Latest / Elon Musk Podcast / Nadella says Musk never raised concerns to him about Microsoft
Transcript
- 0:00Elon Musk is suing Sam Altman, Greg Brockman and Microsoft for
- 0:04$150 billion, claiming they stole a charitable organization
- 0:08to create an $852 billion artificial intelligence empire.
- 0:14That financial demand is, I mean, it is staggering.
- 0:18And the accusation really strikes at the very foundation
- 0:21of corporate law because, you know, this entire dispute
- 0:24centers around an organization that originally presented itself
- 0:27to the world as a strict nonprofit.
- 0:29The stated goal was purely altruistic, right?
- 0:32The founders declared they were dedicating the organization
- 0:35entirely to protecting humanity from the potential dangers of
- 0:38artificial intelligence. But well, to survive the brutal
- 0:42economic realities of tech development, that organization
- 0:46completely restructured, they adopted A capped profit model,
- 0:49took in billions upon billions of dollars in corporate
- 0:51investment, and transferred all of their valuable intellectual
- 0:54property into a commercial entity.
- 0:56So can a mission to protect humanity actually survive the
- 0:59financial gravity of a trillion dollar technology market?
- 1:03That is the exact tension driving this entire courtroom
- 1:06battle. Yeah.
- 1:07And we have to look at how this started to understand the
- 1:09magnitude of that shift. Elon Musk, the plaintiff here,
- 1:14provided the critical early funding.
- 1:16He donated 10s of millions of dollars to start this artificial
- 1:19intelligence lab. He did, yeah.
- 1:20And he personally helped recruit the initial engineering and
- 1:23research talent too. Right, because the fundamental
- 1:26agreement, the entire premise of the organization, was that this
- 1:29would be a nonprofit open source operation designed specifically
- 1:32to serve as a counterweight to Google's dominance in the tech
- 1:35sector. Exactly.
- 1:37The idea was that if one massive, profit driven
- 1:41corporation controlled the most powerful technology ever
- 1:43created, well, that would be incredibly dangerous for
- 1:46society. So the solution was to create an
- 1:49open research lab that effectively belonged to
- 1:51humanity. You fund it with donations.
- 1:53You publish the research freely for anyone to use, and you keep
- 1:56the profit motive entirely out of the equation.
- 1:59So the engineers can focus on safety rather than quarterly
- 2:02earnings, right? But that philosophical ideal, it
- 2:05immediately crashed into a fundamental physical roadblock.
- 2:09I mean, the astronomical cost of computing power.
- 2:11Greg Brockman, the president of the company, actually testified
- 2:14in court that their internal financial projections showed
- 2:17their computing bills were on track to rise to $50 billion.
- 2:20Wait. Backup.
- 2:22Why does creating this software cost $50 billion?
- 2:26I mean I know no hardware is expensive and semiconductor
- 2:28companies are making a killing right now, but 50 billion is the
- 2:32gross domestic product of a small country.
- 2:35Are they actually buying the physical hardware or just
- 2:38renting server time? How does the math on that even
- 2:41work? Well, it requires looking at
- 2:43what artificial intelligence actually is at a physical level.
- 2:47OK, traditional software is highly efficient.
- 2:49A human being writes specific lines of code, compiling logic
- 2:52into a program that a standard computer can run easily.
- 2:55Yeah, you could run complex traditional software on a basic
- 2:58consumer laptop because the computer is just following
- 3:00predefined instructions. Exactly.
- 3:03But the system this lab was building is fundamentally
- 3:05different. They were building massive
- 3:06neural networks. You do not write the logic for a
- 3:09neural network. You build a blank architecture,
- 3:12and then you force that architecture to process
- 3:15unimaginable amounts of data until it recognizes patterns and
- 3:19forms its own internal logic. So you are basically throwing an
- 3:23entire library of information at a blank wall until the computer
- 3:27learns how to read the books on its own.
- 3:29That is a great way to put it, yeah.
- 3:31And throwing that data requires immense, sprawling physical
- 3:35infrastructure. We are talking about data
- 3:37centers the size of massive shopping malls.
- 3:39Inside those buildings are thousands upon thousands of
- 3:42highly specialized, incredibly expensive servers.
- 3:46Each server contains multiple graphics processing units.
- 3:49These units are designed to perform simple mathematical
- 3:52calculations simultaneously. Millions of calculations
- 3:55happening in parallel billions of times a second.
