Speaker 1: Call Zone Media. Hi, I'm Edzeitron and welcome back to
Speaker 1: Better Offline. As I've discussed in my last episode, there
Speaker 1: are four intractable problems that are going to stop generative
Speaker 1: AI from going much further. It's massive energy demands, its
Speaker 1: massive computation demands. It's hallucinations when it authoritatively tells you
Speaker 1: something that isn't true or makes horrible mistakes in images,
Speaker 1: and the fact that these large language models have this
Speaker 1: insatiable need for more training data. Yet I think what
Speaker 1: might pop this bubble is a far simpler problem. Generative
Speaker 1: AI simply does not deliver the magical automation that everybody
Speaker 1: has been fantasizing about, and I don't think consumers or
Speaker 1: enterprises are actually impressed. A year and a half after launch,
Speaker 1: it seems like the kind of immediate and unquestioning in
Speaker 1: fact youation with chat GBT and for that matter, or
Speaker 1: other generative AIS has softened. Instead, there's this rising undercurrent
Speaker 1: of apathy and mistrust and of course failure that's kind
Speaker 1: of hard to ignore. In June twenty twenty three, traffic
Speaker 1: to chat GPT's website, where people access the chat GPT
Speaker 1: bot in a web browser fell for the first time
Speaker 1: since launch, starting a trend that's continued for five of
Speaker 1: the following eight months. According to data from similar Web,
Speaker 1: people are becoming more aware of the technology's limitations, like
Speaker 1: as I mentioned, hallucinations, which, as I note, is when
Speaker 1: chat gpt confidently asserts things that aren't true, which can
Speaker 1: be in writing, when it gives you an incorrect fact,
Speaker 1: or in an image when it gives a dog eighteen
Speaker 1: legs to make matters worse. According to data from data Ai,
Speaker 1: which used to be known as Appanny, chat gbt's downloads
Speaker 1: in iOS have begun to drop from a high of
Speaker 1: just over seven hundred thousand a week to a plateau
Speaker 1: of around four hundred and fifty thousand to five hundred
Speaker 1: thousand a week since early twenty twenty three, which sounds
Speaker 1: impressive until you hear that only seven point three five
Speaker 1: percent of people who downloaded chatgbt in January twenty twenty
Speaker 1: four actually used the app again thirty days after they
Speaker 1: downloaded it, cratering from a high of twenty eight percent
Speaker 1: a month after the app launched in June twenty twenty three.
Speaker 1: In fact, things immediately appear to have fallen apart in
Speaker 1: July twenty twenty three, only two months after launch, only
Speaker 1: four point five nine percent of users opened the app
Speaker 1: for a second time. Numbers like these tell the story
Speaker 1: of a buzzy new application that isn't actually providing users
Speaker 1: with much utility. I think the generative AI engine has
Speaker 1: started to sputter for customers, for businesses, and indeed for
Speaker 1: the startups that create them. That's bad news for any
Speaker 1: industry that's yet to reach profitability or indeed sustainability, and
Speaker 1: especially for generative AI, which remains relying on a kind
Speaker 1: of an indefinite supply of cash to operate. Back in
Speaker 1: April twenty twenty three, Dylan Patel, chief analyst at Semi Analysis,
Speaker 1: calculated that GPT three, the previous generation of chech GPT
Speaker 1: current ones known as GPT four, cost around seven hundred
Speaker 1: thousand dollars a day to run. It's about twenty one
Speaker 1: million dollars a month, or two hundred and fifty million
Speaker 1: dollars a year. In October twenty twenty three, Richard Windsor,
Speaker 1: the research director at large of Counterpoint Research, which is
Speaker 1: one of the more reliable analyst houses, hypothesized that open
Speaker 1: AI's monthly cash burn was in the region of one
Speaker 1: point one billion dollars a month, based on them having
Speaker 1: to raise thirteen billion dollars from Microsoft, most of it,
Speaker 1: as I noted in credits for its Azure cloud computing
Speaker 1: service to run their models. It could be more, it
Speaker 1: could be less. As a private company, only investors and
Speaker 1: other insiders can possibly know what's going on in open Ai. However,
Speaker 1: four months later, Reuter's would report that open aye made
Speaker 1: about two billion dollars in revenue in twenty twenty three,
Speaker 1: a remarkable sum that much like every other story about
Speaker 1: open ai, never mentions profit. In fact, I can't find
Speaker 1: a single reporter that appears to have asked Sam Mormon
Speaker 1: about how much profit open ai makes, only breathless hype
Speaker 1: with no consideration of its sustainability. Even if open ai
Speaker 1: burns a tenth of windsors estema about one hundred million
Speaker 1: dollars a month, that's still far more money than they're making.
Speaker 1: There's not a single story out there talking about them
Speaker 1: making a profit, and I don't think they make in one.
Speaker 1: Here's one thing we can be certain of. Though things
Speaker 1: are getting more expensive, progress in generative AI means increasingly
Speaker 1: complex models, and as I previously mentioned open AI's attempted
Speaker 1: God damn it a Rakis model one, built specifically to
Speaker 1: wow Microsoft by making chatgiputy more efficient, failed to actually
Speaker 1: make it more efficient. Their attempts to make this a
Speaker 1: better company are not working. Windsor the aforementioned analyst in
Speaker 1: a separate blog also pointed out that there's nothing really
Speaker 1: sticky about these companies. There's nothing stopping someone from switching from, say,
Speaker 1: chat GPT to anthropics clawed two model. They're all trained
Speaker 1: on similar data sets, and they all produce very similar answers.
Speaker 1: And what one model might be better a one thing than another,
Speaker 1: they're fundamentally very very similar. There's also nothing stopping someone
Speaker 1: from simply giving up on generative AI altogether. It doesn't
Speaker 1: seem to be the plug and play automation god that
Speaker 1: everybody's been replicate to be, and judging by the plateauing
Speaker 1: Chat GPT user numbers, I think that might already be happening.
