Speaker 1: Welcome to tech Stuff, a production from iHeartRadio. Hey there,
Speaker 1: and welcome to tech Stuff. I'm your host, Jonathan Strickland.
Speaker 1: I'm an executive producer with iHeart Podcasts and How the
Speaker 1: Tech Are Yet Now. Normally I say tech news items
Speaker 1: for Tuesdays and Thursdays, But over this past weekend a
Speaker 1: pretty big sequence of events happened and it really merits
Speaker 1: a deeper discussion. I'm sure most of you have at
Speaker 1: least heard something about this story. The short version is
Speaker 1: Sam Altman, the CEO of open Ai, received his walking
Speaker 1: papers from the company's board of directors. Then the board
Speaker 1: kind of flipped out and begged him to come back
Speaker 1: to the company, and he ultimately decided now I'm good,
Speaker 1: y'all can do this on your own. And last I heard,
Speaker 1: he has now joined Microsoft's Advanced AI department. Which is
Speaker 1: a heck of a weekend. So today I thought we
Speaker 1: would talk a bit about Altman, We talk a bit
Speaker 1: about open Ai, We chat about what went down behind
Speaker 1: closed doors this past Friday, why the board of directors
Speaker 1: fired Altman, why they then switched gears so quickly, and
Speaker 1: what it all means going forward. Now. I did an
Speaker 1: episode titled the Story of Open AI at the beginning
Speaker 1: of this year, which published in January. I am going
Speaker 1: to retread a lot of that same ground here in
Speaker 1: a slightly different context, because it's necessary to really unravel
Speaker 1: what was going on over the last weekend. So first up,
Speaker 1: who is Sam Altman. Well, he grew up in Saint Louis, Missouri,
Speaker 1: and as a kid he became really interested in programming.
Speaker 1: According to The New Yorker, he was programming as early
Speaker 1: as age eight, and that he went so far to
Speaker 1: take a part a Macintosh computer in order to learn
Speaker 1: how it worked. He also challenged social restrictions and taboos.
Speaker 1: When a Christian group announced a boycott for an assembly
Speaker 1: that was supposed to be focused on sexuality, Altman came
Speaker 1: out to his community as gay, and he challenged them
Speaker 1: to adopt an open attitude toward different ideas. And he
Speaker 1: was just a teenager at the time, so very much
Speaker 1: someone who is curious, motivated, and by most accounts I've read, fearless.
Speaker 1: Altman attended Stanford, but he was only there for two years.
Speaker 1: He studied computer science while he was there. In fact,
Speaker 1: he studied artificial intelligence by some of the leading thinkers
Speaker 1: in the discipline at Stanford, but he dropped out of
Speaker 1: college in order to work on an app and a
Speaker 1: business idea. So in many ways, it was the stereotypical
Speaker 1: founder story of Silicon Valley. Right. You go to Stanford,
Speaker 1: and when you're there, you're really there to make connections.
Speaker 1: You don't bother completing your studies, You drop out of school,
Speaker 1: you make a company, and then you get rich. It's
Speaker 1: kind of like, you know, the whole idea of step one,
Speaker 1: go to Stanford, step two, drop out, step three profit.
Speaker 1: I guess you could argue that if you can make
Speaker 1: a successful tech business, there's no real point to completing
Speaker 1: your studies. I mean, if your studies are all about
Speaker 1: learning the technology and it turns out you already have
Speaker 1: a good mastery of that and you can make a
Speaker 1: profitable business, why would you continue to spend money going
Speaker 1: to school, unless, of course, maybe you would grow more
Speaker 1: as a person and develop a deeper appreciation and understanding
Speaker 1: of things that could perhaps help you when you make
Speaker 1: decisions in the future. But don't listen to me. I
Speaker 1: graduated with a degree in the humanities, so I have
Speaker 1: these wacky ideas about how the experience of college is
Speaker 1: about more than just learning a subject. But that's beside
Speaker 1: the point. Let's get back to Sam Altman. So the
Speaker 1: app he was working on with a few friends was
Speaker 1: called Looped loopt, and it was meant to let users
Speaker 1: to share their location data with selected other users, So
Speaker 1: you can make friends with people on the app, and
Speaker 1: then you could share your precise location with that person,
Speaker 1: kind of a shorthand way of saying here I am.
Speaker 1: And it could facilitate stuff like real world meetups. Like
Speaker 1: imagine that you're heading to a concert venue and it's
Speaker 1: a big venue. There's a lot of different interests and stuff.
Speaker 1: You get there, you're going to meet up with your friends.
Speaker 1: You use this app to say this is specifically where
Speaker 1: I am, so that you can find each other. That's
Speaker 1: kind of a use case. The Looped team applied to
Speaker 1: the Why Combinator accelerator company to become part of their program.
Speaker 1: So let's talk about Why Combinator for a moment. It is,
Speaker 1: as I said, a startup accelerator organization. So Why Combinator
Speaker 1: its purpose is to provide early funding in promising startup
Speaker 1: ideas in order for them to start to get off
Speaker 1: the ground. So it's an early investment part of a
Speaker 1: startup so that they can at least get a chance
Speaker 1: to mature into an actual business. Now, in return for
Speaker 1: this early investment, why Combinator takes a small percentage of
Speaker 1: ownership in the startup. So let's say that why Combinator
Speaker 1: provides you know, a fairly modest sum in the early days,
Speaker 1: Like it was a lot of money, don't get me wrong,
Speaker 1: Like maybe like one hundred thousand dollars or maybe one
Speaker 1: hundred and twenty thousand dollars. That's a lot of money,
Speaker 1: but it's a tiny amount when you think about what
Speaker 1: a company needs to actually run. So this is really
Speaker 1: just to get a startup to go from idea to
Speaker 1: something slightly more you know, coherent. But in return, why
Speaker 1: Combinator gets like, you know, seven percent ownership of that startup. Now,
Speaker 1: let's say that startup is something like Dropbox, and then
Speaker 1: years down the road it's worth you know, more than
Speaker 1: ten billion dollars. Well, that becomes a heck of a
Speaker 1: return on investment. Right, you can have a huge profit
Speaker 1: as this startup accelerator, even if just a few of
Speaker 1: the startups really hit it big. Ideally, you want them
Speaker 1: all to hit big and then you get huge payouts
Speaker 1: down the line, and you become an important part of
Speaker 1: the whole tech startup ecosystem, which is exactly what why
Speaker 1: Combinator said up to do now why Combinator launched in
Speaker 1: two thousand and five, that was the same year that
Speaker 1: Looped would become part of its inaugural class of startups. Essentially, now,
Speaker 1: not all startups make it. Obviously, Looped at least appeared
Speaker 1: to do well initially, at least on paper. Altman and
Speaker 1: his colleagues secured a couple of major rounds of investment funding,
Speaker 1: Series A and Series B. The company's valuation hit more
Speaker 1: than one hundred and seventy million dollars. But they were
Speaker 1: running into a tiny little problem. They had developed this app,
Speaker 1: and they couldn't convince people to use it. They were
Speaker 1: all thinking that, you know, Looped was going to be
Speaker 1: this really useful and popular tool. Everyone was going to
Speaker 1: download it. But turns out the general public didn't seem
Speaker 1: to agree with that, and so in twenty twelve, Looped
Speaker 1: that team accepted an offer from the company green Dot,
Speaker 1: and they sold Looped for around forty three million dollars.
