Better Offline - Pop Culture

Episode Date: July 17, 2024

When the money gets nervous, so should you. In this episode, Ed Zitron walks you through a remarkable report from global investment bank Goldman Sachs where multiple economists call BS on the AI movement - and why it's time for the rest of the world to follow suit. LINKS: https://tinyurl.com/betterofflinelinks Newsletter: wheresyoured.at Reddit: http://www.reddit.com/r/betteroffline Discord chat.wheresyoured.at Ed's Socials - http://www.twitter.com/edzitron instagram.com/edzitron https://bsky.app/profile/zitron.bsky.social https://www.threads.net/@edzitron See omnystudio.com/listener for privacy information.

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Another podcast from some SNL late-night comedy guy, not quite. Unhumor me with Robert Smygel and friends. Me and hilarious guests from Bob Odenkirk to David Letterman, help make you funnier. This week, my guest, S&L's Mikey Day and headwriter, Streeter Seidel, help an a cappella band with their between songs banter. Where does your group perform? We do some retirement homes.

Those people are starving for banter. Listen to humor me with Robert Smigel and Friends on the I-Heart Radio app, Apple Podcasts, or wherever you get your podcasts. The story I've told myself can then shape my behavior, and that can lead me to sabotage the possibility of connection. This Mental Health Awareness Month, tune into the podcast Deeply Well with Debbie Brown if you've been searching for a soft place to land while doing the work to become whole. This podcast is for you to hear more.

Listen to Deeply Well with Debbie Brown from the Black Effect Podcast Network on the Iheart Radio app, Apple Podcasts, or wherever you get your podcast. Well, I know that assholes grow on trees, but I'm here to trim the leaves. This is better offline. I'm your host Ed Citron. It's bullshit week here at Better Offline Headquarters. The thousands of elves that worked for me have been finding me things that say bullshit for no reason when I wrote the episode weeks ago. I don't know what to do with them. But anyway, we're starting with one of the largest financial institutions in the world, calling bullshit on generative AI.

As usual, don't take my word for it. Check the episode notes for links that map to everything I'm talking about. I've tried my best to map them to exactly what I'm saying too, and you can feel free to yell about it, like yell out the words, like the Beastie Boys, or just follow along. Because I think it's important for you to know where I'm getting all of this from versus just assuming that I made it up somehow. That is an accusation I've had made, and I don't really know how I would do that. Anyway, the episode, I'm very sorry. At the tail end of June, Goldman Sachs, one of the largest global investment banks, put out the 31-page report titled Gen A.I.

Too much spend? Too little benefit? And that's with a question mark at the end. that includes some of the most damning literature on generative AI that I've ever seen. And yeah, that weepy sound and the background you hear is the slow, painful deflation of the bubble I've been warning you about since March. The report covers AI's productivity benefits, which Goldman remarks are likely limited, AI's returns, which are likely to be significantly more limited than anticipated, and AI's power demands, which are likely so significant

that utility companies will have to spend nearly 40% more in the next three years to keep up with the demand from hyperscalers and rot economists like Google and Microsoft. The report is so significant because Goldman Sachs, like any investment bank, doesn't care about your feelings or your happiness or emotions or anything unless doing so is profitable. It'll gladly hype up anything it thinks it will make a bug. Back in May, it published a report which claimed that AI, not just generative AI, was showing very positive signs of eventually boosting GDP and productivity, even though said report report buried within it, constant reminders that AI had yet to impact productivity growth,

and states that only 5% of companies report using Generative AI in regular production. For Goldman to suddenly turn on the AI movement suggests that it's extremely anxious about the future of Generative AI, with almost everybody agreeing on one core point in the report, that the longer the Generative AI takes to make people money, the more money that it's going to need to make. The report also includes an interview with economist Darren Asimoglu of MIT, which can be found by the way on page 4 of the document, which you can find in this episode spreadsheet of links.

An institute professor who published a paper back in May called the simple macroeconomics of AI that argued that, and I quote, the upside to US productivity and, consequently, GDP growth from generative AI will likely prove much more limited than many forecasts expect. A month has only made Asimoglu more pessimistic, declaring that truly transformative changes won't happen quickly and few, if any, will likely occur within the next 10 years. And that generative AI's ability to affect global productivity is low, because, and I quote again, many of the tasks that humans currently perform are multifaceted

and require real-world interaction, which AI won't be able to materially improve anytime soon. What makes this interview, and really the whole rapport, so remarkable, is how thoroughly and aggressively it attacks every bit of marketing collateral that the artificial intelligence movement has. Asimoglu specifically questions the belief that AI models will simply get more powerful as we throw more data and GPU, graphics processing unit, the thing that crunches the numbers, capacity at them and specifically asks a question. What does it mean to double AI's capabilities? How does that make something like, say, a customer service rep better? Seriously, though, what does better really get them?

Less errors? How do you quantify less errors without factoring in the current state introducing them? It's not great. And this really is a specific problem with the whole Gen. I.A.I. Fantasyists bullshit spiel. They heavily rely on the idea that not only will these large language models, LLMs, like ChatGPT, get more powerful, but the getting more powerful will somehow grant it the power to do...

Something? As Asamoglu says, what does it mean to double it? What does that do? No, really? What does that more actually mean? We've heard people talk about this for 18 months saying the more powerful chat GPT gets, the better it will get. But what does better even look like? GPT40, the latest version of chat GPT, other than accepting more inputs, is kind of the same thing. the capabilities have not really changed. And while one might argue that more powerful will mean faster generative processes, there really is no barometer for what better looks like, and perhaps that's why ChatGBT, GBT, Clord, and other LLMs have yet to take a leap

beyond being able to generate pictures of Garfield and lingerie or Scooby-Doo with a gun. Anthropics clawed LLM might be, and I quote, best in class, according to TechCrunch, but that only means that it's faster and more accurate, which is cool, but not really the future or revolutionary or unnecessarily good in all cases. I should add that these are questions that I and other people writing about AI kind of should have been asking the whole time. Generative AI generates outputs based on text-based inputs and requests, and eventually multimodal will mean you'll be able to look at something and generate an answer too.