Speaker 1: It's also important to remember that while generative AI is
Speaker 1: shiny and new artificially, intelligence is absolutely not, and over
Speaker 1: the past decade it's found a number of homes from
Speaker 1: expensive security apps that detect when a hacker is trying
Speaker 1: to break into a corporate network. The spam filters proof
Speaker 1: for reading tools like grammarly, Plenty of Things, even Siri
Speaker 1: on your iPhone. In these context, AI is either a
Speaker 1: small component of a larger product or something that directly
Speaker 1: builds on human efforts. This stuff is actually valuable. AI
Speaker 1: based spam filters are typically better than those reliant on
Speaker 1: hand coded rules, for example, But it's also from a
Speaker 1: marketing perspective, can of boring generative AIS A law is
Speaker 1: that it can supplant humans either partially or entirely, producing
Speaker 1: entire creative works that otherwise would have taken hours and
Speaker 1: carried a real financial cost. But behind this glitzy technology
Speaker 1: and media hype, the unspoken truth is that generative AI
Speaker 1: holds way over the financial markets because it's regarded as
Speaker 1: a tool to eliminate an entire swarth of jobs in
Speaker 1: the creative and knowledge economies. It's a ghastly promise and
Speaker 1: it underpins the vast market value of otherwise commercially unviable
Speaker 1: generative AI companies like open Ai and Anthropic, and it's
Speaker 1: what is driving I believe the multi billion dollar investments
Speaker 1: we've seen from Microsoft, Amazon, and Google yeah, I see
Speaker 1: no evidence of mass adoption of generative AI, and by
Speaker 1: research suggests the enterprise adoption, which is the meat of
Speaker 1: what would actually make these companies money, it just isn't there.
Speaker 1: Deep within the earnings reports and the quotes of every
Speaker 1: major cloud provider claiming that the AI revolution is here
Speaker 1: is a deeply worrying trend. The AI revenue really isn't
Speaker 1: contributing much to the bottom line outside of vacuous media coverage,
Speaker 1: and I think the internal story is going to be
Speaker 1: much bleaker. In early March, The Information published the story
Speaker 1: about Amazon and Google tamping down GENERATIVEAI expectations, with these
Speaker 1: companies dousing their salespeople's excitement about the capabilities of the
Speaker 1: tech they're selling. A tech executive is quoted in the
Speaker 1: article saying that customers are beginning to struggle with questions,
Speaker 1: simple questions like is AI actually providing value? And how
Speaker 1: do I evaluate how AI is doing? And a Gartner
Speaker 1: analyst told Amazon Web Services sales staff that the AI
Speaker 1: industry was at the peak of the hype cycle around
Speaker 1: large language models and other generative AI, which is a
Speaker 1: somewhat specific code for it's not going to get much
Speaker 1: better anytime soon. This article confirms many of my suspicions
Speaker 1: that and I quote the information here, other software companies
Speaker 1: that have touted generative AI as a boon to enterprises
Speaker 1: are still waiting for revenue to emerge, citing the example
Speaker 1: of professional services firm KPMG buying forty seven thousand subscriptions
Speaker 1: to Microsoft's Copilot AI at a significant discount on the
Speaker 1: thirty dollars a c sticker price. Except KPMG bought the
Speaker 1: subscriptions without really have engaged whether their employees actually got
Speaker 1: anything out of it. They bought it, and I'm not
Speaker 1: kidding you entirely so that if any KPMG customers ask
Speaker 1: questions about AI, they'll be able to answer them. Was
Speaker 1: so clearly in the bot Oh my god. Anyway, as
Speaker 1: I've hinted, it's also not obvious how much AI actually
Speaker 1: contributes to the bottom line. In Microsoft's Q four twenty
Speaker 1: twenty three earnings report, gief financial officer Amy Hood reported
Speaker 1: that six points of revenue growth in its Azureine Cloud
Speaker 1: Services division was attributed to AI services. I went around
Speaker 1: the web and I read every bloody article about their earnings.
Speaker 1: I looked, and I looked and everyone was saying, Oh,
Speaker 1: this is really good. I found someone who said it
Speaker 1: was six percent of their revenue, and I went, that
Speaker 1: sounds like complete bollocks to me. So I went and
Speaker 1: spoke with Jordan Novette, who's covered Microsoft for many years.
Speaker 1: He is a great cloud reporter over at CNBC, and
Speaker 1: he actually covered Microsoft's earnings for the NBC itself, and
Speaker 1: he confirmed that what this means is that AI contributed
Speaker 1: six percent of the thirty percent of year over year
Speaker 1: growth in Microsoft's as your Cloud services. That is a
Speaker 1: percentage of a percentage. So by the way that that means,
Speaker 1: so thirty percent growth year of year. So six percent
Speaker 1: year of a year growth is from AI. Could be good,
Speaker 1: but also all of the rest of it came not
Speaker 1: from new products, just from the natural growth of the company.
Speaker 1: It's unclear how much money that really is, but six
Speaker 1: percent of the year over year growth isn't really that
Speaker 1: exciting anyway elsewhere. Amazon CEO Andy Jasse, who took over
Speaker 1: from Bezos a few years ago and was the chief
Speaker 1: of Amazon Web Services, said that generative AI revenue was
Speaker 1: still relatively small, but don't worry, you said it would
Speaker 1: drive tens of billions of dollars of revenue over the
Speaker 1: next several years, adding that virtually every consumer business Amazon
Speaker 1: operated in already had or would have generative AI offerings.
Speaker 1: Now they can just say that stuff. I really want
Speaker 1: you to know. You can say what you want on
Speaker 1: earning scores, as long as you're not just outright lying,
Speaker 1: like saying we have one hundred billion dollars in cash,
Speaker 1: but you have fifty dollars. That is a lie. You
Speaker 1: can't do that. But you can be like iah At
Speaker 1: We've got all sorts of AI and everything. Now it's
Speaker 1: bloody magically. Take you don't take a look, but it's there.
Speaker 1: I promise you. They can just say what they want.
Speaker 1: But don't worry, they're not the only ones. Salesforce chief
Speaker 1: financial officer Amy Weaver said in their most recent earning
Speaker 1: score that Salesforce was not factoring in material contribution from
Speaker 1: Salesforce's numerous AI products in its financial year twenty twenty five.
Speaker 1: Guidance software company Adobe shares slid in their last earnings.
Speaker 1: It's the company failed to generate meaningful revenue from its
Speaker 1: masses of AI products, with analysts now worried about its
Speaker 1: ability to actually monetize any of these generative products. Service
Speaker 1: now claimed to its earnings that generative AI was meaningfully
Speaker 1: contributed to its bottom line. Yet a story from The
Speaker 1: Information quotes their chief financial officer as saying that from
Speaker 1: a revenue contribution perspective, it's not going to be huge.
