Speaker 1: Zone Media. Well, I know that assholes grow on trees,
Speaker 1: but I'm here to trim the leaves. This is Better
Speaker 1: off Line. I'm your host ed dait tron. It's bullshit
Speaker 1: Week here at Better Offline headquarters. The thousands of elves
Speaker 1: that work for me have been finding me things that
Speaker 1: say bullshit for no reason. When I wrote the episode
Speaker 1: weeks ago. I don't know what to do with them.
Speaker 1: But anyway, we're starting with one of the largest financial
Speaker 1: institutions of the world calling bullshit on Generative AI as usual.
Speaker 1: Don't take my word for it. Check the episode notes
Speaker 1: for links that map to everything I'm talking about. I've
Speaker 1: tried my best to map them to exactly what I'm
Speaker 1: saying too, and you can feel free to yell about
Speaker 1: it like yell out the words like the Beastie Boys,
Speaker 1: or just follow along, because I think it's important for
Speaker 1: you to know where I'm getting all of this from,
Speaker 1: versus just assuming that I made it up somehow. That
Speaker 1: is an accus I've had made. I don't really know
Speaker 1: how I would do that anyway, the episode I'm very sorry.
Speaker 1: At the tail end of June, Goldman Sachs, one of
Speaker 1: the largest global investment banks put out the thirty one
Speaker 1: page report titled JENAI too much, spend too little benefit
Speaker 1: that's with the question mark at the end. That includes
Speaker 1: some of the most damning literature on generative AI that
Speaker 1: I've ever seen. And yeah, that weep sound in the background.
Speaker 1: You here is the slow, painful deflation of the bubble
Speaker 1: I've been warning you about since March. The report covers
Speaker 1: AI's productivity benefits, which Goldman remarks are likely limited, AI's returns,
Speaker 1: which are likely to be significantly more limited than anticipated,
Speaker 1: and AI's power demands, which are likely so significant that
Speaker 1: utility companies will have to spend nearly forty percent more
Speaker 1: in the next three years to keep up with the
Speaker 1: demand from hyperscalers and rot economists like Google and Microsoft.
Speaker 1: The report is so significant because Goldman sacks, like any
Speaker 1: investment bank doesn't care about your feelings or your happy
Speaker 1: or emotions or anything unless doing so is profitable. It'll
Speaker 1: gladly hypob anything it thinks it will make a bug.
Speaker 1: Back in May, it published a report which claimed that AI,
Speaker 1: not just generative AI, was showing very positive signs of
Speaker 1: eventually boosting GDP and productivity. Even though said report buried
Speaker 1: within it, constant reminders that AI had yet to impact
Speaker 1: productivity growth and states that only five percent of companies
Speaker 1: report using generative AI in regular production. For Goldman to
Speaker 1: suddenly turn on the AI movement suggests that it's extremely
Speaker 1: anxious about the future of generative AI, with almost everybody
Speaker 1: agreeing on one core point in the report that the
Speaker 1: longer the generative AI takes to make people money, the
Speaker 1: more money that it's going to need to make. The
Speaker 1: report also includes an interview with economist Darren Smoglu of MIT,
Speaker 1: which can be found by the way on page four
Speaker 1: of the document, which you can find in this episode
Speaker 1: spreadsheet of links. An Institute professor who published a paperback
Speaker 1: in May called the Simple Macroeconomics of AI that argued
Speaker 1: that and I quote the upside to US productivity and
Speaker 1: consequently GDP growth from genera IVAI will likely prove much
Speaker 1: more limited than many forecasts that expect a month has
Speaker 1: only made Asmoglue more pessimistic, declaring that truly transformative changes
Speaker 1: won't happen quickly and few, if any, will likely occur
Speaker 1: within the next ten years, and that genera ivai's ability
Speaker 1: to affect global productivity is low because and I quote again,
Speaker 1: many of the tasks that humans currently perform are multifaceted
Speaker 1: and require real world interaction, which AI won't be able
Speaker 1: to materially improve anytime soon. What makes this interview, and
Speaker 1: really the whole report so remarkable is how thoroughly and
Speaker 1: aggressively it attacks every bit of marketing collateral that the
Speaker 1: artificial intelligence movement has. Asmoglu specifically questions the belief that
Speaker 1: AI models will simply get more powerful as we throw
Speaker 1: more data and GPU graphics process unit the thing that
Speaker 1: crunches the numbers capacity at them, and specifically asks a question,
Speaker 1: what does it mean to double AI's capabilities? How does
Speaker 1: that make something like say a customer service rap better? Seriously, though,
Speaker 1: what does better really get them less errors? How do
Speaker 1: you quantify less errors without factoring in the current state
Speaker 1: introducing them? It's not great And this really is a
Speaker 1: specific problem with the whole GENII fantasists bullshit spiel. They
Speaker 1: heavily rely on the idea that not only will these
Speaker 1: large language models llms like chat GPT get more powerful,
Speaker 1: but the getting more powerful will somehow grant it the
Speaker 1: power to do something. As Asimoglu says, what does it
Speaker 1: mean the double it What does that do? No? Really,
Speaker 1: what does that more actually mean? We've heard people talk
Speaker 1: about this for eighteen months, saying the more powerful chat
Speaker 1: GBT gets, the better it will get. But what does
Speaker 1: better even look like? GPT four Oh, the latest version
Speaker 1: of chat GPT, other than accepting more inputs, is kind
Speaker 1: of the same thing. The capabilities have not really changed,
Speaker 1: and while one might argue that more powerful will mean
Speaker 1: faster generative processes, there really is no barometer for what
Speaker 1: better looks like, and perhaps that's why Chat GBT, Claude
Speaker 1: and other lms have yet to take a leap beyond
Speaker 1: being able to generate pictures of Garfield and Lingerie are
Speaker 1: Scooby Doo with a gun anthropics. Claude LM might be
Speaker 1: and I quote, best in class according to tech Crunch,
Speaker 1: but that only means that it's faster and more accurate,
Speaker 1: which is cool, but not really the future or revolutionary
Speaker 1: or necessarily good in all cases. I should add that
Speaker 1: these are questions that I and other people writing about
Speaker 1: AI kind of should have been asking the whole time.
Speaker 1: General FAI generates outputs based on text based inputs and requests,
Speaker 1: and eventually multimodal will mean be able to look at
Speaker 1: something and generate an answer too, and these requests can
Speaker 1: be equally specific and intricate. Yet the answer is always
Speaker 1: as obvious as it sounds generated fresh, meaning that there's
Speaker 1: no actual knowledge or indeed intelligence operating in any part
Speaker 1: of the process. As a result, it's easy to see
Speaker 1: how this gets better ish faster, but much much harder to,
Speaker 1: if not impossible, to see how generative AI leads any
Speaker 1: further than where we're already at. And by that, I
Speaker 1: mean what does it do other than what it's doing today?