And these requests can be equally specific and intricate, yet, the answer is always as obvious as it sounds generated fresh, meaning that there's no actual knowledge or indeed intelligence operating in any part of the process. As a result, it's easy to see how this gets better-ish, faster, but much, much harder to, if not impossible, to see how generative AI leads any further than where we're already at. And by that, I mean, what does it do other than what it's doing today? What does chat GPT do today that's radically different to 18 months ago? The jump between, say, two generations of iPhones,

from the first iPhone to what would be the iPhone 3G, I think it would be, someone's going to email and say I'm wrong and I'll say to them, you're very rude. Anyway, but that jump was huge. Faster internet meant you could do more with the phone. There was the app store. These were new functionalities added. Two years after the phone.

first iPhone. Two years after the first chat GPT and I guess you could talk to it and in response that's not really great. How does GPT, a transformer based model that generates answers probabilistically, as in what the next part of the generation is most likely to be based on what's been inputted, based entirely on training data? How does it do anything more than generate paragraphs of occasionally accurate text or images? Maybe a picture of Scooby-Doo in Laundra. I don't know. But how do any of these models even differentiate from each other when most of them are trained on the same training data that they're already running out of? And what's crazy is, I mentioned that I should have asked this.

I really should have. Every single episode of mentioned AI, what does better even look like? What does more powerful even look like? Because when we say better, does that mean faster? Does that mean quicker to generate things? It means it can generate more things. And the answer is usually not. It's not that it can actually function in a different way.

It's just that you can do more. It can grow more. Hey, remember the idea of growth at all costs? Jesus. But seriously, though, this feels like the question to ask Sam Altman or Miramarati, the CTO of OpenAI. Like, what's next? What's next? Oh, you can generate videos.

When can I use that? Cool. What does better look like there other than not horrible looking? Okay. But what more can you? do? Because this thing, this thing can't think. It's generating stuff. It doesn't know anything. It has training data. It eats up and then craps out an answer. How is that going to lead to even automation? I just, and then how do you even deal with the fact that it really is running out of training

data? And I've argued before the training data crisis is one that does not get enough attention, but it's sufficiently dire now that it has the potential to halt, or at least dramatically slow, any AI development in the future, by which I mean generative AI. As one paper published in the Journal of Computer Vision and Pattern Recognition found, in order to achieve a linear improvement in model improvements, you need an exponentially large amount of data. So it's not like they read something and then work something out from there. They need so much more to learn one thing kind of right.

It's not very good. And maybe it is another way to put it. each additional step of training becomes increasingly and exponentially more expensive to take two. It requires you to get a bunch of training data and process more of it, but it also requires extremely expensive technology, GPUs, and a ton of energy to actually do so. And this infers a steep financial cost, not merely in just obtaining the data, but also, as I mentioned, the compute required to process it. And Anthropic CEO Dario Amadale said that the AI models currently in development

will cost as much as a billion dollars to train. And within the next three years, we may see models that cost 10 or 100 billion dollars to train, which is just insane, as that's roughly three times the GDP of Estonia, a beautiful, quite cold country. But back to Mr. Darren Asimogler,

who doubts that LLMs can even become super-intelligent, and that even his most conservative estimates of productivity gains, and I quote, may turn out to be too large if AI models prove less successful in improving upon more complex tasks. And I think that's really the root of the problem. All of this excitement, every second a breathless beat-off hype has been built on this idea that the artificial intelligence industry, led by Generative AI,

will somehow revolutionize and automate everything from robotics to the supply chain, despite the fact that Generative AI is not actually going to solve these problems because it is not built to do so. I wouldn't have a calculator to drive my fucking car, Jesus Christ. And while Asamoglu may have some positive things to say, for example, that AI models could be trained to help scientists conceive of and test new materials, which actually already happened thanks to Google DeepMind researchers, his general verdict is kind of harsh,

that using generative AI and, quote, too much automation too soon, could create bottlenecks in other problems for firms that no longer have the flexibility and troubleshooting capabilities that human capital provides. In essence, replacing humans with AI, might break everything if you're one of those bosses that doesn't actually know what the fuck it is they're talking about. But you know what? I'm sure the following advertisements are from people who know exactly what they're talking about.

Another podcast from some SNL late-night comedy guide, not quite. Unhumor me with Robert Smygel and friends. Me and hilarious guests from Jim Gaffigan to Bob Odenkirk to David Letterman help make you funnier. This week, my guest, SNL's Mikey Day and head writer Streeter, Idell, help an a cappella band with their between songs banter. There's that worst singer in the group? The worst?

Yeah. Me. Is there anything to the idea that because you're from Harvard, you only got in because your parents made a huge donation. The group. The yard birds, right? That's the name. The Harvard yard, but they're open.

Do you have a name suggestion? We're open. Since you guys are middle aged. One erection. Listen to humor me with Robert Smigel and Friends on the IHeart radio app, Apple Podcasts, or wherever you get your podcast. Humor me. I need some jokes to make me seem funny. Run a business and not thinking about podcasting, think again. More Americans listen to podcasts than ad-supported streaming music from Spotify and Pandora.

And as the number one podcaster, IHearts twice as large as the next two combined. So whatever your customers listen to, they'll hear your message. Plus only IHeart can extend your message to audiences across broadcast radio. Think podcasting can help your business. Think IHeart. Streaming, radio, and podcasting. Let us show you at iHeartadvertising.com. That's iHeartadvertising.com.