Speaker 1: Going to be a bit honest and feeling a little
Speaker 1: insane with this stuff. I feel crazy every time I
Speaker 1: think about these stories, because elsewhere in the media, so
Speaker 1: many people are saying how big and successful the generative
Speaker 1: AI revolution is, and it's going to be Yeah. Every
Speaker 1: time I look at the actual places where they write
Speaker 1: down how much money it makes, any of the actual
Speaker 1: signs of growth and significance and utility and adoption, it's
Speaker 1: just not there. It's just breathless hype, with this kind
Speaker 1: of whisper of stagnation and non existent adoption. And while
Speaker 1: there are startups beginning to mind usefulness out of general AI,
Speaker 1: and they do inside by automating internal queries and customer
Speaker 1: sport questions, these are integrations rather than revolutions, and they're
Speaker 1: far from the substance of a true movement. Maybe the
Speaker 1: darker truth of the generative AI boom is that it's
Speaker 1: a feature, not a product, and that these features might
Speaker 1: be built entirely off the back of large language models
Speaker 1: which are unsustainable to run, grow, or even make better.
Speaker 1: What if AI only drives a couple percentage points of
Speaker 1: real revenue growth of these companies. What if what we're
Speaker 1: seeing today is the upper limit, not the beginning. Honestly,
Speaker 1: I'm beginning to believe that a large part of the
Speaker 1: AI boom is just hot air, and it's being pumped
Speaker 1: up through a combination of executive bullshittery and very compliant
Speaker 1: media that's so happy to write stories imagining what AI
Speaker 1: can do, yet seems unable to check what it can
Speaker 1: do or what it's doing. It's so weird. Now, there's
Speaker 1: a bloke over at the Wall Street Journal called Chipcutter
Speaker 1: who should really look into if you want to know
Speaker 1: why your boss keeps asking you to go back to
Speaker 1: the office. Wall Street Journal's Chip Cutter. He loves to
Speaker 1: write things about how bosses are good and how returning
Speaker 1: to the office is good. He wrote a piece in
Speaker 1: March about how AI is being integrated into the office,
Speaker 1: and most of it was just hundreds of words of
Speaker 1: him guessing about what people might do but when he
Speaker 1: gets to the bottom and he starts talking about companies
Speaker 1: using it, it's almost entirely exact samples of people saying, yeah,
Speaker 1: it makes too many mistakes for us to rely on it,
Speaker 1: and we're just experimenting it. Elsewhere in the media, the
Speaker 1: New York Times talked with Salesforce is head of AI
Speaker 1: Clara's share and in this I think six hundred and
Speaker 1: seven hundred word article, didn't really get to say much
Speaker 1: of anything about AI or what their products do. All
Speaker 1: she said was that the Einstein Trust layer handles data.
Speaker 1: And you may think I'm being facetious here, that's all
Speaker 1: she said about that, and then she added that it
Speaker 1: would be transformational for jobs the way the internet was.
Speaker 1: What what does that mean? Why am I reading this
Speaker 1: in the newspaper? Why is this what I read in
Speaker 1: the newspaper? How is this helping? I know I rant
Speaker 1: a lot on this podcast, and I'm going to keep
Speaker 1: doing it. You're stuck with me, all right, it's free, Okay,
Speaker 1: you don't pay for this unless you do cooler zone media,
Speaker 1: which you should pay for anyway. I know I'm ranting,
Speaker 1: But the reason that this stuff really infuriates me is
Speaker 1: it's misinformation on some level. I know it's kind of
Speaker 1: dramatic to say, oh, they're misinforming people by suggesting that
Speaker 1: AI can do stuff, but it is. It is misinformation.
Speaker 1: When you're letting corporate executives go in the newspaper and
Speaker 1: talk about how amazing their products will be without asking
Speaker 1: them what they can do today, you're just giving them
Speaker 1: free press. You're not giving them credit for stuff they've done.
Speaker 1: You're giving them credit for things they're making up on
Speaker 1: the spot. And when you do that, you make the
Speaker 1: rich richer and the poor poorer. You centralize power in
Speaker 1: the hands of assholes, people who are excited, people who
Speaker 1: are borderline masturbatory, jumping around saying, oh God, I can't
Speaker 1: wait till and replace humans with fucking computers. Good news
Speaker 1: is they're not going to be able to, but that's
Speaker 1: what they're excited about, and that's what they're getting media
Speaker 1: coverage around. The media has been fooled, just like they
Speaker 1: were with the metaverus, by this specious promise train of
Speaker 1: the generative AI generation, and these worthless executives champions these
Speaker 1: half truths and this magical thinking has spread far faster
Speaker 1: due to the fact that AI actually exists and is
Speaker 1: doing something, and it's actually much easier to imagine how
Speaker 1: it might change our lives, unlike the metaverse. Even if
Speaker 1: the way it might do so is somewhere between improbable
Speaker 1: and impossible, it is easy to think about how my work.
Speaker 1: You know, you could use an AI to or make
Speaker 1: data entry or boring busy work. Surely all of this
Speaker 1: you can automate, right, And when you use chat GPT
Speaker 1: you can almost kind of, sort of somewhat see how
Speaker 1: it might happen. Even if when you open up chat
Speaker 1: GPT and try and make it do something, it's always
Speaker 1: a bit off, never seems to quite do it. I'm
Speaker 1: in a very in my day job, my PR firm.
Speaker 1: I'm in a spreadsheet and document heavy business. Of all
Speaker 1: the people who this could help, you think it would
Speaker 1: be me A lot of my work is hey, all
Speaker 1: of these things I need him in a spreadsheet. It
Speaker 1: can't bloody do it. And I'm sure you listeners will
Speaker 1: probably email me and say, oh, I've used CHATGPT for this,
Speaker 1: don't care. I really mean that this thing is not
Speaker 1: changing the world. And actually I think far more of
Speaker 1: you have already shared. Thank you. By the way, easy.
