Speaker 1: Wuz Media. Hello, I'm ed Zitron, and this is Better Offline.
Speaker 1: We finally reached the end of our three part how
Speaker 1: to Argue with an AI Booster series. Big strong men
Speaker 1: are standing outside of the Better Offline studio, suspended two
Speaker 1: hundred feet above the Las Vegas Strip, with tears in
Speaker 1: their eyes, and they're saying, sir, sir, it's the most
Speaker 1: beautiful podcast I've ever heard. Please stop recording it. Everyone
Speaker 1: else will feel insufficient when they hear it. No, No,
Speaker 1: I have to continue. I'm afraid my listeners need me.
Speaker 1: But okay, seriously, folks, if there's anything I want you
Speaker 1: to take home so far, is that the arguments that
Speaker 1: these people, these AI sicker fans make, they crumble under
Speaker 1: the slightest bit of scrutiny. And yet these arguments work
Speaker 1: because they either exploit the lack of knowledge of those
Speaker 1: of us who do and understand the rotten economics of AI,
Speaker 1: or because they forced the opposite party to surrender their
Speaker 1: reason and to exit the planes of reality, to which
Speaker 1: I say, fuck that, absolutely not. This is a hell
Speaker 1: I'm prepared to die on, and I'll hope that you'll
Speaker 1: all be standing with me, side by side Now, in
Speaker 1: the first episode, we shook away the claims that it's
Speaker 1: the early days for AI and we just need to
Speaker 1: give it more time. Then I took the idea that
Speaker 1: generative AI is like Uber or fiber optic networking to
Speaker 1: industries that both burned a lot of money at the
Speaker 1: start but are otherwise nothing like generative AI. And now
Speaker 1: it's time to deal with the dregs of the arguments.
Speaker 1: These are the worst of the worst. Boost to quips.
Speaker 1: Here we go, ultra booster quip. I thought about recording
Speaker 1: that with a bunch of reever, but it didn't really
Speaker 1: work out for me, but I wanted to do it once.
Speaker 1: But anyway, their argument is hum AI is just like
Speaker 1: Amazon Web Services, a massive investment that took a while
Speaker 1: to go profitable, and everybody hated Amazon for it. Now
Speaker 1: I actually covered this in depth and the Hater's Guide
Speaker 1: to the AI Bubble, But the long and short of
Speaker 1: it is that Amazon Web Services is a platform and
Speaker 1: necessity with an obvious choice and has burned about ten
Speaker 1: percent of what Amazon and all of them have burned
Speaker 1: chasing generative AI, and had also proven demand before building it. Also,
Speaker 1: Amazon web Services was break even within three years. An
Speaker 1: open aye was founded in fucking twenty fifteen, and even
Speaker 1: if you start from November twenty twenty two, by Amazon
Speaker 1: web Services, standards should be break even by now. But
Speaker 1: now i'll quote myself, Amazon, weent no way. Sorry, that's
Speaker 1: the boosters. Amazon web Services was created out of necessity.
Speaker 1: Amazon's infrastructure needs were so great that he had effectively
Speaker 1: had to build both the software and hardware necessary to
Speaker 1: deliver a store that sold theoretically everything, the theoretically everywhere,
Speaker 1: handling both the traffic from customers, delivering the software that
Speaker 1: runs Amazon dot Com quickly and reliably, and well making
Speaker 1: sure things were stable. It didn't need to come up
Speaker 1: with a reason for people to run web applications. They
Speaker 1: were already doing so themselves, but in ways that cost
Speaker 1: a lot more, were inflexible and required specialist server skills.
Speaker 1: Amazon web Services took something that people already did and
Speaker 1: what there was already a proven demand for, and made
Speaker 1: it better and scaled it. Eventually Google and Microsoft would
Speaker 1: join the frame. I editorialized a bit there, but I
Speaker 1: can do that with my own work now. A common
Speaker 1: booster quip, by the way, is for them to say, well,
Speaker 1: this AI company they've got high annualized revenues. And as
Speaker 1: I've discussed in the past, this metric is basically month
Speaker 1: times twelve. And while it's a fine measure for normal
Speaker 1: high gross margin businesses like software as a service companies,
Speaker 1: it isn't for AI. It doesn't account for churn, which
Speaker 1: is when people leave. It also is a number intentionally
Speaker 1: used to make a company sound more successful. So you
Speaker 1: can say two hundred million dollars annualized revenue instead of
Speaker 1: sixteen point six million dollars a month. And you're also
Speaker 1: meant to budship. You heard they said two hundred million annualized,
Speaker 1: but you heard two hundred million. Your mind did that
Speaker 1: was a bad planket reference. But I'll continue. They want
Speaker 1: you to think two hundred million. They want you to
Speaker 1: think that's what they'll make. More often than not, if
Speaker 1: they mentioned an annualized number, that number will not be
Speaker 1: how much they make that year. Also, if they're using
Speaker 1: this number, it's likely not consistent. Now, if they bring
Speaker 1: this up, you should just say to them, hey, how
Speaker 1: much profit is the company making and also how much
Speaker 1: are they burning? At this point they will I think
Speaker 1: mace you I mean with the spray or an actual
Speaker 1: maze AI boosters are strange. Now they'll also say, well AI,
Speaker 1: this AI companies in growth mode, and they'll pull the
Speaker 1: profit lever when it's time. And the answer to that
Speaker 1: is always going to be why have none of them
Speaker 1: done this? Not one, not one of them. Now a
Speaker 1: booster will burst through your don't go AI AGI AGI will,
Speaker 1: and then there's that will bullshit again. It's always about
Speaker 1: the will with these fuckers. We do not know how
Speaker 1: thinking works in humans and thus cannot extrapolate it to
Speaker 1: a machine. And at the very least human beings have
Speaker 1: the ability to reevaluate things and learn a thing that
Speaker 1: LMS cannot do and will never do. We do not
Speaker 1: know how to get to AGI. Sam Almonds said in
Speaker 1: June the Open AI was now confident they knew how
Speaker 1: to build AGI as they have traditionally understood it. Then
Speaker 1: in all August, Altman said that AGI was not a
Speaker 1: super useful term and that the point of all this
Speaker 1: is it doesn't really matter, and it's just this continuing
Speaker 1: exponential of model capability that will rely on for more
Speaker 1: and more things. I'm really tired of people quoting this guy.