Hey, everyone. It's Ryder Strong and Will Ferdell from PodMeets World. And now the Podmeets Twirled podcast. We're two men who were completely clueless to reality TV, who now have covered Dancing with the Stars, traders, and we're gearing up for the season finale of Survivor. So yeah, now we're experts. I know we annoyed a lot of our listeners by our severe lack of survivor knowledge.

That is the point of the show. I'm just going to remind you. I have watched some survivor. I obviously haven't watched enough. Did people not like it? Yeah. Just because we? Yeah.

We'll be recapping the big conclusion in the 50th season. From the final attempts at gameplay to the desperate pleas of finalists to a bunch of, ha, who. Again, we are experts. So make sure to tune into Pod Meets Twirled for all our Survivor 50 takes. Listen to PodMeets Twirled on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts. And we're back. The report also includes a pallet cleanser for the quirked-up AI hype fiends.

And you'll find it on page 6. Where Goldman Sachs is Joseph Briggs argues that generative AI will, and I quote, likely lead to significant economic upside-based, and I shit you not. entirely on the idea that AI will replace workers in some jobs and then allow them to get jobs in other fields. Briggs also argues that, and I quote again, the full AI automation of AI exposed tasks that are likely to occur over a longer horizon could generate significant cost savings, which assumes that generative AI or AI itself will actually replace these tasks, but also that's such a funny thing to say. hey, you know, automating tasks over a long time could save money.

Fucking hell, I should get a job at Goldman's X. Anyway, anyway, sorry. I should also add that, unlike every single other interview in the report, Briggs continually mixes up AI and generative AI, and at one point suggests that recent generative AI advances are foreshadowing the emergence of a superintelligence. This is like suggesting that because I squeezed my washing up liquid and it sprayed across the wall, that I'm one step closer to becoming Picasso.

I included this part of the report because sometimes, very rarely, I get somebody suggesting that I'm not considering both sides. The reason I don't generally include both sides of this argument is that the AI hype side generally makes arguments based on the assumption that things will happen, such as a transformer model that probabilistically generates the next part of a sentence or a picture somehow gaining sentience. I wish my calculator gained sentience during high school. I was a very lonely child.

I did not have many friends. But no, all it would do is just let me kind of make it look like it said boobs. Then I'd get in a lot of trouble. But anyway, Francois Chalet, an AI researcher at Google, recently argued that large language models like chat GPT can't lead to average general intelligence, the sentient AI that everyone's excited about, explaining in detail in an interview with a podcast that I've linked in there,

that models like GPT are simply not capable of the kind of reasoning and theorizing that makes a human brain work. Shely also argues that even models specifically built to complete the tasks of his abstraction and reasoning corpus, a benchmark test for AI, skills and true intelligence that he invented, are only doing so because they've been fed millions of data points of people solving the test, which is kind of like measuring somebody's IQ based on them studying really hard to complete an IQ test, except even dumber. But the reason that I'm suddenly bringing up these super intelligences, or H.E.I. Artificial General Intelligence, average general intelligence.

Lots of people say different things. The reason I'm saying it is because throughout every single defense of generative AI is a really nasty, deliberate attempt to get around the problem that generative AI doesn't actually automate many tasks. While it's good at generating answers, sometimes even correct ones, or creating things based on a request, sometimes with the right number of fingers, there's no real interaction with the task or the person giving the task or considering what the task needs at all, just the abstraction of things said to output generated, albeit in quite a complex way. Tasks like taking someone's

order and relaying it to the kitchen at a fast food restaurant might seem elementary to most people, and I won't write easy because working in fast food is a hard and horrible job. It might seem elementary though, but it isn't for an AI model that generates answers without really understanding the meaning of any of the words, and really I shouldn't have said the word really that. It doesn't understand anything. Last year, Wendy's a burger chain here in America, announced that it would integrate its generative, fresh AI ordering system into some restaurants. In late June, it revealed that the system requires human intervention on 14% of the orders. On one Redditters' post, they noted that Wendy's AI regularly required three attempts to get it to understand them and would

sometimes cut you off if you weren't speaking fast enough. Hey, it's 2am, I, connecting the words chicken sandwich to Diet Coke's difficult for me. Another burger place here in America, White Castle, which implemented a similar system in partnership with Samsung and Soundhound, fared a little better with a remarkable 10% of orders requiring human intervention. Last month, McDonald's discontinued its own AI ordering system, which it built with IBM and deployed to more than 100 restaurants, likely because it... wasn't very good, with one customer rang up for literally hundreds of chicken nuggets like the

I think you should leave sketch. However, to be clear, McDonald's system wasn't actually based on generative AI. And if nothing else, all of these examples illustrate this disconnect between those building AI systems and how much or really how little, they understand the jobs they wish to eliminate. Little humility or doing a real job goes a long way. Another thing to note is that on top of Genera AI generally cocking up these orders, Wendy still requires human beings to make the fucking food, despite all of this hype, all of this media attention, all of this incredible investment,

the supposed innovations don't even seem capable of replacing the jobs that all of these horny capitalists have been planning for them to do. Not that I think they should, just I'm tired of being told that this future is inevitable or indeed here. It's not to really accept what the problem, is with generative AI, though. It isn't good at replacing the kind of jobs that actually affect the economy, but commoditizing distinct acts of labor and in the process, the early creative jobs that help people build portfolios to advance in their industries. The freelancers having

their livelihoods replaced by bosses using generative AI aren't being replaced so much as they're being shown how little respect many bosses have for their craft, or the customer they allegedly serve. Copy editors and concept artists provide far more valuable work than any generative AI can. Yet an economy dominated by managers who don't appreciate or participate in labor means that these jobs are constantly under assault from large language models, pumping out stuff that all looks and sounds the same to the point that the BBC reports that copyrighters are now being paid to help them make the AI sound more human. One of the most fundamental misunderstandings of the bosses replacing these workers with generative AI is that you are not just asking for a thing,

but outsourcing the risk and responsibility for delivering it. When I hire an artist to make a logo, my expectation is that they'll listen to me, then add their own flair, then we'll go back and forth with drafts until we have something I like and that they're proud of too. I'm paying them not just for their time, but for their years, learning their craft and the output itself. And so the ultimate burden of production is not just my own. and that their experience means that they can adapt to circumstances that I might not have thought of.

