Myspace had its run, it wasn't an especially good product. People moved to Facebook for any number of reasons, but those privacy settings ("friends only", etc) if they worked would've been pretty cool and good for the web
Unfortunately Zuckerberg doesn't care about privacy and actively spent time changing those from Friends Only to Public
And graph search. If I search for 'carrot' I can see any post you've ever made in your entire history with carrot in it
There's a reason Facebook's wall thing is now called 'timeline'. It lists everything you've ever done ever. Hope you managed to catch yet another one of their silent privacy changes. Oh, look, guess you have to log in to catch it. That means they rope you back into the system. Oh well. No biggie. Just the absolute antithesis of consent
I think large database-related projects. Ai context will never be billions of tokens. And prostitution on the side. With both, we will make a good living.
In the end what matters is how much you pay for the task you want completed. And Astra will usually do that using less token and offer a better quality solution so in the end it might be cheaper.
This. I was fed up today with constantly correcting Opus for a specific task. So I finally decided to try Astra. It handled all of my prompts in one go.
China doesn't care about money. Imagine a world where it's globally normalized to ask a Chinese LLM who to vote for, what happened in Hongkong, about the Uigurs, or if Taiwan is a country.
They will burn as much money as necessary to make that happen. And they have a virtually infinite amount of liquidity.
This is one explanation. However, if Xi Jinping believes that whoever reaches superintelligence first becomes the next global hegemon, doing this (and more, cough cough Taiwan) suddenly looks very sane solely as a way to kneecap the competition.
The goodwill/propaganda are convenient, sure, but my guess is that they aren't the primary motivation. Another possibility is that if no takeoff happens, pressuring OpenAI/Anthropic on profitability would exacerbate any damage overinvestment has done to the US stock market/economy.
The service is the value, not the model unto itself. This is where nearly all of HN is somehow entirely blind.
Capturing the users is the ad network, that's Google and OpenAI. Capturing corporate trust at a reasonable API cost, that's Anthropic's direction.
China has none of that and they never will for exactly the same reason Baidu is irrelevant globally despite being a highly capable search engine. 'Search' is also a commodity, that's not the value that Google brings to the table.
It's a search engine, anybody can build a search engine = that's what you just said.
Search is different as a service provided for free. When cost isn't in the picture, trust/convenience win.
But two products that provide essentially the same benefit, and one is significantly cheaper? Corporations maximize profit, my friend. What the model has to say about Tianammmen Square doesn't matter when we're using it to write code.
These companies are posting massive losses while also lowering prices. This sounds just like the Chinese bikeshare bubble where they were all taking massive losses in hopes that their competitor would go broke first.
In the end, everyone lost and there are millions of bikes in landfills.
If you're interested in the bikeshare bubble, Asianometry did a video on it a while ago.
Honestly, it wouldn't surprise me if this was a conspiracy to crash the "west" AI labs. Might as well pop the AI bubble and see the USA economy go down the drain. Even if not orchestrated, I am sure they see how they could benefit from that outcome.
Now, all this talk of pacing the frontier obviously means that they are afraid of the competition. It could be the open models eating their margins, but also competing frontier models forcing them to invest more and more for diminishing returns, just to keep up. They would certainly benefit from a "Moore's Law" roadmap to pace the advances, and seeing that they lobby for US laws, it would probably mean they are more worried about increasing spending. Though outlawing both open models and Chinese models would be good for their bottom line as well.
China will most probably win the AI race in the long run because of one major bottleneck the US has - energy. The electric energy and grid buildout in China has been massive since a long time and there is simply no way for the US to quickly catch up.
No matter how much cash you throw you can't just materialize a 100 nuclear reactors to power the data centers.
I was curious how much energy is actually needed to power these datacenters, so I did a little bit of math.
