Monologue: Tokenpocalypse Now

Summary

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Better Offline: Monologue – "Tokenpocalypse Now"

Host: Ed Zitron
Date: June 26, 2026
Episode Theme:
A sharp, satirical dive into the chaotic economics behind AI models and the cracks emerging in the industry. Zitron dissects how enterprises are dealing with soaring AI costs, the rise of open source models, and the underlying "cargo cult" mentality among tech leaders gambling billions on ill-defined AI futures.

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Episode Overview

Ed Zitron uses this solo monologue to unpack the shifting economic realities of generative AI deployment across the tech industry. He highlights the contradictions, poor planning, and mounting financial pressure as expensive proprietary AI meets enterprise cost controls and competition from cheap open-source models. Throughout, he skewers the credulous optimism (“cargo cult”) of tech executives, predicting an imminent burst in the AI hype bubble and a resulting shakeout.

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Key Discussion Points & Insights

1. The AI Bubble: Fraying at the Edges

• Atmosphere of Uncertainty: Zitron notes the recent "little spurts of air coming out of the AI bubble" but observes, “It's unclear when it'll burst, what will burst it really, even what's going on. Half the time they just all seem to be running around like a billion Mr. Beans.” (03:02)
• Catalyst Events Loom: The AI boom could collapse rapidly if a major company fails, funding dries up, or hyperscale cloud providers (Amazon, Google, Microsoft) rein in capital expenditures.
• Satya Nadella’s Changing Tune: Zitron mocks Microsoft CEO Nadella for publicly warning against reliance on a single lab, despite being “rock hard for OpenAI and...Anthropic” just months ago. “It's almost as if he's just doing random shit based on what he thinks might work. You know, like a fucking cargo cult.” (04:09)

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2. Tokens, Costs, and the Enterprise Reality Check

• The Token Economy Explained: Recent shifts by OpenAI and Anthropic force large enterprise customers to pay by-the-token, ending an era of “burn[ing] $8,000 worth of tokens a month on Claude and $14,000 a month on OpenAI’s ChatGPT…for 200 bucks a month.” (05:03)
• Sudden Spending Limits: With real costs now hitting, companies like T-Mobile, Brex, Uber, Meta, Walmart, Coinbase, and Cisco introduce strict usage caps. Meta reportedly even had a “token maxing leaderboard.” (05:38)
• No One Has a Plan: “None of these companies have a plan. Nobody integrating AI has a plan. If they did, they would have been like, yeah, let's make sure we know how much this is going to cost... but they don't.” (05:56)
• Hilarious Use-Cases: Accenture, per leaked audio, saw “soaring token spend” largely driven by non-engineers converting PDFs to slides—tasks that could be outsourced cheaply, further highlighting waste. (06:25)
• The Pain is New: Now just three months in, “they're already screeching like they're pecked to death by birds.” (07:03)

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3. The Rise of Open Source (and China’s Influence)

• GLM 5.2 Challenges the Leaders: Zhipu’s GLM 5.2 coding model is “competitive with Anthropic’s Opus 4.8 at somewhere between a quarter and a sixth the price.” (07:24)
• Practical Performance: In real benchmarks, GLM 5.2 sometimes uses more tokens and takes longer, but may deliver better results (e.g., “cleaned up dead code and verified the build compiled before completing—something Opus...didn’t bother to do”). (08:15)
• Open Weights Advantage: GLM 5.2’s unrestricted MIT License allows any company or individual to freely use, self-host, or fine-tune the model—making it uniquely disruptive. (09:01)
• Brand Loyalty Persists: Despite open source promise, most enterprises “like name brands” (OpenAI, Anthropic), even if “Anthropic shit is constantly broken.” (09:43)
• Potential Industry Shakeup: The real competitive threat comes if “Microsoft, Amazon or Google offer GLM 5.2 via their [AI platforms],” potentially catalyzing an exodus from expensive closed models. (10:04)
• Ed Zitron’s Prediction: “Now does feel like the perfect time for a shift towards open source models, if only because everyone is crapping themselves about cost.” (10:25)

