The US blocked high power graphics cards to specific countries, and then got all shaken up when their money moat was pole-vaulted by an embargo’d country wielding jank cards.
Why is this a big deal, exactly?
Who benefits if the US has the best AI, and who benefits if it’s China?
Is this like the Space Race, where it’s just an effort to spit on each other, but ultimately no one really loses, and cool shit gets made?
What does AI “supremacy” mean?
No. We are not.
With typical capitalist efficiency, the titans of industry are going to boil off half an ocean in an ignorant attempt to simulate a human brain that requires what, about 2 kilowatt-hours of relatively clean chemical energy a day?
Never mind there being no shortage of said brains.
I think a bunch of ignorant politicians in the US think that’s going to be their ticket for competing with China because they refuse to invest into workers. They’re basically betting that AI would allow them to automate a lot of the jobs, and that’s how they’ll get back on top.
Some assholes gave congresscritters a bunch of money to get their businesses a cozy monopoly and special treatment. They were seeing AI as a profit center they could corner the market on thanks to govt-industry collusion. Looks like ginormous data centers and export controlled GPU cards may not be as essential to AI research as thought, and now the emergency is their stock is tanking.
I think, people who say that believe that we’re close to actually-intelligent AI (or artificial general intelligence, AGI). And when we get there, it’s possible that we might suddenly be able to automate lots of complex tasks, possibly even shove it onto robots and have it take on physical labor and things like that.
It’s the wet dream of capitalists, because they don’t need to employ anyone anymore. And I guess, folks are also afraid that such AI could be used for war.
Who the fuck do they think they will sell things to if no one has any money but them 🤔
Machine learning isn’t my bag, so I couldn’t say. But it’s interesting that currently the best tools are open source, including China’s DeepSeek. Google: “We Have No Moat And Neither Does OpenAI”
Well, they’re not actually open-source. The models are freely available, but the training data is not, so it’s not actually possible for competitors to reproduce the same result.
Asterisk on that - I consider black forest’s image generation models to be leading, and their pro variants are commercial only.
That said everything else has leading models that are all open source I think, except for ChatGPT which is becoming obsolete right now.
This news cycle is one hell of a nothing burger.
They have sunken too much money and can’t go backwards now. Thats all. They will eat themselves in a bid to stay ahead.
Don’t believe the hype: LLMs are not AI. Not even close. They are in fact, much closer to pattern recognition models. Fundamentally, our brains are able to ‘understand’ any query posed to it. Only problem is we don’t know what ‘understanding’ even means. How can we then even judge if some model is capable of understanding, or is the output just something that is statistically most likely?
Second, can AI even know what a human experience is like? We cannot give AI inputs in the exact form we receive them in. In fact, we cannot input the sensations of touch, flavor and smell to AI at all. So, AI as of yet cannot tell you how a freshly baked bread smells like or feels like, for example. Human experience is still our domain. That means our inspirations are intact and AI cannot create works of art that feel truly human.
Finally, AI by default has no concept of truth or false. It takes every statement in it’s training data as true, unless, they are labelled individually by hand. Of course, such an approach doesn’t scale well for petabytes of text data. So, LLMs tend to hallucinate stuff because again it is only giving out text that is only statistically most likely, given the input.
In short, we still don’t have many pieces of puzzle that is true AI. We know it is possible because we exist, but that’s about it. Sure, AI is doing better than humans in specific cases, but they nowhere close humans in understanding and reasoning.
that didn’t really answer my question
I guess you are right. Think of it this way, LLMs are doing great at solving specific sets of problems. Now, people in charge of the money think that LLMs are the closest thing to an intelligent agents. All they have to do is reduce the hallucinations and make it more accurate by adding more data and/or tweaking the model.
Our current incentive structure reward results over everything else. That is the primary reason for this AI race. There are people who falsely believe that by throwing money at LLMs they can make it better and eventually reach true AGI. Then, there are others who are misleading the money men, even when they know the truth.
But, just because something is doing great at some limited benchmark doesn’t mean that model can generalise it to all the infinite situations. Again look at my og comment for why it is so. Intelligence is multi-faceted and multi dimensional.
This is unlike space race in one primary way. In space race, we understood the principles for going to space well enough since the time of Newton. All we had to do was engineer the rocket. For example, we knew that we have to find the fuel that can generate maximum thrust per kg of fuel oxygen mixture burnt. The only question was what form it would. Now you could just have many teams look for many different fuels to answer this question. It is scalable. Space race was an engineering question.
Meanwhile, AI is a question of science. We don’t understand the concept of intelligence itself very well. Focussing on LLMs solely is a mistake because the progress here might not even translate well and maybe even harm the larger AI research.
There are in scientific community who believe that we might never be able to understand intelligence because to understand it a higher level of intelligence is needed. Again, not saying it is true. Just that there are many ideas and viewpoints present with regards to AI and intelligence in general.
That’s all well and good—that LLMs aren’t AGI—but not really what’s being asked.