Speaker 1: That's also a lot of money, but it did not
Speaker 1: cover the amount of money that venture capitalists had invested
Speaker 1: into looped, so it was a negative return for investors.
Speaker 1: You know, sometimes you bet on the ponies and you lose.
Speaker 1: But Altman walked away with around five million bucks, so
Speaker 1: it was a pretty decent return for him, even though
Speaker 1: the app that he had worked on for several years
Speaker 1: never really gained traction. Now, in the wake of this disappointment,
Speaker 1: Altman founded a venture capital company of his own, and
Speaker 1: it was called Hydrazine Capital. So he sunk most of
Speaker 1: his personal wealth that he had earned from this sale
Speaker 1: into this new venture capital company, and he also raised
Speaker 1: millions more from other investors. He focused on investing in
Speaker 1: companies that were in the y Combinator program, and he
Speaker 1: was largely successful in this. He was picking some really
Speaker 1: good startups, and he was backing ones that would become
Speaker 1: a big deal in the tech space a few years
Speaker 1: down the road, and so he was seeing big returns
Speaker 1: on those investments. Within just a few years, his venture
Speaker 1: capital firm increased in value by an order of magnitude.
Speaker 1: But Altman wasn't super happy doing this work. He didn't
Speaker 1: find it rewarding on a personal level. Financially sure, but
Speaker 1: on a personal level, he didn't really like the work,
Speaker 1: so he then extricated himself from the venture capital company
Speaker 1: to try and do something else. Now, around this same time,
Speaker 1: the folks who were behind why Combinator were looking to
Speaker 1: hand off the whole accelerator program to someone else to
Speaker 1: lead it, and that someone else ended up being Sam Altman.
Speaker 1: The guy had gone through the process with looped and
Speaker 1: now he would be running it, and he reportedly agreed
Speaker 1: without hesitation. He was eager to do this job. It
Speaker 1: was something that he didn't even necessarily know he wanted
Speaker 1: to do, but once he was offered it, he was
Speaker 1: really enthusiastic about doing it. So he really ramped up
Speaker 1: y Combinator, and Altman began recruiting, you know, startups that
Speaker 1: were focused on science and technology, so we're talking about
Speaker 1: bleeding edge stuff like quantum computing or nuclear power or
Speaker 1: AI that kind of stuff. Around this time, he started
Speaker 1: to be part of a group that included Elon Musk,
Speaker 1: and this group ostensibly wanted to develop artificial intelligence in
Speaker 1: a responsible, accountable way while being extra careful not to
Speaker 1: do anything foolish to make safe artificial intelligence. You know,
Speaker 1: they didn't want to go down the wrong path and
Speaker 1: do something like accidentally unleash Skynet and terminators all over
Speaker 1: the place, so this group would become open ai. Now,
Speaker 1: the original open ai was a non profit organization, and
Speaker 1: the whole idea was to help in this effort to
Speaker 1: foster the development of artificial intelligence in a responsible and
Speaker 1: safe way. It wasn't some for profit company pushing a
Speaker 1: generative AI chatbot at that time, and it was not
Speaker 1: yet a partner to massive companies like Microsoft. So Altman
Speaker 1: was running y Combinator, and he also began to work
Speaker 1: with the open ai folks and tried to recruit various
Speaker 1: leaders in artificial intelligence to join open ai. In twenty fifteen,
Speaker 1: Sam Altman published a two part blog post about machine
Speaker 1: intelligence and quote why you should fear it end quote,
Speaker 1: And it starts off with the comfort sentence and I
Speaker 1: quote development of superhuman machine intelligence SMI is probably the
Speaker 1: greatest threat to the continued existence of humanity end quote.
Speaker 1: Now Altman allows that other massive threats, like say, an
Speaker 1: asteroid hitting the Earth, are possibly more likely to happen
Speaker 1: than super human intelligent machines run amok, but he also
Speaker 1: points out that a lot of the other threats that
Speaker 1: we think of, like super volcanoes and climate crisis might
Speaker 1: end up having a massive impact on the human population,
Speaker 1: but probably wouldn't just totally wipe out humans in totality.
Speaker 1: But superhuman machine intelligence, he argued, did have that potential,
Speaker 1: and that this is why he thought of it as
Speaker 1: being the most important or perhaps most dangerous threat. Almand
Speaker 1: goes on in those blog posts to point out that
Speaker 1: SMI doesn't have to be malevolent to be a threat.
Speaker 1: Just setting an SMI to complete a task like trying
Speaker 1: to manage resources could end up causing massive human harm.