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4. Economics of AI Infrastructure & The Cloud

• Shift to On-Premises Hardware: Zitron argues that the economics of running large AI models in the cloud are fundamentally unworkable. “The underlying economics of cloud based GPU compute do not make sense for anybody.” (15:46)
• Predicts Local AI as the Endgame: The future of LLMs may be “locally run models on expensive specialist hardware,” much as Nvidia is now selling expensive machines for in-house deployment. (16:14; 16:27)
• Industry-Wide Unprofitability: Even with cheaper models, the costs are still “hundreds of thousands or millions of dollars a month.” (17:35) Nobody is profitable, even startups like Base10 or Chinese providers like Zhipu: “Other than that we’re super profitable... Yeah, it’s a really fucking stupid industry.” (17:24)

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5. The “Cargo Cult” of AI, Herd Mentality, & Twitter Hysteria

• Executives Clueless, Following Fads: “A great deal of AI usage is cargo cult shit driven by executives that don't do any work and people that feel pressured into adopting AI by their peers or the media.” (21:15)
• Peer Pressure & Algorithmic Madness: Zitron lampoons the panicked online culture—“I call it the Dunces Casino…you just crank the thing and a bunch of insane people come out.” (21:18)
• AI as Mass Market Panacea: Instead of being a specialist, risk-versus-reward software tool, it’s been massively oversold for “basically any problem.” (21:02)
• Classic Twitter Rant Example: “If you don't use agents, you're going to die, they're going to kill your wife, they're going to eat your dog.” (21:32)

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6. Structural Problems & Missed Opportunities

• Leaders Have Unlimited Resources, But No Vision: “They could do anything. And they choose to do this...remember that this is what they chose to do.” (30:40, 30:46)
• Real Problems Ignored: Tech giants could fix their own platforms (“make Facebook better...Microsoft Teams stable…Google Search could work again”) but do not, since it would “make the growth go down.” (31:06, 31:20)
• Too Late for a Pivot: By the time they realize the error, “they'll realize that they've pissed away the only opportunity they really had to change direction.” (31:27)
• Bubble Will Burst: “Gravity exists and this era will come to an end.” (32:04)

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Notable Quotes and Memorable Moments

• "It's almost as if he's just doing random shit based on what he thinks might work. You know, like a fucking cargo cult." — Ed Zitron on Microsoft/Satya Nadella (04:09)
• "None of these companies have a plan. Nobody integrating AI has a plan. If they did, they would have been like, yeah, let's make sure we know how much this is going to cost... but they don't." (05:56)
• "Now just three months into enterprises paying the actual cost of AI and they're already screeching like they're pecked to death by birds." (07:03)
• "People generally like name brands and even though anthropic shit is constantly broken." (09:43)
• "The underlying economics of cloud based GPU compute do not make sense for anybody." (15:46)
• "This is just a guess they would ever think about that. But I think it’s possible. I think it’s really the only economically viable end for this. Unless there are just going to be companies that lose billions of dollars a year for no apparent reason." (18:27)
• "A great deal of AI usage is cargo cult shit driven by executives that don't do any work..." (21:15)
• "Twitter is driving people insane using AI, but not because of Grok or anything, but because it just fire hoses nutters into your feed..." (21:46)
• "This is the intentional choice of Google, Microsoft, Meta and Amazon. They could have done anything else. Anything." (30:49)

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Timestamps for Important Segments

