How To Argue With An AI Booster, Part One

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welcome to better offline i'm your host ed zitron

As ever, check out the episode notes for merchandise, my newsletter, various links, things that I just write for myself.

I don't actually leave little notes, but maybe I should.

But as promised in my last monologue, we've got a three-part episode this week, and we're talking about AI boosters, the people who insist, despite very little proof and all evidence to the contrary, that generative AI is the future.

Open AI and Anthropic are perfectly healthy companies, and what we're witnessing isn't an inflation of a massive, dangerous bubble that might eat our entire economy, but rather the emergence of a brand new paradigm in tech that's just as meaningful as the smartphone and cloud computing revolutions.

I even saying that out loud makes me feel a little crazy, but yeah, that's what they believe.

These people exist, they're often wrong, in fact they're mostly wrong, and they're also really, really annoying.

And so as a public service, I'm going to spend the next three episodes explaining how to talk with them without losing your sanity, will to live, or your ability to operate in society.

Now, what makes me qualified to do this?

Well, in the last two years, I've written no less than half a million words, with many of them dedicated to breaking both existent and previous myths about the state of technology and the tech industry itself.

Now let's start with something every critic has experienced, the massive double standard between those perceived as skeptics and those who are optimistic or optimists.

To be skeptical of AI is to commit yourself to a near-constant amount of demands to prove yourself, and endless snags of, but what about, with each one, no matter how small, presented as a fact that defeats any points you may have had, have, or will have in the future.

Conversely, being an optimist allows you to take things like AI 2027, which I will fucking get to, seriously to the point that you can write an entire feature-length fan fiction piece in the New York Times and nobody will bat an eyelid.

In any case, things are beginning to fall apart.

Two of the actual reporters, the real ones at the New York Times, rather than columnists who kind of act like adult babies, reported in late August that Meta is yet again restructuring its AI department for the fourth time, and that it's considering downsizing their overall AI division, which sure doesn't seem like something you'd do if you thought AI was the future.

Meanwhile, the markets are thoroughly spooked by an MIT study covered by Fortune that found that 95% of generative AI pilots at companies are failing and providing no RROI.

And though MIT Nanda has now replaced the link to the study with some sort of Google form to request access, you can find the full PDF linked in the show notes.

By the way, this is the kind of thing that is a PR firm wanting to try and set up interviews.

Not for me, thank you.

Just like to read the thingy that you put out.

Very rude.

In any case, the report is actually grimmer than Fortune made it sound, saying that 95% of organizations are getting zero return on generative AI.

The report says that adoption is high, but transformation is low, adding that few industries show the deep structural shifts associated with past general-purpose technologies, such as new market leaders, disrupted business models, or measurable changes in customer behavior.

And saying that out loud, that is right.

What is being disrupted by AI?

Search?

Kind of.

That just means that search sucks.

Anyway, yet the most damning part was there was a part called the five myths about

AI in the enterprise, which is probably the most wilting takedown of this movement I've ever seen.

And I'm going to quote it adverbatum.

Okay, number one, and they present these as the first statement is something that isn't going to happen, or they're questioning.

AI will replace most jobs in the next few years.

What it actually says is research found limited layoffs from Gen AI, and only in industries that are already affected significantly by AI.

There is no consensus among executives as to hiring levels over the next three to five years.

Another statement they challenge: generative AI is is transforming business.

No, no, no.

Adoption is high, but transformation is rare.

Only 5% of enterprises have AI tools integrated into workflows at scale, and seven of nine sectors show no real structural change.

And I want to thank them for putting this there.

I made this exact point in February in my newsletter, There's No AI Revolution.

Links in the show notes as ever.

Enterprises are slow in adopting new tech is another commonly held thing, and they say, enterprises are extremely eager to adopt AI, and 90% have seriously explored buying an AI solution.

Another statement they challenge, the biggest thing holding back AI is model quality, legal data and risk.

And then they say, which is my favorite quote, what's really holding it back is that most AI tools don't learn and don't integrate well into workflows.

I really do love that.

I love that so much'cause it's like the thing holding AI back is that it sucks.

And the final one, the final challenge statement they make is the best enterprises are building their own tools.

Internal builds fail twice as often.

And that's twice as often in a thing where 95% fail.

Anyway, these are brutal, dispassionate points that directly deal with the most common boosterisms.

