DaseindustriesLtd
late version of a small language model
Tell me about it.
User ID: 745
I would welcome such a subhuman overreaction.
Okay. I think the elderly care is mainly a problem of machine vision and manual dexterity. I believe these guys will solve it in five years tops.
Wefang is implying basically stereotype threat: that the Chinese don't innovate from 0 to 1 because there's a stereotype that job belongs to the West
Wenfeng.
No, it's not a stereotype threat argument, it's an argument about perceived opportunity cost of exploration vs exploitation which is miscalibrated in the age of large domestic revenue generators. He's not arguing they should be like Whites. He's arguing they can now afford to do what Whites do compulsively, if you will.
Your condescension and willful misinterpretation will be your undoing in this dialogue and outside it.
I look down on WEIRDs for one more reason. You are ultimately tool-like, your mentality is that of servitors and cowering peasants. Your "internal dignity" is inextricably bound to collective judgement, you feel the need to justify your value to some imagined audience, to some Baron, some market or some Moral Community. You are ashamed of brute, terminal-value ethnocentrism the sort of which Judaism preaches, so you need to cling to those spiritualist copes wrapped in HBD lingo. "H-here's why we are Good, why we still deserve a place under the sun, sire!" This exposes you to obvious predation and mockery by High-Skill Immigrants like Count.
On the object level: yes, probably on average the Chinese are indeed less "creative" even with optimal incentives, and this has obvious implications at the tails. (though if we think OpenAI is an impressive example of bold creativity, what about NVidia? What did Jensen "merely improve"? As a CEO, he's roughly in the same league as Altman and Musk, I think). The question – raised by R1 there – is, how many more True Breakthrough innovators do we even need before innovation begins to accrete on itself without human supervision? Maybe just a handful. Again, there's been virtually no fundamental progress in AI since 2017, and we're all doing just fine. It may be that architecturally V3 is more sophisticated and innovative than the modern OpenAI stack. Imagine that. After all, Western geniuses are afraid to show their work these days.
Incidentally, I myself have submitted several minor ideas to DeepSeek; maybe they found use for those, maybe not, but I'll find use for the result of their labor and not cope that they needed my input.
It may be that the mode of production implied by the stage of our technological development makes your race, with all its creative perks and industrial drawbacks, less economically useful than it used to be. This only means you need to move that much faster to find reasons to protect your interests unconditionally, before everyone turns equally economically useless.
Honestly this feels like a cope to me. There obviously was a breakthrough in LLMs in the West: politically, economically, technologically, culturally. It wasn't born in China, but they obviously have a significant part to play downstream of their undeniable talent pool.
What are you talking about? Have you stopped reading my post there?
It's hard to say Deepseek would have accomplished these things without drafting on OpenAI's introduction of LLMs to the world,
Here's what I think about this. The Chinese are not uncreative. It's worse: they're cowardly, conservative, and avoid doing exploratory shit that seems high-risk, and they buy into your theory of their own inferiority, and steelman it as “good at execution”. As Wenfeng says:
Another reason that domestic large models have rarely dabbled in innovation at the architectural level before is that few people have dared to go against the stereotype that America is better at the technological innovation from 0 to 1, while China is better at the application innovation from 1 to 10. Not to mention that this kind of behavior is very unprofitable -- the usual thinking is that, naturally, in a few months, someone would have made the next generation of models, and then Chinese companies can just follow the leader, and do a good job of application. Innovating the model structure means that there is no path to follow, and there are a lot of failures to go through, which is costly in terms of time and money.
There will be more and more hardcore innovation in the future. It may not be yet easily understood now, because the whole society still needs to be educated by the facts. After this society lets the hardcore innovators make a name for themselves, the groupthink will change. All we still need are some facts and a process.
You are watching these facts come in.
I repeat, I've been a believer in this theory of “fundamental Western progress, incremental Eastern refinement”. Eight years into Transformer era (Ashish Vaswani et al., 2017), I start to doubt it. Whites are just people who are sexually attractive, relatively trustworthy, and provide linear labor to verbal-tilted Brahmins who max corporate KPIs leveraging even more verbal-tilted Ashkenazim like Altman who are good at raising capital.
That's about it at this point.
The most credible, big-brained, innovation-heavy alternative to Transformer was Mamba (Tri Dao, Albert Gu). It also didn't go far. I've read perhaps hundreds of Western papers of purportedly brilliant innovations, they're narcissistic shit that doesn't scale. Sepp Hochreiter is peddling his xLSTM that has no utility, Schmidhuber is making some boastful noises as usual, Sutskever and Karmack are supposedly doing… something. Mistral is dead in the water…
I am not saying this out of racism. I am reporting on what I see happening. All historical inventions and discoveries of note? Yes, those were White work. But time is accelerating. Maxwell's equations seem not far from "muh gunpowder" of the Middle Kingdom now, to my eyes. Do something new, folks. You're losing face.