Speaker 1: What does chat GBT do today? That's radically different to
Speaker 1: eighteen months ago. The jump between say, two generations of iPhones,
Speaker 1: from the first iPhone to what it would be the
Speaker 1: iPhone three g I think it would be someone's going
Speaker 1: to email and say I'm wrong, and I'll say to them,
Speaker 1: you're very rude anyway, But that jump was huge, which
Speaker 1: faster internet meant you could do more with the phone.
Speaker 1: There was the app store, These were new functionalities added
Speaker 1: two years after the first iPhone, two years after the
Speaker 1: first chat GBT, and uh, I guess, I guess you
Speaker 1: could talk to it in a response that's not really
Speaker 1: great How does GPT, a transformer based model that generates
Speaker 1: answers probabilistically, as in, what the next part of the
Speaker 1: generation is most likely to be based on what's been inputed,
Speaker 1: based entirely on training data, How does it do anything
Speaker 1: more than generate paragraphs of occasionally accurate text or images,
Speaker 1: maybe a picture of Scooby Doo in lingerie. I don't know.
Speaker 1: But how do any of these models even differentiate from
Speaker 1: each other when most of them are trained on the
Speaker 1: same training data that they're already running out of? And
Speaker 1: what's crazy? Is I mentioned that I should have asked this,
Speaker 1: I really should have every single episode of mentioned AI.
Speaker 1: What does better even look like? What does more powerful
Speaker 1: even look like? Because when we say better, does that
Speaker 1: mean faster? Does that mean quicker to generate things? I
Speaker 1: mean it can generate more things? And the answer is
Speaker 1: usually not. It's not that it can actually function in
Speaker 1: a different way. It's just that you can do more,
Speaker 1: it can grow more. Hey, remember the idea of growth
Speaker 1: or cost Jesus right, But seriously, though, this feels like
Speaker 1: the question to ask Sam Ultiman or Mirror Marati the
Speaker 1: CTO of open AI's like, what's next? What's next, Oh,
Speaker 1: you can generate videos? When can I use that? Cool?
Speaker 1: What does better look like? They're other than not horrible looking? Okay,
Speaker 1: but what what more can GPT do? Because this thing,
Speaker 1: this thing can't think it's generating stuff, It doesn't know anything.
Speaker 1: It has training data. It eats up and then craps
Speaker 1: out an answer. How is that going to lead to
Speaker 1: even automation? I just and then how do you even
Speaker 1: deal with the fact that it really is running out
Speaker 1: of training data? And I've argued before the training data
Speaker 1: crisis is one that does not get enough attention, But
Speaker 1: it's sufficiently dire now that it has the potential to
Speaker 1: halt or at least dramatically slow any AI development in
Speaker 1: the future, by which I mean generative AI. As one
Speaker 1: paper published in the Journal of Computer Vision and Pattern
Speaker 1: Recognition found, in order to achieve a linear improvement in
Speaker 1: model improvements, you need an exponentially large amount of data.
Speaker 1: So it's not like they read something and then work
Speaker 1: something out from there. They need so much more to
Speaker 1: learn one thing kind of right, it's not very good
Speaker 1: and maybe there's another way to put it. Each additional
Speaker 1: step of training becomes increasingly and exponentially more expensive to
Speaker 1: take two. It requires you to get a bunch of
Speaker 1: training data and process more of it, but it also
Speaker 1: requires extremely expensive technology GPUs and a ton of energy
Speaker 1: to actually do so, and this infers a steep financial cost,
Speaker 1: not merely in just obtaining the data, but also, as
Speaker 1: I mentioned, the compute required to process it. And Anthropics
Speaker 1: CEO Dario Amadel said that the AI models currently in
Speaker 1: development will cost as much as a billion dollars to train,
Speaker 1: and within the next three years we may see models
Speaker 1: that cost ten or one hundred billion dollars to train,
Speaker 1: which is just insane, as that's roughly three times the
Speaker 1: GDP of Estonia, a beautiful, quite cold country. Back to
Speaker 1: mister Darren Smoblo, who doubts that llms can even become
Speaker 1: super intelligent and that even his most conservative estimates of
Speaker 1: productivity gains and I quote may turn out to be
Speaker 1: too large if AI models prove less successful in improving
Speaker 1: upon more complex tasks, and I think that's really the
Speaker 1: root of the problem. All of this excitement, every second
Speaker 1: of breathless beat off hype has been built on this
Speaker 1: idea that the artificial intelligence industry, led by General AVAI,
Speaker 1: will somehow revolutionize and automate everything from robotics to the
Speaker 1: supply chain, despite the fact that general IVAI is not
Speaker 1: actually going to solve these problems because it is not
Speaker 1: built to do so. I willn't have a calculator to
Speaker 1: drive my fucking car Jesus Christ. And While Asamoglu may
Speaker 1: have some positive things to say, for example, that AI
Speaker 1: models could be trained to help scientists conceive of and
Speaker 1: test new materials, which actually already happened thanks to Google
Speaker 1: DeepMind researchers, his general verdict is kind of harsh that
Speaker 1: using generative AI and quote too much automation too soon
Speaker 1: could create bottlenecks and other problems for firms that no
Speaker 1: longer have the flexibility in troubleshooting capabilities that human capital provides.
Speaker 1: In essence, replacing humans with AI might break everything. If
Speaker 1: you're one of those bosses that doesn't actually know what
Speaker 1: the fuck it is they're talking about, But you know what,
Speaker 1: I'm sure the following advertisements from people who know exactly
Speaker 1: what they're talking about, and we're back. The report also
Speaker 1: includes a palate cleanser for the quirked up AI hype fiends,
Speaker 1: and you'll find it on page where Goldman sax As.
Speaker 1: Joseph Briggs argues that generative AI will and I quote
Speaker 1: likely lead to significant economic upside based and I shit
Speaker 1: you not entirely on the idea that AI will replace
Speaker 1: workers in some jobs and then allow them to get
Speaker 1: jobs in other fields. Briggs also argues that, and I
Speaker 1: quote again, the full AI automation of AI exposed tasks
Speaker 1: that are likely to occur over a longer horizon could
Speaker 1: generate significant cost savings, which assumes that generative AI or
Speaker 1: AI itself will actually replace these tasks. But also, that's
Speaker 1: such a funny thing to say, Hey, you know, auto
Speaker 1: mating tasks over a long time could save money. Fucking hell,
Speaker 1: I should get a job at Goldmann Sex anyway, anyway. Sorry.
