In short
Better Offline Podcast Episode Summary: Pop Culture
Episode Overview
- Host: Ed Zitron
- Key Theme: The skepticism surrounding the generative AI industry, as emphasized by a report from Goldman Sachs.
Episode Highlights
Introduction to the Episode
- Ed Zitron introduces the theme of the week: "bullshit," particularly focusing on the inflated promises surrounding generative AI.
- Reference to Goldman Sachs’ 31-page report titled *Gen AI, Too Much Spend? Too Little Benefit?* which questions the viability and promises of generative AI.
Key Findings from the Goldman Sachs Report
- Productivity Benefits: AI’s productivity benefits are likely limited.
- Projected Returns: Financial returns from AI investments are expected to be significantly lower than anticipated.
- Power Demands: A projected 40% increase in utility costs to support data center operations by tech giants like Google and Microsoft.
Expert Insights
- Daron Acemoglu (MIT Economist):
- Argues generative AI will have limited impact on productivity and GDP in the near future.
- Suggests that AI cannot improve complex tasks due to the multifaceted nature of human jobs.
The Reality of Generative AI
- Zitron critiques the marketing hype that AI models simply get better with more data and processing power.
- Questions like "What does it mean to double AI's capabilities?" and "What does ‘better’ look like in AI?" are raised.
- Comparison with Historical Technology Improvements: Contrasts generative AI's evolution with significant past technological leaps like the smartphone.
Financial Viability and Economic Impact
- Analysis of the high costs associated with training AI models (up to $1 billion per model).
- The unsustainable nature of current AI business models, where the costs of development may outweigh the potential benefits.
- Concerns about the energy infrastructure's ability to support the growing demands of AI technologies.
The Future of Jobs and Creative Work
- Zitron warns of the impact of generative AI on creative industries, highlighting how it commoditizes labor and undermines the value of skilled work.
- Real-world examples (e.g., Wendy’s AI ordering system) reveal AI’s limitations and the necessity for human oversight.
Critique of Optimism in AI Predictions
- Zitron challenges the belief that generative AI will inevitably lead to job creation, emphasizing the lack of transformative applications.
- Goldman Sachs analysts express skepticism about the expected revenue expansion from AI initiatives.
Conclusion
- Zitron concludes that the hype surrounding generative AI may not translate to reality, warning of a potential bubble in the AI market.
- Call to action for accountability within the tech industry regarding the promises made about AI.
Key Takeaways
- Skepticism of AI: The reports and expert opinions highlighted in this episode call for a critical reevaluation of the optimistic narratives surrounding AI.
- Economic Implications: The costs associated with generative AI may not yield the anticipated economic benefits, leading to broader concerns about sustainability.
- Impact on Labor: Generative AI may disrupt labor markets but fail to produce the promised productivity gains, raising ethical questions about its implementation.
Links & Resources
- [Goldman Sachs Report: Gen AI, Too Much Spend? Too Little Benefit?](https://tinyurl.com/betterofflinelinks)
- Ed Zitron's Social Media: [Twitter](http://www.twitter.com/edzitron), [Instagram](https://instagram.com/edzitron), [Threads](https://www.threads.net/@edzitron)
Final Thoughts
- Ed Zitron reflects on the evolution of the podcast and expresses gratitude to listeners for their support, while emphasizing the need for a continued dialogue about the implications of generative AI in society.
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This summary encapsulates the key themes and discussions from the podcast episode, providing a comprehensive overview of the skepticism surrounding generative AI as presented by Ed Zitron.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00This is an iHeart Podcast.
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1:12This is the cloud built for AI and all your biggest workloads. Right now, with zero commitment, try OCI for free. Head to oracle.com slash strategic. That's oracle.com slash strategic. Wells Fargo announced a new$20 million program in 2025, teaming up with nonprofits to support small business owners. That's how Wells Fargo is helping strengthen small businesses and communities. Wells Fargo, the bank of doing. Learn more at wellsfargo.com slash say do. Call Zone Media. Well, I know that arseholes grow on trees, but I'm here to trim the leaves. This is Better Offline. I'm your host, Ed Zitron.