- 3:57And I am assuming pushing that much data through that many
- 4:01chips requires A tremendous amount of power.
- 4:03Oh, the electricity demands are staggering.
- 4:07A single data center running these training models can
- 4:09consume more electricity than a mid sized city.
- 4:13You have to pull power directly from the grid at an industrial
- 4:16scale. That is wild.
- 4:18But the electricity used to power the chips is only half the
- 4:21equation. Actually, when you run thousands
- 4:24of chips at maximum capacity, they generate an enormous amount
- 4:27of physical heat. Just to keep the machines from
- 4:29literally melting down requires massive industrial cooling
- 4:33systems. You have complex plumbing
- 4:35systems pumping thousands of gallons of chilled water through
- 4:39the server racks continuously. So the infrastructure required
- 4:42just to prevent the building from Catching Fire is a multi
- 4:45$1,000,000 engineering project on its own.
- 4:47Precisely. That makes sense when you were
- 4:49trying to simulate human reasoning.
- 4:51You are pushing electricity through microchips at an
- 4:54unprecedented scale. Right.
- 4:55And during the early days of this lab, one of their major
- 4:58projects involved training an artificial intelligence model to
- 5:01play and beat human champions in highly complex strategic video
- 5:05game tournaments. Oh right, I remember that.
- 5:08Yeah, training a system to process that much visual
- 5:11information, to learn strategy from millions of simulated
- 5:15matches, It requires A continuous, uninterrupted flow
- 5:18of massive computing power. The model plays against itself
- 5:22millions of times a day to learn from its mistakes.
- 5:25You are essentially renting supercomputers by the minute,
- 5:28and the meter is always running. Every single second of training
- 5:32burns through cash. And this physical reality
- 5:35completely limits the viability of purely donor funded research.
- 5:39You simply cannot fund $50 billion in server costs through
- 5:43charitable galas and philanthropic grants.
- 5:45I mean, even the most generous billionaires in the world are
- 5:48not going to write a recurring $50 billion check just to cover
- 5:51a nonprofit's electricity and server rental bills.
- 5:54You hit on the exact mechanism that forced the change.
- 5:56This changes the organization's trajectory entirely.
- 5:59It opens up the absolute necessity for corporate backing.
- 6:02The leadership team looked at the math and realized that to
- 6:05achieve their stated goal of building advanced artificial
- 6:09intelligence diligence well, they had to abandon the pure
- 6:12nonprofit model. The computational requirements
- 6:16forced a transition into a capped profit entity.
- 6:20They needed a structure they could offer a massive financial
- 6:23return to private investors in order to attract the billions of
- 6:27dollars required to rent the service.
- 6:29It's like starting a neighborhood community garden to
- 6:31feed the poor, only to realize that the soil is bad so you need
- 6:34fertilizer. Then the local well runs dry so
- 6:38you need to build a water pipeline.
- 6:39Before you know it, you need to purchase a global agricultural
- 6:43conglomerate just to afford the water bill for your little
- 6:45community plot. That is a very accurate analogy.
- 6:48You start with this pure localized intention to do good,
- 6:52but the physical resource requirements force you to become
- 6:54the exact type of corporate machine you were initially
- 6:57trying to provide a safe alternative to.
- 6:59And, well, the necessity for endless computing power leaves
- 7:02directly into the arms of the one entity that could actually
- 7:05provide it on a global scale. Right, Microsoft.
- 7:08Yes, Microsoft enters the picture.
- 7:10They offer a multibillion dollar investment to keep the
- 7:14artificial intelligence lab alive.
- 7:16However, the structure of this investment is incredibly
- 7:19specific. How so?
- 7:21Microsoft did not just wire billions of dollars of liquid
- 7:24cash into the lab's checking account.
- 7:27The investment was heavily structured around providing
- 7:29cloud computing credits on Microsoft's own proprietary
- 7:33servers. Wait, so Microsoft wasn't just
- 7:35handing over cash, they were basically paying the lab in
- 7:38company store tokens? They give the lab billions in
- 7:41credits, but those credits can only be spent renting
- 7:44Microsoft's own hardware. That is the core of the
- 7:47arrangement. Yeah, the Artificial
- 7:49Intelligence Lab gets the computing power they desperately
- 7:51need to train their models, but they are entirely locked into
- 7:54Microsoft's ecosystem. Oh wow.
- 7:56They tune their software to run efficiently on Microsoft's
- 7:59specific hardware setup. This creates vendor lock in.
