The bottleneck has moved from producing a thing that works to knowing that the thing was the right thing to build. The more of the latter they can take on, the fewer knowledge workers are needed at all. So rather than 5% of every knowledge worker's salary going into tokens, 100% of the knowledge worker's total employment cost goes into tokens and you get a 20x productivity boost as a theoretical minimum across those tasks.

That's the game. There's a view you could take of this that this is just a growing of the pie: with those cost dynamics a lot more "small businesses" get a vast amount of leverage, so the overall economy grows without replacing the knowledge workers. I'm not sure I trust the MBA class to have that view.

I thought Anthropic and OpenAI's combined CapEx has been <100B?

source: https://isaiprofitable.com/

> We're talking about a world where you need 5% of every knowledge workers salary to go into tokens.

They are assuming ~10% global GDP growth instead of ~3%. You probably don't need the same %s if the pie grows a ton.

I'm highly skeptical we get that growth, but if you aren't, it makes it easier to digest.

You are making the assumption that the models are only used / paid for by 2.5% of the population (your knowledge workers value). There will be new value created by these models which people are happy to pay for which simply did not exist at all before. It is also naive to say that the hyperscalers are going to be expecting a return on this in 5 years, it will be entirely propped up by investments / IPOs as has been the case with any tech company for decades now to reach scale. The hyperscalers are currently spending ~650b combined annually, which they have the cash for and can sell in future compute instantly.

Somehow Uber and WeWork survived the same kind of grand projections that they never met.

There is also the EV (expected value) of developing AGI. Even if you personally believe the probability is low within the lifetime of either of these companies, the value would still be extraordinarily high, enough to forgive a $5T or so miscalculation here or there.

YEPPP... and I'm kind of shocked at how many people can't do simple math.

Let's put it context. Google's annual revenue seems to be north of $400B. So if OpenAI suddenly had Google's revenue, it would still be insufficient to recover their investment.

and it's a ticking time bomb because $1T in servers, CPUs, GPUs and memory is going to be worth $200B in 5 years. You can say they can keep using what they've got. Sure. But they're also not going to stop spending on new hardware. And the competitor that comes along in 5 years and spends $1T doing the exact same thing is going to have a huge advantage.

OpenAI at this point reminds me very much of the Russ Henneman pre-money hype cycle.

Source on 200 million knowledge workers worldwide? My understanding is that it's just above 1 billion. I dont think a billion subscriptions at $1000/yr is out of the question but it might take a decade to get roiling

Here is a serious question.. Can we sell into the hype cycle and on the way down with this: https://safebots.ai/costs.html

> $5t to $10t to make back in the next 5 years

Wait what? They spent 2 order of magnitude less on hardware.

> unless we figure out how to make developers 2x, 5x, 10x as productive on stuff that matters, this isn't going to play out well.

Simple - you make them work 2x, 5x, or 10x more hours.