Speaker 1: The SMI might determine that the biggest cause of resource
Speaker 1: depletion is the human race, So presto, you get rid
Speaker 1: of the people, and now you don't have to worry
Speaker 1: about these resources running out anymore. Now that's an oversimplification,
Speaker 1: but you get the idea. Altman's point is if you
Speaker 1: don't develop artificial intelligence in a way that is safe,
Speaker 1: you can get terrible consequences, whether that was your goal
Speaker 1: or otherwise. And of course there are malicious ways to
Speaker 1: use AI. Right You could develop AI in an effort
Speaker 1: to try and come up with new biological weapons. For example,
Speaker 1: that's often a scenario that's cited by concerned critics of
Speaker 1: artificial intelligence. That's certainly something that could potentially happen. So
Speaker 1: again Altman saying, well, you need to have the right
Speaker 1: team responsible to develop AI in a way that is
Speaker 1: most likely to benefit people and to protect people from
Speaker 1: malicious or badly designed AI. So Altman makes an argument
Speaker 1: that machine intelligence could hit an inflection point once recursive
Speaker 1: self improvement becomes a real possibility. That means, if we
Speaker 1: get to the point where we can create machines that
Speaker 1: are smart enough to reprogram themselves, and to reprogram themselves
Speaker 1: in a way that is better than what humans could do,
Speaker 1: so to program these machines at a higher than human
Speaker 1: level of capability, a superhuman capability, if you will, then
Speaker 1: machines suddenly engage in self improvement and can do so
Speaker 1: at increasingly shorter intervals. They get better at doing the
Speaker 1: thing that they're doing, so they get better at improving themselves,
Speaker 1: and they improve themselves over and over, and this becomes
Speaker 1: a version of the singularity, which is a moment where
Speaker 1: change is so sudden and it's happening all the time
Speaker 1: that effectively it becomes impossible to even describe the present,
Speaker 1: everything will change and continue to change at a rate
Speaker 1: that's beyond our ability to describe. Altman says, we might
Speaker 1: be creeping toward that now, and maybe we're creeping toward
Speaker 1: it at a rate that's just impossible for us to
Speaker 1: notice because it's so gradual. That makes it really tricky,
Speaker 1: because it could be that it goes from it's happening
Speaker 1: so slowly that we can't notice it, to it's happening
Speaker 1: so quickly that we are unable to describe it, and
Speaker 1: that there's no point in the middle where we can say,
Speaker 1: wait a second. So in part two of his blog posts,
Speaker 1: Altman makes a clear argument. He says, quote, the US
Speaker 1: government and all other governments should regulate the development of SMI.
Speaker 1: In an ideal world, regulation would slow down the bad
Speaker 1: guys and speed up the good guys. It seems like
Speaker 1: what happens with the first SMI to be developed will
Speaker 1: be very important end quote. Essentially, what Altman is arguing
Speaker 1: here is that if ethical researchers develop a superhuman machine
Speaker 1: intelligence first, they can employ that SMI to prevent the
Speaker 1: development or deployment of malevolent or poorly built SMIs. So
Speaker 1: we unleash our good guy Superman against their bad guy
Speaker 1: General Zod or you know whatever whichever superhero supervillain pairing
Speaker 1: you happen to like. Interestingly, this is going to come
Speaker 1: back again when we talk about Altman and his appearances
Speaker 1: around the world while talking about the potential for AI regulations.
Speaker 1: Before we dive any further into this, let's take a
Speaker 1: quick break to thank our sponsors and we'll be right back.
Speaker 1: So Altman went so far in his blog posts to
Speaker 1: say that he thinks, generally speaking, that tech is often overregulated,
Speaker 1: but on the flip side, he doesn't want to live
Speaker 1: in a world that has no regulation at all. In
Speaker 1: some cases, you can see regulation as a necessary evil
Speaker 1: that maybe it does slow down innovation or it has
Speaker 1: unintended consequences, but in the absence of regulation you can
Speaker 1: have some really poorly thought out deployments that can cause
Speaker 1: a lot of harm. From twenty fifteen to twenty eighteen,
Speaker 1: Open Ai operated as a nonprofit organization. The organization championed
Speaker 1: the open part of its name, claiming that it would
Speaker 1: freely share research and its patents with AI researchers all
Speaker 1: around the world, all in an effort to ensure safety
Speaker 1: in AI development. Greg Brockman, one of the co founders,
Speaker 1: identified a short list of top AI researchers, and the
Speaker 1: organization as a whole began to recruit several of them
Speaker 1: to join open ai as the first employees of the organization.
Speaker 1: The talent helped attract more talent. Some folks said they
Speaker 1: actually joined open ai because it was where you could
Speaker 1: work on really exciting research with the most brilliant and
Speaker 1: talented people in the discipline, even though it would mean
Speaker 1: you wouldn't be making as much money there as you
Speaker 1: could somewhere else. Even high paid individuals at companies like
Speaker 1: Google found themselves switching jobs for the chance to work
Speaker 1: on something that they saw as important and challenging and
Speaker 1: potentially critical to the survival of humanity. One of those
Speaker 1: people who would also be listed as a co founder
Speaker 1: of open ai was Ilia Sutzkiver, who would become chief
Speaker 1: Scientist at open ai and would join the board of directors.
Speaker 1: Musk reportedly played a critical role in recruiting Sutzkiver over
Speaker 1: to open Ai. Like it went back and forth between
Speaker 1: open Ai and Google, which really wanted to hold on
Speaker 1: to him, and reportedly the Musk was a big reason
Speaker 1: why Sutskever eventually moved over to open ai, and also
Speaker 1: Ilia Sutzkever is one of the people who would ultimately
Speaker 1: be part of the decision making group that fired Sam
Speaker 1: Altman this past weekend. Anyway, we're up to twenty eighteen,
Speaker 1: and behind the scenes there was drama a bruin, and
Speaker 1: much of it was in the cauldron known as Elon Musk.