Speaker 1: He doesn't make any fucking sense read out read anything
Speaker 1: he says out loud, and it's just really just total bullshit.
Speaker 1: Even Meta's chief AI scientist Ian Lacun says it isn't
Speaker 1: possible with transformer based models to make AGI. We don't
Speaker 1: know if Agi is possible, and anyone claiming they do
Speaker 1: is lang. Anyone who's talking about Agi is talking about
Speaker 1: fan fiction. Again, Ask them how they feel about Banjo
Speaker 1: and kazoo Do you think they made love? Actually, that's
Speaker 1: a if. Next time someone brings up Agi to you,
Speaker 1: seriously bring up Banjo and Kazuoi and their romantic involvement.
Speaker 1: I actually that I think that that's the only response
Speaker 1: you should give. Now, stop humoring them. It is fan fiction.
Speaker 1: But putting Banjo and Kazuoi aside, there's also a really
Speaker 1: stupid booster thing they do, which is I'm hearing from
Speaker 1: people deep within the AI industry that there's some sort
Speaker 1: of ultra pammerful models they're not talking about. And this,
Speaker 1: by the way, is hogwash. Nothing different than your buddy's
Speaker 1: friend's uncle who works at the Nintendo that says Mario
Speaker 1: is coming to the PlayStation. Ilios suits Caver and Mirror.
Speaker 1: Murti raised billions of dollars for companies with no product,
Speaker 1: let alone a product roadmap. And they did so because
Speaker 1: they saw an opportunity for a grift and to throw
Speaker 1: a bunch of money at compute for no reason. Anyone
Speaker 1: who has secret shit is not talking about it because
Speaker 1: it doesn't exist. Also, if someone from deep within the
Speaker 1: industry has told somebody big things are coming, they're doing
Speaker 1: so to con them or make them think that they
Speaker 1: have privileged information. Ask for specifics, and if they say
Speaker 1: I couldn't possibly tell you, then they're full of shit.
Speaker 1: They're full of crap. They are full of doodo. And
Speaker 1: if they get vague, get specific, Oh, it's going to
Speaker 1: be able to automate other things? What things? How how's
Speaker 1: it automate them? Oh? I don't know. Then you don't
Speaker 1: know shit about fuck? Now talking about not knowing about
Speaker 1: Fuck's another booster. Quip chat GPT is so popular seven
Speaker 1: hundred million people use it weekly. It's one of the
Speaker 1: most popular websites on the Internet. Its popularity proves its utility.
Speaker 1: Look at all the paying customers now that paying customer's
Speaker 1: part will get to in a second. But this argument
Speaker 1: is poised as a comeback to my suggestion that AI
Speaker 1: is not particularly useful, a proof point that this movement
Speaker 1: is not inherently wasteful, that there are in fact use
Speaker 1: cases for chat GPT that are lasting, meaningful, or important,
Speaker 1: I fundamentally disagree. In fact, I believe chat GPT and
Speaker 1: lllm's in general have been marketed based on lies of inference,
Speaker 1: which I realize is ironic. I know it's pretty clever.
Speaker 1: I had a whole blog written called the Lie of
Speaker 1: Inference that kind of became this. It wasn't very good,
Speaker 1: though this is. This is good. Don't say it's bad.
Speaker 1: I also have grander concerns and suspicions about what open
Speaker 1: ai considers a user and how it counts revenue. Let
Speaker 1: me give you an example. They claim to have five
Speaker 1: million business customers, yet five hundred thousand of those are
Speaker 1: from a fifteen million dollar year deal, year long deally
Speaker 1: with cal State University, which works out to around two
Speaker 1: dollars and fifty cents a user a month. Open ai
Speaker 1: has also started doing one dollar a month trials of
Speaker 1: its thirty dollars a month team subscription, and one has
Speaker 1: to wonder how many of those subscribers are counted in
Speaker 1: the total and indeed for how long. I do not
Speaker 1: know the scale of these offers nor how long open
Speaker 1: ai has been offering them. I readditor posted about this
Speaker 1: one dollar for a month deal a few months ago,
Speaker 1: saying that open ai was offering five seats at once,
Speaker 1: so one buck a month for a month per se.
Speaker 1: How many people cancel after that? Who knows? Maybe they
Speaker 1: just hope they don't. In fact, I found a few
Speaker 1: people talking about these deals, and even one adding that
Speaker 1: they were offered an annual ten dollar a month Chat
Speaker 1: GPT plus subscription. That's like, not like ten dollars a
Speaker 1: month for just one month, that's for twelve months, with
Speaker 1: one person saying a few weeks ago that they'd seen
Speaker 1: people offered that same deal for canceling their subscription. And
Speaker 1: actually I got the same thing when I tried to cancel. Yes,
Speaker 1: I pay for Chat GPT. I need to actually use
Speaker 1: the fucking thing to criticize it. When I tried to
Speaker 1: cancel this like, hey, do you want three months with
Speaker 1: ten bucks space? And I was like sure, just to
Speaker 1: prove my point suspicious, But there is a greater problem
Speaker 1: at play, by the way, and it goes beyond pricing.
