by multitudes of magnitude. 

The analysis rests almost entirely on conflation, omission, and insane amounts of techno-optimism.

The current capabilities of these machines are grossly exaggerated. Their likely costs are absurdly lowballed. The potential market size is substantially overstated. Alternative robotic approaches that would be undeniably more efficient, productive, and cheaper are virtually ignored altogether.

The eighty-six report has one paragraph on why multi-purpose robots should characters from I, Robot which mainly boils down to the Cylon Design Fallacy.

 Why humanoids? Many investors reading this report will ask the question “why do we need robots shaped like humans?” There are indeed strong arguments for robotics to take many highly specialized forms (robot arms, snake-shaped robots, robot dogs, robotic dust and as many form factors as you can imagine). However, many robot and AI experts say the strongest argument for robots in a human form factor is that in a world already created for humans, the environment is already "brownfielded" for humanoids. Nvidia CEO Jensen Huang recently stated “The easiest robot to adapt into the world are humanoid robots because we built the world for us. We also have the most amount of data to train these robots than other types of robots because we have the same physique." Additionally, think of the great variety of tasks that humans are able to perform with our bare hands or using tools and the multitude of machines designed for human hands and fingers.

Notice the -- if you'll pardon the phrase -- sleight of hand here. There's no reason a robot with 5-fingered hands with opposable thumbs needs to be otherwise humanoid. Being bipedal is arguably the main driver of cost and complexity but it barely figures it all in the only reasons they give for going with the humanoid design.

As we've discussed before, the bipedal humanoid design has lots of problems. It is needlessly complex and expensive, bringing virtually no added functionality in most situations. It's unstable—even those impressive Boston Dynamics demonstrations have to edit out the scenes where the robot falls over. In addition to the daunting engineering challenges of building a robot that walks on two legs, there's also the issue of a top-heavy design, since the battery is generally stored in the torso. This places the center of gravity three to four times higher than what you get with more traditional wheeled-base designs.

Worse still, having the batteries relatively inaccessible means these robots must be taken offline for substantial periods just to recharge—compared to more traditional designs, which often allow for fast and easy battery swaps.

It's remarkably difficult to make a compelling case for bipedal locomotion in robots, and the arguments presented barely address the elephant in the room. In particular, the "training" argument applies mostly to arms and hands. Outside of a few isolated applications, if you replace the legs with wheels, you get a cheaper, more efficient, more stable, and more reliable machine—one that also has the added benefit of being able to operate virtually 24/7.

The authors lean heavily on the biomimicry throughout the report.  

 Along similar lines, note how Morgan Stanley equates "humanoid" with "general purpose."

 This is a huge misrepresentation of the state of robotics. There is no reason whatsoever that a general-purpose or multi-purpose robot needs to be humanoid. If anything, it is in many ways a particularly poor design choice due to its instability, its complexity and cost, and the limitations imposed by naive biomimicry. The design has no innate advantages in performing complex tasks or demonstrating dexterity. If anything, the previously mentioned instability puts it at a disadvantage when it comes to delicate work.

 These are incredibly thin arguments if you're trying to defend design choices determining a multi-trillion-dollar shift in the economy that would replace a large portion of the workforce. I suspect that, on some level, the people making these arguments realize how unconvincing they are—which might be why they're never prominently featured in these analyses and articles. You have to dig quite a ways into this massive document before you reach the one and only paragraph justifying the humanoid design. But of course, that's not the real reason. These robots look the way they do because it seems cool and futuristic—like something out of a science fiction movie. From a serious business standpoint, those reasons are indefensible. But if your primary objective is to build a hype bubble, they make perfect sense.

In case you think I'm being unfair about the sci-fi crack:

 

 And, of course, Elon is cited.

