Techies are throwing billions at robots; the 'hardware tourists' are piling in

Getty Images; Rebecca Zisser/BI

For decades, hardware was a hard sell in Silicon Valley. Now investors are pouring tens of billions into machines that can do things in the real world.

A Goldilocks set of conditions has made robotics one of tech's hottest bets. As investors look beyond chatbots to the next frontier in AI, cheaper hardware, smarter AI models, labor shortages, and competition with China are fueling interest in machines capable of performing physical work.

Robotics and physical AI companies raised $33.4 billion globally in the first half of this year alone, according to PitchBook data. That's already more than the $28.7 billion the sector raised in all of last year — and an astronomical rise from 2020, when funding came in at just under $5 billion.

Investors are writing billion-dollar checks to fund both the machines and the AI brains behind them. Defense company Anduril raised $5 billion in May, co-led by Thrive Capital and Andreessen Horowitz. Autonomous shipbuilder Saronic raised $1.75 billion in March in a round led by Kleiner Perkins. Skild AI, which builds software to control different kinds of robots, raised $1.4 billion in January in a round led by SoftBank. Physical Intelligence, which is also building an AI model to command robots, raised about $1 billion in May, co-led by Leopold Aschenbrenner's Situational Awareness and Lux Capital.

"This is off the charts," Ken Goldberg, a UC Berkeley robotics professor and cofounder of warehouse robotics startup Ambi Robotics, told Business Insider. "In my 45 years in this field, this is the most funding and energy and interest in robotics that I've ever seen."

This is the first installment of Robonomics, Business Insider's new series on the rise of robots and their impact on business, jobs, and everyday life. We'll go inside factories and warehouses where humans work alongside robots, meet the founders, investors, and workers driving the boom, and examine how the technology is reshaping industries from manufacturing to defense. We'll also ask how close robots are to becoming part of everyday life, and what is still standing in their way.

The prize is enormous. Unlike software, which is largely confined to work done on screens, robotics companies are going after physical labor, from factories and construction sites to robot butlers in every home. Nvidia CEO Jensen Huang, who popularized the term "physical AI," has described robotics as the "technology industry's first opportunity to address a $50 trillion industry that has largely been void of technology until now." Many Nvidia veterans have launched their own robotics startups.

Nvidia CEO Jensen Huang

Bloomberg/Bloomberg via Getty Images

But investors are pricing companies as though the robot revolution has already arrived. Startups still in research and development command multibillion-dollar valuations, often with little revenue and few deployments to show for it. Humanoid maker Figure AI, for example, secured a $39 billion valuation last year, even as its deployments remain limited to small factory pilots.

"Robotics is going to happen, and a lot of money will still be lost," said Sarah Guo, founder of the venture firm Conviction, which is an investor in robotics startups Sunday Robotics and Watney. "Both things are true."

From not to hot

From industrial arms assembling electronics to Roombas cleaning floors, robots have long been part of everyday life.

What venture investors struggled to see was how to make money from them. Building robots required expensive hardware, factories, and supply chains, often to produce machines that could perform just one narrow task. Why fund that when you could back a college dropout building the next viral app?

Guo used to tell fellow investors that robotics was a good way to lose a lot of money over many years. "The models didn't work," she said. "Every robot was a brittle, single-purpose system hand-built for one task."

Ajay Agarwal, a partner at Bain Capital Ventures, was among the few investors willing to bet on robotics during the internet era. In 2004, he backed Kiva Systems, which pioneered warehouse automation with fleets of mobile robots that brought products directly to human workers.

A Kiva Systems robot moves a shelf to fill orders at an Amazon fulfillment center

Bloomberg/ Getty Images

Bain led every successive funding round because Kiva was "not able to raise money on Sand Hill Road," Agarwal told Business Insider. By the time Amazon bought it for $775 million in 2012, Bain was its only institutional investor.

More than two decades later, AI has changed the calculation. Advances in machine learning are helping robots perceive their surroundings, make decisions, and adapt to new tasks, raising hopes that companies can build more versatile machines instead of engineering a different robot for every job. Cheaper computing and hardware are also making the economics more attractive.