• [02:44] – Ed Zitron introduction and theme setup
• [03:02] – Observations on the unpredictable AI bubble and tech leader behavior
• [04:09] – Mocking Satya Nadella’s shifting alliances and lack of vision
• [04:26] – Transition from all-you-can-use enterprise AI to per-token billing
• [05:29] – Real companies begin capping employee AI spending (“tokenpocalypse now”)
• [06:25] – Leaked stories of waste at Accenture, with AI used for menial tasks
• [07:17] – Early industry pain, companies “screeching like they’re pecked to death by birds”
• [07:24] – The rise and benchmarking of Zhipu’s open-source GLM 5.2 model
• [08:15] – Open source model beats expensive competitor in real-world metric
• [09:01] – The significance of truly "open weights" models
• [10:25] – Zitron’s prediction: Shift towards open source and cost controls
• [15:46] – Economics of AI: cloud GPU vs. on-premises hardware
• [17:24] – “It’s a really fucking stupid industry”: everyone loses money
• [21:15] – Explaining the “cargo cult” mentality of AI adoption
• [30:46] – Leaders could fix real problems, but growth obsession overrides logic
• [32:04] – The conclusion: Gravity exists; the era will soon end

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Tone, Language, and Style

Ed Zitron delivers this episode in his hallmark acerbic, sarcastic British style—a blend of deeply informed tech insight, exasperation, and dark humor. He peppers in pop culture allusions (“Mr. Beans”, “Tim and Eric”, “Dunces Casino”), curses liberally, and frequently mocks the absurdities and herd behavior of tech executives.

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Summary & Takeaways

“Tokenpocalypse Now” captures a pivotal moment in the commercial AI saga, where the mismatch between hype, economics, and reality is impossible to ignore—even for top tech companies. Zitron argues that the AI industry is dominated by leaders improvising at scale, burning billions without clear direction, vulnerable to smarter, cheaper open-source challengers, and inevitably heading toward a deflationary reckoning. The episode balances critical analysis, humor, and listener engagement, including candid feedback on the feedback he gets—inviting more, as long as it's not about the “surveillance” conspiracy.

End Note:
Next week, Zitron promises an episode focusing on polymarket influencer marketing—a departure from AI, but no less weird.

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For listeners old and new, this episode is an incisive, unfiltered roadmap to the perils—and unintentional comedy—of tech’s current AI addiction.

Transcript

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[Ed Zitron]

Call zone Media. Hello and welcome to the second of this week's Better Offline Monologues.

I'm your host, Ed Zitron.

Better Offline it's been a funny few weeks watching the little spurts of air

coming out of the AI bubble.

It's unclear when it'll burst, what will burst it really, even what's going on.

Half the time they just all seem to be running around like a billion Mr.

Beans. But I get the sense that everything will accelerate dramatically based on one or

two big events, things that just knock the confidence of everyone.

Maybe it's an AI company dying, or a funding ground not coming together. Or maybe it's a hyperscaler cut. In Capex, Goldman Sachs analyst Rich Piratovsky said last week that he believed that everybody was spending simply to remain competitive.

Fucking love that, don't you?

And added that the first hyperscaler to signal that it can slow the pace of spending would likely see its share price rewarded. If I had to bet. I think it's between Meta and Microsoft, the latter of which has made numerous noises about using cheaper AI models like

DeepSeek and its Copilot cowork product.

Yeah, and also I should add that Satya Nadella keeps doing interviews where he's

like, yeah, no one company should have all that.

We shouldn't rely on one lab.

One lab being able to be shut down at any time is bad. We can't.

It's really funny watching this guy change

his tune, considering how a year and

a half ago, a year ago he

was rock hard for OpenAI and six months after that rock harder for Anthropic.

It's almost as if he's just doing random shit based on what he thinks might work. You know, like a fucking cargo cult. Anyway, as I've mentioned, over the last few months, both Anthropic and OpenAI both started to charge their enterprise customers, companies with over 150 users, for the actual cost of their AI token spend as

of the middle of Q1 2026.

To explain, when you use a regular

ChatGPT or Claude account, you burn tokens. Each one about 3/4 of a word,

up to a 5 hour or weekly

limit depending on what kind of model you're using. So with Anthropic on their Claude subscription, Opus 4.8 and Fable when it was around, had a specific limit to themselves.

But anyway, just the more powerful the

model, powerful being meshed by the companies, of course, the more it burns and the less you can use it on

a regular subscription, you're able to burn. And I am not kidding. $8,000 worth of tokens a month on Claude and $14,000 a month on OpenAI's

ChatGPT codec subscription, all for 200 bucks a month.