- 8:03Which is fascinating because an internal e-mail from a Microsoft
- 8:06executive surfaced during the trial and it shows they knew
- 8:09exactly what was happening behind the scenes.
- 8:11Oh, absolutely. This executive explicitly
- 8:14questioned if the original donors knew that an open source
- 8:17effort to gather top talent was being used to build a closed
- 8:20commercial product on its back. That internal communication is a
- 8:24crucial piece of evidence for the plaintiff.
- 8:27It highlights the ethical and financial realities of this
- 8:30partnership. Microsoft secured a massive
- 8:32equity stake in the newly formed Capped Profit subsidiary, Right?
- 8:36And through this arrangement, Microsoft has already recognized
- 8:39billions of dollars in actual revenue from the partnership
- 8:43because, well, when the lab uses those cloud credits, it
- 8:47registers as consumption on Microsoft's balance sheet,
- 8:50boosting their cloud divisions metrics.
- 8:52So Microsoft gets to report massive usage numbers to Wall
- 8:55Street, which pumps up their own stock price while simultaneously
- 8:59owning a huge chunk of the most valuable artificial intelligence
- 9:02startup in the world. Exactly.
- 9:04Furthermore, expert financial testimony presented in court
- 9:08revealed the true scale of the windfall.
- 9:10The value of Microsoft's cloud credits has gained over $100
- 9:13billion in value. As the Artificial Intelligence
- 9:17Labs valuation skyrocketed, Microsoft provided the
- 9:20infrastructure and in return, their investment multiplied
- 9:24exponentially. So the cloud credits were
- 9:26essentially a casino chip that paid out $100 billion.
- 9:29Pretty much. And this dynamic completely
- 9:31limits the artificial intelligence labs independence.
- 9:34It changes them from a sovereign open Research Institute into a
- 9:38dependent entity tied exclusively to 1 corporate
- 9:42infrastructure. They rely on Microsoft servers
- 9:44to exist. Yes, if Microsoft turns off the
- 9:47servers, the lab ceases to function.
- 9:49This opens up the plaintiff's specific legal claim that
- 9:53Microsoft actively aided and abetted a breach of charitable
- 9:57trust. How does that specific legal
- 9:59claim work? Because aiding and abetting a
- 10:02breach of trust sounds like a criminal charge, but this is
- 10:05corporal litigation. Right.
- 10:06So in the context of a charitable trust, the argument
- 10:09is that Microsoft knowingly facilitated the dismantling of a
- 10:12charity to secure an exclusive commercial advantage.
- 10:15OK, I see the plaintiff is arguing that Microsoft looked at
- 10:18A5O1C3 charity, saw the incredible technology the
- 10:23researchers were building, and use their massive server
- 10:26infrastructure as leverage to pry that technology out of the
- 10:30public domain. And into a closed commercial
- 10:32structure that Microsoft could control and profit from.
- 10:35Exactly. So the money gets huge and the
- 10:37people get complicated. Very complicated.
- 10:39You go from a group of idealistic researchers trying to
- 10:42save the world to executives managing $100 billion valuation
- 10:47swings. And the trial exposed a wealth
- 10:50of internal documents detailing this internal shift.
- 10:53One of the most revealing pieces of evidence was Greg Brockman's
- 10:56private diary. Oh right, the diary.
- 10:58Yeah. In an entry written during the
- 11:00period when the company was exploring the restructuring from
- 11:03a pure nonprofit to the capped profit model, he asked himself
- 11:07what it would take for him to reach $1 billion financially.
- 11:10Wow. And today, his personal stake in
- 11:12the capped profit entity is valued at $30 billion.
- 11:16Hold on. $30 billion. And he did not invest his own
- 11:21personal funds to acquire that equity, right?
- 11:25He acquired that through his role as a founder when they
- 11:29restructured the company. Correct.
- 11:31He acquired founder shares in the new capped profit entity.
- 11:35He contributed his labor and leadership essentially sweat
- 11:38equity rather than fronting billions in cash.
- 11:41You look at a $30 billion personal stake and you contrast
- 11:45that with the initial donors who funded the labs creation.
- 11:49The people who donated the original cash got a charitable
- 11:52tax deduction and nothing else. The founders who managed the
- 11:55transition ended up with 10s of billions of dollars in personal
- 11:59wealth. That alone makes the jury look
- 12:01very closely at their motivations.