These are not things that you can train in a dataset, because they're derived from experiences inside and outside of the creative process. While one can teach a generative AI what a billion images look like, AI doesn't get hand cramps or a call at 8pm saying that something needs to pop more. It doesn't have moods, nor can it infer them from written or visual media, because human emotions are extremely weird, as are our moods, our bodies and our general existences. We're disgusting and weird and beautiful.

And I realize all of this is a little flowery, but even the most mediocre copy ever written is on some level a collection of experiences. And fully replacing any creative is so very unlikely if you're doing so based on copying a million pieces of someone else's homework. Now, if I was looking for something creative, I get it from one of the following advertisements, which I am sure align perfectly with the things that I'm talking about

won't make me look weird, won't have people email me. No, you're going to love the advertisements, and then you're not going to email me about them. Another podcast from some SNL late-night comedy guide, not quite. Unhumor me with Robert Smigel and friends, me and hilarious guests from Jim Gaffigan to Bob Odenkirk, to David Letterman, help make you funnier. This week, my guest, SNL's Mikey Day and head writer Streeter Seidel,

help an a cappella band with their between songs banter. The worst singer in the group? The worst? Yeah. Me. Is there anything to the idea that because you're from Harvard, you only got in because your parents made a huge donation. The group.

The yard birds, right? That's the name. The Harvard yard, but they're open. Do you have a name suggestion? We're open. Since you guys are middle aged. One erection. Listen to you.

Humor Me with Robert Smigel and Friends on the IHeart Radio app, Apple Podcasts, or wherever you get your podcast. Humor me. I need some jokes to make me seem funny. Run a business and not thinking about podcasting, think again. More Americans listen to podcasts than ads supported streaming music from Spotify and Pandora. And as the number one podcaster, IHearts twice as large as the next two combined. So whatever your customers listen to, they'll hear your message. Plus only IHeart can extend your message to audiences across broadcast radio. Think podcasting can help your business.

Think IHeart. Streaming, radio, and podcasting. Let us show you at iHeartadvertising.com. That's iHeartadvertising.com. Hey, everyone. It's Ryder Strong and Will Ferdell from PodMeets World. And now the PodMeets Twirled podcast. We're two men who were completely clueless to reality TV,

who now have covered Dancing with the Stars, traders, and were gearing up for the season finale of Survivors. So yeah, now we're experts. I know we annoyed a lot of our listeners by our severe lack of survivor knowledge. That is the point of the show. I'm just going to remind you. I have watched some survivor. I obviously haven't watched enough.

Did people not like it? Yeah. Just because we? Yeah. We'll be recapping the big conclusion in the 50th season from the final attempts at gameplay to the desperate pleas of finalists to a bunch of, ha, ooh. Ha, ha, ooh. Again, we are experts.

So make sure to tune into Pod Meets Twirled for all our Survivor 50 takes. Listen to PodMeets Twirled on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts. All right, we're back in the room. The most fascinating part of the Goldman Sachs report, and you'll find it on page 10, is an interview with Jim Covello, Goldman Sachs' head of global equity research. Covello isn't a name you'll have heard unless you are, for whatever reason, a big semiconductor head. But he's consistently been on the right side of history, named as one at the top. semiconductor analysts by L.O.I. research for years, successfully catching the downturn in fundamentals

in multiple major chip firms far before others did, at times mocked for, quote, being wrong, and then turning out to be so very, very right. And Jim, Jim Covello, in no uncertain terms, thinks that generative AI, the whole bubble, this whole generative monstrosity, kind of full of shit. Kevello believes that the combined expenditure of all parts of the generative AI boom, data centers, utilities, applications, will cost a trillion dollars in the next several years alone, and he asks one very simple question. What trillion dollar problem will AI solve? He notes that replacing low-wage jobs with tremendously costly technology is basically the polar opposite of the prior technology transitions that he's witnessed in the last 30 years.

Just to be consistent with my AI to national GDP rubric, $1 trillion is roughly half the GDP of Italy, or the entire Danish economy multiplied by two and a half times. Yes, Denmark. An EU and NATO member state that gave the world, among other things, a Zenpig, Lego and Aqua, the artist behind 1997 Sakerin Song of the Year, Barbie Girl. One amazing country,

and apparently their GDP is just a footnote in comparison to how much we have to spend on generating pictures of, well, Garfield in lingerie shooting at Scooby-Doo at this point, I'm just going to keep escalating. One particular myth that Covello dispels, and this was my favorite part, is that many people compare generative AI to the early days of the internet. And he notes that even if it's in its infancy, the internet was a low-cost technology solution

that enabled things like e-commerce to replace costly incumbent solutions, and that AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn't designed to do. And that is a quote, by the way, that those are a beast. He also dismisses the suggestion that tech starts off expensive

and gets cheaper over time as revisionist history, and that's a quote. And that, quote, again, the tech world is too complacent in the assumption that AI costs will decline substantially over time. He specifically notes that the only reason that Moore's law was capable of enabling smaller, faster cheaper chips,