Pretty, pretty good deal, right? You know, it's like the discount prices

sketch from Tim and Eric that I

reference every so often just to see

if anyone emails me.

And so yeah, after years of being able to burn thousands of dollars of tokens for $200 a month, enterprises are suddenly having to pay the actual costs. The result is multiple companies capping their workers token spend.

As I've reported, both T Mobile and

Brex have done so and others have

reported that Uber, Meta, Walmart, Coinbase and Cisco have all done so. Meta notably had a token maxing leaderboard.

Very funny. Again, just changing direction based on random signals. None of these people have a plan. None of them. None of these companies have a plan. Nobody integrating AI has a plan. If they did, they would have been like, yeah, let's make sure we know how much this is going to cost. Or let's make sure we know whether

this is good or not.

Whether we can measure the roi, you know, anything that would suggest anyone knew what the hell they're doing, but they don't. And 404Media reports that management consultancy firm and evil corporation Accenture, which is an insane way of saying that and I'm just going to keep. Has seen what it cause. Soaring token spend based on leaked audio recordings with with much of that token spend being driven by non engineers doing

things like converting PDFs into presentation slides.

I love this shit. This is the easiest stuff in the

world, made slightly easier, but probably worse, costing way more.

You could definitely hire an extra, but you could just hire a contractor to do this. You could hire a bloke at 45

bucks an hour to do that for you.

He'd be the happiest man alive. Probably cost you less too. I know.

God, this stuff is exhausting.

You ever sit and wonder what you

could do with the rest of that money?

I could have, I don't know, like what? Like millions of dollars a month. I could have like a week's worth of Diet Coke. Anyway, it turns out that telling your workers that AI can do basically anything

and to use it as much as

possible starts costing you a lot of money when you actually pay what it costs. As I've said before, we're barely three months into enterprises paying the actual cost of AI and they're already screeching like they're pecked to death by birds. And that joke is courtesy of Keisuke,

who said that to me about a

year ago when we talked about the

amount of money that Anthropic was allowing people to burn on Claude subscriptions.

Meanwhile, the threat of open source models appears to be getting more serious. I've heard from numerous sources that Chinese AI lab Zhipu's GLM 5.2 coding model is competitive with Anthropic's Opus 4.8 at somewhere between a quarter and a sixth the price, but that seems to vary

based on the cost of the task.

As far as whether GLM 5.2 is actually competitive goes, it appears that the hype is somewhat real, but you kind of had to check your sourcing open source AI coding company Klein ran benchmarks on a natural bug from its repo and found that while GLM used twice as many tokens to fix it, it also did so at a cheaper cost

41 cents versus Opus 4.8's 81 cents. Opus was quicker, taking 1.6 minutes versus GLM's 4.7 minutes.

But one thing that stood out was that GLM, to quote Klein, cleaned up dead code and verified the build compiled

before completing something that Opus, the more expensive Frontier model run by the company

that loses billions of dollars, apparently didn't bother to do. It's just one bug, but GLM 5.2 seems to score well on many of the major benchmarks, coming third on cybersecurity firm Semgrep's cyber benchmarks, with the top two being Semgrep's own harness.

So their own thing that they put

on top of the models running Opus 4.8 and GPT 5.5, followed by GLM 5.2, which is interesting. It's very interesting. If I if I was glammy Sam Albin, I'd be looking at this and getting a little worried. I'd genuinely be looking at them and even saying huh, why don't I train my own? But you know, that might actually be a bad idea, even though it's fully possible, because GLM 5.2 is a true open weights model and it's released under

something called the Unrestricted MIT License, which means you can anyone by the way, company, a regular person, whomever can self host and fine tune it or use

it in any way they wish. And yeah, I mean in theory any company that wants to use LLMs could

either run their own version of it locally, albeit on a rig that costs

tens of thousands of dollars, or pay

an inference provider like base 10 to spin up and train their own version.

Now I must be clear that there's not a ton of evidence that running

GLM 5.2 is profitable for the inference provider. In fact, there's really not.