2:03Better Offline It's bullshit week here at Better Offline headquarters. The thousands of elves that work 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 to, 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.
2:43That 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 a 31-page report titled Gen AI, Too Much Spend? Too Little Benefit? 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 in 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.
3:37The 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'll make a buck. 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 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.
4:23That 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 S. Amoglu of MIT, which can be found by the way on page four of the document, which you can find in this episode's 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 forecasters 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.
5:06And 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 report, 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.
5:50What 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 ai fantasists bullshit spiel they heavily rely on the idea that not only will these large language models llms like chat gpt get more powerful but the getting more powerful will somehow grant it the power to do something? As Asimoglu says, what does it mean to double it?
6:33What 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? GPT-4.0, 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 chat gbt claude 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.
7:20Anthropics Claude 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. general fai 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, if not impossible, to see how generative AI leads any further than where we're already at.
8:20And by that, I mean, what does it do other than what it's doing today? What does ChatGPT 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 first iPhone, two years after the first JetGPT, and I guess you could talk to it in a response?
8:59That'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 lingerie? 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.
9:35I really should have. Every single episode I've 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? Does it mean 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 it 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 Mira Morati, the CTO of OpenAI. Like, what's next? What's next?
10:12Oh, 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 GPT 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.
10:52by 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 here's another way to put it. each additional step of training becomes increasingly and exponentially more expensive to take too. 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.
11:36And 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 Anthropix CEO Dario Amadel 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 Assamoglu, 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.
12:21And I think that's really the root of the problem. All of this excitement, every second of 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 Asimoglu 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.
13:04That using generative AI and, quote, too much automation too soon could create bottlenecks and other problems for firms that no longer have the flexibility in 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.
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15:22New customer offer first three months only. Then full price plan options available. Taxes and fees extra. See mintmobile.com. And we're back. The report also includes a palate cleanser for the quirked-up AI hype fiends, and you'll find it on page 6, where Goldman Sachs' 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.
16:02Which 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 Sachs. 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.
16:42I 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 for 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.
17:15Then I'd get in a lot of trouble. But anyway, Francois Chollet, an AI researcher at Google, recently argued that large language models like ChatGPT 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. Schley 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.
17:56Which 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 HEI, artificial general intelligence, average general intelligence, lots of people say different things. The reason 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.
18:45Tasks 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 though, 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.
19:20On one Redditor's 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. Mate, it's 2am, 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.
20:03sketch. 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 generative 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.
20:44Not that I think they should, just I'm tired of being told that this future is inevitable, or indeed here. It's time 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.
21:21Copy 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 copywriters are now being paid to help them make the AIs 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.
21:56when 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.
22:31While 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.
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24:57All 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 of the top semiconductor analysts by LRAE 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.
25:32And Jim, Jim Covello, in no uncertain terms, thinks that generative AI, the whole bubble, this whole generative monstrosity, It's kind of full of shit Covello believes that the combined expenditure Of all parts of the degenerative 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 One trillion dollars 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 Zempig, Lego and Aqua The artist behind 1997's second 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?
26:46I'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 was 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.
Read the full transcript
27:30He 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 Llama, the meta one. So does ChatGPT. It's all the same. There's no competition here.
28:06Kind of like 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 A100 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.
28:40And 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 cavallo's interview because 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 is 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 generative AI will be big.
29:30And 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 that 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.
30:12And 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.
30:51But 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, Sundar.
31:27And 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 art i'm just not sure where it is and i don't think jim is either he ends with one important and brutal note that the more time that passes without 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.
32:18He 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.
32:34While 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 hyperscalers 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.
33:16Utilities, 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 McGuire who's so often full of shit.
33:54In essence, on top of generative AI not having any killer apps, not meaningfully or helpfully 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 Jane has regrettably heard 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 them owning it.
