Ego, Fear and Money - How the A.I.
Fuse Was Lit
The people who were most afraid of the risks of
artificial intelligence decided they should be the ones to build it. Then
distrust fueled a spiraling
competition.
Elon Musk celebrated
his 44th birthday in July 2015 at a three-day party thrown by his wife at a California
wine country resort dotted with cabins. It was family and friends only, with children
racing around the upscale property in Napa Valley.
This was years before
Twitter became X and Tesla had a profitable year. Mr. Musk and his wife, Talulah Riley — an actress who played a beautiful but dangerous
robot on HBO’s science fiction series “Westworld” — were a year from throwing in
the towel on their second marriage. Larry Page, a party guest, was still the chief
executive of Google. And artificial intelligence had pierced the public consciousness
only a few years before, when it was used to identify cats on YouTube — with 16
percent accuracy.
A.I. was the big
topic of conversation when Mr. Musk and Mr. Page sat down near a firepit beside
a swimming pool after dinner the first night. The two billionaires had been friends
for more than a decade, and Mr. Musk sometimes joked that he occasionally crashed
on Mr. Page’s sofa after a night playing video games.
But the tone that
clear night soon turned contentious as the two debated whether artificial intelligence
would ultimately elevate humanity or destroy it.
As the discussion
stretched into the chilly hours, it grew intense, and some of the more than 30 partyers
gathered closer to listen. Mr. Page, hampered for more than a decade by an unusual
ailment in his vocal cords, described his vision of a digital utopia in a whisper.
Humans would eventually merge with artificially intelligent machines, he said. One
day there would be many kinds of intelligence competing for resources, and the best
would win.
If that happens,
Mr. Musk said, we’re doomed. The machines will destroy humanity.
With a rasp of frustration,
Mr. Page insisted his utopia should be pursued. Finally
he called Mr. Musk a “specieist,” a person who favors humans over the digital life-forms of the future.
That insult, Mr.
Musk said later, was “the last straw.”
Many in the crowd
seemed gobsmacked, if amused, as they dispersed for the night, and considered it
just another one of those esoteric debates that often break out at Silicon Valley
parties.
But eight years
later, the argument between the two men seems prescient. The question of whether
artificial intelligence will elevate the world or destroy it — or at least inflict
grave damage — has framed an ongoing debate among Silicon Valley founders, chatbot
users, academics, legislators and regulators about whether the technology should
be controlled or set free.
That debate has
pitted some of the world’s richest men against one another: Mr. Musk, Mr. Page,
Mark Zuckerberg of Meta, the tech investor Peter Thiel,
Satya Nadella of Microsoft and Sam Altman of OpenAI. All
have fought for a piece of the business — which one day could be worth trillions
of dollars — and the power to shape it.
At the heart of
this competition is a brain-stretching paradox. The people who say they are most
worried about A.I. are among the most determined to create it and enjoy its riches.
They have justified their ambition with their strong belief that they alone can
keep A.I. from endangering Earth.
Mr. Musk and Mr.
Page stopped speaking soon after the party that summer. A few weeks later, Mr. Musk
dined with Mr. Altman, who was then running a tech incubator, and several researchers
in a private room at the Rosewood hotel in Menlo Park, Calif., a favored deal-making spot close to the venture capital offices
of Sand Hill Road.
That dinner led
to the creation of a start-up called OpenAI later in the
year. Backed by hundreds of millions of dollars from Mr. Musk and other funders,
the lab promised to protect the world from Mr. Page’s vision.
Thanks to its ChatGPT chatbot, OpenAI has fundamentally
changed the technology industry and has introduced the world to the risks and potential
of artificial intelligence. OpenAI is valued at more than
$80 billion, according to two people familiar with the company’s latest funding
round, though Mr. Musk and Mr. Altman’s partnership didn’t make it. The two have
since stopped speaking.
“There is disagreement,
mistrust, egos,” Mr. Altman said. “The closer people are to being pointed in the
same direction, the more contentious the disagreements are. You see this in sects
and religious orders. There are bitter fights between the closest people.”
Last month, that
infighting came to OpenAI’s boardroom. Rebel board members
tried to force out Mr. Altman because, they believed, they could no longer trust
him to build A.I. that would benefit humanity. Over five chaotic days OpenAI looked as if it were going to fall apart, until the board
— pressured by giant investors and employees who threatened to follow Mr. Altman
out the door — backed down.
The drama inside
OpenAI gave the world its first glimpse of the bitter
feuds among those who will determine the future of A.I.
