TSMC has a factory in the USA now, ASML too. OpenAI, Google, xAI and Nvidia are natively in the USA.
While no other country is even close to build AI on their own.
Is the USA going to "own" the world by becoming the keeper of AI? Or is there an alternative future that has a probability > 0?
So far, I haven't seen any indication that this is the case. And I'd say, hyped up speculations by people financially incentivized to hype AI should be taken with an entire mine full of salt.
If one country moves along this direction faster than the others, no country will stand a chance to compete with them militarily or economically.
Having hardware and software suppliers all together makes it more likely even if you assume (like I do) that we're at least one paradigm shift away from the right architecture, despite how impressively general Transformers have been.
But software is easy to exfiltrate, so I think anyone with hardware alone can catch up extremely fast.
Currently there is no hard ROI on LLMs for example other than force bundling and using it to leverage soft outcomes (layoffs) and generating trash. User interest and revenue drops off fairly quickly. And there are regulations coming in elsewhere.
It’s really not looking good.
Second, how could AI not be the deciding geopolitical factor of the future? You expect progress to stop and AI not to achieve and surpass human intelligence?
A big lesson seems to be that one can rapidly close the gap, with much less compute, once paths have been blazed by others. There’s a first-mover disadvantage.
A word generator is not intelligence. There’s no “thinking” involved here.
To surpass human intelligence, you’d first need to actually develop intelligence, and llms will not be it.
As far as I know, Waymo is still not even remotely able to operate in any kind of difficult environment, even though insane amounts of money have been poured into it. You are vastly overstating its capabilities.
Is it cool tech? Sure. Is it safely going to replace all drivers? Doubt, very much so.
Secondly, this only works if progress in AI does not stagnate. And, again, you have no grounds to actually make that claim. It's all built on the fanciful imagination that we're close to AGI. I disagree heavily and think, it's much further away than people profiting financially from the hype tend to claim.
Even China has not yet managed to even remotely catch up with this hardware stack. Even though the trail has been blazed by ASML, TSMC and Nvidia.
Easily. Natural resources, human talent, land and supply chains all are and will be more important factors than AI
> You expect progress to stop
no
> and AI not to achieve and surpass human intelligence
yes
It really depends on how they go about it. It can easily instead end up with lots of people without work, no social security and disillusioned with the country. Instead of being economically great, the country may end up fighting uprisings and sabotage.
But how are animals with nerve-centres or brains different? What do we think us humans do differently so we are not just very big probabilistic prediction systems?
A completely different tack: if we develop the technology to engineer animal-style nerves and form them into big lumps called 'brains', in what way is that not artificial and intelligence? And if we can do that, what is to stop that manufactured brain from not being twice or ten times larger than a humans?
People think LLMs are intelligent because intelligence is latent within the text they digest, process and regurgitate. Their performance reflects this trick.
ASI also will not be magic. Like what exactly would it be doing that enables the country to subject the others? Develop new weapons? We already have the capability to destroy earth. Actually come to think of it, if ASI is an existential threat to other nations, maybe the rational action would be to nuke whichever country develops it first. To safe the world.
You see what I am saying? There is such a thing as the real world with real constraints.
Or, as is already being done, use them to influence opinion and twist perception within tools and services that people already use, such as social media.
On the other hand if the economic benefit isn't shared across the whole of society it will become a destabilising factor and hence reduce the overall economic benefit it might have otherwise borne.
Reasoning models are trying to address that now, but monologueing in token-space still feels more like a hack than a real solution, but it does improve their performance a good bit nonetheless.
In practical terms all this means is that current LLMs still need a hell of a lot of hand holding and fail at anything more complex, even if their "System 1" thinking is good enough for the task (e.g. they can write Tetris in 30sec no problem, but they can't write SuperMarioBros at all, since that has numerous levels that would blow the context window size).
China has a realistic prospect of developing an independent stack.
It'll be very difficult, especially at the level of developing good enough semiconductor fabs with EUV. However, they're not starting from scratch in terms of a domestic semiconductor industry. And their software development / AI research capabilities are already near par with the US.
But they do have a whole of nation approach to this, and are willing to do whatever it takes.
In current LLM neural networks, the signal proceeds in one direction, from input, through the layers, to output. To the extend that LLM's have memory and feedback loops, it's that they write the output of the process to text, and then read that text and process it again though their unidirectional calculations.
Animal brains have circular signals and feedback loops.
There are Recurrent Neural Network (RNN) architectures, but current LLM's are not these.
I see this statement thrown around a lot and I don't understand why. We don't process information like computers do. We don't learn like they do, either. We have huge portions of our brains dedicated to communication and problem solving. Clearly we're not stochastic parrots.
> if we develop the technology to engineer animal-style nerves and form them into big lumps called 'brains'
I think y'all vastly underestimate how complex and difficult a task this is.
It's not even "draw a circle, draw the rest of the owl", it's "draw a circle, build the rest of the Dyson sphere".
It's easy to _say_ it, it's easy to picture it, but actually doing it? We're basically at zero.
* "I know how this works and it's just numbers all the way down" is not an argument of any validity, just to be clear- everything eventually is just physics, blind mechanics.
On Internet comment sections, that's not clear to me. Memes are incredibly infectious, and we can see by looking at, say, a thread about Nvidia. It's inevitable that someone is going to ask about a moat. In a thread about LLMs, the likelihood of stoichastic parrots getting a mention approaches one, as the thread gets longer. what does it all mean?
I have not noticed companies or colleagues 10x'ing (hell, or even 1.5x'ing) their productivity from these tools. What am I missing?
Maybe LLMs can't work on huge code bases yet, but for writing bespoke software for individuals who need a computer to do xyz but can't speak the language, it already is working wonders.
Being dismissive of LLMs while sitting above their current scope of capabilities gives strong Microsoft 2007 vibes; "The iPhone is a laughable device that presents no threat to windows mobile".
If every single human on earth was an identical clone with the same cultural upbringing and similar language conversation choices and opinions and feelings, they still wouldn't work like an LLM and still wouldn't be stochastic parots.
I see people getting replaced by AI left and right.
Translators, illustrators, voice over artists, data researchers, photographers, models, writers, personal assistants, drivers, programmers ...
I think the idea that the United States "owns" Grok 3 would be news to Musk and the idea it "owns" ChatGPT would be news to Altman.
The amount of “work” done there is staggering and yet adoption appears abysmal, using such solutions with success only happens as part of a really “well oiled” machine.
And what about the simple difficulty going from 99% to 99.9%. What percentage are we even talking about today? We don’t know, but very rich people think it is cool and blindly keep investing more billions.
It's fine to chase hype for hobbyist or starter projects, but part of being an engineer is understanding how things actually work and what their limitations are.
It's not a virtue to deify a statistics model and make it your entire personality.
If you aren't an engineer, I get why you think it's magic. Everything is magic when you don't understand how it works.
Nobody thought the iPhone was magic. It was an instant hit because the capabilities were immediate and obvious, and Apple had a long history of being able to execute.
If you find it useful, by all means, use it. But this is the new blockchain.