was because competitors like, AMD forced Intel and other companies to compete. A thing that doesn't really seem to be happening with Nvidia, which is a near stranglehold on GPUs required to handle generative AI. And indeed, all of these other companies aren't really making competitive products. They're just kind of making the same thing. Google has their own video and text and image generator. So does Lama, the meta one, so does chat GPT. It's all the same. There's no competition here. Kind of like a a cartel almost. Good idea for an episode. And while there are companies making these graphics process units aimed at the AI market, especially in China, where US trade restrictions

prevent local companies from buying high-powered cards, like the A-100 that Nvidia makes for fears that they'll be diverted to the Chinese military, they're not doing so at the same scale as Nvidia, and Covello notes that, and I quote, the market is too complacent about the certainty of cost declines. He also notes that costs are so high that even if they were to come down, they'd have to do so dramatically. And that the comparison to the early days of the internet, where businesses often relied on $64,000 service from Sun Microsystems, and there was no live cloud storage like Amazon Web Services or Linode or Azure,

those days paled in comparison to the current costs of generative AI, and that's even before you include the replacement of the power grid, which he says is a necessity to keep the boom going. I could probably just read you the entirety of Covello's interview, it's just so nasty. I want to roll around on the floor on it. It's amazing. And he's so good.

And he even attacks one of my least favorite things where he believes that when people say, oh, people didn't really think the iPhone was a big deal. The internet was a big deal. But specifically the iPhone and smartphones, they didn't think it was going to be big and thus generate of AI will be big. And he just says it's complete nonsense. He says that he sat through hundreds of presentations in the early 2000s,

many of them including roadmaps that accurately fear how smartphones eventually rolled out, specifically noting things like GPS. So when GPS technology came down, of course that would be in a smartphone. That makes perfect sense. Just to be clear, this guy is a software and hardware analyst. He sits through presentations about what the future might look like all the time. And he said there's no such roadmap for generative AI. And there's no killer app either.

He also notes the big tech companies now have no choice but to engage in an artificial intelligence arm race, given the hype, which will continue the trend of massive spending. And he believes that there are, and I quote, low odds of AI-related revenue expansion, in part because he doesn't believe that generative AI will make workers smarter, just more capable of finding better information faster, which is not great, by the way. And that any advantages that generative AI gives can be arbitraged away, because the tech can be used everywhere, and thus you can't, as a company, really raise prices, In fact, and bridging off from what he said there,

what might happen is a race to the bottom. Or maybe when things get too expensive, everyone will get more expensive too. None of this is good, by the way, for them. But in plain English. Just saying it, I'm just going to put it out there. You'll be surprised by what I'm about to say. Generative AI isn't making any money for anybody because it doesn't actually make companies that use it any extra money.

efficiency is useful, but it's not company defining. Covello also adds that hyperscalers like Google and Microsoft will also garner incremental revenue from AI, not the huge returns that they're perhaps counting on given their vast AI-related expenditures over the last two years and their ridiculous things they've been doing like putting generative AI in search Jesus Christ, Sondar. And this is damning for many reasons,

chief of which is that the biggest thing that artificial intelligence is meant to do is be smart and make you smarter. Being able to access information faster might make you better at your job, but that's efficiency rather than allowing you to do something new. You're not actually really even being enhanced. This is one step above Google,

but maybe it's an internal Google search, I guess. You can generate really crappy looking up. I'm just not sure where it is that I don't think Jim is either. He ends with one important and brutal note, that the more time that passes with a lot, that significant AI applications, the more challenging, and I quote, the AI story will become, with corporate profitability likely floating the bubble as long as it takes for the tech industry

to hit a more difficult economic period, kind of like we saw in the middle of 2022. He also adds his own prediction. Investor enthusiasm may begin to fade if important use cases don't start to become more apparent in the next 12 to 18 months. And I think he's being a little optimistic. While I won't recount the rest of the report, one theme brought up repeatedly is the idea that America's power grid is literally not ready for generative AI. In an interview with former Microsoft VP of Energy, Brian Janus, on page 15, the report details numerous, nightmarish problems that the growth of generative AI is causing to the power grid, such as hypers like Microsoft, Amazon, and Google, increasing their power demands from a few hundred megawatts in the early 2010s to a few gigawatts by

2030, enough to power multiple American cities, or the centralization of data center operations from multiple big tech companies in northern Virginia, potentially requiring a doubling of grid capacity over the next decade. Utilities, they've not experienced a period of load growth, as in a significant increase in power draw in nearly 20 years, which is a problem because power infrastructure is slow to build and involves numerous, onerous permitting and bureaucratic measures to make sure it's done properly or at all. And the total capacity of power projects waiting to connect to the grid grew 30% in the last year and wait times of 40 to 70 months. Expanding the grid is no easy

or quick task. And Mark Zuckerberg said that these power constraints are the biggest thing in the way of AI, which is sort of true and remarkable for a guy who's so often full of shit. In essence, on top of generative AI not having any killer apps, not meaningfully or hopefully increasing productivity or GDP, not generating any revenue, not creating any new jobs or massively changing existing industries, it also requires America to rebuild its power grid, which is a good thing, which Brian Janus regrettably had that the US has kind of forgotten how to do. US doesn't really do big infrastructure anymore. It's not a great scene. I don't know. Perhaps Sam Altman's energy breakthrough could be these fucking AI companies being made to pay for new power

infrastructure. And I don't mean the moaning it. I mean tax them. Tax their asses. They're burning the world. Make them pay for it. The reason I so agonizingly picked apart this report is that if Goldman Sachs is saying this, things are very, very bad. And it also directly attacks the specific hype tactics of AI freaks, the sense that generate of AI will create new jobs. It really hasn't in the last 18 months. The sense that costs will come down. They haven't, and there doesn't seem to be a path for them to do so in a way that matters. And that there's this incredible demand for these products, they claim exists, and there really isn't, and I don't see a path to it. Even Goldman Sachs, when describing the efficiency benefits of AI, added that it was able to create an AI that

updated historical data in its company models more quickly than doing so manually. With one problem, it costs six times as much to do. I love the AI future. I love artificial intelligence. I think it's so good that it's saving so many. I feel crazy. I feel crazy. I feel.