Speaker 1: At Better off Line dot com. You can email me
Speaker 1: your ideas and your angry comments, so you can go
Speaker 1: on the reddit to complain. But the thing I'm hearing
Speaker 1: for most people is, yeah, I've tried it and it
Speaker 1: didn't do enough. I tried it and there were too
Speaker 1: many mistakes. There was a Wall Street Journal article back
Speaker 1: in February about how Amazon and Google were having trouble
Speaker 1: selling AI services because well, when they went to sell
Speaker 1: them these companies, these financial services companies in particular, they
Speaker 1: were saying, yeah, but these hallucinations could actually get the
Speaker 1: sec mad at us. And the answer that they had was, yeah,
Speaker 1: what if we just made it so that the models
Speaker 1: would sometimes say they don't know stuff. Every time you
Speaker 1: get to a reckoning with AI where you want it
Speaker 1: to be better, where you're like, hey, AI executive, how
Speaker 1: will this actually be fixed these hallucination problems, for example,
Speaker 1: they come up with the most meanly mouthship. And I
Speaker 1: truly believe it's because there is no answer to these problems,
Speaker 1: as I said in the previous episode, and I think
Speaker 1: that's why I can't find any companies that have integrated
Speaker 1: generative AI in a way that's truly improved their bottom
Speaker 1: line other than Klana, which allows you to do zero
Speaker 1: percent interest free loans on almost anything. It's a very
Speaker 1: worrying company anyway. They claimed that their AI powered support
Speaker 1: bot was estimated to drive a forty million dollar amount
Speaker 1: in profit improvement in twenty twenty four, which does not,
Speaker 1: by the way, despite it being troubleted by members of
Speaker 1: the media, otherwise mean that they made forty million dollars
Speaker 1: in profit. I actually can't find what profit improvement refers to.
Speaker 1: And this is the classic AI boom story. By the way,
Speaker 1: there's always this weird verbal judo going on where they're like, yeah, sir,
Speaker 1: forty million dollars in profit improvement, upwards, downwards and side
Speaker 1: to sidemark, it's really good, And I think it's just
Speaker 1: headline grabbing. I think it's just buzz. And despite fears
Speaker 1: to the contrary, AI doesn't appear to be replacing a
Speaker 1: large amount of workers, and when it has, the results
Speaker 1: have been pretty terrible, like when Microsoft replaced MSN dot
Speaker 1: COM's editorial team with a series of AI bots that
Speaker 1: have spread misinformation and conspiracy theories, things like Joe Biden
Speaker 1: falling asleep. It's so weird. Interestingly, There was also a
Speaker 1: study in Boston Consultancy Group, and just as a note,
Speaker 1: if anyone would love the opportunity to just replace workers
Speaker 1: with robots, it's BCG, mckenzi, Accentia. All these companies were
Speaker 1: absolutely they would be giving, however much open ai wanted
Speaker 1: to do that, and then they would charge fifty million
Speaker 1: dollars for in integration that didn't work, which I guess
Speaker 1: makes AI perfect them putting that aside. In a study
Speaker 1: from BCG, they found the consultants that solved business problems
Speaker 1: with open AI's GPT four model performed twenty three percent
Speaker 1: worse than those who didn't use it, even when the
Speaker 1: consultant was warned about the limitations of generative AI and
Speaker 1: the risk of hallucinations. Yeah, really great stuff. To be clear,
Speaker 1: I am not advocating for the replacement of workers with AI. However,
Speaker 1: I'm saying that if it was actually capable of replacing
Speaker 1: human outputs, even if it was even anywhere near doing so,
Speaker 1: any number of these massive, horrifying firms would be doing
Speaker 1: so at scale, and planning to do so more as
Speaker 1: the models improve. They'd be fuddling cash right up. Open
Speaker 1: ayes ass it would be incredible, but the reality of
Speaker 1: the AI boom is kind of a little more boring.
Speaker 1: It recently came out that Amazon's cashless just walk out
Speaker 1: technology in some of their stores. You could walk in,
Speaker 1: scan a QR code, and then you could just grab
Speaker 1: your rouse tomato sauce and your condoms or whatever, your
Speaker 1: weird magazines. I don't know what they sell, and there
Speaker 1: I'm not giving any more money to Amazon than I
Speaker 1: need to. Anyways, everyone thought, oh, it's just AI. You
Speaker 1: could just walk in. It's the cameras would tell you
Speaker 1: through computer vision what you had bought. It would be great.
Speaker 1: Now it turns out that there's one thousand workers in
Speaker 1: India that were monitoring these cameras and approving transactions. Worse still,
Speaker 1: open AI used Kenyan workers who were paid less than
Speaker 1: two dollars an hour to train chet GPT's outputs, and
Speaker 1: they currently pay fifteen dollars an hour. I think for
Speaker 1: American contractors, no benefits of course, you know, fuck workers, right,
Speaker 1: that's the thing underneath this whole thing. It's just this
Speaker 1: undercurrent of disrespect for human beings, and it pisses me off.
Speaker 1: And I realized I'm pissed off about a lot of things.
Speaker 1: You'd be listening for like an hour now half an
Speaker 1: hour in this episode. Anyway, I'll keep going. But yeah,
Speaker 1: like I said, if AI was changing things, if AI
Speaker 1: was actually capable of replacing a person, it would have happened.
Speaker 1: It would be happening right now, It'd be happening at scale.
Speaker 1: It would be so much worse than things feel now, unless,
Speaker 1: of course, it just wasn't possible. What if what we're
Speaker 1: seeing today is not a glimpse of the future, but
Speaker 1: actually the new terms of the present. What if generator
Speaker 1: of AI isn't actually capable of doing much more than
Speaker 1: what we're seeing today. What if there's not really a
Speaker 1: clear timeline when it will actually be able to do more.
Speaker 1: What if this entire hype cycle has been built, goosed,
Speaker 1: and propped up by this compliant media, ready and willing
Speaker 1: to take whatever these career embellishing bullshitters have to say.
Speaker 1: What if this is just another metaverse, but with a
Speaker 1: little bit more product. Every single time I've read about
Speaker 1: the amazing things that artificial intelligence can do, I just
Speaker 1: see somebody attempting to add fuel to a fire that's
Speaker 1: close to going out. When the Wall Street Journals Joanna
Speaker 1: Stern wrote about Sora open ayes yet to be released
Speaker 1: video generating chatbot. She talked about how its photorealistic clips
Speaker 1: were good enough to freak her out. And I get
Speaker 1: it at first glance. These do look like people, these
Speaker 1: images do. They look like something approaching a video. They
Speaker 1: look almost real, kind of like text some chat GBT
Speaker 1: is almost right or it's right fully, but it doesn't
Speaker 1: feel right. But much like the rest of these outputs,
Speaker 1: you look a little closer, and they have these weird
Speaker 1: errors like cars disappearing in and out of the shot,
Speaker 1: or a different car coming out from behind something, or
Speaker 1: completely different images between frames. Are these strange, unrealistic moments
Speaker 1: of lighting, and they're never much longer than thirty seconds. Stern,
Speaker 1: who by the way, I deeply respect, isn't really afraid
Speaker 1: of what Sura can do. But what would happen if
Speaker 1: open ai was able to fix the hallucination problems that
Speaker 1: makes these videos kind of unwatchable. Well, it's easy to
Speaker 1: imagine tools like Saura could eventually play a role in
Speaker 1: online disinformation campaigns, churning out like lifelike videos of politicians
Speaker 1: saying or doing appalling things. We can all breathe a
Speaker 1: sigh of relief in knowing that the videos themselves are
Speaker 1: often so flawed. You can pretty much instantly see their
Speaker 1: AI generated Also, SRA is not available to the public yet,
Speaker 1: and I don't even know if it ever will be.