One billion humanoid robots by the 2040s? Tesla CEO Elon Musk has been increasingly focused on Optimus (Palo Alto engineering center) in recent months, per his comments. Tesla first unveiled its humanoid robot, Optimus, on September 30, 2022. The bipedal robot included 28 actuators in two categories: 1) rotary actuators, consisting of harmonic reducers, ball bearings and sensors, for rotating motions such as shoulders and elbows; 2) linear actuators, comprising planetary rollers, ball bearings and sensors for linear motions like human muscles. Twelve actuators for two hands. Many more details have been kept internally at the company. In January of this year, Elon Musk said he expected to see over 1 billion humanoid robots in operation by the 2040s. At Tesla's June 13th 2024 annual shareholder meeting, Mr. Musk stated he expects to have at least 1,000 Optimus robots working at Tesla next year, and that "things are gonna scale up very rapidly from there." In the same meeting, Mr. Musk expressed his confidence that humanoid robots will eventually outnumber human beings and "probably be 20 billion or more" (no timeline shared).

 

In case you're new here, Musk has predicted a million Tesla robotaxis on the road "next year" every year since 2019 and predicted SpaceX would make its first Mars landing in 2022.

 

Surprisingly, despite Elon Musk's involvement, this may turn out to be a scam.

 

Folks, we've been keeping an eye on hype and bubbles for a long time here at the blog, and we've accumulated a pretty good track record. So take it from me: we are looking at a metaverse-level event with humanoid robots. When the dust settles, hundreds of billions of dollars will have been wasted on an embarrassing techno-optimist hash of bad engineering, flawed economic reasoning, and hackneyed sci-fi tropes.

I just went through the Morgan Stanley rainbows and unicorns report on our robot future. I'll have more to say about that in the coming days (spoiler alert: it's bad). For now, here are a couple of threads from an actual engineer who does a good job laying out the absurdity of it all.

The Cylon (TOS) Design Fallacy

Just to be clear, I'm talking about these Cylons...

 

... not these Cylons.

In the pilot of the original Battlestar Galactica, Apollo and Starbuck steal a Cylon fighter. They're able to do this because those ships, like all of the others depicted in the show, appear to be designed for human use. They have manual controls, display screens, life support systems, and voice communications—all things that were either unnecessary or horribly inefficient for technology designed to be used by a race of robots.

It's best not to try to think too deeply about that 1978 show. For one thing, we know the reason that Cylons looked like they did. It was because the producer, Glen Larson, blatantly ripped off Star Wars and got sued for it (Larson was one of the few people in Hollywood who couldn't get along with the famously well-liked James Garner—to the extent that Garner once punched Larson in the mouth over plagiarized Rockford scripts) . Cylon centurions looked the way they did because they were supposed to remind people of Imperial stormtroopers.

The Cylon design fallacy is that robots should be designed to interface with systems that were designed to interact with humans and systems designed to work with robots should interface with them in the same ways they would interact with humans.

The standard argument for humanoid bipedal robots, put forward by people like Elon Musk, is that they can do anything that humans can do physically. That's a dubious claim, but even if they could back it up, it's really not that impressive a boast. Most of what we do requires tools, which raises an interesting question: since robots are tools, why pick a design that is far more expensive and less efficient just so it can use tools that only look the way they do because they were designed for humans to use?

Bipedal humanoid robots are inevitably top-heavy and unstable compared to other designs, badly suited for lifting, carrying, and stacking heavy objects—particularly those where the load can shift while moving (think of a half-full container of liquid or a box with loose objects that can slide around). It's true that a humanoid robot could operate equipment such as a forklift, but if you're going to go to that expense, you could get an autonomous forklift that would do the same things at far less than the combined price—with the added advantage of being more compact, since it would not need space for a driver.

As for the argument that the same robot could go from working in a factory to cleaning your house, why would we want it to? You’ll be paying for functionality you don’t need and compromising on functionality that you do. And even if you insist on a one-size-fits-all model, what reason—other than the naivest of naive biomimicry—is there to believe that the sci-fi movie robot is the design you’d want to go with?

I hate to reschedule "The Cylon (TOS) Design Fallacy" yet again, but we had a big news day on the Tesla front

I've got some real posts coming up on Elon's Optimus and the humanoid robot bubble, with any luck starting tomorrow, but the last three days of April were just too eventful to ignore.