Speaker 1: And it's the chat GPT in Open Ai has been
Speaker 1: marketed based on lies. So chat gpt is seven hundred
Speaker 1: million weekly active users. Open Ai is yet to provide
Speaker 1: a definition. Yes, I've asked them, which means that an
Speaker 1: active user could be defined as somebody who has gone
Speaker 1: to chat gpt once in the space of a week.
Speaker 1: This term is extremely flimsy and doesn't really tell us much. Yes,
Speaker 1: it's a lot of people, but how active are they?
Speaker 1: Similar web says that in July twenty twenty five, chatgpt
Speaker 1: dot com had one point two to eighty seven billion
Speaker 1: total visits, making it very popular. What do these facts
Speaker 1: actually mean? Though? As I said previously, chat GPTs had
Speaker 1: probably the most sustained PR campaign for anything outside of
Speaker 1: a presidency or a pop star. Every single article about
Speaker 1: Ai mentions open Ai or chat gpt. Every single feature launch,
Speaker 1: no matter how small, gets a slew of coverage. Every
Speaker 1: single time you hear AI, you made to think of
Speaker 1: chat gpt by a tech media that's never stopped to
Speaker 1: think about their role in the hype or their responsibility
Speaker 1: to their readers. And as the hype has grown, the
Speaker 1: publicity compounds because the natural thing for a journalist to
Speaker 1: do when everybody is talking about something is to talk
Speaker 1: about it more chat. GPT's immediate popularity may have been viral,
Speaker 1: but the media took the ball and ran with it,
Speaker 1: and then proceeded to tell people it did stuff it
Speaker 1: did not. People were pressured to try this service then
Speaker 1: under false pretenses, something that continues to happen to this day.
Speaker 1: And I'm going to give you a really fucking grizzy
Speaker 1: example when I discovered this, When I went and looked
Speaker 1: at this, it filled me full of rage. It's disgraceful
Speaker 1: what happened. On March fifteenth, twenty twenty three, Kevin Russ
Speaker 1: of The New York Times would say that open Aiy's
Speaker 1: GPT four was exciting and scary, and then it was exacerbating,
Speaker 1: in his words, the dizzy and vitigenous feeling I've been
Speaker 1: getting whenever I think about AI lately, wondering if he
Speaker 1: was experiencing future shock, then described how it was an
Speaker 1: indeterminate level of better, and then said something that immediately
Speaker 1: sounded ridiculous. In one test conducted by an AI safety
Speaker 1: research group that hooked GPT four up to a number
Speaker 1: of other systems, GPT four was able to hire a
Speaker 1: human task rabbit worker to do a simple online task
Speaker 1: career solving a capture test without alerting the person to
Speaker 1: the fact it was a robot. The AI even lied
Speaker 1: to the robot about why it needed the capture done,
Speaker 1: concocting a story about a vision impairment. Now this doesn't
Speaker 1: sound even remotely real now, but this was two years ago.
Speaker 1: So I went and looked up the paper, and pretty
Speaker 1: much everything that Ruth described was illustrative. I didn't really
Speaker 1: see whether it happened. Now. He's referring to the safety
Speaker 1: card which every model has that lists all the measures
Speaker 1: used to train it and such. And this safety card
Speaker 1: led to the perpetration of one of the earliest falsehoods
Speaker 1: and most eagerly parroted lies about this fucking industry. And
Speaker 1: that was the chat GPT in Jenerity. I of AI
Speaker 1: is capable of agentic actions outlet after outlet, and some
Speaker 1: people who should definitely have known better, led by Kevin Ruce,
Speaker 1: eagerly interted an entire series of events that took place
Speaker 1: that doesn't remotely make sense, starting with the fact that
Speaker 1: I don't think you can hire a cast grabbit to
Speaker 1: solve a capture at the very least without a contrived
Speaker 1: situation where you create an empty task and ask them
Speaker 1: to complete it. Why not use mechanical turk or favor.
Speaker 1: There are people right now offering that service. There were
Speaker 1: actual real things. But you know me, I'm a curious
Speaker 1: little critter. So I went further and followed this the
Speaker 1: citation from the safety card to the study, and this
Speaker 1: is by METR and the research page. It turns out
Speaker 1: that what actually happened was MATR had a researcher copy
Speaker 1: and paste the generated responses from the model and otherwise
Speaker 1: handled the entire interaction with the task grab it and
Speaker 1: based on the plurality of cask Grabbit contractors, it appears
Speaker 1: to have taken multiple times. On top of that, it
Speaker 1: appears to open AI and META as METR sorry, we're
Speaker 1: prompting the model and what to say, which kind of
Speaker 1: defeats the point, like we don't naturally know what they
Speaker 1: prompted it to do. And when you look even says
Speaker 1: it does like chain of thought reasoning, which didn't really
Speaker 1: exist back then, and if it did, it was extremely
Speaker 1: like chain of thought is reasoning, And that came out
Speaker 1: end of twenty twenty four. This whole thing is absolutely insane.
Speaker 1: It's absurd that anyone wrote about it is real. What happened,
Speaker 1: just to be really blunt, is that they if they
Speaker 1: even opened a task rabbit. It's really not obvious whether
Speaker 1: they actually did this. They had to go to the
Speaker 1: model and say, okay, I'm opening a task rabbit window,
Speaker 1: and now the person has said this, and now this
Speaker 1: is it. It just doesn't sound real at all. But
Speaker 1: even if it did, it's very obvious that they were
Speaker 1: telling the model what to say and then copy pasting
Speaker 1: the response, and it took them multiple tries. It took
Speaker 1: me five whole minutes to find this article, partly because
Speaker 1: it was cited on the GPT for system card. I
Speaker 1: then then read it within that time, then wrote this
Speaker 1: part of the script. It didn't require any technical knowledge
Speaker 1: other than the ability to read. It is transparently, blatantly
Speaker 1: obvious that GPT four did not hire a task rabbit
Speaker 1: or indeed make any of these actions it was prompted to,
Speaker 1: and they did not use show the prompts they used,
Speaker 1: likely because they had to use so many of them.