- 12:03Absolutely. But the testimony regarding the
- 12:04internal culture is even more intense.
- 12:06Former executives, including Mira Morati, testified about a
- 12:10deeply ingrained culture of lying at the executive level.
- 12:13Yeah, Morati's testimony provided a look inside the daily
- 12:16operations during the period of hyper growth.
- 12:19She claimed the chief executive officer actively hid safety
- 12:22reviews from the staff and from the nonprofit board of
- 12:24directors. She testified that he pushed a
- 12:27massive, highly aggressive revenue target that was
- 12:30explicitly mandated by Microsoft in order to secure further
- 12:34rounds of funding. OK, I have to push back a little
- 12:36here though. If you look at the reality of
- 12:39the tech industry, these executives were simply doing
- 12:43what was required to survive and ship products in a hyper
- 12:47competitive market. How do you mean?
- 12:49Well, we just established that they were burning millions of
- 12:52dollars a day on server compute. If they do not hit those revenue
- 12:56targets, they do not get the next tranche of server credits
- 12:59from Microsoft. If they do not get the server
- 13:02credits, the company dies, the research stops entirely, and a
- 13:06competitor wins the race to build the technology.
- 13:08That is the practical business argument, yes.
- 13:10Right, so hiding safety reviews might be terrible management,
- 13:13but pushing hard for revenue is just how a startup stays alive
- 13:17when the burn rate is that high. The problem with that defense,
- 13:20though, is that you cannot separate the management tactics
- 13:23from the legal structure they agreed to operate under.
- 13:26Actively hiding safety reviews directly contradicts the
- 13:29founding charitable mission of protecting humanity.
- 13:32When they incorporate it as a nonprofit, they legally bound
- 13:35themselves to that specific mission.
- 13:38That mission is not just a marketing slogan, it is the
- 13:40entire legal basis of the lawsuit.
- 13:43But surely the law allows a nonprofit to generate revenue to
- 13:47sustain its operations. I mean, hospitals and
- 13:49universities are nonprofits and they charge for their services
- 13:52to keep the lights on. They do, but the generation of
- 13:54revenue must serve the charitable mission, not
- 13:57superseded. If the leadership is ignoring
- 14:00safety protocols specifically to chase commercial revenue
- 14:03mandated by a corporate partner while they are violating the
- 14:06fiduciary duty of the nonprofit. I see.
- 14:09Fiduciary duty in a charitable trust means the directors must
- 14:12put the mission of the charity above all other concerns,
- 14:15including financial survival. If the only way to survive is to
- 14:19abandon the mission and build unsafe products for profit, the
- 14:22legal requirement is to let the organization fail.
- 14:25Wow, really? Yes, you do not pivot to a
- 14:27commercial enterprise and enrich yourself.
- 14:29So by hiding the safety reviews to hit the revenue targets, they
- 14:33were effectively proving that the commercial demands of
- 14:36Microsoft had taken priority over the charitable mission to
- 14:40protect humanity. Exactly.
- 14:42This internal behavior completely changes the
- 14:45perception of the leadership team from altruistic researchers
- 14:48to ruthless corporate executives.
- 14:51It limits their ability to claim in front of a jury that they
- 14:54were acting purely for the public benefit, and this opens
- 14:57up severe legal vulnerability regarding the unjust enrichment
- 15:01charges. An unjust enrichment is that
- 15:04legal concept which states that if you use assets that belong to
- 15:07a charity to make yourself rich, the law requires you to return
- 15:11those financial gains. Correct, you cannot use a
- 15:14charity as an incubator for your own personal wealth.
- 15:17That makes total sense. The legal obligation to a
- 15:19charity does not just disappear because the business environment
- 15:22gets tough or the computing costs get too high.
- 15:25You made a promise to the public and you have to honor it.
- 15:28Exactly. But while the Labs leadership
- 15:30faces immense scrutiny for their greed, the plaintiff's own
- 15:33motives are dragged right into the light during cross
- 15:36examination. Yes, the defense strategy relies
- 15:39heavily on exposing the plaintiff's actions to dismantle
- 15:42his moral high ground. The plaintiff's own allies and
- 15:45former associates testified against his purely altruistic
- 15:49narrative. Oh yeah, this part is wild.
