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Hello and welcome to Better Offline.

I'm, of course, your host, Ed Zittron.

We're in the third episode of our four-part series where I give you a comprehensive explanation as to the origins of the AI bubble, the mythology, sustaining it, and why it's destined to end really, really badly.

Now, if you're jumping in now, please start from the very beginning. The reason why this is a four-parter, my first ever, is because I want it to be comprehensive and because this is a

very big subject with a lot of moving parts and even more bullshit. A few weeks ago, I published a

premium newsletter that explained how everybody is losing money on generative AI, in part because

the costs of running AI models is increasing, and in part because the software itself doesn't do enough to

warrant the costs associated with running them, which are already subsidised and unprofitable

for the model providers. Outside of OpenAI, and to a lesser extent, anthropic, nobody seems to be

making much revenue, with the most successful company being any sphere,

makers of AI coding tool cursor, which hit $500 million of annualized, so $41.6 million in one month, a few months ago, just before Anthropic and Open AI jacked up the prices for priority

processing on enterprise queries, raising their operating costs as a result.

In any case, that's some piss-poor

revenue for an industry that's meant to be the future of software. Smartwatches are projected

to make $32 billion this year, and as I've mentioned in the past, the Magnificent Seven expect

to make $35 billion or so in revenue from AI this year, and I think in total, when you throw

in core, even all them, It's barely $55 billion in

total. Even Anthropic and Open AI seem a little lethargic, both burning billions of dollars

while making, by my estimates, no more than $2 billion in Anthropics case this year so far,

...