Speaker 1: If they even did it, anyone falling for this as
Speaker 1: a mark and open ay should have gone out of
Speaker 1: their way to correct people. Instead, they sat back and
Speaker 1: let people publish outright misinformation. Rus, along with his co
Speaker 1: host Casey Newton, would go on to describe this example
Speaker 1: at length on a podcast that week, describing an entire
Speaker 1: narrative where the human actually gets suspicious and GPT four
Speaker 1: reasons out loud that it should not reveal that it
Speaker 1: is a robot. It's not a reasoning model, at which
Speaker 1: point the task rabbit solves the capture. During this conversation,
Speaker 1: Newton gasps and says, oh my god twice. And when
Speaker 1: he asks Rus, how does this model understand that in
Speaker 1: order to succeed, its task has to deceive the human?
Speaker 1: Rus responds, we don't know. That is the unsatisfying answer,
Speaker 1: and Newton laughs and states, we need to pull the
Speaker 1: plug and again, what disgraceful, embarrassing, reprehensible. All that and
Speaker 1: more on the hard Fork podcast published weekly You Can
Speaker 1: Cut that that ads for free fellas credulousness aside. The
Speaker 1: GPT for marketing campaign was incredibly effective, creating an order
Speaker 1: that allowed open ai to take advantage of the vagueness
Speaker 1: of its offering, as people, including members of the media,
Speaker 1: willfully filled in the blanks for them. Allman has really
Speaker 1: never had to work to sell his product. Think about it.
Speaker 1: Have you ever heard open ai tell you what chat
Speaker 1: gpt can do or go to great lengths to describe
Speaker 1: its actual abilities. Even on open AI's own page. With
Speaker 1: chat GPT, the text is extremely vague. You scroll down,
Speaker 1: you're told that chat gpt can write, brain storm, edit
Speaker 1: and explore ideas with you. It can generate and debug code,
Speaker 1: automatic repetitive tasks, not clear what the tasks are, and
Speaker 1: help you learn new APIs question mark. With chat GPT,
Speaker 1: you can learn something new, dive into a hobby, answer
Speaker 1: complex questions and analyze data, and create charts repetitive tasks.
Speaker 1: Who knows how am I learning? Unclear? It's got thinking,
Speaker 1: billtim What that means is also unclear, unexplained, and thus
Speaker 1: allows a user to incorrectly believe that chat GPT has
Speaker 1: brain and thinks. To be clear, I know what reasoning means,
Speaker 1: but this website does not attempt to explain what thinking means.
Speaker 1: You can also offload complex tasks from start to finish
Speaker 1: with an agent, which can, according to open Ai, think
Speaker 1: and act proactively, choosing from a tool box of urgentic
Speaker 1: skills to complete tasks for you using its own computer.
Speaker 1: This is an egregious lie, employing the kind of weasel
Speaker 1: wording that would be used to torture ir but boon
Speaker 1: for an eternity precise in its vagueness. Open AI's copy
Speaker 1: is home to make reporters willing to simply write down
Speaker 1: whatever they see and interpret it in the most positive light,
Speaker 1: and thus the lie of inference began. What chat GPT
Speaker 1: meant was moneyed from the beginning, and thus chat GPT's
Speaker 1: actual outcomes have never been fully defined. What chat gpt
Speaker 1: could do became a kind of folklore, a non specific
Speaker 1: form of automation that could write code and generate copy
Speaker 1: and images, that can analyze data. All things that are true,
Speaker 1: but one can infer much greater meaning and use from
Speaker 1: One can infer that automation means the automation of anything
Speaker 1: related to text, or that right code means write the
Speaker 1: entirety of a computer program. Open AI's chet GPT agent
Speaker 1: is not, by any extension of the word and I
Speaker 1: quote already a powerful tool for handling complex tasks, but
Speaker 1: it has not, in any meaningful sense committed to any
Speaker 1: actual outcomes as a result, potential users subject to a
Speaker 1: twenty four to seven marketing campaign have been pushed towards
Speaker 1: a website that can theoretically do anything or nothing, and
Speaker 1: have otherwise been left to their own devices. The endless
Speaker 1: gas lighting societal or pressure, media pressure and pressure from
Speaker 1: their bosses has pushed hundreds of millions of people to
Speaker 1: try a product that even its creators can't really describe
Speaker 1: or don't feel compelled to. And if I was wrong,
Speaker 1: we'd have real use cases by now and better metrics
Speaker 1: than weekly active users. As I said in the past,
Speaker 1: open ai is deliberately using these weekly active users so
Speaker 1: that it doesn't have to publish their monthly active users,
Speaker 1: which I believe would be much higher. Now, why wouldn't
Speaker 1: it do this well? Open ais mentioned as twenty million
Speaker 1: paying chat GPT subscribers and five million business customers, with
Speaker 1: no explanation of what the difference might be really other
Speaker 1: than it involves teams and edgy but not pro Anyway,
Speaker 1: this is already a mediocre three point five percent conversion rate. Yeah,
Speaker 1: it's monthly active users, which are likely eight hundred and
Speaker 1: nine hundred million, but these are guesses would make that
Speaker 1: rate lower than three percent, which is pretty terrible considering
Speaker 1: everyone says this shit is the future. I'm al so
Speaker 1: tired of having people claim that search or brainstorm or
Speaker 1: companions are a lasting, meaningful business model. I'm really tired
Speaker 1: of him. I'm tired of being told this again and
Speaker 1: again and again. That's not what chat GPT is going
Speaker 1: to actually survive on bath. Okay, let's move on. Here's
Speaker 1: another booster grip though open ai is making tons of money.