Speaker 1: I should also add that, unlike every single other interview
Speaker 1: in the report, Briggs continually mixes up AI and generative AI,
Speaker 1: and at one point suggests that recent generative AI advances
Speaker 1: are foreshadowing the emergence of a superintelligence. This is like
Speaker 1: suggesting that because I squeeze my washing up liquid and
Speaker 1: it's sprayed across the wall, that I'm one step close
Speaker 1: to becoming Picasso. I included this part of the report
Speaker 1: because sometimes, very rarely I get somebody suggesting that I'm
Speaker 1: not considering both sides. The reason I don't generally include
Speaker 1: both sides of this argument is that the AI hype
Speaker 1: side generally makes arguments based on the assumption that things
Speaker 1: will happen, such as a transformer model that probabilistically generates
Speaker 1: the next part of a sentence or a picture somehow
Speaker 1: gaining sentience. I wish my calculator gained sentience. During high school,
Speaker 1: I was a very lonely child. I did not have
Speaker 1: many friends. But no, all it would do is just
Speaker 1: let me kind of make it look like it said boobs.
Speaker 1: Then I'd get in a lot of trouble. But anyway.
Speaker 1: Francois Chole, an AI researcher at Google, recently argued that
Speaker 1: large language models like CHET GPT can't lead to average
Speaker 1: general intelligence, the sentient AI that everyone's excited about, explaining
Speaker 1: in detail in an interview with a podcast that I've
Speaker 1: linked in there, that models like GPT A simply not
Speaker 1: capable of the kind of reasoning and theorizing that makes
Speaker 1: a human brain work. Schley also argues that even models
Speaker 1: specifically built to complete the tasks of his abstraction and
Speaker 1: reasoning corpus a benchmark test for AI skills and true
Speaker 1: intelligence that he invented are only doing so because they've
Speaker 1: been fed millions of data points of people solving the test,
Speaker 1: which is kind of like measuring somebody's IQ based on
Speaker 1: them studying really hard to complete an IQ test except
Speaker 1: even dumber. But the reason that I'm suddenly bringing up
Speaker 1: these superintelligences or AGI artificial general intelligence average general intelligence,
Speaker 1: lots of people say different things. The reason I'm saying
Speaker 1: it is because throughout every single defense of generative AI
Speaker 1: is a really nasty, deliberate attempt to get around the
Speaker 1: problem that GENERATIVAI doesn't actually automate many tasks. While it's
Speaker 1: good at generating answers, sometimes even correct ones, or at
Speaker 1: creating things based on a request, sometimes with the right
Speaker 1: number of fingers, there's no real interaction with the task
Speaker 1: or the perse and giving the task, or considering what
Speaker 1: the task needs at all. Just the abstraction of things
Speaker 1: said to output generated orbit in quite a complex way.
Speaker 1: Tasks like taking someone's order and relaying it to the
Speaker 1: kitchen at a fast food restaurant might seem elementary to
Speaker 1: most people and I won't write easy, because working in
Speaker 1: fast food is a hard and horrible job. It might
Speaker 1: seem elementary, though, but it isn't for an AI model
Speaker 1: that generates answers without really understanding the meaning of any
Speaker 1: of the words. And really, I shouldn't have said the
Speaker 1: word really that it doesn't understand anything. Last year, Wendy's,
Speaker 1: a burger chain here in America, announced that it would
Speaker 1: integrate its generative Fresh AI ordering system into some restaurants.
Speaker 1: In late June, it revealed that the system requires human
Speaker 1: intervention on fourteen percent of the orders. On one redditor's post,
Speaker 1: they noted that Wendy's AI regularly required three attempts to
Speaker 1: get it to understand them, and would sometimes cut you
Speaker 1: off if you weren't speaking fast enough. Hey, it's two,
Speaker 1: am I connecting the words chicken sandwich, the diet codes
Speaker 1: difficult for me. Another burger place here in America, White Castle,
Speaker 1: which implemented a similar system in partnership with Samsung and SoundHound,
Speaker 1: fared a little better, with a remarkable ten percent of
Speaker 1: orders requiring human intervention. Last month, McDonald's discontinued its own
Speaker 1: AI ordering system, which it built with IBM and deployed
Speaker 1: to more than one hundred restaurants, likely because it wasn't
Speaker 1: very good, with one customer rang up for literally hundreds
Speaker 1: of chicken nuggets like the I think you should leave sketch. However,
Speaker 1: to be clear, McDonald's system wasn't actually based on GENERATIVAI,
Speaker 1: and if nothing else, all of these examples illustrate this
Speaker 1: disconnect between those building AI systems and how much, or
Speaker 1: really how little they understand the jobs they wish to eliminate.
Speaker 1: Little humility or doing a real job goes a long way.
Speaker 1: Another thing to note is that, on top of generative
Speaker 1: AI generally cocking up these orders, Whendy still requires human
Speaker 1: beings to make the fucking food. Despite all of this hype,
Speaker 1: all of this media attention, all of this incredible investment,
Speaker 1: the supposed innovations don't even seem capable of replacing the
Speaker 1: jobs that all of these horny capitalists have been planning
Speaker 1: for them to do. Not that they think they should,
Speaker 1: just I'm being told that this future is inevitable or indeed,
Speaker 1: here it's starting to really accept what the problem is
Speaker 1: with generative AI, though it isn't good at replacing the
Speaker 1: kind of jobs that actually affect the economy but commoditizing
Speaker 1: distinct acts of labor, and in the process the early
Speaker 1: creative jobs that help people build portfolios to advance in
Speaker 1: their industries. The freelancers having their livelihoods replaced by bosses
Speaker 1: using generative AI aren't being replaced so much as they're
Speaker 1: being shown how little respect many bosses have for their
Speaker 1: craft or the customer they allegedly serve. Copy editors and
Speaker 1: concept artists provide far more valuable work than any generative
Speaker 1: AI can yeat. An economy dominated by managers who don't
Speaker 1: appreciate or participate in labor means that these jobs are
Speaker 1: constantly under assault from large language models pumping out stuff
Speaker 1: that all looks and it sounds the same, to the
Speaker 1: point that the BBC reports that copywriters are now being
Speaker 1: paid to help them make the ais sound more human.