Speaker 1: Not a big surprise there, right, because Elon Musk is
Speaker 1: kind of a magnet for drama in the tech sphere
Speaker 1: and the business sector. So Musk was on the board
Speaker 1: of directors for open Ai, but in twenty eighteen he
Speaker 1: left open ai entirely, and the official story was that
Speaker 1: Musk chose to step down because of a potential conflict
Speaker 1: of interest because there he was on the board of
Speaker 1: directors for an organization working on artificial intelligence, but he
Speaker 1: also was CEO of Tesla, a car company that was
Speaker 1: pushing hard to develop and deploy autonomous driving capabilities to
Speaker 1: the market, and autonomous driving is of course a subset
Speaker 1: of artificial intelligence, so stepping down was the responsible thing
Speaker 1: to do because of this potential conflict of interest between
Speaker 1: the two companies. There was, however, more to his decision
Speaker 1: than just that. So, according to Business Insider, Musk was
Speaker 1: not happy with open Ay's progress. He compared it negatively
Speaker 1: to Google. He was saying Google is spending huge amounts
Speaker 1: of money and is getting ahead in artificial intelligence research,
Speaker 1: and he argued Musk argued that Google, and he specifically
Speaker 1: targeted Larry Page in this criticism, was not paying any
Speaker 1: attention to safety, that safety was not a factor when
Speaker 1: it came to Google's approach to artificial intelligence, and so
Speaker 1: that was one of the things he said that it
Speaker 1: was critical of open ai, saying you're not doing enough,
Speaker 1: and he was kind of pointing at Sam Altman as
Speaker 1: the reason for them, that Altman's leadership was the reason
Speaker 1: why open ai was lagging behind. So Musk then reportedly
Speaker 1: went to other co founders of open ai, including Sam Altman,
Speaker 1: and essentially he said, I want to run open ai,
Speaker 1: and he was told in no uncertain terms that this
Speaker 1: would not happen, and so, again, according to Business Insider,
Speaker 1: Musk decided to take his ball and leave. His ball
Speaker 1: also included a sizable investment or donation to open ai,
Speaker 1: so when he left, he left with a whole bunch
Speaker 1: of money that otherwise was going to go to the
Speaker 1: organization and didn't. Musk would later say he disagreed with
Speaker 1: the direction of open ai and that the company wasn't
Speaker 1: nearly as open as its name would suggest. That last
Speaker 1: criticism happened after open Ai would create a for profit
Speaker 1: company in twenty nineteen. Musk actually leveled the lack of
Speaker 1: openness at open Ai that critique. Around twenty twenty, Musk
Speaker 1: also was founding his own ai research organization and would
Speaker 1: occasionally throw shade at open Ai and Sam Altman. And
Speaker 1: I am not an Elon Musk fan. Most of y'all
Speaker 1: know this. I'm not a huge fan of Elon Musk. However,
Speaker 1: at least some of the criticisms he had toward open
Speaker 1: Ai I actually agree with, or at least I think
Speaker 1: they were true, like the fact that open ai was
Speaker 1: becoming less open. I think that criticism has merit. Meanwhile,
Speaker 1: open Ai was in a pretty tough position because, as
Speaker 1: it turns out, artificial intelligence research is expensive, so you
Speaker 1: need access to a whole lot of compute power and
Speaker 1: that's not cheap, and then you also need to have
Speaker 1: the money to attract the best talent, especially if your
Speaker 1: goal is to be the first to develop superhuman machine
Speaker 1: intelligence that is ethically sound. Like, if that's your goal
Speaker 1: and you need to outpace everybody else who's also working
Speaker 1: on developing superhuman machine intelligence, you got to spend the
Speaker 1: big bucks to get the top of the class to
Speaker 1: come over to your organization. And a nonprofit organization is
Speaker 1: just not the fastest way to gather huge amounts of
Speaker 1: money needed to fund research and operations. It would be
Speaker 1: way easier if you could get investors to pour money in,
Speaker 1: but investors want a return. Meanwhile, a nonprofit is a
Speaker 1: place where you donate money. You're not expecting return on
Speaker 1: your donation. It's no an investment. This is what led
Speaker 1: to the decision to create a for profit arm of
Speaker 1: open ai, which in turn would generate money that could
Speaker 1: be theoretically at least used by the nonprofit part of
Speaker 1: open ai to further the original organization's goals and mission.
Speaker 1: So the result was open Ai LP, which open Ai
Speaker 1: called a capped profit company. So what the heck is
Speaker 1: a capped profit company? That's actually a really good question,
Speaker 1: because I've found two somewhat conflicting answers from various sources.
Speaker 1: Like they lay it out in two different ways that
Speaker 1: are similar but distinct. So I'm going to give you
Speaker 1: both of the ways that it has been explained in
Speaker 1: various sources, because I'm gonna be honest with y'all. I'm
Speaker 1: not a business person. Despite the fact that I have
Speaker 1: hosted a business podcast of the Best, I'm not really
Speaker 1: a business person, so I can't pretend like I have
Speaker 1: a firm grip on this. And also, open ai was
Speaker 1: kind of charting new territory while they were announcing this.
Speaker 1: But here are the two ways that it is frequently described.
Speaker 1: So version number one means that open ai would accept
Speaker 1: investments from venture capitalists and that would pay out returns
Speaker 1: on those investments from profits, but only up to a
Speaker 1: certain amount. So in open AI's case, the early backers,
Speaker 1: the people who first poured money in to open ai,
Speaker 1: would have a cap of one hundred times their initial investment.
Speaker 1: So let's take a very simple scenario. Let's say that
Speaker 1: some kids in your neighborhood want to start a lemonade
Speaker 1: stand and you invest one dollar into their lemonade stand. Now,
Speaker 1: let's say the kids running the stand turn out to
Speaker 1: be business geniuses and your dollar investment helps lead that
Speaker 1: stand into making tens of thousands of dollars in profits, Like,
Speaker 1: even after the expenses, these kids are raking in tens
Speaker 1: of thousands of dollars. However, when you invested, you did
Speaker 1: so knowing there was a one hundred time cap on returns,
Speaker 1: So that means the most you're ever going to get
Speaker 1: from the stand is one hundred dollars. It's a one
Speaker 1: hundred times return on your investment. Meanwhile, those snot nosed
Speaker 1: kids who never could have made the stand without your
Speaker 1: dollar are pocketing thousands of bucks and they're franchising across
Speaker 1: the town, those rotten kids. Anyway, that's one version of
Speaker 1: how the capped profit structure work. It works, investors can
Speaker 1: make a return, but only up to a certain amount,
Speaker 1: the early backers being one hundred times whatever they put in,
Speaker 1: and that means if they put in ten million dollars,
Speaker 1: they could potentially make as much as a billion dollars
Speaker 1: in returns if open ai profited that much. So you
Speaker 1: know it does add up. However, there is a second
Speaker 1: explanation for capped profit that, like I said, is slightly different.