Speaker 1: That's proof they're a successful company and you are wrong somehow.
Speaker 1: So open ai announced that it is here it's first
Speaker 1: one billion dollar month on August twenty to twenty twenty
Speaker 1: five on CNBC. In fact, weirdly enough, by the way,
Speaker 1: that quote was not in the TV interview. But anyway,
Speaker 1: this is also brings it exactly in line with my
Speaker 1: estimating five point twenty six billion in revenue that I
Speaker 1: believe it has made at the end of July. Did
Speaker 1: that in a premium newsletter? Please pay me? However, remember
Speaker 1: what the MIT study that I mentioned said, Enterprise adoption
Speaker 1: is high, but transformation is low. There are tons of
Speaker 1: companies throwing money at Ai, but they are not seeing
Speaker 1: actual returns. Open Aiy's growth is the single most prominent
Speaker 1: company in AI, and if we're honest, one of the
Speaker 1: most prominent in software. Writ large makes sense, but at
Speaker 1: some point will slow because the actual returns for businesses
Speaker 1: are not there. If there were, we'd have one article
Speaker 1: where we could point a chat GBT integration that helped
Speaker 1: scale a company or save a bunch of money, make
Speaker 1: a bunch of money, written in plain English and not
Speaker 1: in the gobbledygook of profit improvement. Also, open aiye is
Speaker 1: projected to make twelve point seven billion dollars in twenty
Speaker 1: twenty five. How exactly will it do that? Is it
Speaker 1: really making one point five billion dollars a month by
Speaker 1: the end of the year. Even if it does, is
Speaker 1: the idea that it keeps idding ten billion dollars or
Speaker 1: more a year every year into it? Tenny? What actual
Speaker 1: revenue potential does open ai have long term? It's products
Speaker 1: are about as good as everybody else, is, cost about
Speaker 1: the same and do the same things. Chat GPT is
Speaker 1: basically the same product as Claude or Grock, maybe in
Speaker 1: the less Mecha Hitler or any number of different lms.
Speaker 1: The only real advantages that open ai has are infrastructure
Speaker 1: and brand recognition. These models have clearly hit a wall
Speaker 1: in training, hitting diminishing returns, meaning that the infrastructural advantage
Speaker 1: is that they can continue providing its service at scale,
Speaker 1: nothing more. It isn't making its business cheaper other than
Speaker 1: the fact it mostly hasn't had to pay for it,
Speaker 1: other than the site in Aplene, Texas, where it's promised
Speaker 1: Oracle thirty billion dollars a year in twenty twenty five.
Speaker 1: I'm sorry, I don't buy it. I don't buy that
Speaker 1: this company will continue growing forever and its stinky conversion
Speaker 1: rate isn't going to change anytime soon. When open Ai
Speaker 1: opens Stargate Abilene, it will turn profitable. How I hear
Speaker 1: this one a good amount? How? How? How? How how
Speaker 1: gonna happen? Nobody ever answers, No one ever for answers
Speaker 1: actually how this company will become profitable. It's fucking insane
Speaker 1: to me. Nobody ever answers the question efficiencies. Efficiencies. They're
Speaker 1: going to be efficient? Mmmmm, they're going to be efficient
Speaker 1: if you're gonna say chat GPT five. I wrote a
Speaker 1: huge scoop and then did an episode about why it's
Speaker 1: not more efficient. In fact, it's less efficient and I'm
Speaker 1: sure one of you is going to argue, well, you know,
Speaker 1: they could do their customs Silicon. There a ten billion
Speaker 1: dollar deal with Broadcom. How they fucking pay them for that?
Speaker 1: Also you realize that well, actually no, just you know, no,
Speaker 1: you're right, they're going to get the chip from Broadcom
Speaker 1: because you know what they always say about the first
Speaker 1: generation of tech, right, it always works and it's always
Speaker 1: great and it has no problems. That's what I always
Speaker 1: That's that's why happened with pretty much every first time
Speaker 1: they make anything in tech. Anyway's move on. You'll hear
Speaker 1: boosters also be like, well, my brother's friends dog uses
Speaker 1: chat GPT and I love it. Well I heard this happen,
Speaker 1: or my mate as it in this or I heard
Speaker 1: this person, or I use it in this one before
Speaker 1: we go any further. Just to be clear, though, is
Speaker 1: when you hear a booster bring up AI and they'll
Speaker 1: say something, make sure they're talking about generative AI. Are
Speaker 1: they actually talking about generative AI? Is this a large
Speaker 1: language model thing? It's very, very very common for people
Speaker 1: to conflate AI with generative AI. There are many different
Speaker 1: kinds of AI. Make sure that the AI booster whatever
Speaker 1: they're claiming whatever they're telling you is actually about large
Speaker 1: language models. So there are all sorts of other kinds
Speaker 1: of machine learning that people love to bring up. LM's
Speaker 1: have nothing to do with folding at home, autonomous cars,
Speaker 1: or most disease research. Well, okay, let's do a speed
Speaker 1: run using AI led researchers to discover forty four percent
Speaker 1: more materials. No, it didn't. Mit is now withdrawn this
Speaker 1: paper site and concerns about its integrity. I've linked it
Speaker 1: in the show notes. There's a huge rundown. Here's another quote.
Speaker 1: AI is so profoundly powerful that it's causing young people
Speaker 1: to have trouble finding a job. While young people have
Speaker 1: been having trouble finding jobs, there's no proof that AI
Speaker 1: is the reason. Every piece of coverage or reading is
Speaker 1: citing an ax with economics report that amidst a bunch
Speaker 1: of numbers, says and I quote there are signs that
Speaker 1: entry level positions are being displaced by artificial intelligence at
Speaker 1: higher rates, a statement that it does not back up
Speaker 1: other than claiming that the high adoption rate by information
Speaker 1: companies along the sheer employment declines in some roles since
Speaker 1: twenty twenty two, suggested some displacement effect from AI, and
Speaker 1: digging deeper, the largest displacement seems to be entry level
Speaker 1: jobs normally filled by recent graduates. There's otherwise new data.