Speaker 1: One of the most fundamental misunderstandings of the bosses replacing
Speaker 1: these workers with generative AI is that you are not
Speaker 1: just asking for a thing, but outsourcing the risk and
Speaker 1: responsibility for delivering it. When I hire an artist to
Speaker 1: make a logo, my expectation is that they'll listen to
Speaker 1: me theyn add their own flare then will go back
Speaker 1: and forth with drafts until we have something I like
Speaker 1: and that they're proud of too. I'm paying them not
Speaker 1: just for their time, but for their years learning their
Speaker 1: craft and the output itself, and so the ultimate burden
Speaker 1: of production is not just my own, and that their
Speaker 1: experience means that they can adapt to circumstances that I
Speaker 1: might not have thought of. These are not things that
Speaker 1: you can train in a data set, because they're derived
Speaker 1: from experiences inside and outside of the creative process. While
Speaker 1: one can teach a generative AI what a billion images
Speaker 1: look like, AI doesn't get handcrams or a call at
Speaker 1: eight pm saying that something needs to pop more. It
Speaker 1: doesn't have moods, nor can it infer them from written
Speaker 1: or visual media, because human emotions are extremely weird, as
Speaker 1: our moods, our bodies, and our general existences. We're disgusting
Speaker 1: and weird and beautiful. And I realize all of this
Speaker 1: is a little flowery, but even the most mediocre copy
Speaker 1: ever written is on some level a collection of experiences,
Speaker 1: and fully replacing any creative is so very unlikely if
Speaker 1: you're doing so based on copying a million pieces of
Speaker 1: someone else's homework. Now, if I was looking for something creative,
Speaker 1: I get it from one of the following advertisements, which
Speaker 1: I am sure aligned perfectly with the things that I'm
Speaker 1: talking about. Won't make me look weird, won't have people
Speaker 1: email me. No, you're going to love the advertisements, and
Speaker 1: then you're not going to email me about them. All Right,
Speaker 1: we're back in the room. The most fascinating part of
Speaker 1: the Goldman Sex Report, and you'll find it on page ten,
Speaker 1: is an interview with Jim Cavello Goldman sax Is head
Speaker 1: of Global Equity Research. Cavello isn't a name you'll have
Speaker 1: heard unless you are, for whatever reason, a big semiconductor head,
Speaker 1: but he's consistently been on the right side of history,
Speaker 1: named as one of the top semiconductor analysts by LI
Speaker 1: Research for years, successfully catching the downturn in fundamentals in
Speaker 1: multiple major chip firms far before others did, at times
Speaker 1: mocked for quote being wrong and then turning out to
Speaker 1: be so very very right. And Jim, Jim Cavello, in
Speaker 1: no uncertain terms, thinks that GENERATIVEAI the whole bubble, this
Speaker 1: whole generative monstrosity kind of for shit. Cavello believes that
Speaker 1: the combined expenditure of all parts of the GENERATIVEAI boom,
Speaker 1: data centers, utilities, applications will cost a trillion dollars in
Speaker 1: the next several years alone, and he asks one very
Speaker 1: simple quest question, what trillion dollar problem will AI solve?
Speaker 1: He notes that replacing low wage jobs with tremendously costly
Speaker 1: technology is basically the polar opposite of the prior technology
Speaker 1: transitions that he's witnessed in the last thirty years. Just
Speaker 1: to be consistent with my AI to national GDP rubric,
Speaker 1: one trillion dollars is roughly half the GDP of Italy
Speaker 1: or the entire Danish economy multiplied by two and a
Speaker 1: half times. Yes, Denmark an EU and NATO member state
Speaker 1: that gave the world, among other things, a zempic, Lego
Speaker 1: and Aqua, the artist behind nineteen ninety seven Saccharin song
Speaker 1: of the Year Barbie Girl, one amazing country, and apparently
Speaker 1: their GDP is just a footnote in comparison to how
Speaker 1: much we have to spend on generating pictures of well
Speaker 1: Garfield in lingerie shooting at Scooby Doo. At this point,
Speaker 1: I'm just going to keep escalating one particular myth that
Speaker 1: Cavello dispels, and this was my favorite part is that
Speaker 1: many people compare generative AI to the early days of
Speaker 1: the Internet, and he knows so. It's that, even if
Speaker 1: it's in its infancy, the Internet was a low cost
Speaker 1: technology solution that enabled things like e commas to replace
Speaker 1: costly incumbent solutions, and that AI technology is exceptionally expensive,
Speaker 1: and to justify those costs, the technology must be able
Speaker 1: to solve complex problems, which it isn't designed to do.
Speaker 1: And that is a quote, by the way, hello's a beast.
Speaker 1: He also dismisses the suggestion that tech starts off expensive
Speaker 1: and gets cheaper over time as revisionist history, and that's
Speaker 1: a quote, and that quote again, the tech world is
Speaker 1: too complacent in the assumption that AI costs will decline
Speaker 1: substantially over time. He specifically notes that the only reason
Speaker 1: that Moore's law was capable of enabling smaller, faster, jeeper
Speaker 1: chips was because competitors like AMD forced Intel and other
Speaker 1: companies to compete, a thing that doesn't really seem to
Speaker 1: be happening with Nvidia, which is a near stranglehold on
Speaker 1: GPUs required to handle generative AI. And indeed, all of
Speaker 1: these other companies aren't really making competitive products. They're just
Speaker 1: kind of making the same thing. Google has their own
Speaker 1: video and text and image generator, sodas Lama, the Metawe,
Speaker 1: sodas chat GPT. It's all the same. There's no competition here.
Speaker 1: Kind of look a a cartail. Almost good idea for
Speaker 1: an episode. And while there are companies making these graphics
Speaker 1: process units aimed at the AI market, especially in China,
Speaker 1: where US trade restrictions prevent local companies from buying high
Speaker 1: powered cards like the A one hundred and video makes
Speaker 1: for fears that they'll be diverted to the Chinese military,
Speaker 1: they're not doing so at the same scale as in video,
Speaker 1: and Cavello notes that and I quote, the market is
Speaker 1: too complacent about the certainty of cost declients. He also
Speaker 1: notes that costs are so high that even if they
Speaker 1: were to come down, they'd have to do so dramatically,
Speaker 1: and that the comparison to the early days of the Internet,
Speaker 1: where businesses often relied on sixty four thousand dollars service
Speaker 1: from Sun Microsystems and there was no live cloud stories
Speaker 1: like Amazon Web Services or linod or Azure, those days
Speaker 1: paled in comparison to the current costs of generative AI,
Speaker 1: and that's even before you include the replacement of the
Speaker 1: power grid, which he says is a necessity to keep
Speaker 1: the boom going. I could probably just read you the
Speaker 1: entirety of Cavello's interview because it's just so nasty. I
Speaker 1: want to roll around on the floor on it. It's amazing
Speaker 1: and he's so good, and he even attacks one of
Speaker 1: my least favorite things, where he believes that when people say, oh,
Speaker 1: people didn't really think the iPhone was a big deal,
Speaker 1: the Internet was a big deal. Put specifically the iPhone
Speaker 1: and smartphones, they didn't think it was going to be big,
Speaker 1: and thus generative will be big. And he just says
Speaker 1: it's complete nonsense. He says that he sat through hundreds
Speaker 1: of presentations in the early two thousands, many of them
Speaker 1: including road maps that accurately fear how smartphones eventually rolled out,
Speaker 1: specifically noting things like GPS. So when GPS technology came down,
Speaker 1: of course that would be in a smartphone. That makes
Speaker 1: perfect sense. Just to be clear, this guy is there
Speaker 1: and he's a software and hardware analyst. He sits through
Speaker 1: presentations about what the future might look like all the time,
Speaker 1: and he said there's no such roadmap for generative AI,
Speaker 1: and there's no killer app either. He also notes the
Speaker 1: big tech companies now have no choice but to engage
Speaker 1: in an artificial intelligence ARM race given the hype, which
Speaker 1: will continue the trend of massive spending. And he believes
Speaker 1: that there are and I quote low odds of AI
Speaker 1: related revenue expansion, in part because he doesn't believe that
Speaker 1: generative AAI will make workers smarter, just more capable of
Speaker 1: finding better information faster, which is not great, by the way,
Speaker 1: and that any advantages that generative AI gives can be
Speaker 1: arbitraged the way because the tech can be used everywhere,
Speaker 1: and thus you can't as a company really raise prices.