Generative AI isn't transforming anything.

AI isn't replacing anyone.

Enterprises are trying to adopt generative AI, but it doesn't fucking work.

And the thing holding back AI is the fact it doesn't fucking work.

This isn't a case where the enterprise is suddenly going to save these companies because the enterprise has already tried and it is not working.

And what's hilarious as well is so many people people say, well, there's just this enterprise opportunity they haven't got into yet.

Actually, they have.

They've got into the enterprise.

They're sticking their fingers in all the bits of the SaaS and it isn't working.

And the enterprise loves money.

The enterprise will do, even if it's a genuinely evil product, they will push it.

Like, look at Salesforce, an entire company based on them.

Anyway, an incorrect read of the study that's been going around is that the learning gap that makes these things less useful is because of human issues, like human error.

When the study actually says that the fundamental gap that defines the Gen AI divide is that users resist tools that don't adapt, model quality fails without context, and UX suffers when systems can't remember.

This isn't something you, as a person, learn your way out of.

These products don't do what they're meant to do, and people are realizing it when they try and use them.

Nevertheless, boosters will still find a way to twist this study to mean something else.

They'll claim that AI is still early, that the opportunity is still there, that we didn't confirm that the internet and smartphones were productivity boosting, or that we're in the early days of AI somehow.

Three years and hundreds of billions of dollars and thousands of articles it.

Yeah, we're in the early days.

We're in the early days when all the money and all the land has gone into this.

And I'm tired.

I'm tired of having the same arguments with these people.

And frankly, I'm sure you are too.

No matter how blindly obvious evidence is to the contrary, they will find ways to ignore it.

They continually make these smug comments about people wishing things would be bad or suggesting you are stupid.

And yes, that is their belief, by the way, for not believing that generative AI is disruptive.

Today, and in this three-parter, I'm going to give you the tools to fight back against the AI boosters in your life.

I'm going to go into the generalities of the booster movement, the way they argue, the tropes they cling to, and the ways in which they use your own self-doubt against you.

They're your buddy, your boss, a man in a gingham shirt, epic steakhouse, who won't leave you the fuck alone, a editor, a writer, a founder, or just a common or garden con artist.

Whoever the booster in your life is, I want you to have the words to fight them with.

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So an AI booster is not, in many cases, an actual fan of artificial intelligence.

People like Simon Willison or Max Wolf, who actually work with LLMs on a daily basis, don't see the need to repeatedly harass everybody or talk down to them about their unwillingness to pledge allegiance to the graveyard smash of generative AI.

In fact, the closer I've found someone to actually building things with LLMs, the less likely they are to emphatically argue that I'm missing out on something by not doing so myself.

No, no, no, the AI booster is symbolically aligned with generative AI.

They're fans in the same way that somebody is a fan of a sports team, their houses emblazoned with every possible piece of tat and crap they can find, their Sundays living and dying by the successes of the team, except even fans of the Dallas Cowboys have a tighter grasp on reality.

But not Micah Parsons.

Anyway, Kevin Roos and Casey Newton are two of the most notable boosters, and as I'll get to later in this series, neither of them have a consistent or comprehensive knowledge of AI, despite being at the New York Times, though Casey Newton is a contractor.

He's a contractor just for a podcast, which I can't insult

due to my own contractual relationships.

Nevertheless, they will insist that everybody is using AI for everything, which is the title of an article they put out, a statement that even a booster should realize is incorrect based on the actual abilities of the models.

But that's because it isn't about what's happening.

It's not about what's actually happening.

It's about allegiance.

AI symbolizes something to the AI booster, a way that they're better than other people, that makes them superior because they're, unlike cynics and skeptics, able to see the incredible potential in the future of AI, but also how great it is today, though they never seem to be able to explain why it is other than it replaced Search for Me and I use it to draw connections between articles I write, which is something I do for free without AI with my fucking brain.

Boosterism is a kind of religion interested in finding symbolic proof that things are getting better in some indeterminate way, and that anyone that chooses to believe otherwise is ignorant or stupid or...

I actually don't know what it is that they're meant to be missing.

Let me give you an example.

Thomas Potasik, he wrote a piece called My AI Skeptic Friends Are All Nuts, and it was catniped for boosters, a software engineer using technical terms like interact with Git and MCP, vague charts, and of course an extremely vague statement that says hallucinations aren't a problem.