Some of Silicon Valley's biggest names are now chasing that vision. Former Uber CEO Travis Kalanick's Atoms raised $1.7 billion in July to pursue automation in food, mining, and transportation. Rivian CEO RJ Scaringe's Mind Robotics has raised $900 million this year, while former Cruise CEO Kyle Vogt's home robotics startup, The Bot Company, has raised at least $300 million.

Big Tech and AI labs, too, are joining the rush. OpenAI has advertised robotics jobs with base salaries reaching $500,000 a year. Meta acquired robotics startup Assured Robot Intelligence in May and is testing robots in its data centers. Google has invested in humanoid maker Apptronik, which is also working with DeepMind to develop AI models for robots. Elon Musk, meanwhile, is staking Tesla's future on the Optimus humanoid.

Tesla's Optimus humanoid

CFOTO/ Getty Images

Some venture firms are setting aside dedicated capital for robotics. In August, Andreessen Horowitz raised $1.1 billion for "Machine Age," its first fund focused on the physical infrastructure behind AI, including robotics.

The gold rush

For longtime robotics investors, alarm bells are ringing. Industry veterans whisper about "hardware tourists" piling into robotics deals — investors drawn by AI hype who underestimate how difficult it is to build machines that work reliably in the real world. There is precedent for caution. Venture firms poured billions into autonomous vehicles in the 2010s, only to see startups fold or consolidate as self-driving technology proved harder and more expensive to commercialize than expected. Years later, only a handful of deep-pocketed players have managed to bring robotaxis to the public.

Robotics faces its own formidable obstacles. Unlike large language models trained on vast amounts of internet text and images, robots lack a comparable trove of data showing them how to act in the physical world. Dozens of startups are now scrambling to collect it, but nobody knows how much will be enough. And even smarter AI won't eliminate the challenges of manufacturing, maintaining, and deploying expensive hardware.

"The most difficult part of physical AI is the physical part," said Charly Mwangi, a partner at VC firm Eclipse who has backed The Bot Company and robotics startup Genesis AI. "The next few years are going to be really, really hard for the robotics industry as companies go from the lab to deployments."

Some of the most speculative robotics bets are attracting the biggest checks. Humanoids and general-purpose robot models were the two fastest-growing areas of robotics investment last year, according to venture firm F-Prime. "You cannot raise money on demos forever," said Sanjay Aggarwal, an F-Prime partner and coauthor of the firm's annual robotics report. "I would personally be surprised if all these companies independently exist two or three years from now."

There are signs that some startups are becoming real businesses. Field AI, which is building an AI "brain" that works across robots, has crossed $100 million in revenue and customer contracts from more than 30 customers, including construction firms, data center operators, and defense companies, Business Insider previously reported. Skild AI said last month that it had reached $100 million in annual recurring revenue from more than 60 customers. Its projects include robots assembling Nvidia's Blackwell chips with Foxconn and kitchen pilots with Mitsui, a Japanese conglomerate.

An Nvidia GB200 Blackwell GPU

Bloomberg/ Getty Images

Believers see robotics on the cusp of a breakthrough that could put machines to work in nearly every corner of the economy. Brad Porter, the former head of Amazon Robotics who now runs workplace robotics startup Cobot, says the field could be nine to 18 months away from major advances in dexterous manipulation — the ability of robots to handle objects with the ease of human hands.

"When I think of a 'ChatGPT moment' for robotics, it is cracking dexterous manipulation," Porter said. "Then there will be a Cambrian explosion of robots."

The question is whether these breakthroughs will arrive quickly enough to justify the money pouring in.

At Business Insider's Growth Mode event this month, Menlo Ventures partner Matt Murphy singled out robotics among the fields attracting enormous amounts of financing "before they're really showing traction." Abundant funding, he warned, can make startups "sloppy."

For investors, he said, that means "a lot more opportunity to have a really big crater."