Speaker 1: You just need to look at the hands or the backgrounds.
Speaker 1: Look at the people in the background of any AI
Speaker 1: generated photo or video. They often contain too many fingers
Speaker 1: so you can't see their faces. Or in Sora's videos,
Speaker 1: their legs don't look right. It's so weird and I
Speaker 1: don't I don't know how to put it perfectly, but
Speaker 1: they don't feel human. Just to be clear, though Sora
Speaker 1: is dead on arrival, no one actually has access to it.
Speaker 1: It's unclear when it will come out. Every journalist that
Speaker 1: has quote unquote use Sura has just given a prompt
Speaker 1: to open ai to run. But there's also a very
Speaker 1: obvious problem that kind of relates to something I mentioned
Speaker 1: in the previous episode. Open AI and every generative AI company,
Speaker 1: they're all dependent on high quality data to train the models,
Speaker 1: and video data is so much larger, more complex, and
Speaker 1: harder to find. There's less of it because it's visual media,
Speaker 1: and it's just a much bigger, more complex model and
Speaker 1: a much harder computational task to create video moving image
Speaker 1: is it's actually kind of putting aside my anger about
Speaker 1: Generative AI. It's amazing they've done even this, but to
Speaker 1: be clear, as amazing as it might look, it isn't
Speaker 1: enough to do anything. It's just a kind of a
Speaker 1: do hickey. And this data is so much more complex
Speaker 1: than the text based data that open ai is running
Speaker 1: out of to make CHATGBT spit out words. Even if
Speaker 1: there were enough data, there's pretty good reason why open
Speaker 1: ai is coy about when they'll release the model. Like
Speaker 1: I said, it's expensive and complex to run, and at
Speaker 1: no point has anyone on how the fuck this actually
Speaker 1: makes them any money, how they sell this. It's so weird,
Speaker 1: to be clear, when you use surra it turns text
Speaker 1: prompts into a video. You can't edit the video, you
Speaker 1: can't change the video. The video is what the video
Speaker 1: looks like. There's no way to make Sora make the
Speaker 1: same thing multiple times, which makes the very basics of
Speaker 1: making film, which is multiple angles of the same thing,
Speaker 1: completely goddamn impossible. In fact, consistency between the same two
Speaker 1: prompts is impossible from these models because they're all probabilistic.
Speaker 1: We've recently seen some of the first quote unquote movies
Speaker 1: made with sourra and the first one was called Airhead,
Speaker 1: which is about a minute long. It's this man with
Speaker 1: a balloon head walking around and it's got this it's
Speaker 1: very twee. It sucks. It's just putting aside the aipart.
Speaker 1: It's just crappy, and it's got a guy being like, yeah,
Speaker 1: having a balloon head is difficult. Yeah, it's weird. I
Speaker 1: hate having a balloon head. I hope I don't get popped.
Speaker 1: It sucks. It's really bad filmmaking. But also each shot,
Speaker 1: and there's multiple mbile shots of this guy with a
Speaker 1: yellow balloon head looks completely different. It's a different balloon
Speaker 1: every goddamn time. And it's so funny because you have
Speaker 1: these guys on twittering like, oh my god, oh my god,
Speaker 1: I am crying and pissing myself. This is the best
Speaker 1: thing I've ever seen. But it isn't. It's so close
Speaker 1: yet so far away, And the only reason it's impressive
Speaker 1: is people are willing to sit there and say, but
Speaker 1: what if it wasn't shit? But it is it really
Speaker 1: is like every other generative output. It's superficially impressive, kind
Speaker 1: of sort of lifelike, but once you look at it
Speaker 1: for more than a moment, it's just flawed, terribly, irrevocably flawed.
Speaker 1: It's time to wake up. We are not in the
Speaker 1: early days of AI. We're decades in and we're approaching
Speaker 1: the top of the s curve of innovation. There are
Speaker 1: products being built, don't worry, but it's all things like
Speaker 1: Claude Author, which creator Matt Schumer calls a chain of
Speaker 1: AI systems that will write an entire book for you
Speaker 1: in minutes, and I call a new kind of asshole
Speaker 1: that can shit more than you'd ever believe. Generative AI
Speaker 1: is the ugliest creation of the rot economy, and its
Speaker 1: main selling point is that can generate a great deal
Speaker 1: of passable material. Images generated from generative AI models like
Speaker 1: open Ayes Dali all have the same kind of eerie
Speaker 1: feel to them, as they're mostly trained on the same data,
Speaker 1: some of it licensed from shutstock, some of it outright
Speaker 1: plagiarized from hundreds of artists. Without sounding too wanky and philosophical,
Speaker 1: everything created by generative AI feels soulless, and that's because
Speaker 1: it is no matter how detailed the problem, no matter
Speaker 1: how well trained the model, no matter how well intentioned
Speaker 1: the person writing that prompt these are still mathematical solutions
Speaker 1: to the emotional problem of creation. One cannot recreate the
Speaker 1: subtle fuck ups and delightful little neurological errors that make
Speaker 1: writing a book, or a newsletter or a podcast special.
Speaker 1: While this podcast is admittedly trying to generate what I
Speaker 1: believe AI might do in the future, it's not generative,
Speaker 1: and it's not generated as a result of me mathematically
Speaker 1: considering how likely an outcome is. My fury is not
Speaker 1: generated by an algorithm telling me that this is the
Speaker 1: right thing to be angry at. I'm pissed off because
Speaker 1: I feel like we're all being like to and treated
Speaker 1: like idiots. What makes things created by humans special isn't
Speaker 1: doing the right thing or the best thing, but the
Speaker 1: outputs that result in us fighting past are on imperfections
Speaker 1: and maladies like the strep infection I've been fighting for
Speaker 1: the last few days, and like, look, to my knowledge,
Speaker 1: you can't give a generative AI strep throat. But if
Speaker 1: I ever find out it's possible, I will make it
Speaker 1: my damn mission to give it to chat GBT. All
Speaker 1: of this hype is predicated on solving problems with artificial
Speaker 1: intelligence models that are only getting worse, and open AI's
Speaker 1: only answers to these problems are a combination of will
Speaker 1: work it out eventually, trust me, and we need a
Speaker 1: technological breakthrough in both chips and energy. That's why Sam
Speaker 1: Moultman has been trying to raise seven trillion dollars and
Speaker 1: that's not a mistake, by the way, to make a
Speaker 1: new kind of AI chip, because there's no sign that
Speaker 1: this or even future generations of chips will actually fix anything.