And I quote.

Now I'm sure there are still environments where hallucination matters, but hallucination is the first thing developers bring up when somebody suggests using LLMs despite it being more or less a solved problem.

Is it?

Anyway, my favorite, favorite part though, let me quote this.

A lot of LLM skepticism probably isn't really about LLMs, it's projection.

People say LLMs can't code when what they really mean is LLMs can't write Rust, which by the way is a coding language.

Fair enough.

But people select languages in part based on how well LLMs work with them.

So Rust people should get on that.

What?

Nobody projects more than an AI booster.

They thrive on the sense that they're oppressed and villainized after years of seemingly every other, every goddamn outlet on earth claiming they're right, regardless of whether there's any proof.

They sneer and jeer and cry constantly, the people not showing adequate amounts of awe when an AI lab says, we did something in private, we can't share it with you, but it's so cool.

And constantly act act as if they're victims as they spread outright misinformation, either through getting things wrong or never really caring enough to check if they're right.

Also, none of the booster arguments actually survive a thorough response, as Nick Suresh proved with his hilarious and brutal takedown of Patasek's piece.

Suresh is a great guy, he's been on the show before, and I've linked to his piece in the show notes, and I'm going to bring him back on.

He's written for my newsletter as well.

Absolute legend.

Now, there are, I believe, some people who truly do love using LLMs, yet they are not the ones defending them.

Patasek's piece drips with condescension, to the point that I feel like he's trying to convince himself how good LLMs are, because boosters are eternal victims.

He wrote them a piece that they could send around to skeptics saying, yeah, see, without being able to explain why it was such a brutal takedown, mostly because they can't express why other than, well, this guy gets it.

One cannot be a big smart genius that understands the glory and power of AI while also acting like a scared little puppy every time somebody tells them it sucks.

You know what?

This is a great place to start.

This is a great place to get into how to deal with AI boosters because AI boosters love being victims and you should not play into it.

When you speak to an AI booster, you may get the instinct to shake them vigorously or respond to their post by saying to do something with your something or that they're stupid.

I understand the temptation, but you want to keep a level head here.

Keep your head on the swivel.

They thrive on this victimization.

I'm sorry if you're an AI booster and this makes you feel bad.

Please reflect on your work and how many times you've referred to somebody who didn't understand AI in a manner that suggested that they were ignorant or tried to gaslight them by saying AI was powerful while providing no actionable ways of proving this or proof or just being able to point at it being powerful.

You cannot and should not allow these people to act as if they're being victimized or othered.

Throughout this series, I'm going to address a very specific thing.

I'm going to use a term, booster quip.

This refers to the things that they say and how often you hear them.

These are lines that you'll hear them say again and again and again and again.

They're common arguments, common cliches that demand a response.

And let's start with our first booster quip.

You're just being a hater for attention.

Contrarians just do it for clicks and headlines.

First and foremost, there are boosters at pretty much every major think tank, government agency, and media out there.

It's extremely lucrative being an AI booster.

You're showered with panel invites, access to executives, and you're able to get headlines by saying how scared you are of the computer.

And it's really easy to do so.

Being a booster is easy and I must be clear when I say booster it doesn't always have to mean overt.

It could just mean the things you choose not to do.

It could mean the things you choose not to criticize them for or the things you just write down that they say.

But really we're talking about the worst of them.

But this, if you hear that sentence and you don't think you're a booster, you can be a booster by the way if you just choose not to criticize them.

But we're talking about the real arsholes.

Being a critic requires you to constantly have to explain explain yourself in a way that boosters never have to.

Now, if a booster says this to you, if they say you're just being a hater for attention, you're just doing this for clicks, ask them to explain, first of all, what they mean by clicks or attention and how they think you are monetizing it, how this differs in its success from, say, anybody who interviews and quotes Sam Altman or Dario Wario Amadei or whomever from Anthropic on Hard Fork.

Ask them what the difference is.

And ask them why do they believe your intentions as a critic are somehow malevolent, as opposed to those literally reporting what the rich and powerful want them to.

There's no answer here because this is not a coherent point of view.

Boosters are more successful, get more perks, and are in general treated better than any critic at pretty much every major out there.

Fundamentally, these people exist in the land of the vague, and they don't like it when you force them to get specific.