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Dario Amodei spent 2,000 words laying out to a critic on X why Anthropic must persist in the AI ‘race to the top’

Anthropic CEO Dario Amodei engaged in a lengthy exchange with a critic on X.

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• Dario Amodei responded to a critic on X who said Anthropic wasn't delivering on its safety commitments.
• He said Anthropic would be best placed to make AI safe by staying at the top of the game.
• The critic, Nathan Calvin from Encode AI, said Anthropic was trying to win a race to superintelligence.

Anthropic CEO Dario Amodei disputed a criticism that the company was putting AI safety in the back seat in its "race to the top."

On Tuesday, the executive wrote a nearly 2,000-word response to a critical X post which said Anthropic was trying to win a race to superintelligence and deprioritizing AI safety.

The original Monday X post was by Nathan Calvin, the chief strategy officer of Encode AI, an AI-safety advocacy nonprofit. Calvin listed nine actions by Anthropic over the past year that he said undermined its safety commitments, including signing deals for more than $500 billion in compute and increasingly relying on Claude to develop its AI models. His post was lengthy, too, at over 1,500 words.

Amodei said in his response that while he was a "fan of the investigative work" Calvin had done for AI safety, he disagreed with many of Calvin's criticisms.

Amodei said his position was that Anthropic can do more to keep the AI industry safe if it stays at the frontier.

"Our strategy has always been what I've called the 'race to the top' — by showing how it's possible to build the technology responsibly, we can raise the bar for the entire industry," Amodei wrote.

He then wrote out his own nine-item list of actions that were "very costly" to Anthropic commercially, but had "strong safety benefits." This included releasing its powerful Mythos model only to a select group of cybersecurity partners and restricting the sale of its AI services to Chinese state-controlled companies.

However, Amodei acknowledged Anthropic could have handled some of the issues Calvin raised better. These included a draft bill Anthropic circulated to Congress this month — obtained exclusively by Politico — that critics said would make it harder for the federal government to block dangerous AI models.

"We'll always try to do better but, again, I am extremely proud of our track record and stand by it," he wrote.

Amodei and Calvin's exchange comes at a time when model safety has become one of the most pressing issues in the AI sphere. In September, AI researchers predicted an "AI apocalypse," in which the increasingly capable and rogue technology could kill all of humanity in the next decade.

In response to the concerns, AI chiefs like Amodei, OpenAI CEO Sam Altman, and SpaceXAI CEO Elon Musk all agreed to "pace the frontier," referring to slowing down AI development to ensure there were enough checks and balances in place.

Meanwhile, Anthropic is on the brink of its hotly anticipated IPO, expected to list at a $2 trillion valuation in November. Last week, it reported a third-quarter revenue of $16.8 billion.

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South Korea's stock market is flashing another warning about the AI trade

The Kospi's sharp reversal shows how volatile South Korea's AI-fueled stock rally has become.

Chris Jung/NurPhoto/Getty Images

• South Korea's Kospi sank 4% as Samsung and SK Hynix extended the AI-stock selloff.
• AI cloud firm Elice crashed 32% in its market debut, despite frenzied demand for its IPO.
• The rout is another warning that investors are reassessing the AI trade's sky-high valuations.

South Korea's AI-stock rout deepened Tuesday as Elice, a cloud-infrastructure company, crashed 32% in its market debut.

The benchmark Kospi index closed 4% lower, despite a rebound in Wall Street tech stocks on Monday. Index heavyweights Samsung Electronics and SK Hynix fell 3% and 4%, respectively.

South Korean chipmakers are major suppliers of memory used in AI systems, making their shares a closely watched gauge of the global AI boom.

The Kospi's latest selloff marks another blow for a market that has swung from boom to a nearly 40% bust in just four months.

The turmoil has also hit companies hoping to capitalize on the AI boom.

Elice, a South Korean company that rents out computing power for AI workloads, closed at 61,500 won on the Kosdaq, far below its IPO price of 90,500 won. The company raised about 201 billion won, or $151 million, in the Kosdaq's largest IPO this year.

The company's disastrous debut came despite overwhelming demand, with institutional and retail subscriptions topping available shares by roughly 400 times.