I genuinely have looked Nor do we have any significant signs that customers are

moving away en masse from OpenAI and anthropic models.

People generally like name brands and they

even though anthropic shit is constantly broken.

Go look at their stability page, Stability page, uptime page. I don't know what you call that.

Email me if you know what they call that. Or I could just look after this. Going to keep going though.

Nevertheless, people want name brands.

People like paying for a company that ostensibly works on this and keeps it updated.

How true is that? Who knows?

I don't think people are buying LLMs because of particularly sensible reasons anyway.

But what might change things would be Microsoft, Amazon or Google offering GLM 5.2

via their Foundry, Bedrock or Vertex AI platforms.

And even then it's hard to tell if customers are excited about AI or

just paying OpenAI and anthropic to use

buzzy models really isn't clear. We should know by now. All that being said, now does feel

like the perfect time for a shift

towards open source models, if only because

everyone is crapping themselves about cost.

Everyone is really freaking out and I think that this is going to be the time when we start separating the wheat from the chaff.

The people that actually like this stuff

versus the people who just feel good because they're doing AI and they don't know what else to do with their time and they like forcing people to use it.

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[Ed Zitron]

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[Ed Zitron]

OpenRouter's rankings show

a dramatic move away from Frontier labs.

The top 10 most popular models are

all open source, say for opus 4.7

at 6, opus 4.8 at 8 and

sonnet 4.6 at 10, as well as

a mysterious new model called Alpha, which

is currently free to use, which is

probably why it's trending. To be clear, Anthropic's models still dominate

the top models by task across the board, and that's based on the spend on the task.

I hate to give him any credit though, I really don't like doing this, but Scott Galloway recently made the point that China could thrive by AI dumping

high quality open source models into the ecosystem as a means of destabilizing the major model providers.

And I hate to say that's what's happening.

It's like a fucking broken clock, I guess.

Zhipu and Minimax are both partially government

funded by the Chinese government and also

both woefully unprofitable, but neither do so

at the scale of Anthropic or OpenAI.

And while both do the kayfabe discussion

of AGI and autonomous compute and all

that bullshit, they seem far more focused on creating open weight models to compete with them. And just for the differentiation here, open source means you can share some of

it, open weights means you actually can diddle with the model itself.

That's a flattening. Someone's going to email, they're going to

be mad at me.

I don't care.

Sorry, like it gets the point across. All right, just write on the subreddit if you're mad anyway.

In truth, I think the future of LLMs will end up being locally run

models on expensive specialist hardware.

The underlying economics of cloud based GPU

compute do not make sense for anybody.

You need to make sure the GPUs are saturated.

You have to buy in advance, otherwise you won't like, you just won't be able to get the capacity. And if you have less people than you expect, you will lose money for sure. And if you have more people than you expect, you have to get more compute, which means you'll also lose money.

So as long as you can Goldilocks this bullshit, maybe you'll eke out the

world's worst gross margins in history, or you'll just lose money, which is what everyone's doing.

But I think there may be a point at which zpu, Minimax or even American model developers Start focusing more on services driven custom deployments and become boring,

ugly license driven monstrosities like Oracle.

And that's the thing. I've talked to quite a few people

recently and they are all saying the same thing. Even Nvidia is moving into this realm and they're selling these giant hundred grand machines. I think that's kind of interesting.

And like I said, that GPU compute it requires a certain critical mass of customer demand that I don't believe will

exist once the cargo culture of the AI bubble passes.

Because GPU commitments are done a few

years in advance and any drop or

lull kills the margins of even a cheap to run model. Remember base 10?

Just, they're an inference provider. They just raised one and a half billion dollars. They're not profitable. I mean Zepu isn't profitable. And they do the same thing that OpenAI does with their stuff where they

say oh yeah, yeah, our cost of revenue is lower than revenue. However, when you add the sales and

marketing, it's actually, it's actually unprofitable as well. Oh also we lose hundreds of millions of dollars because of training.

Other than that we're super profitable.