They will drag you toward what's just on the horizon, but never quite define what the thing that dazzles you so much will be, or when it will arrive.

Really, their argument comes down to one thought.

You must must get on board now because at some point it will be so good you'll feel so stupid for not believing something that kind of sucks wouldn't be really good.

And if this line sounds familiar it's because you've heard it a million times before, most notably with cryptocurrency, NFTs, metaverse, clubhouse.

Tons of movements actually.

They will make you define what would impress you which is not your job in the same way finding a use case for them isn't your job.

In fact, you're the customer.

You're the consumer.

You are the person AI needs to prove itself to, not the other way around.

But let's go to another booster quip.

When they go,

you just don't get it.

Here's a great place to start.

Say, that's a really weird thing to say.

It is peculiar to suggest that somebody that doesn't get how to use a product is weird and that we as the consumer, as the customer, must justify ourselves to our own purchases.

No, no, no, no.

If I don't get it, it's the booster's job to tell me why.

Make them justify their attitude.

Just like any product, we buy software to serve a need.

This is meant to be artificial intelligence.

Why is it so fucking stupid that I have to work out why it's useful?

The answer is, of course, that it has no intellect, it is not intelligent, and large language models are being pushed up a mountain by a cadre of people who are either easily impressed or invested, either emotionally or financially, in its success due to the company they keep or their intentions for the world.

And if a booster suggests you just don't get it, ask them to explain the following.

What am I missing?

What specifically is it that is so life-changing about this product based on your own experience, not on any anecdotes from other people?

Because they will say, well, I heard of a guy who wrote 10 billion lines of code.

And then the baby looked at me and I cried.

They don't have real things themselves, so...

Cut off the exits, bought up the doors.

And then also ask them what use cases are truly transformative about AI.

Don't let them say, well, I heard in an industry.

Actually make them prove themselves.

Their use cases will likely be that AI has replaced search for them, that they use it for brainstorming or journaling, proofreading an article, or looking through a big pile of their notes or some other corpus of information, and summarizing it, or pulling out insights.

Who gives a shit?

Sorry, not to be too acerbic, but really, who fucking cares?

That shit's so boring.

Hundreds of billions of dollars of wasted investment on this.

And this is what we've got three years in?

Fucking Humpty Dumpty could never have it this good.

Anyway, our next booster quip is one of my faves.

AI is powerful and getting exponentially more powerful.

Now if a booster ever refers to AI being powerful and getting more powerful, ask them the following.

What does powerful mean?

In the event that they mention benchmarks, ask them how those benchmarks apply to real-world scenarios.

If they bring up SWE Bench, the standard benchmark for coding, ask them if they can code and if they cannot, ask them for another example.

I mean, they will tell you that they've spoken with coders.

I've talked with a lot of coders.

I have a great one with Colt Voge coming up, another software engineer talking about LLMs.

It's so funny.

It's so funny when you actually lay this stuff out, how weak their arguments are.

But in the event they mention reasoning, ask them to define it.

Once they've defined reasoning, ask them to explain in plain English what reasoning allows you to do on a use case level, not just how it works.

They will likely bring up the gold medal performance that OpenAI's model got on the Math Olympiad.

Ask them why OpenAI hasn't released that model.

Then ask them what the actual practical use cases that this success has opened up.

They will say it's an innovation, you've got to be patient, and then pepper spray them.

Nope, don't, don't pepper spray anyone.

Anyway, you should also then ask them what use cases have arrived as a result of models becoming more powerful.

If they say vague things like, oh, in coding and oh, in medicine, ask them to get specific.

And then ask them what new products have arrived as a result.

If they say coding LLMs, they will likely add that this is replacing coders.

Ask them where that has happened and ask them to show you proof, links.

And it will not be sufficient to say that a CEO mentioned that they did something with AI inefficiency.

Get numbers.

They just won't.

They won't do this.

They will turn into a pillar of salt.

And we've got two more fucking parts of this.

I mean, you're going to have a ball with this.

Look, the core of the AI boosters argument is that they need to make you feel bad.

They like to gaslight.

And

you need to refuse to let them.

You need to push back heavily.

If there's ever a point where you feel like they are trying to make you feel stupid, ask them why they're doing so.

And to be clear, anyone with a compelling argument doesn't have to make you feel bad to convince you.