- 15:51They revealed internal discussions and emails showing
- 15:54that during the early struggles to fund the compute costs, he
- 15:56actively wanted to merge the nonprofit artificial
- 15:59intelligence lab into his own publicly traded car company to
- 16:02use it as a cash cow. Hold on, the guy's suing them
- 16:06for becoming a for profit. The guy claiming he is the
- 16:09righteous defender of the charitable trust wanted to
- 16:12absorb the charity into his own for profit car company.
- 16:16That is exactly what the testimony confirmed.
- 16:18He recognized the immense value of the research team at the
- 16:22time. His car company was trying to
- 16:24solve the problem of autonomous driving, which is fundamentally
- 16:27an artificial intelligence problem.
- 16:28Right, because you need a system that can understand and navigate
- 16:31the physical world. Yes.
- 16:32So he saw a natural synergy. He demanded majority ownership
- 16:36and the chief executive role over the Artificial Intelligence
- 16:39lab to facilitate this merger. And what was his justification
- 16:43for taking over the charity? His stated reasoning, according
- 16:46to the testimony, was that he needed massive funds to build a
- 16:49city on Mars. Wait, really, Mars?
- 16:53Yes, he viewed the artificial intelligence technology as an
- 16:56engine to generate the trillions of dollars in capital required
- 16:59for interplanetary colonization. He intended to commercialize the
- 17:03technology through his car company to fund his space
- 17:06exploration goals. That is a stunning level of
- 17:09contradiction. You cannot sit in a courtroom
- 17:12and claim you're defending a charity from corporate greed
- 17:15when your own proposed alternative was to take it over,
- 17:18monetize it to build rockets and make yourself the CEO.
- 17:21It is a massive contradiction, and on top of that, he admitted
- 17:25on the witness stand that his own entirely separate competing
- 17:28artificial intelligence company currently uses distilled
- 17:31versions of the exact models he is suing the defendants over.
- 17:35What does that mean technically using distilled versions of the
- 17:37model models? Distillation is a process in
- 17:40artificial intelligence where you take a massive, highly
- 17:43capable model that costs billions of dollars to train,
- 17:46and you use it to train a smaller, cheaper model.
- 17:49Oh OK. The smaller model learns from
- 17:51the outputs of the larger model. It is a way to shortcut the
- 17:54expensive training process. The plaintiff admitted that his
- 17:58new startup relies on the outputs of the commercial models
- 18:01built by the defendants, so he is directly benefiting from the
- 18:05very commercialization he is suing to stop.
- 18:08Precisely. That just completely undermines
- 18:10his entire argument. He is using the commercial
- 18:12products to build his own commercial products while suing
- 18:15them for being commercial. And it gets worse for him.
- 18:18The defense introduced text messages he sent to the founders
- 18:21during the dispute, threatening to make them the most hated men
- 18:23in America if they did not comply with his demands to hand
- 18:26over control. Wow.
- 18:28Yeah, this behavior severely limits the plaintiff's moral
- 18:31high ground in the eyes of the jury.
- 18:33It changes the narrative from a righteous defense of a betrayed
- 18:36charity to a bitter personal dispute between rival
- 18:40billionaires fighting for control over the future of
- 18:43technology. It suggests to the judge and
- 18:45jury that his core objection is not actually that the
- 18:48organization became a for profit entity, but rather that it
- 18:52became a highly lucrative for profit entity that he did not
- 18:56personally control and profit from.
- 18:58Exactly. And the question of who truly
- 19:00controls the company comes to a head during a crisis involving
- 19:04the nonprofit board. I mean, you have this bizarre
- 19:08structure where a nonprofit board of directors legally
- 19:12controls a massive capped profit it.
- 19:16Is a highly unusual structure. We have to look at the dramatic
- 19:19weekend when the nonprofit board actually exercised its power and
- 19:22fired the chief executive officer, citing a lack of candor
- 19:26in his communications. For a brief moment, the
- 19:28nonprofit board did exactly what it was designed to do.
- 19:31It rained in the commercial leadership to protect the
- 19:33mission. Right, because the legal
- 19:35structure of the organization gave the nonprofit board
- 19:37absolute authority. They did not need shareholder
- 19:40approval to remove the CEO. They felt he was lying to them
- 19:43about safety metrics and commercial agreements, so they
- 19:46terminated his employment. In theory, this proved that the
- 19:49nonprofit was still in charge. In theory, yes.
- 19:52But the immediate aftermath of that firing demonstrated where
- 19:55the true power resided. Microsoft staged an overwhelming
- 19:59intervention. The chief executive of Microsoft
- 20:03publicly offered to hire the recently fired CEO and the
- 20:06entire staff of the Artificial Intelligence Lab.