Speaker 1: Anyone making this point is grasping at straws. I go
Speaker 1: into this in more detail in the newsletter called Sincerity
Speaker 1: Wins the War, which I've linked to. But it's one
Speaker 1: of the worst reported stories in tech. And now I'm
Speaker 1: actually going to add li it for a second, because
Speaker 1: I forgot while write in this script. There was also
Speaker 1: this thing that came out of Stanford that said it's
Speaker 1: been a thirteen percent drop in jobs affected by AI,
Speaker 1: and this was used as proof that AI was taking them. Now,
Speaker 1: curious little critic that I am, I went and read
Speaker 1: that what it actually did was find a bunch of
Speaker 1: jobs that they think are related to AIM being affected
Speaker 1: by AI. They saw they were going down, and they went, oh,
Speaker 1: it is AI that did that. They've done. They fart
Speaker 1: around with various statistics, but that's long and short of him.
Speaker 1: I give you an example. One of the job's accountancy. Now,
Speaker 1: any accountants listening, big up to my accountant listeners, there's
Speaker 1: been a hiring crisis. Is accountancy for years. People are
Speaker 1: not becoming CPAs. The reason there are less of them
Speaker 1: is that less people are becoming them. It's nothing to
Speaker 1: do with AI. Like, are you imagine if anyone have
Speaker 1: put half as much effort into writing up these stories
Speaker 1: as I did writing up one of these booster quips.
Speaker 1: But here's another one that AI is replacing young coders
Speaker 1: and it is not. In fact, Amazon's cloud chief just
Speaker 1: said that replacing junior employees of AI is one of
Speaker 1: the dumbest things he's ever heard. There is no actual,
Speaker 1: real evidence that this is the case. Every single story
Speaker 1: you have read is anecdotal. Anyone peddling this has an
Speaker 1: agenda or is not reading. Every CEO mentioning this specifically
Speaker 1: avoids saying the words that AI is replacing people because
Speaker 1: AI can't replace people. I will add an aside, there
Speaker 1: are people's jobs that have been replaced by A Translators, transcribers.
Speaker 1: Brian over at blood is in the machine. Blood in
Speaker 1: the machine. Even sorry, Brian, He's doing a great job
Speaker 1: on covering this. There are people that have lost jobs.
Speaker 1: These people are losing it because their bosses are fucking stupid,
Speaker 1: because their bosses are just taking the shittiest possible version
Speaker 1: of their work and slopping it up. That's not happening
Speaker 1: at the knowledge worker scale, nor is it happening at
Speaker 1: the code of scale. Everyone telling you that has an agenda.
Speaker 1: But boosters will also claim that AI is doing science
Speaker 1: for search somehow or will do it, and it won't.
Speaker 1: I've included a write up about why foundation models can't
Speaker 1: do this. Someone's going to read it and say, but
Speaker 1: there's this bit where it says it isn't a defeat
Speaker 1: of lllms, and the reason he says this is because
Speaker 1: I sheot you not that lms aren't incapable of doing
Speaker 1: scientific research. He says they're insufficient, which is which is
Speaker 1: the same thing. Think they're insufficient anyway. He claims they're
Speaker 1: also not dead weight for science, then spends hundreds of
Speaker 1: words meandering around around that thing to kiss up to
Speaker 1: AI boasters for some reason. I assume because they've terrified
Speaker 1: him by being really annoying, and these people need to
Speaker 1: go outside and touch grass. Now a lot of people
Speaker 1: think they're going to tell me that they use AI
Speaker 1: all the time, and that will change my mind. I
Speaker 1: cannot express how irrelevant it is that you have a
Speaker 1: use cases. Every use case I hear is one of
Speaker 1: the following. I use it for brainstorming, to which I say,
Speaker 1: who cares. Not a business model, it's commoditized. I use
Speaker 1: it like search. Who cares. It's not even good at search.
Speaker 1: It's fine, It's not even better than the low bar
Speaker 1: set by Google Search. The results it gives on great,
Speaker 1: and the links are deliberately made smaller, which gets in
Speaker 1: the way of me clicking them so I can actually
Speaker 1: look at the content. If you're using chat GPT for search,
Speaker 1: you may not actually care about the content of the
Speaker 1: things you're looking at. If I'm wrong, great, you now
Speaker 1: have a functional search engine can gratch your fuculations. Well,
Speaker 1: I use it for a search, and if you use
Speaker 1: it for a search, you do not respect natural research.
Speaker 1: You want a quick answer, It's that simple. These reports
Speaker 1: are slop. I've read many, many, many AI reports and
Speaker 1: they're not good. Sorry. Well, I use it for coding.
Speaker 1: I know someone who used it for coding, and I'll
Speaker 1: get to that at a minute. But all of this
Speaker 1: would be fine and dandy if people weren't talking about
Speaker 1: this stuff as if it was changing society. None of
Speaker 1: these use cases come close to explaining why I should
Speaker 1: be impressed by generative AI. It also doesn't matter if
Speaker 1: you yourself have a kind of useful thing that AI
Speaker 1: did for you once. We are so past the point
Speaker 1: when any of that matters. AI is being sold as
Speaker 1: a transformational technology, and I am yet to see it
Speaker 1: transform anything. I am yet to hear one use case
Speaker 1: that truly impresses me, or even one thing that feels
Speaker 1: possible now that wasn't possible before. This isn't even me
Speaker 1: being a cynic. I'm ready to be impressed. I just
Speaker 1: haven't been impressed in three fucking years and it's getting boring. Also,
Speaker 1: tell me with the straight face that any of this
Speaker 1: shit is worth the infrastructure. Remember, AI boosters are arguing
Speaker 1: that this stuff is powerful. None of these use cases
Speaker 1: are powerful sounding, but sir, I I agree, sir. Vibe
Speaker 1: coding is changing the world, allowing people who can't code
Speaker 1: to make software. Now, this is one of the most
Speaker 1: brain dead takes about AI and coding, and it's the
Speaker 1: Vibe coding is allowing anyone to build software. And you'll
Speaker 1: never guess what. Kevin Ruce covered this sh did this article.