But Elice's IPO valued it far more richly than similar AI cloud companies, whose shares had already lost 20% to 60% over the preceding month, Tan wrote.

Similar concerns are rippling through AI infrastructure markets well beyond South Korea.

US-listed CoreWeave, which rents AI computing power, saw its shares and bonds tumble last week amid concern about its debt-fueled expansion. Nvidia-backed Firmus, meanwhile, withdrew its planned $5 billion Australian IPO, citing volatile market conditions.

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I posted a 'Legally Blonde'-inspired TikTok to capture a CEO's attention. It got me an internship that turned into a full-time job.

Isaac Persky.

Courtesy of Isaac Persky

• Isaac Persky used a creative video to land an internship at Tarte Cosmetics in 2024.
• Maureen Kelly, the CEO of Tarte, was impressed by Isaac's video, leading to his internship offer.
• He returned for a second summer internship and started a full-time position this June.

When I was in college, I wanted a summer internship in New York City, specifically at one company: Tarte Cosmetics. My mom sent me a video of Tarte's founder and CEO, Maureen Kelly, calling on college students to apply to their summer internship program, and it sparked my interest.

I've been posting videos on social media in both the beauty and comedy niches for years, but I thought I'd left that behind when I started college at Chapman University to pursue a more 'serious' career. I was double majoring in economics and public relations and figured Tarte would be a fun way to spend the summer after my sophomore year before turning to a more traditional business or finance path.

I had one problem — I had no connections to Tarte, no family in the beauty industry, and no obvious way to stand out among thousands of applicants. In today's job market, especially for a sought-after position in beauty, it felt more likely I'd get struck by lightning than land an offer.

When I submitted my application in January 2024, I knew I barely had a shot.

This is where most applicants stop

They repeat the process with hundreds of applications, hoping to win the lottery of landing an interview and, ultimately, an offer.

I'm from Nebraska and attended school in Southern California. To be frank, going home for the summer was not an option. I didn't want to trade my glamorous coastal lifestyle for corn and county fairs. I couldn't rely on pure luck to be selected for an interview. I knew that if I could get in front of them, they would see how perfect I was for the role.

I decided to make a video

Since posting videos felt natural to me, I figured, what better way to show that I'm qualified for a marketing job at Tarte than by successfully marketing myself to Tarte. I decided to make something fun and entertaining. Inspired by the iconic Harvard admissions video from Legally Blonde, I created an "Elle Woods-style" application video.

I showed Tarte that I was passionate about working for them, willing to put myself out there, and could actually do the job that I was applying for. I admit, it felt a little ridiculous. I knew that all my friends would see it, and that there was a good chance it wouldn't work out the way I intended, but it was worth a try.

The video got the attention of Maureen Kelly

I woke up one morning in January 2024 to a notification that made me check whether I was still dreaming: a comment from Maureen Kelly on my post. It was a simple 'I 👀 u! OBSESSED,' followed by an email from Tarte's HR team saying they enjoyed my video and wanted to schedule an interview.

From there, I landed a paid internship with Tarte Cosmetics on their social media team. I moved to New York and worked at Tarte for three months. What started as a creative experiment became my entry point into the beauty industry.

The following winter, they offered me the chance to return for the summer of 2025. Despite my initial thoughts that my summer at Tarte would be a one-off adventure, I accepted their offer. It felt like I had found a career that combined my interests in comedy, public relations, and storytelling.

The experience also challenged some assumptions I had about internships

I expected to spend my summers doing small administrative tasks. Instead, I found myself contributing to campaigns with household-name brands and learning from the professionals who had built Tarte. I was particularly struck by Maureen Kelly, who took my ideas as seriously as she did her VPs' and shared her personal advice and can-do attitude with me regularly.

This spring, as I prepared to graduate, I received a full-time offer from Tarte without having to apply again. I officially started my full-time role with Tarte in June.

In college, much of the career advice my classmates and I were given emphasized professionalism and networking, but when employees at your favorite company are getting dozens of 'coffee chat' messages each week from people like you, that advice becomes outdated. Sometimes the best career move isn't sending another application; it's doing something creative with the skills you already have.