- 20:09That is a brilliant and brutal corporate maneuver.
- 20:13They didn't try to buy the company, which would trigger
- 20:15antitrust reviews and lawsuits. They just offered to buy the
- 20:18people. It was a highly calculated move
- 20:21to prevent competitors from acquiring the specialized
- 20:23talent. An artificial intelligence
- 20:25company without its researchers is just a pile of expensive
- 20:28servers. By offering to absorb the entire
- 20:31workforce and match their salaries, Microsoft effectively
- 20:34neutralized the nonprofit board's decision.
- 20:37If the board did not reverse course and reinstate the CEO,
- 20:41they would be left ruling over an empty shell of a company with
- 20:44no employees. While Microsoft instantly
- 20:46acquired the best artificial intelligence team in the world,
- 20:49and the text messages revealed during the trial show exactly
- 20:53how hands on Microsoft was during the reinstatement process
- 20:56over that weekend, the messages show Microsoft executives
- 21:00actively vetting potential new board members for the nonprofit.
- 21:04When certain independent names were suggested for the board,
- 21:07Microsoft executives responded with phrases like strong, strong
- 21:11No. And this event completely limits
- 21:13the defense's argument that the nonprofit board remained fully
- 21:17in charge of the organization. It changes the legal
- 21:20understanding of corporate control, opening up intense
- 21:23regulatory scrutiny. It proves that a corporate
- 21:26partner with absolutely no official voting rights on the
- 21:29board, no legal authority to appoint directors, could
- 21:32completely overrule the independent directors of a
- 21:35charity by using sheer financial weight and the threat of a mass
- 21:39talent exodus. The corporate partner held the
- 21:42server keys in the capital, which meant the nonprofit boards
- 21:45authority was a complete illusion.
- 21:46This single lawsuit threatens to unravel the legal foundation of
- 21:50the entire tech sectors latest gold rush.
- 21:53We're looking at demands that could dismantle the most
- 21:56important corporate alliance in the industry.
- 21:58The exact demands submitted to the court are unprecedented in
- 22:01modern corporate litigation. What exactly is he asking for?
- 22:05The plaintiff wants the return of $150 billion to the charity.
- 22:09He is demanding the complete removal of the current
- 22:12leadership team and most significantly, he is demanding
- 22:15the total unwinding of the for profit structure, forcing the
- 22:19organization to revert entirely to its original nonprofit
- 22:22status. The judge categorized this
- 22:25incredibly complex technological dispute simply as a case of
- 22:28promises and breaches of promises.
- 22:30It allows the ancient established legal doctrine of
- 22:33charitable trust to be wielded directly against a modern tech
- 22:36giant. If you solicit money by
- 22:38promising to build an open charity, you cannot secretly use
- 22:42that money to incubate a closed commercial monopoly.
- 22:45And you should care about this because state attorneys general
- 22:49and international regulators are watching this trial incredibly
- 22:52closely. The company's future initial
- 22:55public offering and its ability to raise capital from global
- 22:58markets are entirely dependent on surviving this legal
- 23:02challenge. Oh, absolutely.
- 23:03If a judge rules that transferring intellectual
- 23:05property from a nonprofit to a capped profit subsidiary is a
- 23:09fundamental breach of trust, the entire valuation of the company
- 23:13collapses instantly. You cannot take a company public
- 23:16if a court might order you to dissolve the corporate structure
- 23:20and give all the assets back to a charity.
- 23:22This changes the risk profile for every startup trying to
- 23:25blend philanthropic missions with venture capital.
- 23:28It limits the ability of founders to use nonprofit status
- 23:31to attract elite talent and early donations by promising to
- 23:34work for humanity only to pivot to commercial profits once the
- 23:38technology is viable. Precisely.
- 23:40You cannot use the moral high ground as a stepping stone to a
- 23:42trillion dollar valuation without facing the legal
- 23:45consequences of the promises you made to get there.
- 23:48Well, the battle over this artificial intelligence empire
- 23:51proves that lending a charitable mission with endless computing
- 23:54costs inevitably forces a choice between original ideals and
- 23:59commercial survival. The Court's decision will
- 24:02ultimately define whether for the benefit of humanity is a
- 24:05legally binding contract or just an obsolete marketing slogan for
- 24:09the world's most valuable companies.
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