> What I don't see is vast areas of industry finding $10s to $100s of billions of value in LLMs.
Translation between languages.
That value dwarfs all programming value that can be had. Economically, culturally, scientifically, spiritually.
Translation between languages.
That value dwarfs all programming value that can be had. Economically, culturally, scientifically, spiritually.
Now do a full movie's subtitles with google translate, in an automated fashion. So that it understands the context and still translates it correctly.
Just by nature of how often it's used etc.
You need workloads for AI be cost effective: software, automation etc.
Hackers always rage and down vote every time I mention this, because they are unable to see beyond their small world. Why didn't they learn that their part of the internet is 0,000000001% of what the world uses the internet for today. It's going to be the same with LLMs. Programming and hacker stuff is going to be 0,0000000000000000000000000000001% of what the world uses AI for. But translation is going to be in the top 5 of use cases.
A developer using sub-agents will consume more tokens 1 Day than a marketing manager will consume 1 Month, easily.
Unless there is something inherently automated about the nature of the AI, it will be a tiny % use case.
Even a lawyer, using AI daily for contracts - that will be relatively light use. They'll make more use doing legal research etc.
Developers and Automation are the 'primary' uses cases for AI, and in the future, we'll start to see AI integrated into Apps - that will be 85% of tokens consumed.
Yes - once translation becomes realtime, and we have our Star Trek Universal Translators, then translation will become more visible, but even by then, a relatively small part of overall consumption, even if it's more highly visible.
And a programmer uses one million tokes, which gives him $100 in sales (or value).
What is then the value of a token?
The comment I answered asked where there is an industry finding 10s or 100s of billion of dollars in value from LLMs. The answer is translation. It's the value they as customers get out of the LLMs, not what cost they are paying for the LLMs.
Value has to be counted in production, not consumption.
> Developers and Automation are the 'primary' uses cases for AI
Just like programmers and scientists were the primary users of the Internet when it began. But things change rapidly.
2) 'Because there was a bit of translation involved in the job' - does not mean that AI is really driving that economic activity.
Again: translation is extremely common. The AI might make that part a bit more efficient, it will be barely noticeable.
3) That level of AI activity will just be some 'compute' on your local machine, nobody will be counting tokens.
Think of it like this:
"Translation is going to get easier because you can download some software that does it". It happens to use the GPU instead of CPU.
The vast majority of this kind of compute will be automation, software and a few other things.
'Translation' will just be a little app on your iPhone.
But why are you talking about "basic translation"? There is no commercial need for that. It has to be high quality, and LLMs deliver that. Human translators deliver that as well, but at a much higher price.
Your number 2 point, what do you mean? In many cases if there was no translation, then there wouldn't have been a sale. It's a direct driver.
Your number 3 point: No matter how cheap it is for the user, the economic value from LLM translation will still be counted in the trillions of dollars. Just like e-mail (which is cheap or free for the user). But you will need an enormous amount of storage space on your local machine to have perfect quality translation between dozens of languages.
I don't know why hackers want to diminish the value of LLM translations. The commercial need for translation is not for finding out what a word means. It needs to be of the highest quality, comparable to professional human translators.
The main problem is I think you're assuming because the current translation market is large (I'm just going to assume it's ~100B in size just from a cursory search), then it will remain large with LLMs. If LLMs are much cheaper than humans, even with a lot of growth in translation volume the total spend may not compensate for it (again most of the volume will probably be using almost free models?). Another is assuming that because something is valuable you can charge a lot for it. Like, oxygen from air is extremely valuable to us. If oxygen somehow depleted we would die almost instantly. It does not mean everyone goes around purchasing oxygen or even less that you can charge absurd amounts for it.
Before AI translation became available, I would hire professional translators. Their rate was about $50-100 for a detailed product page into one language, and it would take them a few days to deliver.
Now with AI translation, I pay about $120 per year for unlimited translation. Meaning dozens of product pages into 5 languages, plus e-mail back and forth with hundreds of customers. All instantly at my convenience.
What this means is that a whole lot of people, sectors and businesses who would never hire professional translator can now have high quality translation at their disposal for a cheap price.
> Another is assuming that because something is valuable you can charge a lot for it.
Even if LLM translation won't deliver trillions of dollars in income to the AI companies, it will without a doubt deliver trillions of dollars in value to customers and users within the coming few years.
Good human translators are still higher in quality than any AI and will always be. But AI translation is currently far beyond good enough for all use cases, except fine literature and maybe complicated juridical stuff. But I'm not familiar with those sectors.
But we'll see. Text editing tools are included on all digital devices, yet companies pay for commercial solutions like MS Office. Cameras and basic image editing tools are included on all smart phones, yet there are millions of advertising agencies around the world. And so on.
eg. processors are needed for everything on the planet. No Intel isn't going to generate annual revenue in the trillions because of that. In the case of frontier companies the moat is even smaller with dozens of players competing. LLMs will become a low-cost commodity. You meanwhile can make billions building applications using them though.
No, but Intel processors are going to generate revenue in the trillions for the economy, which was the original question as far as I understood it.