Sorry. Moving on. Now, there is a remaining defense, and it's also one of the most annoying. People sometimes argue that perhaps open AI has something we don't know about, some sort of big, sexy secret technology that will break the bones of every hater, that will bring me to my knees and beg the machine god for mercy. And I have a counterpoint. No, they don't.

They don't have shit. Seriously, Miramirati, CTO of OpenAI, said in early June that the models that Open AI has in its labs are not much more advanced than those that are publicly available. And that's my answer to all of this. There is no magic trick. There is no secret thing that Sam Orkman has that he's going to reveal to us in the next few months

that makes me eat crow, or some magical tool that Microsoft or Google pops out that makes all of this worth it. There isn't. I'm telling you there isn't we would have seen a sign. There's not even a tinkle. There's not a rumor. There's not a leak.

There's nothing. Generative AI, as I said a few months ago, is peaking if it hasn't already peaked. It can't do more than it's currently doing. At least not much more, other than maybe doing it faster with some new inputs. It isn't getting more efficient. Sequoia hypeman, David Kahn, gleefully mentioned, in a recent blog, that Mvideo's B-100 chips, the kinds used for training and running these models, will have 2.5x better performance for only 25% more cost,

which doesn't mean a goddamn thing, because generative AI isn't going to gain sentience or intelligence or consciousness, because it's able to run faster. I don't even think it's going to be able to do more things. Generative AI is not going to become AGI, nor will it become the kind of artificial intelligence you've seen in science fiction. Ultra-smart assistance like Jarvis from Iron Man would require a kind of consciousness

that no technology currently or may ever be able to produce, which is the ability to both process and understand information flawlessly and make decisions based on experience, which, if I haven't been clear enough, are all entirely distinct things and Generative AI and AI in general doesn't have experiences. They don't have shades of grey. They only have shades of brown. It's a poop.

It was a poop joke. Generative AI at best processes information when it trains on data, but at no point does it learn or understand, because everything it's doing is based on ingesting training data and developing answers based on a mathematical sense of probability, rather than any appreciation or comprehension of the material itself. LLMs are entirely different pieces of technology to that of an artificial intelligence, in the sense that the AI bubble is hyping, and it's disgraceful that the AI industry has taken so much money and attention with such a flagrant offensive lie. The jobs market isn't going to change because of generative AI, because generative AI can't

actually do many jobs, and it's mediocre at the things that it's capable of doing, which is why it's so shocking there are even people who'd replace real people with it. While it's a useful efficiency tool in specific contexts, said efficiency is based off a technology that's extremely expensive, and I believe at some point AI companies like Anthropic and OpenAI are going to have to increase prices or begin to collapse under the weight of a technology that has no path to profitability. If there was some secret way that this would all get fixed,

wouldn't Microsoft or META or Google or maybe Amazon, who's CEO of their cloud platform compared to generative AI to the dot-com bubble in February, wouldn't they have taken advantage of this big, sexy secret? Why am I hearing that Open AI is already trying to raise another multi-billion dollar round after raising an indeterminate amount

at an 80 billion dollar valuation in February? Isn't Open AI's annualized revenue $3.4 billion? Why do they need more money? How much are they burning? Because I'm guessing that if it's more than $3.4 billion, it's got to be a lot more if they're still trying to raise capital, and if they're still going out there lying about what chat GBT could do in the future. But I'll give you an educated guess.

Because whatever they, Open AI and other generative AI hucksters, have today is obviously, painfully, not the future. Generative AI is not the future, but a regurgitation of the past, a useful yet not groundbreaking way to quickly generate new data from old that costs far too much to make the compute and the energy demands worth it. Google grew its emissions by 48% in the last five years, chasing a technology that made its search engine even worse than it already was. And they've got nothing to show for it, other than a bunch of very funny headlines. It's genuinely remarkable how many people have been won over by this. insane con, this unscrupulous manipulation of the capital markets, the media and brainless executives disconnected from production, they're all buying it, and it's all thanks to a tech industry that's

disconnected itself from building useful things. I've been asked a few times when I think the bubble will burst, by the way, and I maintain that part of the collapse will be investor descent, punishing one of the major providers, Microsoft or Google, for a massive investment in an industry that produces little actual revenue. However, I think what will really get the bubble pop in will be a succession of bad events, like, say, Figma, pausing its new AI feature after it immediately plagiarized Apple's weather app,

likely because it was trained on it as part of its training data, crested by one large, nasty ones, such as a major AI company like Chatbot company Character AI, which raised $150 million in funding a few years ago, and the information, great publication, claims, might sell to one of the bigger tech companies. I think someone like character AI could collapse under the weight of an unsustainable business model and unprofitable technology. And just also, do you really need a check?

This is what this company does. You can speak to like Satoro Gojo from Jujutsu Kaysam, which is an anime and a manga. By the way, if you're reading the manga, it's taken too long. And it's weird. It's one of these weird companies you can talk to historical figures and you're kind of like, okay, I assume you have a vague enterprise product. I don't know. It's all just nonsense. It's just when I see these companies and what they raise, I'm just like, what the fuck are you even doing all day?