Speaker 1: So in this version, investors would pour money into open
Speaker 1: ai and open ai would hold back on distributing any
Speaker 1: returns on profits until those profits reached at least one
Speaker 1: hundred times the investments that had been made. So using
Speaker 1: our limonade stand example, you've donated one dollar to the
Speaker 1: limonade stand business, you would not see a return on
Speaker 1: that investment until the liminade stand made at least one
Speaker 1: hundred dollars in profit. At that point you could start
Speaker 1: to receive returns. And a few explanations kind of combine
Speaker 1: the first version I mentioned in this version, and frankly,
Speaker 1: just to be transparent, this kind of confuses me. So
Speaker 1: for example, Time at time dot Com uses the second
Speaker 1: explanation right that you don't get any returns until the
Speaker 1: profits reach one hundred times whatever your investment level was,
Speaker 1: but then includes the phrase quote anything above that being
Speaker 1: the one hundred times profit would be donated back to
Speaker 1: the nonprofit. So if that's the case, it means you
Speaker 1: wouldn't get a return until the profits hit that one
Speaker 1: hundred times your investment, and then anything over one hundred
Speaker 1: times your investment would be going toward the investment into
Speaker 1: the nonprofit or a donation into the nonprofit, which means
Speaker 1: I guess you would be limited to one hundred times.
Speaker 1: I don't know, like maybe it's a combination of these two,
Speaker 1: but it's just been poorly reported in various places. It
Speaker 1: just it seems a little confusing to me, and it
Speaker 1: also seems like it'd be confusing from an investor standpoint
Speaker 1: of whether or not it would even make sense to
Speaker 1: pour money into this. I think a lot of reporting
Speaker 1: around the cap profit nature is just incomplete, and that's
Speaker 1: the problem that there were just there's just a lack
Speaker 1: of good explanations of this. And also, I mean, I'm dense,
Speaker 1: so that's the other part of the problem. But anyway,
Speaker 1: however you frame the context of a capped profit company,
Speaker 1: the structure would give open ai the chance to court
Speaker 1: investors and to hold a whole bunch of money that
Speaker 1: they could then pour into research and recruiting. A one
Speaker 1: hundred times factor is pretty darn big, And arguably you
Speaker 1: could say this was necessary because while open ai had
Speaker 1: this noble mission, the truth is you still had massive
Speaker 1: companies like Amazon and Google and Meta. These companies have
Speaker 1: really deep pockets and a desire to invest in AI research,
Speaker 1: and if you didn't do something, there was just no way,
Speaker 1: no matter how noble the cause you were going to
Speaker 1: keep up with these companies. So that was kind of
Speaker 1: the decision making factors that drove open eye to launch
Speaker 1: this for profit arm of the organization, and that didn't
Speaker 1: make everybody happy. In fact, it was controversial, to put
Speaker 1: it lightly, There were critics who were asking if it
Speaker 1: would even be possible for open ai to continue to
Speaker 1: pursue its mission of ethical AI development while also operating
Speaker 1: a commercial business that was profiting off of artificial intelligence development.
Speaker 1: That these two things could not be in alignment and
Speaker 1: would mean that ultimately open ai would not be able
Speaker 1: to achieve its mission. Complicating matters was that open ai
Speaker 1: began to back away from that whole open part of
Speaker 1: the philosophy, which again Elon Musk would criticize. In twenty twenty.
Speaker 1: Open a Eye sighted a concern that malicious developers might
Speaker 1: take the information the research being shared from open ai
Speaker 1: and use that information to develop nasty and harmful applications,
Speaker 1: or at least poorly designed ones. So now they're saying,
Speaker 1: you know, our knowledge is dangerous. So I know, we
Speaker 1: said we were going to share it so that we
Speaker 1: could benefit humanity, but now we're scared that if we
Speaker 1: share it people will misuse it, so we're not going
Speaker 1: to do that anymore. So again, like Musk was saying,
Speaker 1: it was no longer being as open as the name
Speaker 1: had implied. So yeah, his criticisms had weight. Open ai
Speaker 1: really was moving away from an unassailable nonprofit status and
Speaker 1: also was getting less open in the process. Sure, the
Speaker 1: folks that open ai had explanations for why they were
Speaker 1: doing this, but it didn't change the fact that the
Speaker 1: open Ai of twenty nineteen was fundamentally different than the
Speaker 1: organization that had started in twenty fifteen. All Right, we're
Speaker 1: going to take another break. When we come back, we'll
Speaker 1: talk more about what happened in the following years that
Speaker 1: then led to the situation that we saw unfold this
Speaker 1: past weekend. But first, let's thank our sponsors. Okay, So
Speaker 1: we left off in around twenty nineteen. We're gonna skip
Speaker 1: ahead a few years. So the battle for AI talent
Speaker 1: was a constant one in the tech space, but the
Speaker 1: world at large remained pretty much oblivious to open ai
Speaker 1: and the folks who were involved in that company. Open
Speaker 1: ai just wasn't a name that your average person was
Speaker 1: aware of. But that would change in November twenty twenty two.
Speaker 1: That's when OpenAI introduced the chatbot called chat GPT. This
Speaker 1: chat bot drew on a large language model, the GPT model,
Speaker 1: which had gone through a couple of iterations, and it
Speaker 1: would use that language model to generate responses to queries
Speaker 1: and input. The responses often seemed like a human being
Speaker 1: had actually written it. It didn't come across as your
Speaker 1: typical AI generated text. It seemed more natural than that.
Speaker 1: It also seemed like it was a really smart person
Speaker 1: who wrote the response, someone who appeared to be an
Speaker 1: authority on whatever the subject was. Like any subject you
Speaker 1: could think of, you could put into this thing, and
Speaker 1: chat gpt would generate a response that seemed to be
Speaker 1: pretty definitive. And there were limitations on chat GPT's expertise.