The iPhone didn't need a spurious hype cycle of proof, of people saying, you must look at this.

It is so important.

When it didn't really work, it worked immediately.

Now, I said in my news that it didn't need a fucking marketing campaign.

Yes, there was marketing dollars behind the iPhone, Eric, newcomer.

come at me with better work mate respond to the rest of this but we all kind of got it with the iphone in fact the moment steve jobs announced it piece of shit that he was he was he said here's the phone here's an ipod here's a here's email you could do all these on one device and everyone oh yeah that is good

you that is really obvious that that was good it was impressive because it was impressive and boosters will suggest you are intentional or in not liking ai because you're a hater or a cynic or a luddite they'll suggest that you're ignorant for not being amazed by ChatGPT.

Let me tell you something.

You don't have to be impressed by anything by default and any product, especially software, designed to make you feel stupid for not getting it, is poorly designed.

Chat GPT is the ultimate form of Silicon Valley sociopathy.

You must do the work to find the use cases and thank them for giving you the chance to do so.

AI is not even good, reliable software.

It resembles the death of the art of technology, inconsistent and unreliable by definition, inefficient by design, financially ruinous, and adds to the cognitive load of the user by requiring them to be ever-vigilant of the shit-ass outputs that can come out of him.

So here's a really easy way to deal with this.

If a booster ever suggests you are stupid or ignorant, ask them why it's necessary to demean you to get their point across.

Even if you are unable to argue on a technical level, make them explain why the software itself can't convince you.

And be vigilant.

Boosters seldom live in reality and will do everything they can to pull you off course.

And I should add that there there is a fair criticism here.

I do insult people, I do demean them, I call them babies and I do funny voices, and I do that because I don't respect them.

I'm not, I

am here to tell you how I feel.

I will convince you through the large amounts of work I do and the research I have.

I don't, if you disagree with me, you disagree with me, yeah?

It's fine.

And yeah, these people do sound kind of silly.

I'll get you a Casey Newton thing in a couple of episodes, I think.

Really, it's impossible to call them otherwise.

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Look, if you say that none of these companies make money, they'll say it's in the early days.

If you say AI companies burn billions, they'll say the cost of inference is coming down.

If you say the industry is massively overbuilding, they'll say that this is actually just like the dot-com boom and that the infrastructure will be picked up and used in the future.

If you say there are no real use cases, they'll say Chat GPT has 700 million weekly users.

Every single time, there's the same goddamn arguments.

Which is why, from here on out, I'm going to give you the responses to all of them.

And there's an article version you could print up and stuff it in there.

No, no, no.

No, no violence, everyone.

Be nice.

But you're going to be able to use these arguments going forward.

And let's start with my favorite booster quip.

AI will.

Anytime an AI booster says AI will, tell them to stop.

Tell them to stop and explain what AI can do now.

And if they insist, ask them both when they expect things to happen in the way they're talking about.

And if they say very soon, ask them them to be more specific.

Get them to agree to a date and then call them on that day, or show up at their house.

Hell, you could be waiting inside when they get there, assuming you have a key legally.

Now, here's another one, another booster grip.

They will say agents will automate large parts of our economy, and I will say fucking stop.

There's that will bullshit again.

There's that will, will, will, will.

Agents don't work, they don't work at all.

The term agent means, to quote Max Wolff, a workflow where the LLM can make its own decisions, such as in in the case of web search, where the LLM is told you can search the web if you need to, then can output, I should search the web and search the web.

Yet, agent has now become a mythical creature that means totally autonomous AI that can do an entire job.

If anyone tells you agents are dot dot dot, you should ask them to point to one.

If they say coding, please demand that they explain how autonomous these things are.

And if they say they can refactor entire code bases, ask them what that means and also laugh at them because they will not know.

Ask them to explain how Salesforce's own research shows that agents only have a 58% success rate on single-step tasks.

That's you ask it to do one thing and 35% on multi-step tasks.

And what's crazy as well, and I won't have this in the episode notes, you're just gonna have to look it up.

There is a story that just came out about OpenAI's projections.

They reduced the amount of money they're making over the next few years in agents down $26 billion less.

They just removed that part.

Do you think agents exist now?

Agents are not autonomous.

They do not replace jobs.

They cannot replace coders.

They are not going to do so

because probabilistic models are a horrible means of taking precise actions.