Speaker 1: Generative AI's core problems, it's hallucinations, its massive energy, and
Speaker 1: its massive unprofitable compute demands are not close to being solved.
Speaker 1: I've now watched a frankly alarming amount of interviews with
Speaker 1: both open AI CEO Sam Moultman and their CTO mirror Marati,
Speaker 1: and every time they're saying the same specious empty talking points,
Speaker 1: promising that in the future chap GPT will do this
Speaker 1: and that as all evidence points to their models getting
Speaker 1: worse and through the last years, by the way, they've
Speaker 1: just said the same thing in every interview. They always
Speaker 1: talk about chat GPT being like something or help creatives,
Speaker 1: they never really say how, which just kind of weird.
Speaker 1: But yeah, generative AI models they're expensive, they're compute intensive,
Speaker 1: and they don't seem to provide obvious, tangible, mass market
Speaker 1: use cases. Marathi in Oltmund's futures depend heavily on keeping
Speaker 1: the world believing that development and improvement of these models
Speaker 1: capabilities will continue at this rapacious pace of progress, even
Speaker 1: though it's unquestionably slowed, with open AI even admitting themselves
Speaker 1: that their latest model, GPT four, may actually be worse
Speaker 1: at some tasks. I study from UC Berkeley last year
Speaker 1: found that GPT four was actually worse at coding them
Speaker 1: before and that chat GPT was at times refusing to
Speaker 1: do certain tasks. Nobody wants to work anymore. Well, I
Speaker 1: feel like I'm walking down the street telling people their
Speaker 1: houses are on fire, only to be told to stop
Speaker 1: insulting their new heating system. These models aren't intelligent. They're
Speaker 1: mathematical behemoths generating the best guess on training, data and labeling,
Speaker 1: and thus they don't really know what they're being asked
Speaker 1: to do. You can't fix that. You can't fix hallucinations.
Speaker 1: You can't just make these problems go away with more compute,
Speaker 1: you can mitigate them. The current philosophy, by the way,
Speaker 1: is that you can use another model to look at
Speaker 1: another model's outputs, which, as I mentioned in the previous episodes,
Speaker 1: is very silly. But seriously, everyone telling you hallucinations are
Speaker 1: going away, look a little deeper and look at when
Speaker 1: they actually failed to tell you how they were. It's
Speaker 1: just very silly. Look. Every bit of excitement for this
Speaker 1: technology right now is based on this idea of what
Speaker 1: it might do, as I've said, and that quickly gets
Speaker 1: conflated with what it could do, which allows Sam Mortman,
Speaker 1: who by the way, is far more of a marketing
Speaker 1: person than an engineer. His one startup, Looped was a failure.
Speaker 1: He's failed upwards. He was in Why Combinat he did this.
Speaker 1: It's actually ridiculous. He's so famous. All of this bullshit
Speaker 1: it allows him to sell the dream of open AI,
Speaker 1: and he's selling it based on the least specific promises
Speaker 1: I've seen since Mark Zuckerberg said we'd live in our
Speaker 1: bloody oculus headsets. And it's frustrating because this money and
Speaker 1: this attention could go to important things. We have real
Speaker 1: problems in society. I believe that Sam Moortman and pretty
Speaker 1: much anyone in a position of power and influence in
Speaker 1: the AI space has been tap dancing this entire time,
Speaker 1: hoping that he could amass enough power and revenue that
Speaker 1: his success would be inevitable. Yet I think his hype
Speaker 1: campaign has been a little bit too successful, and it's
Speaker 1: deeply specious, and he, along with the rest of the
Speaker 1: AI industry, has found himself suddenly having to deliver a
Speaker 1: future these not even close to developing. I am always
Speaker 1: scared of automation taking our jobs. I think it's always
Speaker 1: worth being scared of. But I don't think that's the
Speaker 1: thing the tech industry is working on right now. I
Speaker 1: don't think they're close, and I think there's something more
Speaker 1: imminent to fear, and that thing is the bottom falling
Speaker 1: out of generative AI as companies realize that the best
Speaker 1: they're going to see is maybe a few digits of
Speaker 1: profit growth. Companies like Nvidia, Google, Amazon, Snowflake, and Microsoft,
Speaker 1: they have hundreds of billions of dollars of market capitalization
Speaker 1: as well as expected revenue new growth tied into the
Speaker 1: idea that everyone's going to integrate AI into everything, and
Speaker 1: that they'll be doing more than they are today. You
Speaker 1: can already see the desperation coming from these companies, like Microsoft,
Speaker 1: for example, which in March effectively absorbed a company called
Speaker 1: Inflection AI into itself, kind of an acquisition by Stealth.
Speaker 1: Inflection AI is a public benefit company that portrays itself
Speaker 1: as a nicer, gentler version of open AI. It's called product,
Speaker 1: a chat GPT style chatbot touts its empathetic tone, its humor,
Speaker 1: and its emotional awareness. Inflection was created in twenty twenty
Speaker 1: two with an all star founding team that included Reid Hoffmann,
Speaker 1: the founder of LinkedIn, and most of Fars Suleiman, the
Speaker 1: British born co founder of deep Mind, which Google acquired
Speaker 1: in twenty fourteen. In mid twenty twenty three, Microsoft took
Speaker 1: part in a one point three billion dollar funding round
Speaker 1: which saw the company acquire a significant stake in Inflection,
Speaker 1: alongside other AI players like Nvidia. Inflection's core product has
Speaker 1: the same inherent underlying issues as every other generative AI product, Hallucinations,
Speaker 1: for example, but it has an accomplished team that has
Speaker 1: taken a different approach to its competitors. Whereas chat GPT
Speaker 1: and clored two tend to be, or at least aspire
Speaker 1: to be, functional tools that provide information or complete tasks.
Speaker 1: Inflections sought to make its product feel a bit more organic.