Speaker 1: The open Ai announced that chat gpt really only had
Speaker 1: access to information leading up to September twenty twenty one,
Speaker 1: and if you asked it to explain anything that happened
Speaker 1: after September twenty twenty one, you'd be out of luck
Speaker 1: because chat GPT wouldn't have access to that information. But
Speaker 1: right out of the gate, chat gpt seemed incredible. Now
Speaker 1: over the following weeks after its introduction, we would start
Speaker 1: to see various critics and skeptics raise concerns about generative
Speaker 1: AI in general, really and chat GPT in particular. Now,
Speaker 1: some of these conversations had already started because there were
Speaker 1: already text to image generative AI tools out there that
Speaker 1: had prompted some concern. Chat GPT created new discussions about
Speaker 1: how generative AI could make misinformation. They could engage in plagiarism,
Speaker 1: it could slander someone, or it could just produce the
Speaker 1: wrong response due to something that the AI field calls hallucinations.
Speaker 1: Sometimes they call it confabulations instead. So this is when
Speaker 1: an AI model fabricates an answer for whatever reason. Like
Speaker 1: one reason that AI might just make something up is
Speaker 1: that it doesn't have access to relevant information that relates
Speaker 1: to the query. So instead the chatbot produces an answer that,
Speaker 1: from a linguistic perspective, is statistically relevant. In other words,
Speaker 1: it's creating sentences that are linguistically correct but factually incorrect
Speaker 1: because it doesn't know the difference, and it's just trying
Speaker 1: to provide a response to the question that was asked
Speaker 1: of it. Now, this meant that sometimes you could ask
Speaker 1: chat GBT to solve a problem for you, and the
Speaker 1: response you would get would sound authoritative and sound like
Speaker 1: it's correct, but in fact it was entirely wrong. And
Speaker 1: following these criticisms came concerns from lawmakers who began to
Speaker 1: ask the very same questions that open AI was intended
Speaker 1: to address when folks first got together back in twenty
Speaker 1: fifteen to create it in the first place. Now, as
Speaker 1: we all know, the law trails behind technological development, sometimes
Speaker 1: by years. It takes time to make laws, and then
Speaker 1: it takes time to approve them and to pass them
Speaker 1: into law. If you rush, you're likely to make problems worse,
Speaker 1: or at the very least, you're likely to complicate matters
Speaker 1: so that it becomes very difficult to comply with the
Speaker 1: laws you've written. So Altman, who had already made his
Speaker 1: philosophy around regulation known in that blog post from twenty fifteen,
Speaker 1: began to meet with various officials all around the world. Now,
Speaker 1: the idea was that sam Altman would help legislators understand
Speaker 1: the potential risks of artificial intelligence and presumably create the
Speaker 1: most responsible approach to regulations to ensure safety. But skeptics
Speaker 1: were worried that what sam Altman was actually doing was
Speaker 1: just stacking the deck to favor Open a Eye over
Speaker 1: other AI companies. You see, Altman had long held this
Speaker 1: position that it's really important for an ethical group of
Speaker 1: researchers to beat everybody else to the punch to develop
Speaker 1: that superhuman machine intelligence in order to prevent catastrophe. That
Speaker 1: if you don't do that, you're essentially sealing your own doom.
Speaker 1: And of course Altman viewed open AI as that ethical group.
Speaker 1: It is the group that's dedicated to creating ethical, safe AI,
Speaker 1: and Altmann felt that regulations could help mitigate the risk
Speaker 1: of bad actors or inept creators from making dangerous machine intelligence.
Speaker 1: And so these skeptics were arguing Altman's position was that
Speaker 1: regulations should really hold back everybody else and then favor
Speaker 1: open AI and allow it to move forward towards this
Speaker 1: goal of creating benign, protective machine intelligence. So in other words, yeah,
Speaker 1: the AI field needs rights, but more importantly, those regulations
Speaker 1: need to stop every one other than open AI. That
Speaker 1: was how the skeptics saw Sam Altman's position as he
Speaker 1: met with all these different leaders, and in fact we
Speaker 1: saw proposals for putting AI research on hold for half
Speaker 1: a year. In fact, Elon Musk argued for this. Now,
Speaker 1: the skeptics came out again and said, well, I see
Speaker 1: the need to kind of pump the brakes so that
Speaker 1: we make sure that all this work in AI isn't
Speaker 1: going to cause enormous harm in the future. But of
Speaker 1: course Musk is arguing for this because he wants to
Speaker 1: create his own AI research division. And if you force
Speaker 1: the industry as a whole to hold off for six
Speaker 1: months on moving forward, it would give Musk the opportunity
Speaker 1: to start to build out the foundations for his own
Speaker 1: AI division while not losing more ground to competitors like
Speaker 1: open Ai. It's a cutthroat world out in that AI field, y'all. Now.
Speaker 1: In January of this year, in twenty twenty three, news
Speaker 1: broke that Microsoft was investing around ten billion with a
Speaker 1: B dollars in open Ai. Microsoft had already invested billions
Speaker 1: in open Ai over the previous years, in twenty nineteen
Speaker 1: and twenty twenty one, specifically, so this was seen as
Speaker 1: Microsoft's effort to catch up to rivals like Google and Amazon,
Speaker 1: which had already been spending their own billions in AI research.
Speaker 1: The relationship between Microsoft and open Ai would manifest in
Speaker 1: lots of different ways, including in Microsoft incorporating chat GPT
Speaker 1: into its search feature in bing. For a long time,
Speaker 1: Microsoft has been pushing being an edge toward becoming more
Speaker 1: important in the market, but as come up time and
Speaker 1: again up against the brick wall that is Google. In August,
Speaker 1: open Ai announced in an enterprise version of chat gpt,
Speaker 1: and then in September, open Ai allowed the chatbot to
Speaker 1: access information on the Internet for the first time. So
Speaker 1: now that restriction where it could only access information up
Speaker 1: to September twenty twenty one, had been lifted. Now it
Speaker 1: could access real time information around the world. On the
Speaker 1: political side, lawmakers around the world, particularly in the United
Speaker 1: States and in the European Union, began to grow more
Speaker 1: concerned about AI and its possible uses and the risks
Speaker 1: associated with it. So more pressure was building on the
Speaker 1: artificial intelligence discipline in general and open ai in particular,
Speaker 1: because open ai was seen as sort of the leading
Speaker 1: authority in artificial intelligence. Chad GPT had really captured a
Speaker 1: lot of interest around the world, and at the same
Speaker 1: time you had some people within open ai who were
Speaker 1: really clinging onto the ideals of the original nonprofit organization
Speaker 1: and who had growing concerns about where open ai was
Speaker 1: headed because of the for profit arm of the company.