For most people, the idea of posting a video to get a summer internship feels embarrassing

To be honest, it was embarrassing. Putting yourself out there always carries that risk, but sometimes that discomfort is the price of trying something others might not.

Even if it doesn't work out, don't let it reflect on you. I find it best to maintain the mentality that they would be lucky to have you, and frankly, what a disappointment it is that they didn't get you.

Most importantly, I must acknowledge that all of this advice is coming from someone who has the job and got the internship. Yes, I was strategic, and I give myself credit for that, but I was also lucky.

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Amazon knows how to build big. The AI boom is testing just how big it can go.

Prasad Kalyanaraman, vice president of infrastructure services at Amazon Web Services

BASTIEN INZAURRALDE/AFP via Getty Images

• Amazon is on an unprecedented spending spree to build more AI data center capacity than anyone else.
• The company has extensive experience, yet even it's struggling to bring capacity online fast enough.
• Internal documents show Amazon getting bilions of dollars of Nvidia GPUs before they can be deployed.

At an internal staff meeting in September, AWS CFO John Felton had a joke for Prasad Kalyanaraman, the executive overseeing much of Amazon's AI infrastructure expansion.

"You've taken us free cash flow negative as a company, so congratulations," Felton said, according to a recording of the meeting obtained by Business Insider.

The remark was lighthearted. But it captured a stunning reversal.

Just two years ago, Wall Street was debating what Amazon would do with its growing cash hoard. Now, cash flow has evaporated as Amazon embarks on its biggest bet ever, spending $220 billion this year alone to build the physical backbone for AI.

At the meeting, Kalyanaraman did not dispute Felton's premise. Amazon's machine-learning and AI business is "hugely free cash flow negative," he said, adding that he expects the company's free cash flow to remain negative for "the next couple of years or so."

Amazon has made big bets before. It spent heavily on cloud computing, fulfillment centers, and its delivery network long before they became some of the company's most valuable assets. Investors questioned those investments at the time, but Amazon ultimately built enormous, profitable businesses from them.

AI is testing this playbook at a far larger scale. Amazon is committing hundreds of billions of dollars to data centers, servers, and power before investors know how quickly those investments will generate revenue.

The company is the best, or among the best, at building data centers, with decades of experience. But the size and complexity of these projects, and the bottlenecks holding progress back, are challenging — even for such a respected cloud pioneer.

Internal documents reviewed by Business Insider and people familiar with the matter show the company trying to coordinate a sprawling industrial system whose parts move on different schedules. A delay in power, equipment, or construction can leave billions of dollars in hardware waiting — and Amazon's cash tied up — while forecasts and costs keep shifting.

Why Amazon thinks it will work

Amazon says it has strong evidence that the capacity will be needed. AWS revenue grew 37% in the second quarter, its fastest pace in 18 quarters, while its backlog reached $496 billion.

CEO Andy Jassy thinks the company has a "clear line of sight" to strong financial returns from this record investment cycle. In his latest annual shareholder letter, he called AI a "once in a lifetime opportunity" and said Amazon would not be conservative in its investments.

"We've been through this cycle with the first big AWS growth wave, and liked the results," Jassy wrote. "We expect to feel similarly about this next wave."

Investors are concerned by the scale of the industry's expansion, especially as AI data centers are costing more to build and taking longer to complete.

The market is "repricing anything that funds multi-year builds against revenue that arrives later," Dan Ives, an analyst at Yorkville Ives, wrote in a recent report. Growing uncertainty around data center permitting and the political fight over electricity prices have given investors another reason to question how quickly these investments will pay off, he added.

Racks, but not enough power

One major industry challenge is securing enough power to run the equipment that goes inside data centers. This includes expensive racks of servers that contain GPUs and other chips that train and run AI models and services such as ChatGPT.

Internal emails from August show Amazon preparing a new "Early Rack Receipt" process for an expected wave of server racks carrying Nvidia's GB300 chips at US facilities before final deployment.