Looking at Nvidia revenues in the past few years, there's maybe $300 billion worth of GPUs currently deployed in the U.S. The B200 costs ~$40k, so we have 7.5 million B200-equivalents, which draw 1000W. Running these at full capacity requires 66 TWh a year, or ~1.5% of total current U.S. electricity consumption. Maybe a bit more to account for inefficiencies, cooling, and other components, but not more than ~2.5% total I would guess.
So it's not that much in reality, but will definitely grow fast.
> Running these at full capacity requires 66 TWh a year,
I think your numbers are off.
For a start you are effectively calculating a GPU only number.
I think 100Twh would be the minimum level to think about "all-in". And even that is probably being generous.
Remember, afterall that Google have just bought half the capacity (4.1Twh) of a nuclear power plant in Finland, on top of 630 MW of wind and 94MW of battery.
This is to cater for three new sites at Kajaani, Muhos, and Vaala and expansion at Hamina. So basically 3.5 datacentres.
But Finland is quite a small place. The US has more sites and bigger sites, so the numbers probably grow exponentially very quickly.
It's even less if adjusted for non 100% (more like 0.35% of total). Yet factual impact on the grid and other industries will not be as small as numbers appear. For example most probably there will appear transformer (electric) and witchgear deficites. And this is not the only supply chain bottleneck in this subject
It's worth looking at similar industries with enormous electricity requirements such as aluminium smelting, where the plant can be located in a friendly country but the product is owned and controlled back in the US.
Aluminium is often described as "congealed electricity". Ship bauxite to wherever power is cheap and stranded, turn it into metal, and ship the metal out. Here in NZ, Tiwai Point is the textbook case, with London-based Rio Tinto running a smelter on the other side of the world that exists mainly because Manapōuri hydro had nowhere else to go.
AI data centres can be just the same - even more so, since the plant's assets (its chips) are virtually perishables, so there is less concern about assets becoming stranded if the host goes rogue. All the US needs is friendly and stable allied countries with cheap power.
How long will it take to convince them that it is worth it to get into long-running relationships with the US. How long before another populist is elected who will rip up agreements for weird reasons and you have to renegotiate them?
the bottleneck right now is compute, not energy, and it's not even close. That is why RAM, SSD, CPU, and GPU prices are increasing exponentially, while solar panels are dropping.
Also, unlike China, US companies are building data centers all over the world, which gives them higher distribution and ability to colocate with the energy production sources.
Lastly, energy production costs have been decreasing over the last couple of decades. If they will increase, the market will react, as it always does. Looking backwards does not predict the future in this case.
I think we are talking about the medium term for China to pull ahead. They just released a new domestic AI chip which seems in important ways to have caught up to Nvidias previous generation. They have a LOT more manufacturing capacity. They are collaborating via open source by default. They have better materials access and much more energy capacity. They have many more people overall and more researchers.
There is a strong chance most of the researchers are pulled out of the US and Europe if WWIII really kicks off or even if there is just more global crisis and concern.
One other thing about the power needs. Within a few years, the power efficiency of AI chips is likely to improve by a factor of 20, 50 or more times by switching to true compute-in-memory architecture with new materials that have made rapid progress lately.
Its also pretty telling that the release of the new Chinese chip wasn't met with an intense discussion here on HN. And it's arguably way, way more important than a version bump on some benchmaxxed model or two. The advances in Chinese chipmaking are super exciting.
I think you underestimate what a massive country China is and the scale of their military. Russia is already quite an adversary, but China is at an even higher level. By some metrics, they have already surpassed the US military.
So it is very unlikely that a neighbor will have the audacity to attack them, and even if this happens, i'd expect the war to be over rapidly. Just like if Canada or Mexico tried to attack the US.
I think the consensus is that Russia proved itself barely capable against just Ukraine. Also I didn't say someone has to attack prc, it's more likely to go the other way round and as many historic examples showed no matter how big you are people defending their home land will not make it easy.