Speaker 1: So similar to Elon Musk, there were people, high level
Speaker 1: people in open ai who were starting to feel uncomfortable
Speaker 1: with where the organization was going. Now, just a couple
Speaker 1: of weeks ago, open ai held its first developer conference.
Speaker 1: Sam Altman took the stage on November sixth, so not
Speaker 1: long ago, and he took the stage as CEO of
Speaker 1: open Ai, and he listened off some pretty incredible statistics
Speaker 1: like the fact that open ai can count more than
Speaker 1: ninety percent of Fortune five hundred companies as customers. That's incredible.
Speaker 1: It shows how influential open ai is in this field.
Speaker 1: Open AI's partnership with Microsoft also played a huge part
Speaker 1: in Sam Altman's presentation. But again, behind the scenes, things
Speaker 1: were far from honky dory. You had open Ai doing
Speaker 1: gangbusters on a business level, but again some of the
Speaker 1: scientists who were part of the board of directors were
Speaker 1: growing increasingly concerned that the company was guilty of the
Speaker 1: very behaviors that open Ai was meant to head off.
Speaker 1: That open ai was developing and deploying tools without putting
Speaker 1: in appropriate safeguards or considering the consequences of unleashing these
Speaker 1: tools that open ai had become more about monetizing technologies
Speaker 1: and innovation and less about ethical development of artificial intelligence.
Speaker 1: There were also some personal tensions that were growing between
Speaker 1: Altman and other members of the board, such as Ilia Sutzkever. So,
Speaker 1: according to Time, Altman reduced Ilia's role in the company,
Speaker 1: while Ilia worried that Altman was launching side projects that
Speaker 1: would benefit from open AI's work but also not be
Speaker 1: accountable to open ai. So, in other words, ILIO was
Speaker 1: worried about this sort of conflict of interest that Altman
Speaker 1: was going to end up pursuing some developments of artificial
Speaker 1: intelligence that were not governed by the board of open
Speaker 1: ai and thus not constrained by these ethical concerns. So
Speaker 1: this really boiled over. During the developer conference, Altman made
Speaker 1: several announcements that Ilya reportedly objected to, including the unveiling
Speaker 1: of a customizable version of chat GPT that, in theory,
Speaker 1: could run autonomously once it was told what tasks it
Speaker 1: was supposed to handle. So the critics on the board
Speaker 1: outnumbered Altman's supporters. You had essentially two camps. You had
Speaker 1: the people who thought Altman was in the right, including
Speaker 1: Altman and Brockman, and then you had other members who
Speaker 1: were more concerned. And last Friday, that's when the board
Speaker 1: decided it was time to fire Sam Altman. They saw
Speaker 1: Altman as being too reckless, not nearly cautious enough, and
Speaker 1: despite open AI's market performance, which was incredible, they felt
Speaker 1: the company was moving in the wrong direction and that
Speaker 1: it needed new leadership as a result, so they decided
Speaker 1: they had to fire Sam Altman as CEO. Now. Reportedly,
Speaker 1: Altman learned of this fate in a Zoom meeting. Ilia
Speaker 1: was the one who told him that he had to
Speaker 1: go to the Zoom meeting, and it happened shortly before
Speaker 1: the board announced their decision Publicly. Greg Brockman, co founder
Speaker 1: president of open Ai, he was not told of this meeting,
Speaker 1: and in fact, he found out about Sam Altman getting
Speaker 1: fired just shortly before open Ai released the news to
Speaker 1: the public. Similarly, Satya Nadella, the CEO of Microsoft, also
Speaker 1: found out essentially when the news got released to the public,
Speaker 1: and this set off a metaphorical explosion in the tech world. First,
Speaker 1: open AI's board didn't exactly have a real good transition
Speaker 1: plan in place, to handle this, nor did it seem
Speaker 1: to really comprehend the extent of the fallout this decision
Speaker 1: would have, particularly in the way they did it, where
Speaker 1: they did not consult with Microsoft, a partner that was
Speaker 1: going to invest ten billion dollars into the company, or
Speaker 1: talk it over with the other executives before making the decision.
Speaker 1: So even the folks who agreed that Altman was perhaps
Speaker 1: not being cautious enough felt that the board's move was
Speaker 1: poorly thought out and even more poorly executed. It's really
Speaker 1: hard to argue against that. Like, even if you feel
Speaker 1: that Sam Altman was absolutely leading open Ai in the
Speaker 1: wrong way the wrong direction, you can also say that
Speaker 1: the way the board handled this ultimately was disastrous. So
Speaker 1: Greg Brockman announced that he was leaving open Ai once
Speaker 1: the news went public that Sam Altman had been fired,
Speaker 1: So open Ai would see both its CEO and its
Speaker 1: president leave the company in one day. Some members of
Speaker 1: the board, like Ilia, expressed regret for having supported the
Speaker 1: measure to fire Altman, like they said later like I
Speaker 1: kind of wish we hadn't done that. Iliosutskiv would go
Speaker 1: on to sign an open letter saying as much, and
Speaker 1: even threatened to leave Open a Eye along with more
Speaker 1: than five hundred other staff members over this decision. Just
Speaker 1: a big old whoopsie, right, so the board found itself
Speaker 1: in extremely hot water. They had done the classy thing
Speaker 1: of waiting until a Friday to announce a massive decision.
Speaker 1: My guess is this was probably in an effort to
Speaker 1: take at least some of the sting out of the
Speaker 1: news cycle, the idea of being like, well, if it's
Speaker 1: on a Friday afternoon, no one's going to pay attention
Speaker 1: because we're going into the weekend. By the time it
Speaker 1: comes around to Monday, things are going to cool off
Speaker 1: a bit. Plus here in the United States, we're going
Speaker 1: into a holiday week with Thanksgiving, so there won't be
Speaker 1: a whole lot of opportunity to bring a whole lot
Speaker 1: of attention to this, and we'll be able to get
Speaker 1: away relatively unscathed. That is not how it turned out, however. Instead,
Speaker 1: the news media went bonkers with this decision, and how
Speaker 1: could you not chat GPT and open AI. They had
Speaker 1: been the center of so many headlines throughout the whole year.