Speaker 1: In fact, and bridging off from what he said there,
Speaker 1: what might happen is a race to the bottom, or
Speaker 1: maybe when things get too expensive, everyone will get more
Speaker 1: expensive too. None of this is good, by the way
Speaker 1: for them, but in plain English, just saying it, I'm
Speaker 1: just going to put it out there, you'll be supper.
Speaker 1: But what I'm about to say, generative AI isn't making
Speaker 1: any money for anybody because it doesn't actually make companies
Speaker 1: that use it any extra money. Efficiency is useful, but
Speaker 1: it's not company defining. Cavello also adds that hyperscalers like
Speaker 1: Google and Microsoft will also garner incremental revenue from AI,
Speaker 1: not the huge returns that they're perhaps counting on given
Speaker 1: their vast AI related expenditures over the last two years
Speaker 1: and the ridiculous things they've been doing, like putting generative
Speaker 1: AI in search. Jesus Christ Sundar. And this is damning
Speaker 1: for many reasons, chief of which is that the biggest
Speaker 1: thing that artificial intelligence is meant to do is be
Speaker 1: smart and make you smarter. Being able to access information
Speaker 1: faster might make you better at your job, but that's
Speaker 1: efficiency rather than allowing you to do something new. You're
Speaker 1: not actually really even being enhanced. This is one step
Speaker 1: above Google. But maybe it's an internal Google search. I
Speaker 1: guess you can generate really crappy looking ah. I'm just
Speaker 1: not sure where it is that. I don't think Jim
Speaker 1: is either. He ends with one important and brutal note
Speaker 1: that the more time that passes without significant AI applications,
Speaker 1: the more challenging and I quote the AI story will become,
Speaker 1: with corporate profitability likely floating the bubble as long as
Speaker 1: it takes for the tech industry to hit a more
Speaker 1: difficult economic period, kind of like we saw in the
Speaker 1: middle of twenty twenty two. He also add his own prediction,
Speaker 1: investor enthusiasm may begin to fade if important use cases
Speaker 1: don't start to become more apparent in the next twelve
Speaker 1: to eighteen months. And I think he's being a little optimistic.
Speaker 1: While I won't recount the rest of the report, one
Speaker 1: theme brought up repeatedly is the idea that America's power
Speaker 1: grid is literally not ready for GENERAIVAI. In anew in
Speaker 1: an interview with former Microsoft VP of Energy Brian Janus
Speaker 1: on page fifteen, the report details numerous nightmarish problems that
Speaker 1: the growth of GENERAIVAI is causing to the power grid,
Speaker 1: such as hyperscalas like Microsoft and Google increasing their power
Speaker 1: demands from a few hundred megawatts in the early twenty
Speaker 1: to tens to a few gigawatts by twenty thirty, enough
Speaker 1: to power multiple American cities, or the centralization of data
Speaker 1: center operations from multiple big tech companies in northern Virginia,
Speaker 1: potentially requiring a doubling of grid capacity over the next decade.
Speaker 1: Utilities they've not experienced a period of load growth as
Speaker 1: in a significant increase in power draw in nearly twenty years,
Speaker 1: which is a problem because power infrastructure is slow to
Speaker 1: build and involves numerous onerous permitting in bureaucratic measures to
Speaker 1: make sure it's done properly or at all, and the
Speaker 1: total capacity of power projects waiting to connect to the
Speaker 1: grid grew thirty percent in the last year and wait
Speaker 1: times of forty to seventy months. Expanding the grid is
Speaker 1: no easy or quick task, and Mark Zuckerberg said that
Speaker 1: these power constraints are the biggest thing in the way
Speaker 1: of AI, which is sort of true and remarkable for
Speaker 1: maguy who's are often full of shit in essence. On
Speaker 1: top of generative AI not having any killer apps, not
Speaker 1: meaningfully or helpfully increasing productivity, or GDP not generating any revenue,
Speaker 1: not creating any new jobs, or massively changing existing industries,
Speaker 1: it also requires America to rebuild its power grid, which
Speaker 1: is a good thing which Brian Jane has regrettably had
Speaker 1: that the US has kind of forgotten how to do.
Speaker 1: US doesn't really do be give infrastructure anymore. It's not
Speaker 1: a great scene. I don't know. Perhaps Sam Mortman's energy
Speaker 1: breakthrough could be these fucking AI companies being made to
Speaker 1: pay for new power infrastructure. And I don't mean them
Speaker 1: oaning it. I mean tax them, tax their asses they're
Speaker 1: burning the world, make them pay for it. The reason
Speaker 1: I so agonizingly picked apart this report is that if
Speaker 1: Goldman's sex is saying this, things are very, very bad.
Speaker 1: And it also directly attacks the specific hype tactics of
Speaker 1: AI freaks. The sense that generative AI will create new
Speaker 1: jobs really hasn't in the last eighteen months. The sense
Speaker 1: that costs will come down they haven't in there doesn't
Speaker 1: seem to be a part of them to do so
Speaker 1: in a way that matters. And that there's this incredible
Speaker 1: demand for these products they claim exists, and there really isn't,
Speaker 1: and I don't see a path to it even Goldman Sachs,
Speaker 1: when describing the efficiency benefits of AI, added that it
Speaker 1: was able to create an AI that updated historical data
Speaker 1: in its company models more quickly than doing so manually
Speaker 1: with one problem it costs six times as much to do.
Speaker 1: I love the AI future. I love artificial intelligence. I
Speaker 1: think it's so good that it's saving so many I
Speaker 1: feel crazy. I feel crazy, I feel sorry. Moving on now,
Speaker 1: there is a remaining defense, and it's also one of
Speaker 1: the most annoying. People sometimes argue that perhaps open ai
Speaker 1: has something we don't know about, some sort of big, sexy,
Speaker 1: secret technology that will break the bones of every hater
Speaker 1: that will bring me to my knees and beg the
Speaker 1: machine God for mercy. And I have account point. No,
Speaker 1: they don't. They don't have shit. Seriously. Mirror Marati, cto
Speaker 1: of open ai, said in early June that the models
Speaker 1: that open ai has in its labs are not much
Speaker 1: more advanced than those that are publicly available. And that's
Speaker 1: my answer to all of this. There is no magic trick.
Speaker 1: There is no secret thing that Sam Ortman has that
Speaker 1: he's going to reveal to us in the next few
Speaker 1: months that makes me eat cro or some magical tool
Speaker 1: the Microsoft or Google pops out that makes all of
Speaker 1: this worth it. There isn't. I'm telling you, there isn't.