But years before
OpenAI’s near meltdown, there was a little-publicized
but ferocious competition in Silicon Valley for control of the technology that is
now quickly reshaping the world, from how children are taught to how wars are fought.
The New York Times spoke with more than 80 executives, scientists and entrepreneurs,
including two people who attended Mr. Musk’s birthday party in 2015, to tell that
story of ambition, fear and money.
The Birth of
DeepMind
Five years before
the Napa Valley party and two before the cat breakthrough on YouTube, Demis Hassabis, a 34-year-old neuroscientist, walked into a
cocktail party at Peter Thiel’s San Francisco townhouse
and realized he’d hit pay dirt. There in Mr. Thiel’s living
room, overlooking the city’s Palace of Fine Arts and a swan pond, was a chess board.
Dr. Hassabis had once been the second-best player in the
world in the under-14 category.
“I was preparing
for that meeting for a year,” Dr. Hassabis said. “I thought
that would be my unique hook in: I knew that he loved chess.”
In 2010, Dr. Hassabis and two colleagues, who all lived in Britain, were
looking for money to start building “artificial general intelligence,” or A.G.I.,
a machine that could do anything the brain could do. At the time, few people were
interested in A.I. After a half century of research, the artificial intelligence
field had failed to deliver anything remotely close to the human brain.
Still, some scientists
and thinkers had become fixated on the downsides of A.I. Many, like the three young
men from Britain, had a connection to Eliezer Yudkowsky,
an internet philosopher and self-taught A.I. researcher. Mr. Yudkowsky was a leader in a community of people who called themselves
Rationalists or, in later years, effective altruists.
They believed that
A.I. could find a cure for cancer or solve climate change, but they worried that
A.I. bots might do things their creators had not intended. If the machines became
more intelligent than humans, the Rationalists argued, the machines could turn on
their creators.
Mr. Thiel had become enormously wealthy through an early investment
in Facebook and through his work with Mr. Musk in the early days of PayPal. He had
developed a fascination with the singularity, a trope of science fiction that describes
the moment when intelligent technology can no longer be controlled by humanity.
With funding from
Mr. Thiel, Mr. Yudkowsky had
expanded his A.I. lab and created an annual conference on the singularity. Years
before, one of Dr. Hassabis’s two colleagues had met Mr.
Yudkowsky, and he snagged them speaking spots at the conference,
ensuring they’d be invited to Mr. Thiel’s party.
Mr. Yudkowsky introduced Dr. Hassabis
to Mr. Thiel. Dr. Hassabis assumed
that lots of people at the party would be trying to squeeze their host for money.
His strategy was to arrange another meeting. There was a deep tension between the
bishop and the knight, he told Mr. Thiel. The two pieces
carried the same value, but the best players understood that their strengths were
vastly different.
It worked. Charmed,
Mr. Thiel invited the group back the next day, where they
gathered in the kitchen. Their host had just finished his morning workout and was
still sweating in a shiny tracksuit. A butler handed him a Diet Coke. The three
made their pitch, and soon Mr. Thiel and his venture capital
firm agreed to put 1.4 million British pounds (roughly $2.25 million) into their
start-up. He was their first major investor.
They named their
company DeepMind, a nod to “deep learning,” a way for A.I. systems to learn skills
by analyzing large amounts of data; to neuroscience; and
to the Deep Thought supercomputer from the sci-fi novel “The Hitchhiker’s Guide
to the Galaxy.” By the fall of 2010, they were building their dream machine. They
wholeheartedly believed that because they understood the risks, they were uniquely
positioned to protect the world.
“I don’t see this
as a contradictory position,” said Mustafa Suleyman, one of the three DeepMind founders.
“There are huge benefits to come from these technologies. The goal is not to eliminate
them or pause their development. The goal is to mitigate the downsides.”
Having won over
Mr. Thiel, Dr. Hassabis worked
his way into Mr. Musk’s orbit. About two years later, they met at a conference organized
by Mr. Thiel’s investment fund, which had also put money
into Mr. Musk’s company SpaceX. Dr. Hassabis secured a
tour of SpaceX headquarters. Afterward, with rocket hulls hanging from the ceiling,
the two men lunched in the cafeteria and talked.
Mr. Musk explained
that his plan was to colonize Mars to escape overpopulation and other dangers on
Earth. Dr. Hassabis replied that the plan would work —
so long as superintelligent machines didn’t follow and
destroy humanity on Mars, too.
Mr. Musk was speechless.
He hadn’t thought about that particular danger. Mr. Musk soon invested in DeepMind
alongside Mr. Thiel so he could be closer to the creation
of this technology.