On the other hand we know OpenAI did not need Deepseek.
Sure, OpenAI needed another company. OpenAI built its legend on scaling up a Google paper. By your own standards, it's not creative brilliance. It's the sort of talent you condescendingly concede Chinese people have.
Spy satellites contribute so little to the total mass to orbit that you never even needed SpaceX for that (i don't consider Starlink a primarily national security project, because it's not).
For delivering payloads, including probably international ones, China will begin catching up next year. I do not assume that Americans will be contracting them, no, so in that sense SpaceX is poised to maintain its near-monopoly.
It is believed that the crop of reusable rocket startups is attributable to Robin Li, the founder of Baidu, getting into National People's Congress, and advocating for legalization of private space businesses in 2010s. So far, there have been three Chinese entities that have conducted VTOL tests for reusable rockets.
- China Aerospace Science and Technology Corporation (CASC), June 23, 2024
- LandSpace, September 11, 2024
- Space Epoch, May 29, 2025
There are others which are further behind.
Technologically, they are several iterations behind, but strategically I'd say they save significant advantages over the current SpaceX (a usual feature of Chinese fast-following). For example Space Epoch Yuanxingzhe-1 is basically a small Starship (or a better, thicker Falcon-9, if Falcon-9 were designed today). Stainless steel, metholox, will naturally plug into the existing and state-subsidized logistics, including military facilities that currently produce aviation parts (as a small point, Falcon's extreme height-to-width ratio is obviously suboptimal and downstream of American highway standards, but China had no problem building dedicated roads). LandSpace Zhuque-3 VTVL-1 is similar (they can boast of the first metholox engine to make it to orbit).
But as you rightfully notice, it's not clear if this will have much effect on the SpaceX bottom line, since Americans can saturate their cadence anyway. In all likelihood it will only unnerve some people in Washington as a symbolic thing.
I see you took this pretty personally.
All I have to say is that top AI research companies (not ScaleAI) are already doing data engineering (expansively understood to include training signal source) and this is the most well-guarded part of the stack, everything else they share more willingly. Data curation, curricula, and yes, human annotation are a giant chunk of what they do. I've seen Anthropic RLHF data, it's very labor intensive and it instantly becomes clear why Sonnet is so much better than its competitors.
They clearly enjoy designing "algos", and the world clearly respects them greatly for that expertise.
Really glad for them and the world.
Past glory is no evidence of current correctness, however. LeCun with his «AR-LLMs suck» has made himself a lolcow, so has Schimidhuber. Hochreiter has spent the last few years trying to one-up the Transformer and fell to the usual «untuned baseline» issue, miserably. Meta keeps churning out papers on architectures; they got spooked by DeepSeek V3 which architecture section opens with «The basic architecture of DeepSeek-V3 is still within the Transformer (Vaswani et al., 2017) framework» and decided to rework the whole Llama 4 stack. Tri Dao did incredibly hard work with Mamba 1/2 and where is Mamba? In models that fall apart on any long context eval more rigorous than NIAH. Google published Griffin/Hawk because it's not valuable enough to hide. What has Hinton done recently, Forward-Forward? Friston tried his hand at this with EBMs and seems to have degraded into pure grift. Shazeer's last works are just «transformers but less attention» and it works fine. What's Goodfellow up to? More fundamental architecture search is becoming the domain of mentally ill 17yo twitter anons.
The most significant real advances in it are driven by what you also condescendingly dismiss – «low-level Cuda compiler writing and server orchestration», or rather hardware-aware Transformer redesigns for greater scalability and unit economics, see DeepSeek's NSA paper.
This Transformer is just a paltry, fetish, "algo".
Transformer training is easy to parallelize and it's expressive enough. Incentives to find anything substantially better increase by OOM year on year, so does the compute and labor spent on it, to no discernible result. I think it's time to let go of faulty analogies and accept the most likely reality.
Sounds like they need LLM writing assistance more than anyone, then.
I am quite happy with my analytical work that went into the prompt, and R1 did an adequate but not excellent job of expanding on it.
But I am done with this discussion.
I was not aware that this is a forum for wordcels in training, where people come to polish their prose. I thought it's a discussion platform, and so I came here to discuss what I find interesting, and illustrated it.
Thanks for keeping me updated. I'll keep it in mind if I ever think of swinging by again.
Okay. I give up.
I am not sure how to answer. Sources for model scales, training times and budgets are part from official information in tech reports, part rumors and insider leaks, part interpolation and extrapolation from features like inference speed and pricing and limits of known hardware, SOTA in more transparent systems and the delta to frontier ones. See here for values from a credible organization..
$100M of compute is a useful measure of companies' confidence in returns on a given project, and moreover in their technical stack. You can't just burn $100M and have a model, it'll take months, and it practically never makes sense to train for more than, say, 6 months, because things improve too quickly and you finish training just in time to see a better architecture/data/optimized hardware exceed your performance at a lower cost. So before major releases people spend compute on experiments validating hypotheses and on inference, collect data for post-training, and amass more compute for a short sprint. Thus, “1 year” is ludicrous.