Speaker 1: We would have seen a sign. There's not even a tinkle.
Speaker 1: There's not a rumor, there's not a leak. There's nothing.
Speaker 1: Generative AI, as I said a few months ago, is peaking.
Speaker 1: If it hasn't already peaked, it can't do more than
Speaker 1: it's currently doing. At least not much more other than
Speaker 1: maybe doing it faster with some new inputs. It isn't
Speaker 1: getting more efficient. SEQUOIA hype man David Kahn gleefully mentioned
Speaker 1: in a recent blog that Nvideo's B one hundred chips,
Speaker 1: the kinds used for training and running these models, will
Speaker 1: have two point five x better performance for only twenty
Speaker 1: five percent more cost, which doesn't mean a goddamn thing,
Speaker 1: because generative AI isn't going to gain sentience or intelligence
Speaker 1: or consciousness because it's able to run faster. I don't
Speaker 1: even think it's going to be able to do more things.
Speaker 1: Generative AI is not going to become AGI, nor will
Speaker 1: it become the kind of artificial intelligence you've seen in
Speaker 1: science fiction. Ultra smart assistance like Jarvis from Iron Man
Speaker 1: would require a kind of consciousness that no technology currently
Speaker 1: or may ever be able to produce, which is the
Speaker 1: ability to both process and understand information flawlessly and make
Speaker 1: decisions based on experience, which, if I haven't been clear enough,
Speaker 1: are all entirely distinct things. And generative AI and AI
Speaker 1: in general doesn't have experiences. They don't have shades of gray,
Speaker 1: They only have shades of brown. Poops, poop, joke. Generative
Speaker 1: AI at best processes of information when it trains on data,
Speaker 1: but at no point does it learn or understand because
Speaker 1: everything it's doing is based on ingesting, training, data, and
Speaker 1: developing answers based on a mathematical sense of probability rather
Speaker 1: than any appreciation or comprehension of the material itself. Llms
Speaker 1: are entirely different pieces of technology to that of an
Speaker 1: artificial intelligence in the sense that the AI bubble is
Speaker 1: hyping and it's disgraceful that the AI industry has taken
Speaker 1: so much money and attention with such a flagrant offensive lie.
Speaker 1: The jobs market isn't going to change because of generative AI,
Speaker 1: because generative AI can't actually do many jobs, and it's
Speaker 1: mediocre at the things that it's capable of doing, which
Speaker 1: is why it's so shocking. There are even people who'd
Speaker 1: replace real people with it. While it's a useful efficiency
Speaker 1: tool in specific contexts, said efficiency is based off of
Speaker 1: technology that's extremely expensive, and I believe at some point
Speaker 1: AI companies like Anthropic and OpenAI are going to have
Speaker 1: to increase prices or begin to collapse under the weight
Speaker 1: of a technology that has no path to profitability. If
Speaker 1: there was some secret way that this would all get fixed.
Speaker 1: Wouldn't Microsoft or Meta or Google or maybe Amazon, who's
Speaker 1: CEO of their cloud platform compared GENERATIVEAI to dot com
Speaker 1: bubble in February. Wouldn't they have taken advantage of this big,
Speaker 1: sexy secret. Why am I hearing the open AI is
Speaker 1: already trying to raise another multi billion dollar round after
Speaker 1: raising an indeterminate amount at an eighty billion dollar valuation
Speaker 1: in February. Isn't open AI's annualized revenue three point four
Speaker 1: billion dollars? Why do they need more money? How much
Speaker 1: are they burning? Because I'm guessing that if it's more
Speaker 1: than three point four billion dollars, it's got to be
Speaker 1: a lot more if they're still trying to raise capital,
Speaker 1: and if they're still going out there lying about what
Speaker 1: CHATGBT could do in the future. But I'll give you
Speaker 1: an educated guess, because whatever they open AI and other
Speaker 1: generative AI hucksters have today is obviously painfully not the future.
Speaker 1: Generative AI is not the future but a regurgitation of
Speaker 1: the past, a useful, yet not groundbreaking way to quickly
Speaker 1: generate new data from old that costs too much to
Speaker 1: make the compute and the energy demands worth it. Google
Speaker 1: grew its emissions by forty eight percent in the last
Speaker 1: five years, chasing a technology that made its search engine
Speaker 1: even worse than it already was, and they've got nothing
Speaker 1: to show for it other than a bunch of very
Speaker 1: funny headlines. It's genuinely remarkable how many people have been
Speaker 1: won over by this insane con this unscrupulous manipulation of
Speaker 1: the capital markets, the media, and brainless executives disconnected from production.
Speaker 1: They're all buying it, and it's all thanks to a
Speaker 1: tech industry that's disconnected itself from building useful things. I've
Speaker 1: been asked a few times when I think the bubble
Speaker 1: will burst, by the way, and I maintain that part
Speaker 1: of the collapse will be investor descent, punishing one of
Speaker 1: the major providers, Microsoft or Google for a massive investment
Speaker 1: in an industry that produces little actual revenue. However, I
Speaker 1: think what'll really get the bubble poppin will be a
Speaker 1: succession of bad events, like say, Figma pausing its new
Speaker 1: AI feature after it immediately plagiarized Apple's weather, likely because
Speaker 1: it was trained on it as part of its training data,
Speaker 1: crested by one large, nasty one such as a major
Speaker 1: AI company like chatbox company character ai, which raised one
Speaker 1: hundred and fifty million dollars in funding a few years ago,
Speaker 1: and the information great publication claims might sell to one
Speaker 1: of the bigger tech companies. I think someone like character
Speaker 1: ai could collapse under the way of a non sustainable
Speaker 1: business model and unprofitable technology and just also, do you
Speaker 1: really need a chat this is what this company does.
Speaker 1: You can speak to like sotorro Gojo from jiu jitsu Chism,
Speaker 1: which is an anime and amonga. By the way, if
Speaker 1: you're reading the margarets, take it too long and it's weird.