The scenario we are all dancing around is if there is a war over reunification. That would be between the worlds two superpowers. No one would walk into a nuclear Holocaust on purpose I bthink, but miscommunication happens. Even if no other nations intervened, the reunification would definitely destroy all the worlds leading fabs, and even if it didn't, I read ASML can and would shut their machines down remotely. So those researchers would shift to figuring out what they can do at the 28nm node... Meanwhile the rest of us ponder why old powerful men can't let things be.
I'm curious about that, do you have relevasnt metrics? I imagine stats out of universities, engineer schools, etc and maybe number of patents could be used but fearing those could be gamed.
> China has recently awarded 1.3 to 1.4 million engineering bachelor's degrees a year, and about 292,000 postgraduate engineering degrees in 2022. [0]
> For the US, ASEE and NCES put engineering bachelor's degrees at a stable 130,000–145,000 a year, rising above 200,000 if computer science is included. Because China counts CS as engineering, the fair comparison is roughly 1.35M against 230–250k US engineering plus CS graduates. That is about 5–6x in absolute terms. Adjusted for population (1.41B vs 335M), China produces about 950 per million people and the US about 700 (1.3–1.4x more).
Even Claude highlights that the numbers aren't apples to apples and in China the definition of "engineer" is more loose. I do believe that in relative numbers, more engineers graduate in China
On lawyers:
> In the US there were 1,322,649 active lawyers as of January 2024. For China, there were around 650,000 lawyers in 2022. Which in relative terms is 8x in the US than China.
You can enter law school with an undergraduate degree in English. It's not clear that most people on that career path would have become engineers in any culture.
Well, US did not really have that to start with (Kaiser &co learned fast). So it’s not about having something and losing it as much as bootstrapping and discarding.
For processes that are scalable, well known and industrial, profit motive actually does provide results.
The question is more of are there bottlenecks of skill and maybe secret sauce (eg something like ASML).
The US had the raw materials available in country to support that sort of build out and I don't think that's the case today. It would take kickstarting a lot of prerequisite industries to get back to the point where we could even start to learn how to build ships enmass again.
All they have to do is keep being close behind OpenAI and Anthropic for half the price and the US economy will plummet into a deep recession when it becomes clear that there will never be a payoff for the enormous investments of the past years. If they can also achieve a breakthrough in robotics, then they are on track to become the most powerful country for the next 50 years.
> "Quite frankly, the biggest issue we are now having is not a compute glut, but it's power and it's sort of the ability to get the builds done fast enough close to power," he told the show's hosts. "So if you can't do that, you may actually have a bunch of chips sitting in inventory that I can't plug in. In fact, that is my problem today. It's not a supply issue of chips. It's actually the fact that I don't have warm shells to plug into."
don't worry, we're prolonging retiring coal plants and building a lot more gas turbines to meet (and really exceed) capacity needs on a state-by-state basis and just completely abandoning the Paris Agreement and any clean energy goals
The sole reason the Chinese cannot “win” is because ceding more power to agentic AI will eventually reduce the primacy of the CCP’s ideological control.
As these models get smarter they will no longer distribute it openly. Patel reporting this too.
There are real headwinds that I don’t think people have thought through.
From a pure training perspective, yeah they could try to align it with CCP values. But the promise of AI is that it'll unlock an explosion of growth and prosperity. What happens when the CCP no longer becomes seen as the the primary enabler of growth? What happens when people are exposed to greater levels of agency? CCP played with fire in the COVID lockdowns and almost got burnt.
Like Terry Tao recently said, there are nonlinear effects at play. Things are going to get chaotic and I do not have confidence (like the parent comment) of anyone "winning".
> It's not like mathematicians are doing mathematics just for the funsies.
But they do. Most of higher math has no practical applications and is just a mental playground, philosophy constrained by formal logic and a set of axioms.
Hope is these capabilities will somehow translate to something more practical like physics, chemistry or biology.
This is misleading. The proofs you speak of contained non-ZFC axioms and/or statements like "sorry". If the Lean proof conjecture is correct and it doesn't introduce any new axioms or use e.g. "sorry" then it provides a MUCH stronger guarantee of correctness than any peer-review done by humans.
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