Google AI Ultra

The global average salary is somewhere in the region of $1500.

There’s lots of people and companies out there with $250 to spend on these subscriptions per seat, but on a global scale (where Google operates), these are pretty niche markets being targeted. That doesn’t align well with the multiple trillions of dollars in increased market cap we’ve seen over the last few years at Google, Nvda, MS etc.

New technology always starts off available to the elite and then slowly makes its way down to everyone. AI is no different.

This is one of those assumed truisms that turns out to be false upon close scrutiny, and there's a bit of survivorship bias in the sense that we tend to look at the technologies that had mass appeal and market forces to make them cheaper and available to all. But theres tons of new tech thats effectively unobtainable to the vast majority of populations, heck even nation states. With the current prohibitive costs (in terms of processing power, energy costs, data center costs) to train these next generation models, and the walled gardens that have been erected, there's no reason to believe the good stuff is going to get cheaper anytime soon, in my opinion.

Do you have a source for the $1500 number? Seems pretty high.

> turns out to be false upon close scrutiny

Care to share that scrutiny?

Computers, internet, cell phones, smartphones, cameras, long distance communication, GPS, televisions, radios, refrigerators, cars, air travel, light bulbs, guns, books. Go back as far as you want and this still holds true. You think the the majority of the planet could afford any of these on day 1?

It's 6x that. The median is 2x: https://chatgpt.com/share/682ceb2a-b56c-800b-b49d-1a24c48709...

the point is not that AI services will be affordable "eventually" it's that the advantage is so crazy that people who don't have access to them will NEVER be able to catch up. First AI wrappers disrupt industries ->developing nations can't compete coz the services are priced prohibitively -> AI wrappers take over even more -> automation disrupts the need for anyone -> developing nations never develop further. this seems more and more likely not less. cutting edge GPUs for eg - already are going into the stratosphere pricing wise and are additionally being sanctioned off.

How is this different from literally all of human history

It seems you're suggesting that once you start this process of building tech on top of tech, then you get far ahead of everyone because they all have to independently figure out all the intermediate steps. But in reality, don't they get to skip to the end?

e.g. Nations who developed internet infrastructure later got to skip copper cables and go straight to optical tech while US is still left with old first-mover infrastructure.

AI doesn't seem unique.

I disagree. There are massive fixed costs to developing LLMs that are best amortized over a massive number of users. So there's an incentive to make the cost as cheap as possible and LLMs more accessible to recoup those fixed costs.

Yes, there are also high variable costs involved, so there’s also a floor to how cheap they can get today. However, hardware will continue to get cheaper and more powerful while users can still massively benefit from the current generation of LLMs. So it is possible for these products to become overall cheaper and more accessible using low-end future hardware with current generation LLMs. I think Llama 4 running on a future RTX 7060 in 2029 could be served at a pretty low cost while still providing a ton of value for most users.

Yeah, GP is overextending by saying it's always true.

The more basic assertion would be: something being expensive doesn't mean it can't be cheap later, as many popular and affordable consumer products today started out very expensive.

> The global average salary is somewhere in the region of $1500.

The global average salary earner isn't doing a computer job that benefits from AI.

I don't understand the point of this comparison.

The technology itself is not useful. What they're really selling is the data it was trained on. Most of which was generated by students and the working class. So there's a unique extra layer of exploitation in these pricing models.

> The global average salary earner isn't doing a computer job that benefits from AI.

Do you mean the current half baked implementations or just the idea of AI in general?

> I don't understand the point of this comparison.

I don't understand the point of "AI."

> e.g. Nations who developed internet infrastructure later got to skip copper cables and go straight to optical tech

Actually, they skipped cables entirely. Africa is mostly served by wireless phone providers.

...I don't understand where this take keeps coming from.

You can be upset that the models were trained without compensating the people who made the training data. You can also believe that AI is overhyped, and/or that we're already near the top of the LLM innovation curve and things aren't going to get much better from here.

But I've had LLMs write entire custom applications for me, with the exact feature set I need for my own personal use case. I am sure this software did not somehow exist fully formed in the training data! The system created something new, and it's something that has real value, at least to me personally!

The $250 is just rate limiting at the moment. It isn't a real price; I doubt it is based on cost-recovery or what they think the market can bare.

They need users to make them a mature product, and this rate-limits the number of users while putting a stake in the ground to help understand the "value" they can attribute to the product.

The story being told at Wall Street is that this is a once-in-an-era revolution in work akin to the Industrial Revolution. That’s driving multiple trillions of dollars in market cap into the companies in AI markets.

That story doesn’t line up with a product whose price point limits it to fewer than 25-50mn subscriptions shared between 5 inference vendors.

> I am sure this software did not somehow exist fully formed in the training data!

I'm sure it did exist in the training data. It's trained on Github and Stackoverflow. You "custom" application has already been written many times before.

And every time I tested a feature and changed my mind about the minutia of how it should work, and I gave the AI new instructions and it complied--every permutation of that already existed in some GitHub repository somewhere?

I'm sorry, I just find that exceedingly hard to believe. There is a lot of legacy code out there in the world, but not that much!