Speaker 1: It's one of these weird companies you can talk to
Speaker 1: historical figures and you're kind of like, okay, I assume
Speaker 1: you have a vague enterprise product. Oh no, it's all
Speaker 1: just nonsense. It's just when I see these companies and
Speaker 1: want they raise them, just like, what the fuck are
Speaker 1: you even doing all day? But it could be a
Speaker 1: slightly more useful sounding one like Cognition Ai, which raised
Speaker 1: one hundred and fifty seventy five million dollars a two
Speaker 1: billion dollar valuation in April to make an AI software
Speaker 1: engineer with one problem. Well, I mean it's just a
Speaker 1: small one. It was that they had to fake a
Speaker 1: demo of it working. They had to fake the demo,
Speaker 1: and I've included a link in the notes to a
Speaker 1: YouTube of a really great software engineer just sitting there
Speaker 1: saying I'm actually a fan of AI, but this is crap,
Speaker 1: and he just goes through it line by line. Basically,
Speaker 1: there's going to be a moment that spooks the venture
Speaker 1: capital firms, and it's going to spook them into pushing
Speaker 1: one of their startups to sell, which will lead to
Speaker 1: a sudden and unexpected yet very obvious collapse of a
Speaker 1: major player. As valuations drop and people get desperate for
Speaker 1: open AI and anthropic there really is no path profitability,
Speaker 1: only one that includes burning further billions of dollars in
Speaker 1: the hope that they discover something, anything, that might be
Speaker 1: truly innovative or indicative of the future, rather than further
Speaker 1: iterations of generative AI, which is at best an extremely
Speaker 1: expensive new way to process data. I just see no
Speaker 1: situation where open ai and anthropy continue to iterate on
Speaker 1: large language models in perpetuity, because at some point, Microsoft, Amazon,
Speaker 1: and Google will decide that cloud compute welfare isn't a
Speaker 1: business model. And by the way, all of those companies
Speaker 1: I listed, Microsoft, Amazon, and Google have either invested in
Speaker 1: open AI or Anthropic. In the case of Amazon and Google,
Speaker 1: they've only invested in anthropic, and a lot of that
Speaker 1: is in cloud credits, meaning that it's just welfare. It's hilarious,
Speaker 1: very right wing people in the tech industry. You think
Speaker 1: that this kind of welfa would bother them. I know
Speaker 1: what the difference is anyway, Without a real tangible breakthrough,
Speaker 1: one that would require them to leave the world of
Speaker 1: large language models entirely, it's unclear how generative AI companies
Speaker 1: can even survive. GENERATIVEAI is locked in the Red Queen's race,
Speaker 1: burning money to make money in an attempt to prove
Speaker 1: that they one day will make more money, despite their
Speaker 1: being no clear path to making more money than they spend.
Speaker 1: It's all a little wild, a little bit upsetting, and
Speaker 1: a little bit crazy making. And I feel a little
Speaker 1: bit crazy every time I put together one of these
Speaker 1: episodes because it's also patently ridiculous. GENERATIVEAI is unprofitable, unsustainable,
Speaker 1: and fundamentally limited in what it can do thanks to
Speaker 1: the fact that it's probabilistically generating an answer. It's not
Speaker 1: learning anything. It doesn't know anything. It isn't intelligent, it's
Speaker 1: only artificial. It's been eighteen months since this bubble started inflating,
Speaker 1: and since then very little has actually happened involving technology
Speaker 1: doing new stuff, just iterative explorations of the very clear
Speaker 1: limits of what an AI model that generates answers based
Speaker 1: on training data can produce, with the answer being something
Speaker 1: that at times is sort of good. It's obvious, it's
Speaker 1: well documented. GENERATIVEAI costs far too much, it isn't getting cheaper,
Speaker 1: it uses too much power, and doesn't do enough to
Speaker 1: justify its existence. There are no killer apps, and no
Speaker 1: killer apps on the horizon, and there are no answers
Speaker 1: to these problems. I don't know why more people aren't
Speaker 1: saying this as loudly as I am. I don't now
Speaker 1: why everyone's not freaking out. I understand that big tech
Speaker 1: desperately needs this to be the next hyper growth market,
Speaker 1: as they haven't got any others. But pursuing this cause
Speaker 1: our useful environmental disaster causing cloud efficiency boondoggle will send
Speaker 1: shock waves through the industry when it all collapses and
Speaker 1: what's frustrating to me about this is it's becoming obvious,
Speaker 1: and you're seeing people lately kind of come out their
Speaker 1: shells and saying, I'm not sure this is going to
Speaker 1: be good. I'm not sure are we hitting PKI as
Speaker 1: a great piece in the New York Times by someone
Speaker 1: recently saying that we hit PKI and it used a
Speaker 1: bunch of my links. Thank you, Julia. Anyway, putting aside
Speaker 1: my bitterness, the problem here is all of the money
Speaker 1: and power going into this, but also the big lie
Speaker 1: being perpetrated by people. In my next episode, I'm going
Speaker 1: to go into some more of that. I'm going to
Speaker 1: talk about the fact that a lot of these companies
Speaker 1: are not really doing anything that they're kind of doing
Speaker 1: marketing exercises as a means of manipulating the media in
Speaker 1: the markets. It's all just the discrace waste. The people
Speaker 1: getting hurt by Generative AI are people that are working
Speaker 1: contract jobs because it's harder than ever to get a
Speaker 1: full time job. They're being replaced by shitty software that
Speaker 1: cost too much money that will invariably go away when
Speaker 1: this all collapses. And I feel that the media has
Speaker 1: some responsibility here. The markets too, but definitely the media.
Speaker 1: I understand that it's difficult to look at the tech
Speaker 1: industry and think, are they all kind of leading us on?
Speaker 1: But they've done it so many times and this is
Speaker 1: the worst one I've seen. This is ridiculous. Billions of
Speaker 1: dollars wasted, so much time, so much energy, And yes,
Speaker 1: we can cover this, Yes we can talk about this.
Speaker 1: We don't owe them, are both sides. Why do we
Speaker 1: owe them that they wouldn't give us one? Have you
Speaker 1: ever seen a tech entrepreneur go, oh, that was a nice,
Speaker 1: fair interview? Or do they usually piss and moan the
Speaker 1: moment anyone says anything negative. No, the right way to
Speaker 1: look at this now is with suspicion and frankly most innovations,
Speaker 1: but in particular this one, because despite an alarming amount
Speaker 1: people in the media saying things like, oh yeah, well,
Speaker 1: generative I will of course lead to superintelligence, it's never
Speaker 1: going to do that. And we all I don't know
Speaker 1: if you consider me a reporter or a journalist. This
Speaker 1: is a conversation to have with me via my email,
Speaker 1: I guess, but whatever I am, I should not be
Speaker 1: the only one that's really going out this hard, and
Speaker 1: I know I'm not. There are other people, some people
Speaker 1: right about Brian Merchant on the Machine, fantastic Riyer another
Speaker 1: great guy, Paris Mark's another great guy doing great work.
Speaker 1: And Ellen Hewitt the Bloomberger was on a few episodes ago.
Speaker 1: Great coverage of Sam Hortmaan. But nevertheless, it is time
Speaker 1: to start saying when we cover generative AI, specifically open
Speaker 1: AI and Anthropic, hey, where are we with superintelligence? And
Speaker 1: I don't mean what level we're at, I mean what
Speaker 1: is the technology that you have that is going to
Speaker 1: lead to that? And when they refuse to give an answer,
Speaker 1: what should be covered is that they don't have one
Speaker 1: make them dance? Why do we have to do the
Speaker 1: work to make AI important? Why doesn't generative AI impress
Speaker 1: us right now? It's taking money out of people's hands,
Speaker 1: It's killing freelancers. It's really horrible. And the thing to
Speaker 1: cover is that you can cover fun apps. I don't
Speaker 1: have a problem with that, but when it comes to Google, Microsoft, Amazon,
Speaker 1: Open AI, Anthropic, all of these companies, we need to
Speaker 1: treat them as kind of interlopers at this point because
Speaker 1: they need to fucking show us what they're working on them.
