The more logical explanation is that AI is not a wave like the Internet and Mobile, but it is instead a wave like cryptocurrencies, NFTs and tulip bulbs.
If there’s one thing that almost 3 decades at or near the forefront of Tech has taught me is that “novel” is not the same as “better”, and that of all the times a novel technology was pushed by insane amounts of hype, only a handful turned out to match the hype and the ratio of good-ones to bullshit has become much worse in the last 2 decades as the Tech Startup sector fully morphed from Techie-driven to Financeer-driven.
On hype alone “AI” (as in, what’s called now AI for the public, rather than the ML domain) stinks of greed-driven bullshit and the more one analyses the Technical details of LLMs and the Mathematics of it as well as of the improvements over time, the more painfully obvious it becomes that it’s not at all AGI or a path to it, rather it’s an overhyped attempt at it that turned out to be the wrong path. (All of which would’ve been absolutelly fine and a big Scientific step forward if it weren’t for the greedy financeer class and grifters pushing, purelly for their own personal enrichment, for people and companies to adopted it for doing things it’s not suitable for)
AI has an interesting economic trait in that it’s very, very expensive to deploy, and made very fast progress from 2022 to 2024. That caused investors with money to believe that:
Pushing the frontier was going to cost a lot of money. More than any other purported revolutionary tech.
Extrapolation of past improvement meant that whoever was on the cutting edge may end up with a product with a huge paying market.
So whoever wins this race would be rich, and the investment would have been worth it for them.
But since 2024, we’ve seen that the cutting edge got even more expensive much faster than expected, and much of the improvements in performance now come from inference rather than training, which represents a high ongoing cost.
Now, if we extrapolate from that trend line, we’ll see that the market will be much smaller for AI services at the cost it takes to provide that service, and the question then becomes whether the industry can make its operations cheaper, fast enough to profitably provide a service people will pay for.
I have my doubts they’ll succeed, and we might just be looking at the industry like supersonic flight: conceptually interesting, technically feasible, but just a commercial dead end because it’s too expensive.
The economics of it don’t add up and the growth rate of the curve of improvement over time has already significativelly fallen which looking at the historical curves for other technologies is a very strong indication that it’s approaching the limits of how far it will go even though it’s nowhere close to the hype.
So at both levels it all looks like a massive bet in the wrong horse that’s turning out not to be a winner but it keeps getting pushed by those who bet on it in the hope of making enough people and companies dependent that it’s sustained by nothing more than the unacceptable cost of it failing.
(In terms of strategy, it’s similar to how Uber started by using loopholes in the regulations for taxis, investing heavilly in becoming so big and established fast that when Authorities around the world go around to address those loopholes, they ended up accepting Uber and the like as something that could not be reversed and instead of regulating it out of existence, legitimized it. A very similar strategy was used by AirBNB - make the facts on the ground so big and reverting them so damaging that their low-value-adding business model becomes established)
As I see it, the way Microsoft and other AI investors are going at it is to try and create a beach-head for it via hype, branding and lock-in in the expectation that something will come along at some point from the companies they invested in that is actually a genuine breakthrough that uses all the computing capacity created with their investment money.
I think that the reason why from the point of view of the public the AI adoption feels wrong is because it’s almost entirelly top-down, driven by marketing techniques and against the current.
From my own experience, this feel a lot like the hype part of the cycle for the Segway, only with 100x or 1000x more investment money behind it.
The more logical explanation is that AI is not a wave like the Internet and Mobile, but it is instead a wave like cryptocurrencies, NFTs and tulip bulbs.
If there’s one thing that almost 3 decades at or near the forefront of Tech has taught me is that “novel” is not the same as “better”, and that of all the times a novel technology was pushed by insane amounts of hype, only a handful turned out to match the hype and the ratio of good-ones to bullshit has become much worse in the last 2 decades as the Tech Startup sector fully morphed from Techie-driven to Financeer-driven.
On hype alone “AI” (as in, what’s called now AI for the public, rather than the ML domain) stinks of greed-driven bullshit and the more one analyses the Technical details of LLMs and the Mathematics of it as well as of the improvements over time, the more painfully obvious it becomes that it’s not at all AGI or a path to it, rather it’s an overhyped attempt at it that turned out to be the wrong path. (All of which would’ve been absolutelly fine and a big Scientific step forward if it weren’t for the greedy financeer class and grifters pushing, purelly for their own personal enrichment, for people and companies to adopted it for doing things it’s not suitable for)
AI has an interesting economic trait in that it’s very, very expensive to deploy, and made very fast progress from 2022 to 2024. That caused investors with money to believe that:
But since 2024, we’ve seen that the cutting edge got even more expensive much faster than expected, and much of the improvements in performance now come from inference rather than training, which represents a high ongoing cost.
Now, if we extrapolate from that trend line, we’ll see that the market will be much smaller for AI services at the cost it takes to provide that service, and the question then becomes whether the industry can make its operations cheaper, fast enough to profitably provide a service people will pay for.
I have my doubts they’ll succeed, and we might just be looking at the industry like supersonic flight: conceptually interesting, technically feasible, but just a commercial dead end because it’s too expensive.
The economics of it don’t add up and the growth rate of the curve of improvement over time has already significativelly fallen which looking at the historical curves for other technologies is a very strong indication that it’s approaching the limits of how far it will go even though it’s nowhere close to the hype.
So at both levels it all looks like a massive bet in the wrong horse that’s turning out not to be a winner but it keeps getting pushed by those who bet on it in the hope of making enough people and companies dependent that it’s sustained by nothing more than the unacceptable cost of it failing.
(In terms of strategy, it’s similar to how Uber started by using loopholes in the regulations for taxis, investing heavilly in becoming so big and established fast that when Authorities around the world go around to address those loopholes, they ended up accepting Uber and the like as something that could not be reversed and instead of regulating it out of existence, legitimized it. A very similar strategy was used by AirBNB - make the facts on the ground so big and reverting them so damaging that their low-value-adding business model becomes established)
As I see it, the way Microsoft and other AI investors are going at it is to try and create a beach-head for it via hype, branding and lock-in in the expectation that something will come along at some point from the companies they invested in that is actually a genuine breakthrough that uses all the computing capacity created with their investment money.
I think that the reason why from the point of view of the public the AI adoption feels wrong is because it’s almost entirelly top-down, driven by marketing techniques and against the current.
From my own experience, this feel a lot like the hype part of the cycle for the Segway, only with 100x or 1000x more investment money behind it.