Speaker 1: For Microsoft, the appeal was obvious. It has so much
Speaker 1: riding on its AI ambitions, but in terms of money
Speaker 1: spent as well as its share price, that it can't
Speaker 1: really afford to appear stagnant or worse as though it
Speaker 1: made a bad bet. Acquiring Inflection would help it maintain
Speaker 1: its image, especially with idiot Wall Street analysts. But here's
Speaker 1: the problem. Microsoft already holds a massive stake in Open AI,
Speaker 1: and regulators both in America and Europe are wary of
Speaker 1: market consolidation. Acquiring Inflection it'd give them a little too
Speaker 1: much scrutiny. So Microsoft took a third, nastier path. Instead
Speaker 1: of buying the company, it bought the employees, with Suliman
Speaker 1: and the majority of his coworkers jumping ship to found
Speaker 1: Microsoft's new AI division. It secured the talent a subsequent
Speaker 1: six hundred and fifty million dollar licensing deal, yet another
Speaker 1: example of Microsoft basically paying itself, and then gave that
Speaker 1: deal to the shell of Inflection. You know, the one
Speaker 1: without any of the staff left, giving it access to
Speaker 1: the company's tech its IP and there's nothing regulators could
Speaker 1: do to stop him. To be clear, Microsoft is in
Speaker 1: a position where it could easily absorb the shock wave
Speaker 1: of a potential AI bubble burst. It still prints money
Speaker 1: from its other business units like office and cloud computing,
Speaker 1: Microsoft Windows, and the Xbox gaming system, and the same
Speaker 1: is true for the other big names like Google and Nvidia.
Speaker 1: They're well insulated for any slowdown in AI investment or
Speaker 1: from a growing apathy towards AI enterprise customers. I will note, however,
Speaker 1: these massive investments in data centers, if they're all for nought,
Speaker 1: you will see a form of crash. I can't say
Speaker 1: the same for startups, though other companies aren't going to
Speaker 1: be so lucky. Stability AAI, the developer of stable diffusion,
Speaker 1: a generative AI that can produce images from written prompts
Speaker 1: innovative for the time, is perhaps the canary in the
Speaker 1: coal mine of PKI. Stability AI rode the same waves
Speaker 1: as Open AI, especially in twenty twenty three, but now
Speaker 1: that money is tighter and skepticism is higher, it's struggling
Speaker 1: to stay aflow. Although the company raised one hundred million dollars.
Speaker 1: In early twenty twenty three, it burned through nearly eight
Speaker 1: million dollars a month, and in a recent attempt to
Speaker 1: raise further cash they fail. The company routinely missed payroll and,
Speaker 1: according to Forbes, a master sizeable debt with the US
Speaker 1: tax authorities that culminated in threats to seize the company's assets.
Speaker 1: They owed debts to Amazon, Google and core Weave, and
Speaker 1: each compute provider that specializes in AI applications. With negligible
Speaker 1: revenues and rapid cash burn combined with no obvious way
Speaker 1: to monetize the product, stability Ai is now in turmoil,
Speaker 1: with its key talent leaving the company in March, followed
Speaker 1: by the company's CEO and co founder, Amount Mustak. Its
Speaker 1: ongoing existence is in question, with The Financial Times writing
Speaker 1: in March that the company's future, despite once being seen
Speaker 1: as among the world's most promising startups, is in doubt.
Speaker 1: While it would be fair to say that stability Aii
Speaker 1: was unique at its internal turmoil, its external pressures, the
Speaker 1: ability you or lack thereof, to monetize an expensive product,
Speaker 1: and its reliance on external funding to survive much more
Speaker 1: common across the industry. Its survival depended on investors believing
Speaker 1: in a lofty future for AI, where it's integrated into
Speaker 1: every facet of our lives and it plays a role
Speaker 1: in almost every industry, which, of course we now know
Speaker 1: it doesn't. While that belief hasn't been shattered, or at
Speaker 1: least not yet, it's fair to say that expectations and
Speaker 1: aspirations are increasingly tempered after reaching the apex of the
Speaker 1: AI pissfest. The tech industry is getting a hangover, and
Speaker 1: companies like Stability can't survive the headache. But to be clear,
Speaker 1: I am not excited for the AI bubble to pop,
Speaker 1: and on some level, as weird as it sounds, I
Speaker 1: kind of hope it doesn't. Once it bursts, the AI
Speaker 1: bubble will hit far more than the venture capitalists that
Speaker 1: propped it up. This hype cycle has driven the global
Speaker 1: stock markets to their best first quarter in five years,
Speaker 1: and once the markets fully turn on the companies that
Speaker 1: falsely promised an AI revolution, it's going to lead to
Speaker 1: a massive market downturn and another merciless round of layoffs
Speaker 1: throughout the tech sector, led by Microsoft, Google and Amazon.
Speaker 1: This will in turn suppressed tech labor and flood the
Speaker 1: market with techtile. It's going to suck for everyone involved
Speaker 1: in software. A market crash led by the tech industry
Speaker 1: will only hurt innovation, further draining the already low amounts
Speaker 1: going into the hands of venture capitalists that control the
Speaker 1: dollars going into new startups, and once again, the entire
Speaker 1: industry will suffer because people don't want to build new
Speaker 1: things or try new ideas. No, they want to fund
Speaker 1: the same people doing the same things or similar things
Speaker 1: again and again because it feels good to be part
Speaker 1: of a consensus. Even if you're wrong. Silicon Valley will
Speaker 1: continually fail to innovate at scale until it learns to
Speaker 1: build real things again, things that people actually use, and
Speaker 1: things to actually do something. I don't know if I
Speaker 1: want to be right or wrong here. If I'm wrong,
Speaker 1: generative AI could replace millions of people's jobs, something that
Speaker 1: far too many people in the media are excited about,
Speaker 1: despite the fact that the media is the first industry
Speaker 1: that open AI kind of wants to automate. If I'm right,
Speaker 1: we're going to face a dot com bubble s town
Speaker 1: turn in tech, one that's far worse than what we
Speaker 1: saw in the last few years. In any case, I
Speaker 1: do wish the tech industry would get their heads out
Speaker 1: of their asses. I'm tired. I'm tired of watching tech
Speaker 1: firms life their teeth about the future that will live
Speaker 1: in the metaverse, that our future will be decentralized and
Speaker 1: paid for in cryptocurrency, and that our world will be
Speaker 1: automated with chatbots. I truly think that these companies think
Speaker 1: regular people are stupid, which is why Microsoft put out
Speaker 1: a minute long Super Bowl commercial for their Copilot AI
Speaker 1: that featured several prompts like write the code for my
Speaker 1: three D open world game that don't actually do anything
Speaker 1: that prompt I just mentioned. Go type it into Copilot.