One Amazon email projected the company would take delivery of about $5 billion of Nvidia GB300 racks in August, followed by another roughly $3 billion each month "for the foreseeable future."

Some AWS data center sites had room for more racks but not enough available power to turn them on, people familiar with the effort said, leaving the equipment to be staged at intermediary warehouses until the facilities were ready. These people asked not to be identified discussing sensitive matters.

Timing and coordination

Usually, Amazon doesn't pay for racks until the gear is put into a data center, leaving suppliers to carry the cost of the equipment in transit, according to the internal documents obtained by Business Insider. This helps the company conserve cash.

However, the intensity of the AI data center building boom has made this type of coordination harder. Amazon has to compete more for scarce resources as it jockeys with rivals for access to Nvidia GPUs and other AI components.

Under the new "Early Rack Receipt" process, Amazon now takes ownership of these racks earlier in the supply chain, rather than waiting until the equipment reaches a data center.

The means spending cash sooner. And any delays getting the racks installed and plugged into a reliable power source potentially pushes back the moment when revenue starts flowing from these assets.

At least one AWS supply chain team did not have "a clear forecasted path" for getting racks into data centers, according to one of the emails reviewed by Business Insider.

An Amazon spokesperson said the company routinely stages finished hardware near deployment sites so it can be installed once power capacity is available, calling that approach "best business practice."

The spokesperson added that AWS has "long-established systems" to track infrastructure assets and disputed that the broader company lacks a forecasted path for getting racks into data centers.

This problem is not unique to Amazon.

Bernstein analysts wrote in a recent note that power permits, cooling systems, electrical equipment, construction, and hardware all move on separate schedules.

"Timing is imperfect," the analysts said.

"Inherently uncertain"

John Felton, Chief Financial Officer of Amazon Web Services

Chris Jung/NurPhoto via Getty Images

During the internal staff meeting in September, Felton, the AWS CFO, described the broader problem eloquently: "How do you work in the future when the future is inherently uncertain?"

Kalyanaraman, the AI infrastructure leader, said Amazon's internal outlook for the return on its AI investments had improved. But the assumptions behind those returns keep shifting.

"The forecast is changing on a daily basis," Kalyanaraman said. "The world that we live in is extremely dynamic."

Those shifting assumptions include when data centers will be ready and how much equipment AWS needs to keep on hand, he explained.

An eight-week supply buffer might be routine for a smaller company. But at Amazon's scale, Kalyanaraman said, this could mean holding "billions and billions of dollars" worth of additional equipment inventory — tying up precious cash.

Frugality meets the AI boom

Such tensions are especially striking for Kalyanaraman, a 21-year Amazon veteran who earlier this year was promoted to the elite S-team that reports directly to Jassy.

Amazon's founding story is defined by frugality. It famously used cheap doors as desks when founder Jeff Bezos started in Seattle in the mid-90s.

Kalyanaraman has absorbed this lore into bones. In late 2023, as AWS faced slower growth and layoffs, he urged employees to do more with less. "Frugality breeds innovation," he said back then.

That instinct still shapes his approach. In the September meeting this year, Kalyanaraman told Felton that AWS tries to make major investments at the "last responsible moment," when it has the clearest possible view of demand.

"If we can wait to spend the capital as late as possible, it's better for us," he said.

Amazon CEO Andy Jassy

Bloomberg/Getty Images

But the frenetic pace of the AI boom makes this principle difficult to follow. By the time demand is fully visible, the servers, power, and construction capabilities that AWS needs may no longer be available. That puts pressure on the company to commit more money sooner to secure supply and meet its data center capacity goals.

Kalyanaraman recalled telling Jassy in 2023 that AWS would "surely" be out of its capacity crunch by 2027. Instead, Amazon still expects demand to exceed its available capacity in 2027, the AI infrastructure chief said during the meeting this September.

Secured Power at Risk

Getting enough electricity may be the biggest challenge for an industry leader like Amazon.