34:30I 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 generative 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.
35:18With 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 OpenAI 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, Mira Mirati, CTO of OpenAI, said in early June that the models that OpenAI has in its labs are not much more advanced than those that are publicly available.
36:11And that's my answer to all of this. There is no magic trick. There is no secret thing that Sam Altman 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 hype man David Kahn gleefully mentioned in a recent blog that Nvidia's B100 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.
37:12Generative AI is not going to become AGI, nor will it become the kind of artificial intelligence you've seen in science fiction. Ultra-smart assistants 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 joke.
37:48Generative 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.
38:35While it's a useful efficiency tool in specific contexts, said efficiency is based off of 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 OpenAI is already trying to raise another multi-billion dollar round after raising an indeterminate amount at an$80 billion valuation in February?
39:16Isn't OpenAI'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 dollars it's got to be a lot more if they're still trying to raise capital and if they're still going out they're 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.
40:00Google 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 dissent, punishing one of the major providers, Microsoft or Google, for a massive investment in an industry that produces little actual revenue.
40:47However, I think what will really get the bubble popping 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 one, 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 satoru gojo from jujutsu kaisen which is an anime and a manga by the way if you're reading the manga it's taking too long um 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.
41:39I 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 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 engineer just sitting there saying, I'm actually a fan of AI, but this is crap. And he just goes through it line by line.
42:19Basically, 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 OpenAI 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.
42:53I 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 I listed, Microsoft, Amazon, and Google, have either invested in OpenAI 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 think that this kind of welfare would bother them.
43:25I wonder what the difference is. Anyway, without a real tangible breakthrough, one that would 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 there 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.
44:36It'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 hyper-growth market, as they haven't got any others. But pursuing this quasi-useful environmental disaster-causing cloud efficiency boondoggle will send shockwaves through the industry when it all collapses.
45:13And what's frustrating to me about this is it's becoming obvious, and you're seeing people lightly kind of come out of their shells and say, I'm not sure this is going to be good. I'm not sure. Are we hitting PKI? There's a great piece in the New York Times by someone recently saying that we hit PKI 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 lie 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.
45:49That 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 ever to get a full-time job. They're being replaced by shitty software that costs too much money, that 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?
46:25But 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 of people in the media saying things like, oh yeah, well, generate value will of course lead to super intelligence, it's never going to do that.
47:10And 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 at this hard. And I know I'm not. There are other people, some people, Brian Merchant, fantastic writer, another great guy, Paris Marks, another great guy, doing great work. And Alan Huitt with Bloomberg was on a few episodes great coverage of sam altman but nevertheless it is time to start saying when we cover generative ai specifically open ai and anthropic hey where are we with super intelligence 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.
47:59Why 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 the physics the appropriate answer is what the fuck are you talking about you sound like an idiot when brad lightcap coo of open ai 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 because oh i just i'm not sure say it's really weird that a company worth 80 billion dollars as a coo who does not know what's happening same goes for mira marati 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.
49:39They 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 I have 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 show's evolving and it will continue to evolve I know I'm angry I know I'm pissy but I think at this time in history there's a reason to be.
50:20I'm not filling myself for the bag. 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.
50:56The 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 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 as in letter E, letter Z, or Z for my British listeners. Email me, easy at betteroffline.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.
51:29And 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 for 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 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. Mira Marati, Sam Altman, Prabhagar Raghavan, Sandhapishai. I know it sounds silly, but a lot of these ultra rich people, they don't care about experiences.
52:04They 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 Altman, at Sammer on Twitter.
52:40S-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 like me, there are journalists who've done it. And I'm not saying nobody does it. Don't 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.
53:18Because 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 kind of yet to be so. Someone's going to be mad at that. Anyway, thank you.
54:00podcast links, and of course, my newsletter. I also really recommend you go to chat.wheresyoured.at to visit the Discord, and go to r slash betteroffline 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.
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From the publisher
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.
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