Yeah, it's a really fucking stupid industry.

And look, even if GLM 5.2 can

do things at half the cost of

Opus 4.8, that's still half of what in some cases is hundreds of thousands

or millions of dollars a month.

I've heard tell from multiple sources that that hardware demand is growing and that customers at big companies are starting to

look into those high end hardware Sol

and I think that that is the

only future for this stuff and I

think it would reduce the cost significantly

for the end user, probably keep this shit off the Internet or at least massively marginalize the damage that LLM based code can do by focusing on people that actually give enough of a shit to buy the actual machines. And I don't know, I feel like an actual serious fiscal commitment makes companies take things a little bit more seriously. Unless of course you're Microsoft, Google and Amazon and meta buying GPUs at which case who gives a shit.

But I mean if this takes off

it is, it's curtains for Zushia, it's a bad time for OpenAI and Anthropic unless they too start doing these hardware driven things.

This is just a guess. This is just a guess they would ever think about that. But I think it's possible. I think it's really the only economically

viable end for this. Unless there are just going to be companies that lose Billions of dollars a year for no apparent reason.

I just don't think that's going to happen. It's not enough money to do it and God damn. Please go and listen to the OpenAI will not get bailed out AI is not too Big to Fail podcast.

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[Ed Zitron]

I'm tired of getting.

Please don't, please stop emailing me. I love hearing from you. I really, I would love to hear from you all more other than the people who email me saying, I think the GPUs are all for surveillance. I think it's all that. I think it's a big government that's called Oracle. Oracle's first client was the CIA. Oracle has a giant government GPU array. They have several of them. Jesus Christ, that's already happening and they're not doing surveillance on that. They did that with Maven, they did it with the Promise software. Jesus fucking Christ. Sorry, I understand that I sound agitated here. It's just that if the only choice

you can make when looking at something is to say, well, bad thing will

definitely happen, that's not actually an intellectual pursuit. It's just crap on yourself. It's just saying, well, everything's bad, so everything stays bad. I actually want to bring you a message of hope. I don't think these companies get bailed out. I don't think they get anything. I think that they get allowed to die. I think part of their assets might

be scooped up by Amazon, Google and Microsoft. I think the government might take a chunk out of them. Perhaps they get some sort of bridge financing.

But I actually don't know if the government would even extend that because AI

is very unpopular with regular people.

Regular people do not like this and they hate data centers and they have intelligently connected data centers, these horrible AI companies. And so in the end, I tell you, please stop emailing me the surveillance thing. It's not true.

You're wrong.

You sound, you sound like someone that wants to be paranoid but doesn't want

to do the reading well enough to be paranoid. If you want to be paranoid, go read the Promise software, go look at Oracle. Like, go look at the actual history of these companies if you want to be freaked out by something.

But in truth, the AI industry is just a directionless egregore of capital, bumbles

about, and is only kept alive by a belief system that's mostly, mostly growth focused and doesn't really understand how to run a business anymore or even build innovation or technology.

And it's blatantly obvious that LLMs are

at best a classic risk versus reward software tool. Sort of the real sickos that know what they're getting into.

But the problem is it's been sold

as this mass market panacea for basically any problem. And I'll say that my thesis remains undeterred. I believe a great deal of AI usage is cargo cult shit driven by executives that don't do any work and

people that feel pressured into adopting AI

by their peers or the media.

Or of course people that spend 12

to 18 hours a day on Twitter who just follow the algorithm. I call it the Dunces Casino because you just crank the thing and a bunch of insane people come out. And all of these people come out

and they're like, if you don't use agents, you're going to die, they're going to kill your wife, they're going to eat your dog. If you don't use loops, Boris Cherny is going to blow up your house.

Twitter is driving people insane using AI,

but not because of Grok or anything, but because it just fire hoses nutters into your feed who will constantly make you feel terrible for not picking up

the next big AI thing.

It's this insane. It's.

I keep saying cargo cult because that's what it is.

It's people just going around being like,

yeah, you know, this is the big thing now. We all like that, right? We love it, we love it.