The company has 44 gigawatts of data center capacity under development across 16 states, more than double Google, Meta, and Microsoft, according to Cleanview Research estimates.

An internal AWS dashboard called "Secured Power at Risk" tracks utility and regulatory constraints affecting electricity capacity AWS has lined up for its data centers.

The risks include transmission bottlenecks, requirements to reduce use during grid stress, and "use it or lose it" provisions that can jeopardize capacity if a data center project misses usage or construction milestones.

In other words, AWS is not simply waiting for electricity to arrive. It is managing a portfolio of commitments that can become more costly if a data center project is delayed.

Maryland proposals

A submission to Maryland's utility regulator last year, obtained through a public records request, illustrates the kind of exposure that can accompany massive data center buildouts.

Amazon told the Maryland Public Service Commission that large data center customers could help pay for grid upgrades or bring new power capacity to market without burdening other electricity ratepayers.

The company also proposed setting aside collateral to help utilities get more comfortable with the large investments needed to generate more electricity for data centers. Amazon proposed three years of collateral so that if a large electricity customer abandoned unused capacity, the utility would have time to re-sell the power.

The proposal is not evidence that AWS has made such a payment or posted collateral. It does, however, show that large data centers can face extra financial obligations, beyond their own electricity bills, if projects are delayed or cancelled.

The Amazon spokesperson said such utility rules are not unique to AWS. The company has not disclosed how much cash it has paid upfront to secure power.

New constraints 'keep popping up'

The AI buildout also incurs expenses that are harder to model than a conventional capex plan.

In the September meeting this year, Kalyanaraman said that while reviewing plans for gigawatts of capacity in West Texas, AWS confronted a labor problem: There weren't enough nearby pipefitters, electricians, and other skilled workers to build the facilities.

The company's response, he said, was to pay to construct housing complexes near its data centers so workers could live there for the two or three years needed to complete the projects.

Even the crates used to ship servers have become a planning issue. It may seem absurd to worry about the price of a container when servers cost hundreds of thousands of dollars, Kalyanaraman said. But at AWS's scale, where the company needs so many crates, even trivial items can become a material expense.

"We have new constraints that keep popping up," Kalyanaraman said.

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Elon Musk says he'll give every child in America a share in SpaceX

Elon Musk announced on X that he intends to give every child in America a SpaceX share.

Finn Gomez/Getty Images

• Elon Musk says he'll give a SpaceX share to every child in the US next year.
• That would be a $10.5 billion gift based on SpaceX's stock price and roughly 72 million recipients.
• Musk said this would be the "first of many" SpaceX share giveaways but didn't offer further details.

Elon Musk says he'll give every child in the US a piece of his space company, a gift worth around $10.5 billion today.

"Next year, I will give one of my SpaceX shares to every kid in America," Musk wrote in an early Monday post on X. "This will be the first of many."

There are roughly 72 million children in the US based on 2025 census data, and SpaceX stock closed at $146 on Friday. If Musk donated 72 million shares today they would be worth around $10.5 billion.

Musk didn't provide any further details on how the giveaway would work, such as eligibility criteria or specific timing, or whether the shares will be transferred to Trump Accounts.

The Tesla and SpaceX CEO is the world's richest person with an estimated $904 billion net worth as of Friday's close, per the Bloomberg Billionaires Index.

SpaceX — the company behind Falcon rockets, Starship launch vehicles, Starlink satellites, AI chatbot Grok, and X — went public this summer and has about a $2 trillion market capitalization.

Excluding restricted shares and options, Musk owns 4.77 billion SpaceX shares for about a 36% stake, worth just under $700 billion at Friday's close. The rest of his fortune largely comprises his stakes in his other companies, including Tesla, Neuralink, and The Boring Company.

Donating 72 million shares would reduce Musk's number of SpaceX shares by 1.5%. If, as indicated in his X post, he follows that up with further giveaways, his stake could shrink significantly.

Musk's pledge is part of a broader trend of gifting shares to America's children, aimed at ensuring they all own a piece of the stock market and reap its gains over time, and benefit from a lifetime of compounding wealth.