Flush with cash,
DeepMind hired researchers who specialized in neural networks, complex algorithms
created in the image of the human brain. A neural network is essentially a giant
mathematical system that spends days, weeks or even months identifying patterns
in large amounts of digital data. First developed in the 1950s, these systems could
learn to handle tasks on their own. After analyzing names
and addresses scribbled on hundreds of envelopes, for instance, they could read
handwritten text.
DeepMind took the
concept further. It built a system that could learn to play classic Atari games
like Space Invaders, Pong and Breakout to illustrate what was possible.
This got the attention
of another Silicon Valley powerhouse, Google, and specifically Larry Page. He saw
a demonstration of Deep Mind’s machine playing Atari games. He wanted in.
The Talent
Auction
In the fall of 2012,
Geoffrey Hinton, a 64-year-old professor at the University of Toronto, and two graduate
students published a research paper that showed the world what A.I. could do. They
trained a neural network to recognize common objects like flowers, dogs and
cars.
Scientists were
surprised by the accuracy of the technology built by Dr.
Hinton and his students. One who took particular notice was Yu Kai, an A.I. researcher
who had met Dr. Hinton at a research conference and had
recently started working for Baidu, the giant Chinese internet company. Baidu offered
Dr. Hinton and his students $12 million to join the company
in Beijing, according to three people familiar with the offer.
Dr. Hinton turned Baidu down, but the money
got his attention.
The Cambridge-educated
British expatriate had spent most of his career in academia, except for occasional
stints at Microsoft and Google, and was not especially driven by money. But he had
a neurodivergent child, and the money would mean financial security.
“We did not know
how much we were worth,” Dr. Hinton said. He consulted
lawyers and experts on acquisitions and came up with a plan: “We would organize
an auction, and we would sell ourselves.” The auction would take place during an
annual A.I. conference at the Harrah’s hotel and casino on Lake Tahoe.
Big Tech took notice.
Google, Microsoft, Baidu and other companies were beginning to believe that neural
networks were a path to machines that could not only see, but hear, write, talk
and — eventually — think.
Mr. Page had seen
similar technology at Google Brain, his company’s A.I. lab, and he thought Dr. Hinton’s research could elevate his scientists’ work. He
gave Alan Eustace, Google’s senior vice president of engineering, what amounted
to a blank check to hire any A.I. expertise he needed.
Mr. Eustace and
Jeff Dean, who led the Brain lab, flew to Lake Tahoe and took Dr. Hinton and his students out to dinner at a steakhouse inside
the hotel the night before the auction. The smell of old cigarettes was overpowering,
Dr. Dean recalled. They made the case for coming to work
at Google.
The next day, Dr. Hinton ran the auction from his hotel room. Because of an
old back injury, he rarely sat down. He turned a trash can upside down on a table,
put his laptop on top and watched the bids roll in over the next two days.
Google made an offer.
So did Microsoft. DeepMind quickly bowed out as the price went up. The industry
giants pushed the bids to $20 million and then $25 million, according to documents
detailing the auction. As the price passed $30 million, Microsoft quit, but it rejoined the bidding at $37 million.
“We felt like we
were in a movie,” Dr. Hinton said.
Then Microsoft dropped
out a second time. Only Baidu and Google were left, and they pushed the bidding
to $42 million, $43 million. Finally, at $44 million, Dr.
Hinton and his students stopped the auction. The bids were still climbing, but they
wanted to work for Google. And the money was staggering.
It was an unmistakable
sign that deep-pocketed companies were determined to buy the most talented A.I.
researchers — which was not lost on Dr. Hassabis at DeepMind.
He had always told his employees that DeepMind would remain an independent company.
That was, he believed, the best way to ensure its technology didn’t turn into something
dangerous.
But as Big Tech
entered the talent race, he decided he had no choice: It was time to sell.
By the end of 2012,
Google and Facebook were angling to acquire the London lab, according to three people
familiar with the matter. Dr. Hassabis and his co-founders
insisted on two conditions: No DeepMind technology could be used for military purposes,
and its A.G.I. technology must be overseen by an independent board of technologists
and ethicists.
Google offered $650
million. Mark Zuckerberg of Facebook offered a bigger payout
to DeepMind’s founders, but would not agree to the conditions. DeepMind sold to
Google.
Mr. Zuckerberg was
determined to build an A.I. lab of his own. He hired Yann LeCun,
a French computer scientist who had also done pioneering A.I. research, to run it.