It's good. If we all follow this, the great prophecy will come true and then everyone and everyone will make money somewhere, somehow, I think to sickness.

[Kal Penn]

Foreign.

[Ed Zitron]

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[Kal Penn]

Hey everyone, it's Kalpen, host of Earsay, the Audible and iHeart Audiobook Club. This week on the podcast, I'm sitting down with Divergent author Veronica Roth to talk about her sprawling new novel, Seek the Traitor's Son. It's a sci fi fantasy epic about two protagonists on opposite sides of a war and a prophecy neither of them wanted.

[Veronica Roth]

My first book was Divergent, and when that came out, like, because it was so popular, I think it attracted like mostly positivity, but the negativity I sucked in like a sponge. And I think it was like critiques of things I liked when I was like, you know, I was 23 and I wrote this book and it had all my like dorky little cheesy or maybe unrealistic loves in it. And I started to feel a lot of shame about those things. And so for the rest of my career, I steered away from those little things that like, make you feel pleasure when you read. But I also was like, saying no to these parts of myself that I then was like, screw it. Yeah, so that's this book.

[Kal Penn]

Listen to Hearsay, the Audible and iHeart audiobook club on the iHeartradio app or wherever you get your podcasts.

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[Ed Zitron]

Why is it always chaos when we link up?

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[Ed Zitron]

And they got some kick too.

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[Ed Zitron]

It's a genuine sickness.

So I went a little tuck across in there.

What's going on? Why are we using LLMs? What are they going to do to us? What are they going to do to your family? But anyway, back to the podcast, back to the monologue.

I apologize for ad libbing.

I must be clear as well. I do love hearing from you because I keep getting emails from people that

actually use AI and I got one just before I started recording this from a bloke who said, and I quote,

he's used it to deliver good work and seen it, tried to submit absolute crap.

And that really is the AI industry.

Hey, you know, sometime it works and when it does, it's all right, and when it doesn't, it's dog shit.

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Yay.

[Ed Zitron]

Great. I'm so glad we sunk a trillion

plus dollars into this.

Look, these are specialist tools that are being forced to solve generalist problems and they're probabilistic models that fail to do deterministic things. And they're really just an eternal financial black hole for anyone trying to scale

them into a Google search or a meta sized business.

And it's never going to work like that. Just before this as well, I saw

that Broadcom and OpenAI announced their jalapeno chip. This giant dinner place sized motherfucker dinner place, dinner plate. I'm not fixing that.

And it's funny because everyone, everyone's doing

the cargo cult shit around it.

They're all like, oh well, it's going to bring down inference costs. If they did that, that would fix everything. If, if jalapeno fixes everything, then everything will work out. There's no proof that that's the case. Actually here is the thing. If you want, if you want to, like, here's a specific request. If you have an information subscription at some point in the last year, I know there was an information story that

suggested that Broadcom's OpenAI chip would have modest gains.

If you bring that to me, I will fucking, I will Venmo you $5

if you can bring me that story. Seriously, I need that story.

Because I'm pretty sure that if Broadcom's chip was going to change everything for OpenAI, OpenAI would sink every fucking dollar they had into it. OpenAI would dispense with Nvidia instead. It's like, oh yeah, we're getting Microsoft

to pay for some of it and it'll be there in 2027 maybe.

Oh no, sounds like something you pre ordered on Kickstarter and you got it and it kind of sucks.

And it turns out the video was AI generated, which I did just see with this thing where someone had done a Kickstarter where it's, yeah, you can

build things using real principles and you

pour your own cement, but it's really small and the whole thing is AI generated. Fucking hell. This industry really is miserable, isn't it?

All the people. Every other era, other than, of course, crypto and the Metaverse, when something cool happened. Even in the augmented reality era, there were still people doing goofy, funny shit. There were still people doing really interesting things with computer vision. There were people doing interesting things with depth sensing. The fact you can measure stuff on your iPhone, I'm pretty sure you can do on Android too, is because of depth sensing. Cameras and augmented reality. It's cool. The Snap spectacles are embarrassing and if

you get them, I. I assume that they just. That people will just come and beat you up. I mean, it triggers a deep bully instinct. I think in 90% of human beings, you look like Roy Orbison, but so much worse and with so much less talent.