The Trump administration launched Trump Accounts — tax-advantaged investment accounts — for eligible children this summer, with those born between 2025 and 2028 receiving a $1,000 federal seed deposit. Numerous companies have agreed to contribute to them as well.

Michael and Susan Dell contributed $250 to 25 million American children's Trump Accounts earlier this month, a gift totaling $6.25 billion that was allocated first to those in the lowest-income ZIP codes.

SpaceX President Gwynne Shotwell and her husband pledged in July to give SpaceX shares to more than 2 million children.

Correction: October 19, 2026 — An earlier version of this story incorrectly described SpaceX as a private company. It went public in June 2026.

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Smoke Signals: The dangerous fatalism of AGI in Silicon Valley

Getty Images; Tyler Le/BI

Last week, Palantir CTO Shyam Sankar mentioned something bizarre in an interview on CBS News. "So many AI researchers have started smoking as a way of signaling to other researchers how much they believe in AI," he said. Their thinking, he said, goes like this: "I believe so much in AI that it's going to cure cancer. So I'm showing you my chips are all in."

I laughed as I read the quote. It read like a headline in The Onion, mocking the blind optimism of the AI-pilled. But then I felt sad and worried for them. Are they smoking because they believe AI is saving the world, I wondered, or because they believe AI is ending it?

It's been an especially alarming few months here in San Francisco. OpenAI's bots went rogue and hacked another company, and then an Anthropic researcher quit, warning that AI could wipe out the human race. It seemed more believable to me that these researchers were smoking because they didn't think they'd be around for much longer — or at least freaked out about that possibility. I thought of the HBO show "The Leftovers," which features a doomsday cult that chain-smokes. Because they believe the world has ended, they don't mind obliterating their lungs. They're living as though they're already dead.

I asked a handful of people who work in AI and none of them knew anyone who had suddenly taken up cigarettes because of AI. So I don't think what Sankar observed is widespread. But in a story last month about tech founders who smoke, my colleague Henry Chandonnet quoted a guy who wasn't worried about his habit because he believed AI will soon cure lung cancer. Among the people I spoke to, a few recognized that underlying sentiment: AI's going to fix (or destroy) everything, so YOLO. Last year, my former colleague Rob Price reported on these attitudes. Some were spending down their savings. Others were taking dangerous drugs and having orgies. Last year, my former colleague Rob Price reported on these attitudes. Some were spending down their savings. Others were taking dangerous drugs and having orgies.

While AI boomers and doomers expect completely opposite outcomes, I've found it interesting that their very different beliefs often end up manifesting as the same behaviors. Smoke or don't smoke, it doesn't matter: The future is inevitable. In either case, they're relinquishing their fate to a humanity-ending or humanity-saving AI — and ignoring one of the most evidence-backed things they can do to live a healthy future. It's a kind of fatalism, believing that what you do won't change what happens next.

I see traces of that in so many corners of society. What's the point of studying, students say, if they're never going to be as good as ChatGPT at coding or math? What's the point of agonizing over a breakup text, people say, if a bot can write it for them? What's the point of working hard, employees say, if their companies are going to replace them with an agent? In a recent survey by Verasight, 78% felt that they had little or no say over how AI is being developed and regulated.

Even the people who have the most say don't seem to believe they do. Anthropic CEO Dario Amodei has issued increasingly grave warnings about the technology that he himself is creating. He has to keep going, he says, because if he doesn't, a less responsible steward of the industry will. Amodei and his peers sound as if they're utterly powerless in the face of an unstoppable god. If it's really that bad, couldn't they just pull the plug? "Saturday Night Live" captured the strangeness of it all in a recent sketch impersonating Amodei. "If we can pressure lawmakers to create guardrails," Jane Wickline's Amodei deadpanned, "we will be able to stop me."

We need people thinking seriously about the risks of these technologies, and we also need people dreaming big about the immense good they can bring. But neither of these outcomes is inevitable. As we entrust more and more of our work and our lives to AI agents, we shouldn't cede our own agency to them too. I'm not taking up smoking anytime soon.

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