And almost anyone who brings up agents as a booster is either misinformed or in the business of misinformation.

Now here's another booster grip for you.

What I mean is that AI is like the early days of the internet.

Now in many cases, I think they're referring to AI

as being early as a reference to those early days and they never really refer to what that means, because the early days of the internet can refer to just about anything.

Are we talking about dial-up, DSL?

Are we talking about the pre-platform days when people accessed it?

The internet via copy server AOL?

Yes, yes, I remember the article from Newsweek.

I already explained it in my newsletter reality check.

I'm going to quote myself about this fucking article where the guy said the internet wouldn't take off.

In any case, one guy said saying that the internet won't be big doesn't mean a fucking thing about generative AI, and you're a simpleton if you think it does.

One guy being wrong in some way is not a response to my work, and I will crush you like a bug.

Again, I'm using ad hominin attacks.

Who cares?

These fucking people are rude as hell.

Now, if your argument is that the early internet required expensive Sun Microsystem servers to run, Jim Covello of Goldman Sachs addressed that in June 2024 by saying that

the costs paled in comparison, adding that we also didn't need to expand our fucking power grid to build the early web.

Well, sir, there's another booster grip.

Sir, actually people said smartphones wouldn't be big.

This is a straight-up lie, by the way.

I've heard this a good amount.

I've heard at least five people say, yeah, well, people didn't think the iPhone would be big.

The iPhone wasn't going to be big, actually.

This is a lie.

It's a lie.

It's a lie.

You're lying.

Also, as Jim Covello from Godman Snext noted, there were hundreds of presentations in the early 2000s that included roadmaps that accurately fit how smartphones rolled out, and that no such roadmap exists for generative AI.

The iPhone was also an immediate success as a thing that people paid for, with Apple selling 4 million units in the space of 6 months, and this was on an exclusive contract for several years, I think, with Singular Wireless, now called ATT.

Hell, in 2006, since the year before the iPhone launched, there were smartphones, and there was an estimated 7.7 million worldwide smartphone shipments, mostly from Blackberry, Windows Mobile, and Palm.

Though to be generous to the generative AI boosters, I'm going to disregard those because they actually help prove my point more.

And I just want to be clear that the early days of the internet are not a sensible comparison to generative AI.

The original attentional is all you need paper, the one that kicked off the transformer-based large language model era, was published in June 2017.

Chat GPT launched in November 2022.

It's not early.

We're not early anymore.

We haven't been for a while.

But nevertheless, if we're saying early days here, we should actually define what that means.

As I mentioned previously, people paid for the iPhone immediately, despite it being a device that was completely and utterly new on one specific carrier.

While there was a small group of of consumers that might have used similar devices, like the Compaq iPac, it's kind of a cool device.

The iPhone was a completely new kind of computing, sold at a premium, requiring you to have a contract with that specific carrier.

Conversely, Chat GPT's annualized revenue in December 2023 was $1.6 billion, so about $133 million in that month, for a product that had by that time raised over $10 billion.

And while we don't know what OpenAI lost in 2023, reports suggest it burned over $5 billion in 2024.

Big tech has spent over $500 billion in capital expenditures in the last 18 months, and all told, between investments of cloud credits and infrastructure, will likely sink over $600 billion by the year's end.

The early days of the internet were defined not by its lack of investment or attention, but by its obscurity.

Even in 2000, around the time of the dot-com bubble, only 52% of US adults used the internet, and it would take another 19 years for 90% of US adults to do so.

These early days were also defined by its early functionality.

The internet would become so much more because of the things that hyperconnectivity allowed us to do.

And both faster internet connections and the ability to host software in the cloud would change everything.

We could define what better would mean and make reasonable predictions about what people could do on a better internet.

Yet even in those early days, it was obvious why you were using the internet and how it might grow from there.

One did not have to struggle to explain why buying a book online might be useful or quicker than a shop, or why a website might make a quicker reference than having to go to a library, or why downloading a game or a song might be a good idea.

While habits might have needed adjusting, it was blatantly obvious what the value of the early internet was.

It's also unclear when the early days of the internet ended.

Only 44% of US adults had access to broadband internet in 2006.

Were those the early days of the internet?

The answer is no, and that this point is brought up by people with a poor grasp of history and a flimsy attachment to reality.