Hell no. This whole era pisses me off. That's the long and short of it.

I think you've probably got that by

this point, and I apologize that I've

been a little all over the place

with this monologue, but it has been a long few months. I've still got plenty of energy, but this has definitely been a tough few. But it's hard to tell what happens next. I know it's hard. I know.

You asked me when it will burst. I truly don't know.

But I'm gonna do my best every week to inform you, keep you up to date, and to try and explain

what the fuck is going on.

Because quite frankly, I don't think most people have any idea. And I think that that's actually the story of the moment. Because when you look around the tech

industry right now, does this strike you as an industry full of leaders or followers? Meta is apparently working on a poly market competitor after releasing some new $300 fucking glasses that only perverts will wear.

What Microsoft a year ago was saying

open source was bad, now it's good. Six months ago, anthropic was good. Now Mustafa Suleiman says they're too expensive and they're going to stop working with them.

This is an industry full of people working things out as they go along. Except the difference between you and them is that they have billions of dollars. Billions and dollars.

Billions and dollars. I'M keeping it billions of dollars and

also all the talent and all the resources and all the ability to raise debt. They could do anything.

And they choose to do this.

Remember that. Even when this era ends, remember that

this is what they chose to do.

This is the intentional choice of Google,

Microsoft, Meta and Amazon.

They could have done anything else. Anything. And there are real problems they could solve. There are problems they could solve with

their own fucking problems that they've caused with their apps.

They could make Facebook better or Instagram

better, except doing so would lower their revenue.

I don't know. Microsoft could redesign the Office suite to work, to actually work to.

They could make Microsoft Teams stable.

Google Search could work again. Again.

It would lower the growth. It would make the growth go down.

And I think by the time these

fuck nuts realize that they have a

real problem, they'll realize that they've pissed away the only opportunity they really had to change direction. Because had they started this era and just been like, we're out of hyper

growth ideas now, they probably wouldn't say it in those exact words.

They could have said, this is the era of experimentation. This is finding our new business lines, the next Google Search and announced it

like some world's fair bullshit.

I don't know, maybe the markets wouldn't have been quite as happy, but they'd be happier than they're going to be

at the end of this era.

And I think in the end it's frustrating to watch because logic and reason

have gone out the window.

But gravity exists and this era will

come to an end.

And next week we've got an awesome interview, something that's not about AI for once, with two writers from the Wall Street Journal about the greasy, nasty, freaky

world of polymarkets influencer marketing involving all sorts of weird shit like ads that include fake bets on fake polymarket websites.

Genuinely weird shit. And that'll be coming up next Wednesday. I enjoy hearing from you. Please email me.

Easy on a Easyetteroffline.com Jesus Christ. I messed up my own email. It's been a long few weeks, folks, but I'm loving hearing from you.

Please email me.

Please jump on the subreddit. I love to hear from you. I love feedback. I love feedback. That's reasonable. If you send me a typo correction, I'm only going to get mad. But I do love hearing from you. Even the typo correctors, even the pedants. I love having the feedback and I love you all.

I love you all. I enjoy hearing from you.

I enjoy being here and speaking to you.

And I'll speak to you next week. Zitron out.

[Kal Penn]

Hey everyone, it's Kalpen. I'm inviting you to join the best sounding book club you've ever heard with my podcast, Hearsay, The Audible and iHeart Audiobook Club. Every episode, I nerd out with amazing guests and dive into the best new audiobooks available on Audible. It's the book club for your ears. Listen to Earsay, the Audible and iHeart Audiobook Club on the iHeartradio app or wherever you get your podcasts running.

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[Ed Zitron]

last night to this drive. Why is it never chill?

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[Ed Zitron]

Nissan builds for that kind of chaos.

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[Ed Zitron]

Yeah, you can tell.

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