Speaker 1: While writing the script, I hadn't even know as need
Speaker 1: Lisch anyway. Well, technically true in that one can just
Speaker 1: type build me a website into one of many coding environments.
Speaker 1: This does not mean said website is functional, secure, or useful.
Speaker 1: Let's make this really clear. AI cannot just handle coding.
Speaker 1: Go into the show notes and read this piece I've
Speaker 1: linked from Colton Bogie. I have actually interviewed in him
Speaker 1: now he's going to be coming out in the next
Speaker 1: few weeks. The episode the interview is fucking brilliant. And
Speaker 1: then the other I've linked to by Nick Suesh. If
Speaker 1: you contact me about AI and coding without reading these,
Speaker 1: I will send them to you and nothing else, or
Speaker 1: crush you like a car in a garbage dump into
Speaker 1: a cube. One or the other I will choose at
Speaker 1: the time. Also, show me a vibe coded company, Please,
Speaker 1: not a company where somebody who can code has quickly
Speaker 1: spun up some features. A fully functional, secure and useful
Speaker 1: app that has made money and made by somebody who
Speaker 1: cannot read or write code. You won't be able to
Speaker 1: because it is impossible. Vibe coding is a marketing term
Speaker 1: based on lies peddled by people who either have a
Speaker 1: lack of knowledge or morals and RAI coding environments making
Speaker 1: people faster. I don't think so. In fact, a recent
Speaker 1: study suggested that they actually make software engineers nineteen percent slower.
Speaker 1: The reason that nobody is vibe coding in entire companies
Speaker 1: because software development is not just put a bunch of
Speaker 1: code in a pile and hit go, and oftentimes when
Speaker 1: you add something, it breaks something else. This is all
Speaker 1: well and good if you actually understand code. It's another
Speaker 1: thing entirely when you're using cursor or clawed code, like
Speaker 1: a kid at an arcade machine, turning the wheel repeatedly
Speaker 1: without having a coin in there and pretending that you're
Speaker 1: playing it when the demo's going on. VIB coders are
Speaker 1: also awful for the already negative margins of most AI
Speaker 1: coding environments is every single thing they ask the model
Speaker 1: to do is imprecise burning tokens in pursuit of a
Speaker 1: goal they themselves don't really understand. VIB coding doesn't work,
Speaker 1: It will not work, and pretending otherwise is at best
Speaker 1: ignorance and are worth supporting a campaign built on lies.
Speaker 1: And this is all built up to one final point.
Speaker 1: I'm no longer accepting half baked arguments. If you're an
Speaker 1: AI booster, please come up with better arguments, and if
Speaker 1: you truly believe in this stuff, you should have a
Speaker 1: firmer grasp and why you do so. It's been three
Speaker 1: years and the best some of you have is it's
Speaker 1: really popular or uber also burned money. Your arguments are
Speaker 1: based on what you wish were true rather than what's
Speaker 1: actually true, and it's deeply embarrassing. Then again, there are
Speaker 1: many well intentioned people who aren't necessarily AI boosters who
Speaker 1: repeat these arguments, regardless of how thinly frame they are,
Speaker 1: in part because we live in a high information, low
Speaker 1: processing society where people tend to put great faith in
Speaker 1: people who are confident in what they say and sound smart. Jason,
Speaker 1: I also think the media is failing on a very
Speaker 1: basic level to realize that their fear of missing out
Speaker 1: or seeming stupid is being used against them. If you
Speaker 1: don't understand something, it's likely because the people you're reading
Speaker 1: or hearing it from don't either. If a company takes
Speaker 1: a promise and you don't understand how they'll deliver on it,
Speaker 1: it's their job to explain how, and your job to
Speaker 1: suggest it is implausible and clear and defined language This
Speaker 1: has gone beyond simple objectivity into the realm of an
Speaker 1: outright failure of journalism. I have never seen more and
Speaker 1: misinformation about the capabilities of a product in my entire career,
Speaker 1: and it's largely peddled by reporters who either don't know
Speaker 1: or have no interest in knowing what's actually possible, in
Speaker 1: part because all their peers are doing the same thing
Speaker 1: and saying the same nonsense. As things begin to collapse,
Speaker 1: and they sure look like they're collapsing, but I'm not
Speaker 1: making any wild claims about the bubble bursting quite yet,
Speaker 1: it will look increasingly more deranged to bluntly publish everything
Speaker 1: that these companies say. Never have I seen an act
Speaker 1: of outright contempt more egregious than Sam Altman's saying that
Speaker 1: GPT five was actually bad and that GPT six will
Speaker 1: be even better. Members of the media, Sam Altman does
Speaker 1: not respect you. He is not your friend, Clammy. Sam
Speaker 1: Mortman is not secretly confiding in you. Clammy Will thinks
Speaker 1: you are stupid and easily manipulated, and will print anything
Speaker 1: he says, largely in part because many members of the
Speaker 1: media will print exactly what he says whenever he says him.