But it could be a slightly more useful sounding one, like cognition AI, which raised $175 million, a $2 billion valuation in April, to make an AI software engineer with one problem. Well, I mean, it's just a small one. It was that they had to fake a demo of it working. They had to fake the demo. And I've included a link in the notes to a YouTube of a really great software engine. and they're just sitting there saying, I'm actually a fan of AI, but this is crap, and he just goes through it line by line. Basically, there's going to be a moment that spooks the venture capital firms, and it's going

to spook them into pushing one of their startups to sell, which will lead to a sudden and unexpected yet very obvious collapse of a major player as valuations drop and people get desperate. For Open AI and Anthropic, there really is no path to profitability, only one that includes burning further billions of dollars in the hope that they discover something. anything that might be truly innovative or indicative of the future, rather than further iterations of generative AI, which is at best an extremely expensive new way to process data. I just see no situation where OpenAI and Anthropic continue to iterate on large language models in perpetuity, because at some point, Microsoft, Amazon, and Google will decide

that cloud compute welfare isn't a business model. And by the way, all of those companies that listed, Microsoft, Amazon, and Google have either invested in Open AI or Anthropic. In the case of Amazon and Google, they've only invested in Anthropic. And a lot of that is in cloud credits, meaning that it's just welfare. It's hilarious. Very right-wing people in the tech industry. You think that this kind of welfare would bother them. I wonder what the difference is. Anyway, without a real tangible breakthrough, one that require them to leave the world of large language models entirely, it's unclear how generative AI companies can even survive. Generative AI is locked in the Red Queen's race, burning money to make

money in an attempt to prove that they one day will make more money despite their being no clear path to making more money than they spend. It's all a little wild, a little bit upsetting and a little bit crazy making, and I feel a little bit crazy every time I put together one of these episodes, because it's all so patently ridiculous. Generative AI is unprofitable, unsustainable, and fundamentally limited in what it can do thanks to the fact that it's probabilistically generating an answer. It's not learning anything.

It doesn't know anything. It isn't intelligent. It's only artificial. It's been 18 months since this bubble started inflating. And since then, very little has actually happened involving technology doing new stuff, just iterative explorations of the very clear limits of what an AI model that generates answers

based on training data can produce, with the answer being something that at times is sort of good. It's obvious. It's well documented. Generative AI costs far too much. It isn't getting cheaper. It uses too much power and doesn't do enough to justify its existence. There are no killer apps and no killer apps on the horizon. And there are no answers to these problems. I don't know why more people aren't saying this as loudly as I am. And I don't know why everyone's not freaking out. I understand that big tech desperately needs this to be the next hypergrowth market as they haven't got any others. But pursuing this quasi-useful environmental disaster. are causing cloud efficiency boondoggle will send shockwaves through the industry when it all collapses.

And what's frustrating to me about this is it's becoming obvious and you're seeing people lightly kind of come out of their shelves and say, I'm not sure this is going to be good. I'm not sure. Are we hitting PKK? There's a great piece in the New York Times

by someone recently saying that we hit PKK and it used a bunch of my links. Thank you, Julia. Anyway, putting aside my bitterness, the problem here is all of the money and power going into this, but also the big, by being perpetrated by people.

In my next episode, I'm going to go into some more of that. I'm going to talk about the fact that a lot of these companies are not really doing anything, that they're kind of doing marketing exercises as a means of manipulating the media and the markets. It's all just a disgraceful waste. The people getting hurt by generative AI are people that are working contract jobs because it's harder than never to get a full-time job. They're being replaced by shitty software that cost too much money but will invariably go away when this all collapses.

And I feel that the media has some responsibility here. The markets too, but definitely the media. I understand that it's difficult to look at the tech industry and think, are they all kind of leading us on? But they've done it so many times and this is the worst one I've seen. This is ridiculous. Billions of dollars wasted. So much time, so much energy.

And yes, we can cover this. Yes, we can talk about this. We don't owe them both sides. Why do we owe them that? They wouldn't give us one. Have you ever seen a tech entrepreneur go, oh, that was a nice, fair interview? Or do they usually piss and moan the moment anyone says anything negative?

No, the right way to look at this now is with suspicion, and frankly, most innovations. But in particular this one, because despite an alarming amount, people in the media, saying things like, oh, yeah, well, generate if I am, of course, lead to superintelligence. It's never going to do that. And we all, I don't know if you consider me a reporter or a journalist,

this is a conversation to have with me via my email, I guess. But whatever I am, I should not be the only one that's really going out this hard. And I know I'm not. There are other people. Brian Merchant, on the machine, fantastic writer. Another great guy. Paris Marx, another great guy, doing great work. And Alan Hewitt with Bloomberg was on a few episodes ago.

Great coverage of Sam Hortman. But nevertheless, it is time to start saying when we cover generative AI specifically, open AI and anthropic, hey, where are we with superintelligence? And I don't mean what level we're at. I mean, what is the technology that you have that is going to lead to that? And when they refuse to give an answer, what should be covered is that they don't have one. Make them dance. Why do we have to do the work to make AI important?

Why doesn't generative AI impress us? Right now, it's taking money out of people's hands. It's killing freelancers. It's really horrible. And the thing to cover is that. You can cover fun apps. I don't have a problem with that. But when it comes to Google, Microsoft, Amazon, OpenAI, Anthropic, all these companies,

we need to treat them as kind of interlopers at this point because they need to fucking show us what they're working on. and they need, I don't care about the safety side. They don't care about it either. We don't need to worry about the safety issue right now because the only safety issue is the problem we are facing today, which is that millions of people's works being stolen and millions of other people are having their jobs taken in the most mediocre way by shitty bosses who don't do any work.