A year after Dr. Hinton’s auction, Mr. Zuckerberg and
Dr. LeCun flew to Lake Tahoe
for the same A.I. conference. While padding around a suite at the Harrah’s casino
in his socks, Mr. Zuckerberg personally interviewed top researchers, who were soon
offered millions of dollars in salary and stock.
A.I. was once laughed
off. Now the richest men in Silicon Valley were shelling out billions to keep from
being left behind.
The Lost
Ethics Board
When Mr. Musk invested
in DeepMind, he broke his own informal rule — that he would not invest in any company
he didn’t run himself. The downsides of his decision were already apparent when,
only a month or so after his birthday spat with Mr. Page, he again found himself
face to face with his former friend and fellow billionaire.
The occasion was
the first meeting of DeepMind’s ethics board, on Aug. 14, 2015. The board had been
set up at the insistence of the start-up’s founders to ensure that their technology
did no harm after the sale. The members convened in a conference room just outside
Mr. Musk’s office at SpaceX, with a window looking out onto his rocket factory,
according to three people familiar with the meeting.
But that’s where
Mr. Musk’s control ended. When Google bought DeepMind, it bought the whole thing.
Mr. Musk was out. Financially he had come out ahead, but he was unhappy.
Three Google executives
now firmly in control of DeepMind were there: Mr. Page; Sergey Brin, a Google co-founder
and Tesla investor; and Eric Schmidt, Google’s chairman. Among the other attendees
were Reid Hoffman, another PayPal founder, and Toby Ord, an Australian philosopher
studying “existential risk.”
The DeepMind founders
reported that they were pushing ahead with their work, but that they were aware
the technology carried serious risks.
Mr. Suleyman, the
DeepMind co-founder, gave a presentation called “The Pitchforkers
Are Coming.” A.I. could lead to an explosion in disinformation, he told the board.
He fretted that as the technology replaced countless jobs in the coming years, the
public would accuse Google of stealing their livelihoods. Google would need to share
its wealth with the millions who could no longer find work and provide a “universal
basic income,” he argued.
Mr. Musk agreed.
But it was pretty clear that his Google guests were not prepared to embark on a
redistribution of (their) wealth. Mr. Schmidt said he thought the worries were completely
overblown. In his usual whisper, Mr. Page agreed. A.I. would create more jobs than
it took away, he argued.
Eight months later,
DeepMind had a breakthrough that stunned the A.I community and the world. A DeepMind
machine called AlphaGo beat one of the world’s best players at the ancient game
of Go. The game, streamed over the internet, was watched by 200 million people across
the globe. Most researchers had assumed that A.I. needed another 10 years to muster
the ingenuity to do that.
Rationalists, effective
altruists and others who worried about the risks of A.I. claimed the computer’s
win validated their fears.
“This is another
indication that A.I. is progressing faster than even many experts anticipated,”
Victoria Krakovna, who would soon join DeepMind as an
“A.I. safety” researcher, wrote in a blog post.
DeepMind’s founders
were increasingly worried about what Google would do with their inventions. In 2017,
they tried to break away from the company. Google responded by increasing the salaries
and stock award packages of the DeepMind founders and their staff. They stayed put.
The ethics board
never had a second meeting.
The Breakup
Convinced that Mr.
Page’s optimistic view of A.I. was dead wrong, and angry at his loss of DeepMind,
Mr. Musk built his own lab.
OpenAI was founded in late 2015, just a few months
after he met with Sam Altman at the Rosewood hotel in Silicon Valley. Mr. Musk pumped
money into the lab, and his former PayPal buddies, Mr. Hoffman and Mr. Thiel, came along for the ride. The three men and others pledged
to put $1 billion into the project, which Mr. Altman, who was 30 at the time, would
help run. To get them started, they poached Ilya Sutskever
from Google. (Dr. Sutskever
was one of the graduate students Google “bought” in Dr.
Hinton’s auction.)
Initially, Mr. Musk
wanted to operate OpenAI as a nonprofit,
free from the economic incentives that were driving Google and other corporations.
But by the time Google wowed the tech community with its Go stunt, Mr. Musk was
changing his mind about how it should be run. He desperately wanted OpenAI to invent something that would capture the world’s imagination
and close the gap with Google, but it wasn’t getting the job done as a nonprofit.
In late 2017, he
hatched a plan to wrest control of the lab from Mr. Altman and the other founders
and transform it into a commercial operation that would join forces with Tesla and
rely on supercomputers the car company was developing, according to four people
familiar with the matter.
When Mr. Altman
and others pushed back, Mr. Musk quit and said he would focus on his own A.I.
work at Tesla. In February 2018, he announced his departure to OpenAI’s staff on the top floor of the start-up’s offices in
a converted truck factory, three people who attended the meeting said. When he said
that OpenAI needed to move faster, one researcher retorted
at the meeting that Mr. Musk was being reckless.