Speaker 1: Of course, this was going to get a lot of attention,
Speaker 1: and so while they were hoping that they could get
Speaker 1: away with this without it being too painful. Immediately, investors
Speaker 1: started to freak out about this change. A bunch of
Speaker 1: them essentially indicated that they would pull out of open
Speaker 1: ai and they would back whatever Altman chose to do next.
Speaker 1: So if Altman launched his own competing artificial intelligence company,
Speaker 1: they were going to back Altman, not open Ai. There
Speaker 1: were hints that Microsoft could potentially even do the same,
Speaker 1: and that's ten billion dollars plus. You had the general
Speaker 1: staff who felt that this was the wrong move, and
Speaker 1: they felt that this was a terrible mistake, and they
Speaker 1: were threatening a mass walkout of the company. It was
Speaker 1: pretty much the worst reaction you could expect from a
Speaker 1: big announcement. So it did not take very long for
Speaker 1: news to break that the board was trying hard to
Speaker 1: take back what it had done and to try and
Speaker 1: convince Altman and Brockman to return to the company, but
Speaker 1: by then the damage had been done. Altman was not
Speaker 1: interested in coming back. Specifically, he said unless the board
Speaker 1: stepped down, he would not come back, and that would
Speaker 1: become a real sticking point. Mira Murrati, the chief technology
Speaker 1: officer for open Ai, would serve as interim CEO for
Speaker 1: about two whole days. Murati reportedly was the person who
Speaker 1: actually reached out to Altman to try and convince him
Speaker 1: to come back to open AIE. But while Altman did
Speaker 1: return to open AI's headquarters to negotiate, and he said
Speaker 1: it was the first and only time he would ever
Speaker 1: have a guest badge to open AIE, those negotiations didn't
Speaker 1: really go very far, so the board decided on a
Speaker 1: new interim CEO, perhaps because of a perception that Murrati
Speaker 1: was maybe a bit too pro Altman and they needed
Speaker 1: to get someone who would be more in their pocket.
Speaker 1: They chose the former CEO of Twitch, Emmitt Sheer, who
Speaker 1: doesn't have any experience with artificial intelligence. By this time,
Speaker 1: the board directors consisted of just four people, people who
Speaker 1: have been pressured to step down but refused to do so.
Speaker 1: Thus Altman did not come back to the company. Altman
Speaker 1: and Brockman, meanwhile, weren't exactly on the job market for
Speaker 1: very long, because Microsoft swiftly hired both of them to
Speaker 1: head up a new advanced AI research team within Microsoft.
Speaker 1: Nadella also said Microsoft remains committed to supporting open AI,
Speaker 1: hinting that those ten billion dollars, most of which has
Speaker 1: not made its way to open Ai yet. Open Ai
Speaker 1: has received just a fraction of that ten billion dollars,
Speaker 1: but the hint is that that money will continue to
Speaker 1: go to OpenAI, that Microsoft is not backing out of
Speaker 1: that agreement, but Altman is going to end up working
Speaker 1: directly with Microsoft and will have the title of CEO
Speaker 1: for whatever this Advanced AI part of Microsoft ends up
Speaker 1: being called. A few other prominent executives and scientists from
Speaker 1: open Ai are apparently moving over to Microsoft as well,
Speaker 1: so there are already other defections from open Ai to Microsoft. Meanwhile,
Speaker 1: back at open Ai, a lot of folks who work
Speaker 1: within the company have been posting their support for Altman
Speaker 1: on platforms like x so there's a concern that there's
Speaker 1: going to be a mass walkout and resignation following this move.
Speaker 1: Certainly other companies like Microsoft, Google, Amazon, and Meta would
Speaker 1: be eager to get hold of some of that talent,
Speaker 1: and it's entirely possible that the board of open Ai,
Speaker 1: in a move made out of concern for the company's
Speaker 1: safety and humanity safety, may have actually doomed the organization entirely.
Speaker 1: I'm not sure hiring a former CEO of Twitch is
Speaker 1: going to be enough to prevent disaster. Now, all that
Speaker 1: being said, open ai is in an incredible position. A
Speaker 1: recent evaluation placed the company at around eighty six billion dollars.
Speaker 1: Microsoft says it is committed to this ongoing relationship with
Speaker 1: open Ai. Chad GPT is still an incredibly important tool
Speaker 1: in the tech space, particularly with the introduction of the
Speaker 1: enterprise product of chat GPT. So could open ai just
Speaker 1: be too big to fail? Maybe? I think this monumental
Speaker 1: misstep will test that hypothesis. I do not know how
Speaker 1: it's all going to shake out. From a business perspective,
Speaker 1: I would say open ai is in a really strong position.
Speaker 1: But then if the organization suddenly sees a mass defection
Speaker 1: from its researchers and staff, that could very well change.
Speaker 1: So we'll have to see. And of course, now we're
Speaker 1: on a holiday week, so it might be another week
Speaker 1: but before we start getting answers. But yeah, that's kind
Speaker 1: of an update on what went down this past weekend
Speaker 1: and why it happened, Like all those different factors that
Speaker 1: built up to this big explosion of activity. Now you
Speaker 1: have a bit more background as to what was going on.
Speaker 1: As to whose side I'm on, I don't know. I
Speaker 1: do think that Altman's leadership was not always the best
Speaker 1: as far as trying to achieve the goal of ethical AI.
Speaker 1: I do not think that it was almost like engaging
Speaker 1: in a necessary evil kind of thing. But I'm not
Speaker 1: sure that the evil is really necessary. But what do
Speaker 1: I know. I know that AI is very hard and
Speaker 1: very expensive, and I don't know how you get the
Speaker 1: money to do it the right way and still beat
Speaker 1: out all the companies that don't have those restrictions on them.
Speaker 1: So I don't know. I just know that it's a mess.
Speaker 1: But now it's a mess we can put behind us
Speaker 1: until we see what happens next. I hope you are
Speaker 1: all well, and I'll talk to you again really soon.
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