When Sam Altman gets on stage and claims that AI will solve all of physics, the appropriate answer is, what a fuck are you talking about? You sound like an idiot. when Brad Lightcap, COO of OpenAI, says, oh, I don't know if it was trained on YouTube, you should say, why don't you know? And then when he bubbles away, he goes,

oh, I'm not sure, say it's really weird that a company worth $80 billion as a CEO who does not know what's happening. Same goes for Miramorati when she can't answer whether Zora was trained on YouTube. These people must be treated, if not as criminals. As suspicious types, as con artists, as people that have absorbed so much attention, so much money, so much time, so much adulation, they should be held accountable.

And holding them accountable starts with a real evaluation of generative AI. And as I've shown you today, this bubble is full of shit. Now, I'm going to end on a happier note, though. I looked it up yesterday, and as of speaking this out, it's only been four and a half months of this show. I thought it had been six months or a year. time dilation issues in my brain, and I will be seeing a doctor. But I genuinely want to thank all of you. I want to thank everyone who's been there from last episode or the first episode, everyone who's come through through different ways. This shows evolving and it will continue to

evolve. I know I'm angry. I'm pissy. But I think at this time in history, there's a reason to be. I'm not filling myself full of anger. It's naturally there. It's naturally there when I look at an industry, a tech industry that I genuinely love, that genuinely made me the person I am today, and I see what's being done to it. And it makes me so pissed off because technology is everything we do. To discard tech as something that happens just on the computer and then there's real life,

it's kind of silly. They're both the same thing now. We are all influenced by offline and online culture. At times, far more by online culture. As this show progresses, I'm going to get more into that. And the upcoming episodes I have are going to be a lot of fun. The second episode this week is just a real laugh. And it kind of showed me how this show can grow into a more conversational, fun, interesting thing,

where I'd talk to all sorts of folks about all sorts of things in tech and how it affects them. I'm really grateful for you all listening. You'll hear my email after that, and by the way, it's EZ, isn't letter E, letter E, letter Z, or Z from my British listeners? Email me, easy at better offline.com. Message me on Twitter or Facebook or Instagram. I'm always happy to hear from people. I want to know how to make this better. But I know one way is to just keep doing it.

and I'm really excited for the future and I'm very, very thankful to have all of you there. Even the people who are very mad at me if you're not like in Generative AI. But seriously though, one final thing. People will see this stuff and they do contact me fairly regularly and they say what can I do?

And I said this at the end of the shareholder at supremacy as well, but I'll say it here as well. You can't do a ton. What you can do is say people's names. Miramorati, Sam Ormunga, Ragabangavan, Sandhapha, Sanda Pishai. I know it sounds silly, but a lot of these ultra-rich people, they don't care about experiences. They don't really have predators.

What they have is their reputations. But also, what they have is their lies. I know it sounds a bit dramatic to say they're liars, but look at what Sam Altman's saying. The only reason Sam Altman has been able to get where he is today is a series of lies and cons. The way to break generative AI, which it should be broken until it can prove itself profitable and not environmentally destructive, is to push back, to constantly talk about how bad it is, to share your bad experiences with it, share every hallucination, share them publicly on social media channels. Tag Sam Haltman, at Sam are on Twitter.

S-A-M-A. Do it. I know this sounds silly, but guess what? These people have grown so rich and powerful from nobody calling out their shit. And there are people at me, they're journalists, who've done it, and I'm not saying nobody does it. I'll get mad at me. What I'm saying is thousands, tens of thousands, hundreds of, thousands of people listening why this stuff sucks, why it's bad, we'll get to the tech people.

And eventually one of those messages will get to some of these financial people. And when they really turn against this, it will collapse. And if it doesn't, if I'm wrong, well, I'll do an episode about how wrong I am. Just, you know what? This is meant to be informative, it's meant to be entertainment. But also, I don't mind being wrong. It's just kind of yet to be so. Someone's going to be mad at that.

Anyway, thank you. Thank you for listening to Better Offline. The editor and composer of the Better Offline theme song is Matt Rosowski. You can check out more of his music and audio projects at Mattersowski.com. M-A-T-T-O-S-O-S-K-I.com. You can email me at E-Z at Better Offline.com or visit Better Offline.com to find more podcast links and, of course, my newsletter. I also really recommend you go to chat.

Where's Your Ed dot at to visit the Discord, and go to our slash better offline to check out our Reddit. Thank you so much for listening. Better Offline is a production of Cool Zone Media. For more from Cool Zone Media, visit our website, coolzonemedia.com, or check us out on the IHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

Another podcast from some SNL, late-night comedy guy, not quite. Unhumor me with Robert Smygel and friends, me and hilarious guests from Bob Odenkirk to David Letterman help make you funnier. This week, my guest, S&L's Mikey Day and headwriter, Streeter Seidel, help an a cappella band with their between songs banter. Where does your group perform?

We do some retirement homes. Those people are starving for banter. Listen to humor me with Robert Smigel and friends on the I-Heart Radio app, Apple Podcasts, or wherever you get your podcasts. The story I told myself can then shape my behavior, and that can lead me to sabotage the possibility of connection. This Mental Health Awareness Month, tune into the podcast Deeply Well with Debbie Brown

if you've been searching for a soft place to land while doing the work to become whole. This podcast is for you to hear more. Listen to Deeply Well with Debbie Brown from the Black Effect Podcast Network on the Iheart Radio app, Apple Podcasts, or wherever you get your podcast. I'm Joey Dardano.

And on my new podcast, Hope from a Hypocrite, I'll be changing lives, helping people in need with thoughtful solutions. psych! I'm a comedian! I'm not qualified to give good advice. Join me and my comedian friends as we riff, rant, recommend some of the most legally dubious advice known to me. This is Help from a Hypocrite, the worst advice from the dumbest people you know. Listen to Help from a Hypocrite Wednesdays on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts. This is an IHeart podcast. Guaranteed human.