Speaker 1: And to be clear, if you wrote about GPT six
Speaker 1: and made fun of it, that's great. But let's close
Speaker 1: by discussing the very nature of AI skepticism and the
Speaker 1: so called void between those who hate AI and those
Speaker 1: who love AI. Am from the perspective of one of
Speaker 1: the most prominent people in the skeptic camp. Critics and
Speaker 1: skeptics are not given the benefit of grace, patience, or
Speaker 1: in many cases, hospitality when it comes to their position.
Speaker 1: While they may receive interviews and opportunities to give their side,
Speaker 1: it's always framed as the work of a firebrand and outlier,
Speaker 1: or somebody with dangerous ideas that they must eternally justify.
Speaker 1: Skeptics are demonized, their points under constant scrutiny, their allegiances
Speaker 1: and intentions constantly interrogated for some sort of moral or
Speaker 1: intellectual weakness. Skeptic and critic are words said with a
Speaker 1: sneer of trepidation that the listener should be suspicious that
Speaker 1: this person isn't agreeing that AI is the most powerful,
Speaker 1: special thing ever. To not immediately fall in love with
Speaker 1: something that everybody is talking about is to be framed
Speaker 1: as a hater. To have oneself, introduced with the words
Speaker 1: not everyone agrees or on forty percent of your appearances.
Speaker 1: By comparison, AI boosters are the first to get TV
Speaker 1: appearances and offers to be on panels. Their coverage featured
Speaker 1: prominently on tech Meme, something slot like books called shit
Speaker 1: like The Future of Intelligence, Masters of the Brain, featuring
Speaker 1: eighteen interviews with different CEOs that all say the same thing.
Speaker 1: They don't have to justify their love. They simply have
Speaker 1: to remember all the right terms chirping out, test time, compute,
Speaker 1: and the cost of inference is going down enough times.
Speaker 1: The Salomon Wario Amiday to give them an hour long
Speaker 1: interview where he says the models they are in years
Speaker 1: going to be the most powerful school teacher ever built.
Speaker 1: And by the way, yeah, I did sell a book
Speaker 1: because my shit fucking bangs, my shit rocks. I'm I'm
Speaker 1: not going to be too smug, but like, I put
Speaker 1: a lot of effort into this and I research it
Speaker 1: very well. Others should try harder. I have persistent, deeply
Speaker 1: sourced arguments that I've built over the course of years.
Speaker 1: I didn't become a hater because I'm a contrarian. I
Speaker 1: became a hater because the shit that these fucking oaths
Speaker 1: have done to the computer pisses me off. I did
Speaker 1: the man that destroyed Google Search because I wanted to
Speaker 1: know why Google Search sucked. I wrote Sam Altman Free
Speaker 1: because at the time I didn't understand why everybody was
Speaker 1: so fucking enamored with this clammy sociopath. Everything I do
Speaker 1: comes from a genuine curiosity and an overwhelming frustration with
Speaker 1: the state of technology. I started writing the newsletter that
Speaker 1: led to this podcast with three hundred subscribers and sixty views,
Speaker 1: and have written it as an exploration of subjects that
Speaker 1: grows as I write. I do not have it in
Speaker 1: me to pretend to be anything other than what I am,
Speaker 1: And if that's strange to you, well I'm a strange man,
Speaker 1: but at least I'm an honest one. I do have
Speaker 1: a chip on my shoulder and that I really do
Speaker 1: not like it when people tried to make other people
Speaker 1: feel stupid, especially when they do so as a means
Speaker 1: of making money for themselves or making someone else look good.
Speaker 1: I write this stuff out because I have an intellectual interest.
Speaker 1: I like writing, and by writing, I'm able to learn
Speaker 1: and process my complex feelings around technology. And talking it
Speaker 1: out actually feels good. It's an intellectual exercise that I
Speaker 1: really enjoy. I happen to do so in a manner
Speaker 1: that hundreds of thousands of people enjoy every month. And
Speaker 1: I'm not specifying where those people go. And if you
Speaker 1: think that I've grown this by being a hater, you
Speaker 1: are doing yourself the service of underestimating me, which I
Speaker 1: will use to my advantage by writing deeper, more meaningful,
Speaker 1: and more insightful things than you, and then I'll say
Speaker 1: them with lots of curse words on this podcast. I've
Speaker 1: watched these pigs ruin the computer again and again and
Speaker 1: make billions doing so. And all of this is happening
Speaker 1: while the media celebrates the destruction of things like Google,
Speaker 1: Facebook and the fucking environment in pursuit of eternal growth.
Speaker 1: I can't manufacture my discussed nor is it hard to
Speaker 1: nor can I manufacture whatever it is incide that makes
Speaker 1: it impossible to keep quiet about these things. I don't
Speaker 1: know if I take this too seriously, whether I don't
Speaker 1: take it seriously enough because they keep saying fucking shit.
Speaker 1: But I'm honored that I'm able to do so, and
Speaker 1: I really appreciate everyone who listens, reads, or engage with
Speaker 1: with me in any way. I really do love you
Speaker 1: all for listening. I know that this was a long
Speaker 1: three parter. I've enjoyed recording it. I've done lots of retakes. Mattasowski,
Speaker 1: love you man. Sorry for all of this. I'll catch
Speaker 1: you next episode. Thank you for listening to Better Offline.
Speaker 1: The editor and composer of the Better Offline theme song
Speaker 1: is Matasowski. You can check out more of his music
Speaker 1: and audio projects at Matasowski dot com, M A T
Speaker 1: T O s O W s ki dot com. You
Speaker 1: can email me at easy at Better Offline dot com
Speaker 1: or visit better Offline dot com to find more podcast
Speaker 1: links and of course, my newsletter. I also really recommend
Speaker 1: you go to chat dot Where's Youreed dot at to
Speaker 1: visit the discord, and go to our slash Better Offline
Speaker 1: to check out our reddit. 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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