Speaker 1: They need I don't care about the safety side. They
Speaker 1: don't care about it either. We don't need to worry
Speaker 1: about the safety issue right now, because the only safety
Speaker 1: issue is the problem we are facing today, which is
Speaker 1: that millions of people's works being stolen and millions of
Speaker 1: other people are having their jobs taken in the most
Speaker 1: mediocre way by shitty bosses who don't do any work.
Speaker 1: When Sam Altman gets on stage and claims that AI
Speaker 1: will solve all the physics, the appropriate answer is, what
Speaker 1: a fuck are you talking about? You sound like an idiot.
Speaker 1: When Brad light Caps, COO of Open AI says, I
Speaker 1: don't know if it's trained on YouTube, you should say
Speaker 1: why don't you know? And then when he bubbles away, goes, oh,
Speaker 1: I'm not sure. Say it's really weird that a company
Speaker 1: worth eighty billion dollars as a COO who does not
Speaker 1: know what's happening, saying goes from Mira Marati when she
Speaker 1: can't answer whether Sura was trained on YouTube. These people
Speaker 1: must be treated, if not as criminals, as suspicious types,
Speaker 1: as con artists, as people that have absorbed so much attention,
Speaker 1: so much money, so much time, so much adulation. They
Speaker 1: should be held accountable and holding them accountable starts with
Speaker 1: a real evaluation of generative AI. And as I've shown
Speaker 1: you today, this bubble is full of shit. I'm gonna
Speaker 1: end on a happier note, though I looked it up
Speaker 1: yesterday and as of speaking this out, it's only been
Speaker 1: four and a half months of this show show. I
Speaker 1: thought it had been six months or a year. I
Speaker 1: have time dilation issues in my brain and I will
Speaker 1: be seeing a doctor. But I genuinely want to thank
Speaker 1: all of you. I want to thank everyone who's been
Speaker 1: there from last episode or the first episode, everyone who's
Speaker 1: come through through different ways. This show's evolving and it
Speaker 1: will continue to evolve. I know I'm angry, I'm pissy,
Speaker 1: but I think at this time in history, there's a
Speaker 1: reason to be. I'm not feeling myself full of it.
Speaker 1: It's naturally there. It's naturally there. When I look at
Speaker 1: an industry, at tech industry that I genuinely love, that
Speaker 1: genuinely made me the person I am today, and I
Speaker 1: see what's being done to it, and it makes me
Speaker 1: so pissed off. Because technology is everything. We do. To
Speaker 1: discard tech as something that happens just on the computer
Speaker 1: and then there's real life. It's kind of silly. They're
Speaker 1: both the same thing. Now we are all influenced by
Speaker 1: offline and online culture, times far more by online culture.
Speaker 1: As this show progresses, I'm going to get more into that,
Speaker 1: and the upcoming episodes I have are going to be
Speaker 1: a lot of fun. The seconds of this week is
Speaker 1: just a real laugh, and it kind of showed me
Speaker 1: how this show can grow into a more conversational, fun,
Speaker 1: interesting thing where I talk to all sorts of folks
Speaker 1: about all sorts of things in tech and how it
Speaker 1: affects them. I'm really grateful for you all listening. You'll
Speaker 1: hear my email after that. And by the way, it's
Speaker 1: easy as an letter E letter Z or z from
Speaker 1: my British listeners. Email me easy abotter offline dot com,
Speaker 1: message me on Twitter or Facebook or Instagram. I'm always
Speaker 1: happy to hear from people. I want to know how
Speaker 1: to make this better, but I know one way is
Speaker 1: to just keep doing it. And I'm really excited for
Speaker 1: the future and I'm very very thankful to have all
Speaker 1: of you there, even the people who are very mad
Speaker 1: at me if you're not like in Generative AI. But seriously, though,
Speaker 1: one final thing. People will see this stuff and they
Speaker 1: do contact me fairly regularly, and they say, what can
Speaker 1: I do? And I said this at the end of
Speaker 1: the show Older Supremacy as well, but I'll say it
Speaker 1: here as well. You can't do a ton. What you
Speaker 1: can do is say people's names, Mirror Marathi, Sam Prabagar,
Speaker 1: ragavans Under Pashi. I know it sounds silly, but a
Speaker 1: lot of these ultra rich people, they don't care about experiences,
Speaker 1: don't really have predators. What they have is their reputations.
Speaker 1: But also what they have is their lies. I know
Speaker 1: it sounds a bit dramatic to say they're liars, but
Speaker 1: look at what Sam Moltman's saying. The only reason Sam
Speaker 1: Mortman has been able to get where he is today
Speaker 1: is a series of lies and cons. The way to
Speaker 1: break generative AI, which it should be broken until it
Speaker 1: can prove itself profitable and not environmentally destructive, is to
Speaker 1: push back, to constantly talk about how bad it is.
Speaker 1: To share your bad experiences with it, share every hallucination,
Speaker 1: share them publicly on social media channels. Tag Sam Multman
Speaker 1: at Samma on Twitter, Sama do it. I know this
Speaker 1: sounds silly, but guess what these people have grown so
Speaker 1: rich and powerful from nobody calling out their shit. And
Speaker 1: there are people up me. They're journalists who've done it.
Speaker 1: And I'm not saying nobody does it. Don't get mad
Speaker 1: at me. What I'm saying is thousands, tens of thousands,
Speaker 1: hundreds of thousands of people listening while this stuff sucks,
Speaker 1: why it's bad. We'll get to the tech people and
Speaker 1: eventually one of those messages will get to some of
Speaker 1: these financial people, and when they really turn against this,
Speaker 1: it will collapse. And if it doesn't, if I'm wrong,
Speaker 1: well I'll do an episode about how wrong I am,
Speaker 1: because you know what this is meant to be informative,
Speaker 1: it's meant to be entertainment. But also I don't mind
Speaker 1: being wrong, just kind of yet to be so someone's
Speaker 1: gonna be mad at that anyway. Thank you, Thank you
Speaker 1: for listening to Better Offline. The editor and composer of
Speaker 1: the Better Offline theme song is Metasowski. You can check
Speaker 1: out more of his music and audio projects at Matasowski
Speaker 1: dot com, m A. T. T OsO w Ski dot com.
Speaker 1: You can email me an easy, Better Offline dot com,
Speaker 1: or visit Better Offline dot com to find more podcast links,
Speaker 1: and of course my newsletter. I also really recommend you
Speaker 1: go to chat dot where's youreaed dot at to visit
Speaker 1: the discord, and go to our slash Better Offline to
Speaker 1: check out our reddit. Thank you so much for listening.
Speaker 1: Better Offline is a production of cool Zone Media. For
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