Mr. Musk called
the researcher a “jackass” and stormed out, taking his deep pockets with him.
OpenAI suddenly needed new financing in a hurry.
Mr. Altman flew to Sun Valley for a conference and ran into Satya Nadella, Microsoft’s
chief executive. A tie-up seemed natural. Mr. Altman knew Microsoft’s chief technology
officer, Kevin Scott. Microsoft had bought LinkedIn from Mr. Hoffman, an OpenAI board member. Mr. Nadella told Mr. Scott to get it done.
The deal closed in 2019.
Mr. Altman and OpenAI had formed a for-profit company under the original nonprofit, they had $1 billion in fresh capital, and Microsoft
had a new way to build artificial intelligence into its vast cloud computing service.
Not everyone inside
OpenAI was happy.
Dario Amodei, a researcher with ties to the effective altruist community,
had been on hand at the Rosewood hotel when OpenAI was
born. Dr. Amodei, who endlessly
twisted his curls between his fingers as he talked, was leading the lab’s efforts
to build a neural network called a large language model that could learn from enormous
amounts of digital text. By analyzing countless Wikipedia
articles, digital books and message boards, it could generate text on its own. It
also had the unfortunate habit of making things up. It was called GPT-3, and it
was released in the summer of 2020.
Researchers inside
OpenAI, Google and other companies thought this rapidly
improving technology could be a path to A.G.I.
But Dr. Amodei was unhappy about the Microsoft
deal because he thought it was taking OpenAI in a really
commercial direction. He and other researchers went to the board to try to push
Mr. Altman out, according to five people familiar with the matter. After they failed,
they left. Like DeepMind’s founders before them, they worried that their new corporate
overlords would favor commercial interests over safety.
In 2021, the group
of about 15 engineers and scientists created a new lab called Anthropic. The plan
was to build A.I. the way the effective altruists thought it should done — with very tight controls.
“There was no attempt
to remove Sam Altman from OpenAI by the co-founders of
Anthropic,” said an Anthropic spokeswoman, Sally Aldous. “The co-founders themselves
came to the conclusion that they wished to depart OpenAI
to start their own company, made this known to OpenAI’s
leadership, and over several weeks negotiated an exit on mutually agreeable terms.”
Anthropic accepted
a $4 billion investment from Amazon and another $2 billion from Google two years
later.
The Reveal
After OpenAI received another $2 billion from Microsoft, Mr. Altman
and another senior executive, Greg Brockman, visited Bill Gates at his sprawling
mansion on the shores of Lake Washington, outside Seattle. The Microsoft founder
was no longer involved in the company day to day but kept in regular touch with
its executives.
Over dinner, Mr.
Gates told them he doubted that large language models could work. He would stay
skeptical, he said, until the technology performed a task
that required critical thinking — passing an A.P. biology test, for instance.
Five months later,
on Aug. 24, 2022, Mr. Altman and Mr. Brockman returned and brought along an OpenAI researcher named Chelsea Voss. Ms. Voss had been a medalist in an international biology Olympiad as a high schooler.
Mr. Nadella and other Microsoft executives were there, too.
On a huge digital
display on a stand outside Mr. Gates’s living room, the OpenAI
crew presented a technology called GPT-4.
Mr. Brockman gave
the system a multiple-choice advanced biology test, and Ms. Voss graded the answers.
The first question involved polar molecules, groups of atoms with a positive charge
at one end and a negative charge at the other. The system answered correctly and
explained its choice. “It was only trained to provide an answer,” Mr. Brockman said.
“The conversational nature kind of fell out, almost magically.” In other words,
it was doing things they hadn’t really designed it to do.
There were 60 questions.
GPT-4 got only one answer wrong.
Mr. Gates sat up
in his chair, his eyes opened wide. In 1980, he had a similar reaction when researchers
showed him the graphical user interface that became the basis for the modern personal
computer. He thought GPT was that revolutionary.
By October, Microsoft
was adding the technology across its online services, including its Bing search
engine. And two months later OpenAI released its ChatGPT chatbot, which is now used by 100 million people every
week.
OpenAI had beat the effective altruists at Anthropic.
Mr. Page’s optimists at Google scurried to release their own chatbot, Bard, but
were widely perceived to have lost the race to OpenAI.
Three months after ChatGPT’s release, Google stock was
down 11 percent. Mr. Musk was nowhere to be found.
But it was just
the beginning.