Remember, as I'm writing this, Tesla's P/E ratio is 155.30. Toyota's is 7.10. Alphabet's (Google) is 18.23.

Tesla (TSLA) chair sells most of her stocks – her time is done?
Fred Lambert | Apr 29 2025

Tesla’s Chairwoman, Robyn Denholm, has filed to sell another $30 million in Tesla stock. She appears to be completely liquidating her stake in the company she chairs.

This morning, we noted that a Tesla insider made their first stock purchase in five years.

Other than the small purchase from Joe Gebbia disclosed last night, Tesla executives and board members have exclusively exercised stock options and sold them right away.

Robyn Denholm, Tesla’s Chairwoman, has been the top seller. She sold over $150 million worth of Tesla stocks over the last 6 months.

She has received over $600 million in stock compensation since joining the board just 10 years ago, and she has sold over $500 million worth.

While that looks bad, there was a potentially far bigger announcement, but first a bit of background. More from former Elon fan Lambert.

When explicitly asked about Waymo, which is already seen as the market leader by most experts, Musk again claimed that it won’t be competitive because of cost:

Well, okay. The issue with Waymo’s cars is it costs way more money, but that is the issue. The car is very expensive, made in low volume. Teslas are probably cost 25% or 20% of what a Waymo costs and made in very high volume. So, ironically, like, we’re the ones to make the bet that a pure AI solution with cameras and what do you have? The car actually will listen for sirens and that kind of thing. It’s the right move. And Waymo decided that an expensive sensor suite is the way to go, even though Google is very good at AI. So I’m wondering. And it is worth noting that Tesla has both an incredible AI software team and AI hardware chip design team.

While it’s true that Waymo’s vehicles are more expensive, this has little to do with an “expensive sensor suite”, as Musk claimed.

Tesla’s sensor suite, which consists only of cameras, is certainly less expensive than Waymo’s, which includes cameras, radar, and lidar sensors. Still, most of the cost difference is due to Tesla building vehicles in high volumes for consumers while Waymo buys existing vehicles and retrofits them with its sensor suite in much lower volumes.

Talking to Business Insider this week, John Krafcik, who helped launch Google’s self-driving vehicle program and was Waymo’s first CEO until 2021, doesn’t see it as a problem:

In the long run, the cost of sensors has a “trivial cost-per-mile impact over the useful life of a robotaxi,” he told BI,” while also providing massive quantifiable safety benefits.”

Krafcik has been skeptical of Tesla’s efforts for a while and even suggested that what Tesla plans to launch in Austin in June could amount to “faking” self-driving.

If Waymo were in a position to build in high volumes, the math might be very different.

On a completely unrelated note.

Waymo, Toyota strike partnership to bring self-driving tech to personal vehicles
Jennifer Elias, Lora Kolodny

Alphabet-owned Waymo and Toyota on Tuesday announced a preliminary partnership to explore bringing robotaxi tech to personally-owned vehicles.

“The companies will explore how to leverage Waymo’s autonomous technology and Toyota’s vehicle expertise to enhance next-generation personally owned vehicles,” the two companies announced.

The companies said they aim to use the partnership to more quickly develop driver assistance and autonomous vehicle technologies for personal vehicles. Toyota is the world’s largest automaker by sales. 

Waymo co-CEO Tekedra Mawakana said the strategic partnership could also result in the Google-owned company incorporating Toyota’s “vehicles into our ride-hailing fleet.”

And there's this.

To be blunt, I don't see any way out for the company. Elon is—and will remain—the public face of Doge, regardless of how much time he spends in the White House. As long as he is with Tesla, the brand will remain toxic.

But that 155 P/E is wholly dependent on the false belief that he is an engineering genius who will make trillions of dollars through robotaxis and humanoid robots. If he leaves, investors will have to face the fact that this is a small car company with a horrible brand trading at something like 20 times any reasonable value.

Tesla may be the platonic ideal of "The market can stay irrational longer than you can stay solvent," but when sanity does hit, it's likely to hit hard.