The early days of the internet were very, very, very different to to any associated tech boom since, and we need to stop making the comparison.

The internet also grew in a vastly different information ecosystem.

Generative AI has had the benefit of mass media driven by the internet, along with social media and social pressure to adopt AI for multiple years.

And now our last boost equip for the episode.

Um, um actually, I meant something else.

What I mean is that we're in the early days of AI.

All of the other things you said were very misleading.

You misread my statements somehow.

We are not in the early days of generative AI and anyone using this argument is either ignorant or intentionally deceptive.

According to Pew, as of mid-2025, 34% of US adults have used ChatGPT, with 79% saying they had at least heard of it.

And a little about it even.

Furthermore, ChatGPT has always had a free version.

On top of that, a study from May 2023 found that over 10,900 news headlines mentioned ChatGPT between November 2022 and March 2023.

And a BrandWatch report found that in the first five months of its release, ChatGPT received over 9.2 million mentions on social media.

Nearly 80% of people have heard of ChatGPT and over a quarter of Americans have used it.

If we're defining the early days based on consumer exposure, that ship has sailed.

If we're defining the early days by the passage of time, it's been eight years since attention is all you need and three since ChatGPT came out.

While three years might not seem like a lot of time, the whole foundation of an early days argument is that in the early days things do not receive the venture funding, research, attention, infrastructural support or business interest necessary to make them big.

In 2024, nearly 33% of all global venture funding went to artificial intelligence, and according to the information, AI startups have raised over $40 billion in 2025 alone, with Statista adding that AI absorbed 71% of VC funding in the first quarter of 2025.

These numbers also fail to account the massive infrastructure costs that companies like OpenAI and Anthropic don't have to pay for.

The limitations of the early internet were twofold.

The fiber optic cable boom that led to the fiber optic bubble bursting when telecommunications companies massively overinvested in infrastructure, which I will get to shortly.

There was also the lack of scalable cloud infrastructure to allow distinct apps to be run online, a problem solved by Amazon Web Services, among others.

In Generative AI's case, Microsoft, Google, and Amazon have built the fiber optic cables for large language models.

OpenAI and Anthropic have everything they need.

They have, even if they say otherwise, plenty of compute, access to the literal greatest minds in the field, the constant attention of the media and global governments, and effectively no regulations or restrictions stopping them from training their models in the works of millions of people or destroying our environment.

They've already had this support too.

OpenAI was allowed to burn half a billion dollars on a single training run for GPT 4.5 and 5, and they did multiple runs.

If anything, the massive amounts of capital have allowed us to massively condense the time in which a bubble goes from possible to bursting and washing out a bunch of people, because the tech industry is such a powerful follower culture that only one or two unique ideas can exist at one time, and I think those ideas are currently open AI and anthropic.

The early days argument hinges on obscurity and limited resources, something that generative AI does not get to whine about.

Companies that make effectively no revenue can raise $500 million to do the same AI coding bullshit that everybody else does.

In simpler terms, these companies are flush with cash, have all the attention and investment they could possibly need, after all, attention is all you need,

and are still unable to create a product with a defined, meaningful, mass market use case, let alone one that doesn't burn money.

In fact, I believe that thanks to effectively infinite resources, we've speedrun the entire large language model era, and we're nearing the end.

These companies got what they wanted.

And I think I want to die in Minecraft, obviously, but I must press on.

I must.

Just saying all these things out loud, you really get a sense for how illogical these people are and how much bullshit is going around to try and push back against skeptics.

But it's not going to work.

It's not going to work.

I hope you're not tired of me talking about boost equips and doing silly voices as you've got two more of these fucking episodes coming, and I love recording them.

I really do.

They say recording?

Jesus Christ.

My friends, we're in hell, but we're together in hell, and that's fun.

And there's a lot more bullshit to break down.

Speak to you tomorrow

Thank you for listening to Better Offline the editor and composer of the better offline theme song is Matosowski You can check out more of his music and audio projects at matosowski.com m-a-t-t-o-s-o w-s-k-i.com You can email me at easy at betteroffline.com or visit betteroffline.com to find more podcast links and of course my newsletter.

I also really recommend you go to chat.where's your ed.at to visit the Discord and go to r/slash betteroffline to check out our Reddit.

Thank you so much for listening.

Better Offline is a production of CoolZone Media.

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