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Space Exploration

Just sayin': After SpaceX went public Mush became the world's 1st "Trillionaire"; however, a lot of SpaceX employees became "millionaires" too.

SpaceX’s I.P.O. Could Turn 4,400 Employees Into Millionaires

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While Elon Musk may soon become a trillionaire, his rocket company’s market debut is set to change the lives of its current and former employees, too.

As Trevor Hise was getting ready to graduate from college in 2011, his parents wanted him to take what they saw as a stable job at General Electric. But Mr. Hise had landed an internship at a start-up he loved. Against his parents’ advice, he stayed for a full-time job at that young company for the next 12 years.

The start-up was Elon Musk’s SpaceX.

Today, Mr. Hise has more than 100,000 SpaceX shares that he earned from his time working there. With the rocket maker expected to go public this week at $135 a share, Mr. Hise’s SpaceX stock is likely worth at least $13.5 million — a sum that has left him in disbelief.

“The magnitude of this has been ridiculous,” said the 37-year-old, who worked as a SpaceX launch engineer and now considers himself semiretired.

SpaceX’s journey to the stock market has been defined by a series of superlatives. It is the biggest-ever initial public offering of the most dominant space company by the world’s richest man. And it is set to unleash generational wealth if its shares soar in its trading debut at the whopping valuation of $1.77 trillion, five times the market capitalization of General Electric.

SpaceX’s I.P.O. is expected to make a lot of rich people even richer. First in the queue is Mr. Musk, 54, who is likely to become the world’s first trillionaire. His friends, along with Silicon Valley venture capitalists, private investment firms and others who put money into the company, are also set to reap billions.

But one group will gain life-changing wealth for the first time: SpaceX’s current and former employees. The company has 22,000 employees, and hundreds more left over the years. Some were hourly blue-collar workers who toiled at launch sites; others sat for days straight in once-windowless offices at SpaceX’s industrial complex in South Texas. For many, their work is about to pay off big through the stock that was part of their compensation.

More than 4,400 current and former SpaceX employees are likely to become millionaires in the I.P.O., according to an analysis by Hill.com, a San Francisco-based investment platform. Of those, about 400 are expected to earn $100 million or more.
With most I.P.O.s, “you’re usually only going to see the founders become billionaires,” said Andrew Benson, the founder and chief executive of Hill.com, which has facilitated the trading of private SpaceX shares. “It’s uncommon to have 400 people at that threshold” of $100 million, he added. “It speaks to the enormous wealth that’s being created here.”

A SpaceX spokesman did not return a request for comment.

Among SpaceX’s former employees, one winner is Gavin Petit, 42, who joined the company in 2012 as an engineer who oversaw launches. At the time, SpaceX awarded him several thousand shares on top of his $80,000 salary. Each share was worth $13.80, Mr. Petit said.

Over the years, Mr. Petit chose to take his company bonuses in more shares. That was considered risky because SpaceX’s rockets were unproven and sometimes failed. It was not clear his job would survive, Mr. Petit said. It also meant he had to stay at the company for five or more years until all his shares “vested” and were earned over time.

Mr. Petit sometimes sold his SpaceX shares in biannual “liquidity events,” where employees could sell their private shares to other buyers. Those sales helped him pay off his house in Denver. But he mostly held on to his stock and has more than 50,000 shares, enough to make him a millionaire several times over.

Mr. Petit, who left SpaceX in 2023 to work at Katalyst Space Technologies, a robotic spacecraft company, said he was not sure what he would do with his wealth or whether he would sell his shares. Like most companies that go public, SpaceX restricts when employees can sell after an I.P.O., according to its financial filings.
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Former SpaceX welder becomes a millionaire after historic IPO​

Before Juan Hernandez became a welder at SpaceX, he had never heard of the company.

"It was just another contract job for me at the time," he told CBS News correspondent Jo Ling Kent in a broadcast exclusive interview.

Now, just over 10 years later, that leap of faith is paying off following the company's $75 billion initial public offering. Hernandez, who now works at Jeff Bezos-owned rocket startup Blue Origin, has roughly 6,500 SpaceX shares. On Friday, SpaceX stock closed at $160.95, valuing his holdings at $1,046,175.

SpaceX shares started trading on the Nasdaq late Friday morning under the ticker symbol SPCX, marking the long-awaited Wall Street debut of the rocket and satellite company.

Hernandez first heard about SpaceX from a friend who was hired as a welder there. He knew Hernandez's background and figured he'd be a good fit for the job.

"I thought in my head, I don't know what SpaceX is, but let's go," Hernandez said.

When SpaceX hired Hernandez in 2015, he said they offered him $10,000 worth of stock. At the time, he didn't think much of it. His other jobs, for which he was paid hourly, had never offered him stock before.