Speaker 1: It will give you a guide to coding a game
Speaker 1: no code created. Also in the commercial, he types in
Speaker 1: classic truck shop called Pauls. But none of these image
Speaker 1: generators can actually do words, so it just looks like
Speaker 1: go and do it. Trust me. It's funny. But every
Speaker 1: time that these big tech booms happen, every time they say, oh,
Speaker 1: we're going to live in the metaverse and oh we're
Speaker 1: going to be able to automate everything, every time they lie,
Speaker 1: the world turns against the tech industry, and this particular
Speaker 1: boom is so craven in its falsehoods that I think
Speaker 1: it'll have a dramatic chilling effect on tech valuations if
Speaker 1: the bubble pops quite as severely as I expect. And
Speaker 1: Sam Mortman desperately needs you to believe the bubble won't pop.
Speaker 1: He needs you to believe that generative AI will be essential, inevitable,
Speaker 1: and intractable, because if you don't, you'll suddenly realize that
Speaker 1: trillions of dollars in market capitalization and revenue are being
Speaker 1: blown on something it's kind of mediocre. If you focus
Speaker 1: on the present, what open AI's technology can do today
Speaker 1: and will likely do for some time, you see in
Speaker 1: terrifying clarity that generative AI isn't really a society altering technology.
Speaker 1: It's just another form of efficiency driving cloud compute software
Speaker 1: that benefits kind of a small amount of people. If
Speaker 1: you stop saying things like AI could do or AI
Speaker 1: will do, you have to start asking what AI can do,
Speaker 1: and the answer is not that much and probably not
Speaker 1: that much more. In the future. Surra is not going
Speaker 1: to generate entire movies. It's going to continue making horrifying
Speaker 1: human adjacent creatures that walk like the atats from star
Speaker 1: Wars and cartoons that look remarkably like SpongeBob SquarePants Chat
Speaker 1: GPT isn't going to run your business because it can
Speaker 1: barely output a spreadsheet without fucking up the basic numbers,
Speaker 1: if it even understands what you're asking it to do
Speaker 1: in the first place. I think that AI has maybe
Speaker 1: three quarters to prove itself worthwhile before the apocalypse really arrives.
Speaker 1: When it does, you're going to see it first in
Speaker 1: the real infrastructure companies, starting with Nvideo, who's grown to
Speaker 1: about two trillion dollars in market capitalization because of the
Speaker 1: chips they make, which are pretty much the only ones
Speaker 1: that can power the AI revolution. There are other companies
Speaker 1: that AMD in Micron, but m Video is the one
Speaker 1: that's really grown. If you watch any of their notes,
Speaker 1: they're insane. They're just full of fan fiction. Once Nvidia
Speaker 1: starts to see growth slow, and Oracle in particular Oracle
Speaker 1: massive data center company, massive data based company as well
Speaker 1: one of the largest customers Microsoft building data sentence for them.
Speaker 1: Once that starts slowing down, that's when you should start worrying.
Speaker 1: But the real pain's going to come for Amazon, Microsoft
Speaker 1: and Google when it's clear that there's not really that
Speaker 1: much revenue going into their clouds. Once that happens, once
Speaker 1: you start seeing Jim Kramer on CNBC saying I don't
Speaker 1: think the AI boom is here, despite having saying it
Speaker 1: just was, that's when things get nasty and the knock
Speaker 1: on effects will be horrible. It's going to be genuinely painful,
Speaker 1: worse than we've seen the last few years. And it's
Speaker 1: all a result of the same problem. It's all a
Speaker 1: result of the growth of all cost tech economy. When
Speaker 1: things are made to expand, when things are made to
Speaker 1: build more rather than build better, When you're building solutions
Speaker 1: to use compute power to sell cloud computing services rather
Speaker 1: than helping real people make their lives better. Tech is
Speaker 1: not building for real people anymore. And the AI revolution,
Speaker 1: despite its spacious hype, is not really for us. It's
Speaker 1: not for you and me. It's for people at Satching
Speaker 1: the Della of Microsoft to claim that they've increased growth
Speaker 1: by twenty percent. It's for people at sam Altman to
Speaker 1: buy another fucking Porsche. It's so that these people can
Speaker 1: feel important and be rich, rather than improving society at all.
Speaker 1: Maybe I'm wrong, Maybe all of this is the future,
Speaker 1: maybe everything will be automated, but I don't see the signs.
Speaker 1: This doesn't feel much different to the metaverse. There's a product,
Speaker 1: but in the end, what's it really do? Just like
Speaker 1: the metaverse, I don't think many people are really using it.
Speaker 1: All signs point to this being an empty bubble. And
Speaker 1: I'm sure you're sick of this too. I'm sure that
Speaker 1: you're sick of the tech industry telling you the futures
Speaker 1: here when it's the present and it fucking sucks. And
Speaker 1: I'm swearing a lot, and I'm angry, but I'm justified
Speaker 1: in this anger off feel and I'm not telling you
Speaker 1: how to think. And I've heard from some of you saying, oh,
Speaker 1: don't tell me how to think, and I agree. I agree.
Speaker 1: I'm not here to tell you to be angry about anything.
Speaker 1: But I want to give you at least my truth,
Speaker 1: and I want to give you what I see is happening,
Speaker 1: because I don't feel like enough people are doing that
Speaker 1: in the tech industry. And that's what better Offline is
Speaker 1: going to continue to be. I really appreciate you listening.
Speaker 1: It's been about a month month and a half since
Speaker 1: we started. It's only going to get better from here.
Speaker 1: Thank you, thank you for listening to Better Offline. The
Speaker 1: editor and composer of the Better Offline theme song, It
Speaker 1: is Mattersowski. You can check out more of his music
Speaker 1: and audio projects at Mattasowski dot com, M A T
Speaker 1: T O. S O w Ski dot com. You can
Speaker 1: email me at easy at Better Offline dot com, or
Speaker 1: check out Better Offline to find my newsletter and more
Speaker 1: links to this podcast. Thank you so much for listening.
Speaker 1: Better Offline is a production of cool Zone Media. For
Speaker 1: more from cool Zone Media, visit our website cool Zonemedia
Speaker 1: dot com, or check us out on the iHeartRadio app,
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