"It wasn't a big deal. I didn't know anything about it then," he told CBS News. "I didn't know it was gonna be this big, at this point."

Rising through the ranks
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2027 CA DL Kasi Currie (Texas Verbal)

For some reason, didn't view it that way, but am slowly coming into agreement. The pundits can predict, and will also do so, but NIL can change the course of a recruitment. While recruits will say the correct things, underneath it all, hard negotiations take place. And what seems like a great offer, may turn into a 'floor' of negotiations as time progresses.
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Technology Gone Wild: Rise of the Machines

The danger of cognitive surrender
How much should managers let bots do the thinking
Illustration of a man looking at a phone gormlessly. A hand coming out of the top of his head is waving a white flag

Calculators didn’t make everyone innumerate. GPS navigation systems made driving easier. In any conversation about the cognitive effects of artificial intelligence, these two earlier technologies are reasonably likely to come up. Each is a useful entry-point into two big questions. How might AI change the way people think, and should managers do anything in response?
Using calculators and GPS devices are examples of “cognitive offloading”—a deliberate decision to delegate a specific task to technology. In both cases, it has been worth it. Calculators improve students’ mathematical performance, helping to build problem-solving skills and self-confidence. GPS means drivers no longer have to pull over and faff about with maps. It’s harder to get completely lost; it’s easier to avoid terrible traffic.

But there are costs, too. In a 2019 paper, Mark LaCour of the University of Louisiana at Lafayette and his co-authors deliberately programmed calculators to give a group of undergraduates the wrong answers to certain problems. In general they found that there was very little suspicion of slightly inaccurate calculations. Even when answers were patently absurd, some people seemed to accept them without question.

The use of GPS navigation devices can also sap people’s ability to think for themselves. A study conducted by Louisa Dahmani of Harvard Medical School and Véronique Bohbot of McGill University found that greater lifetime use of GPS by drivers was associated with worse spatial memory. Other research shows that pedestrians who navigate with their phones take longer routes and make more stops than physical-map users.

A similar pattern is also visible in online search. Using the internet to look up information is clearly efficient, but there are trade-offs. The “Google effect” refers to a research finding that people have worse recall of information they expect to be able to find online.
AI supercharges these trade-offs. Handing specific tasks to models will often make sense: they are much better than humans at many things. But AI’s range of capabilities, allied to a convenient conversational interface and a seductively confident persona, raises the prospect less of delegation than of wholesale capitulation. Hence “cognitive surrender”, a term coined by Steven Shaw of the Wharton School of the University of Pennsylvania in a recent paper written with his colleague, Gideon Nave.

Messrs Shaw and Nave asked volunteers to answer demanding questions with the assistance of AI, and a little like Mr LaCour’s calculator experiment, randomly introduced errors into the machine’s answers. When the model gave accurate responses, the people using it outperformed a control group of people relying on their own brainpower. When the AI gave the wrong answers, the people using it did much worse than the control group. In other words, people stopped thinking for themselves.

At the moment bosses are more focused on getting employees to use AI than fussing about its effects on how they think. But most employers also value critical thinking: models are still prone to embarrassing errors, for one thing, and novel situations require skilled humans to step in. So it is worth asking what managers can do to encourage cognitive resistance.\

They can deliberately hire workers who enjoy thinking. People with high “need for cognition” (yes, dear reader, that means you) are somewhat, though not entirely, protected against the risk of cognitive surrender, says Mr Shaw. Incentives and feedback can help, too. One of the experiments in his paper introduced monetary rewards for getting things right, and also notified participants during the test whether an item had been answered correctly or not. These techniques encouraged AI users who were being fed the wrong answers to override the model more (though they still did worse than people who relied on their own judgment).

Engineering AI-free periods may have value, too. Another recent study, by Stefanos Poulidis of INSEAD and his co-authors, recruited over 200 chess-club students to train on an AI-assisted platform. Some of the students were automatically given AI tips at a limited number of specific moments; others could click a button at any time to get advice. The students who had on-demand access achieved less than half the performance gains of those who had no say over when they got help. Offloading is fine. Giving up is another matter.■

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Here's a link to the paper for you nerds who actually want to read analyze it:

And for the cool tomato in gumbo type kids, here's a perplexity AI summary of the paper:

Wharton researchers Steven Shaw and Gideon Nave argue that AI is becoming a third kind of cognition, not just a tool for faster thinking. In three preregistered experiments, they found that people often accepted AI answers with little scrutiny, and their performance rose when AI was right but fell when AI was wrong.

They call this pattern cognitive surrender: when users defer judgment and responsibility to AI instead of doing their own reasoning. The paper suggests that AI can boost confidence even after mistakes, and that incentives plus feedback can help people stay more critical.
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