Before reasoning models, post-training was a rounding error in compute costs, even now it's probably <40%. Pre-deployment testing depends on company policy/ideology, but much heavier in human labor time than in compute time.
My impression after obsessively monitoring this situation for days (of course) is that neither side will fold, tariffs are here to stay, and everyone will be poor and mad for it. China of course won't fold, the idea that they're at risk is preposterous, they can well weather complete cessation of export to the US.
Broadly I have concluded that the main problem the US faces is racism towards the Chinese; the ill-earned sense of centrality and irreplaceability. I believe that Trump, Navarro and the rest of that gang are as misinformed as the average MAGA guy on Twitter, given how they speak and that amusing formula. Americans still think that their great consumption is the linchpin of Chinese economy, 10-30% of their GDP (it's more like 3%); that the Chinese produce apparel, “trinkets” and low-quality materials (they also produce things that Americans plausibly cannot start producing at the same quality in years); that American IP is vital for their industry (they're making their own software, OSes, CPUs…) and so on. The idea that American de-industrialization is a product of betrayal by Wall Street Elites who offshored jobs to China also feeds into the delusional notion of possible parity – but the truth is that there has never been a point in history where American industry had scale or diversity comparable to what's going on in China now. The issue with their bad financials is also overblown; as for losing markets, they have the capital at hand for consumption stimulus. This guy from Beijing writes:
China’s PPP GDP is only 25% larger than that of the US? Come on people… who are we kidding? Last year, China generated twice as much electricity as the US, produced 12.6 times as much steel and 22 times as much cement. China’s shipyards accounted for over 50% of the world’s output while US production was negligible. In 2023, China produced 30.2 million vehicles, almost three times more than the 10.6 million made in the US.
On the demand side, 26 million vehicles were sold in China last year, 68% more than the 15.5 million sold in the US. Chinese consumers bought 434 million smartphones, three times the 144 million sold in the US. As a country, China consumes twice as much meat and eight times as much seafood as the US. Chinese shoppers spent twice as much on luxury goods as American shoppers.
…It is prima facie ridiculous that China’s production and consumption, at multiples of US levels, can be realistically discounted for lower quality/features to arrive at a mere 125% of US PPP GDP. … Similarly, analysts who lament that China accounts for 30% of the world’s manufacturing output but only 13% of household consumption are far off the mark. China accounts for 20-40% of global demand for just about every consumer product but much of the services it consumes have been left out of national accounts.
Accordingly, with a higher real GDP, their effective debt to GDP ratio may be as low as 150%, not 200-300%. They have US assets to sell too.
So China can trivially absorb half of the overcapacity freed by reduced trade with the US, and might find buyers for the rest.
My thesis is that in picking this fight, Americans don't understand that they're actually not that big of a deal. Unfortunately, their delusions are globally shared and become reality in their own right. But perhaps not enough to offset the gross physical one.
The actual dangerous thing for China here is that Trump seems determined to immiserate the whole planet, completely irrespective of any geopolitical rivalry, because he's an illiterate anarcho-primitivist and thinks that all trade is theft unless it's barter, basically. America vs. The World, especially with a chain reaction of tariffs on Chinese (and likely also Vietnamese etc…) capacity spillover, results in massive reduction of productivity for everyone. For now, nations like Vietnam are unilaterally dropping tariffs on American crap, but that can't be a big effect because their tariffs were low to begin with, and Americans just don't and cannot produce enough at price points that people of those nations can afford. (We may see IMF loans for 3rd world countries importing overpriced American beef or Teslas or whatever to placate Don, but I doubt it'll be sustainable). I suppose in the long run the idea is that Optimus bots will be churning out products with superhuman efficiency, at least Lutnick argues as much. But that's still years away. Perhaps this extortion of zero balance trade (so in effect, the demand that trading partners buy non-competitive American products) is meant to finance the transition to posthuman automated economy. Bold strategy.
I am of course very amused and curious to see how it'll go. Will Fortress America intimidate the rest of us into submission, likely forever? Or will it be so stubborn, brutal and ham-fisted that humanity will finally rebel and ostracize the rogue state, letting it broil in its own supremacist fantasies? Can Bessent et al. turn 1D “trade le bad” checkers of the King of Understanding Things (懂王) into 4D chess? We shall see.
China's fragile treasure
Tl;DR: after months of observation, I am convinced that DeepSeek has been an inflection point in Chinese AI development and probably beyond that, to the level of reforming national psyche and long-term cultural trajectory, actualizing the absurd potential they have built up in the last two decades and putting them on a straight path to global economic preeminence or even comprehensive hegemony. It is not clear to me what can stop this, except the idiocy of the CCP, which cannot be ruled out.
Last time I wrote on this topic I got downvoted to hell for using DeepSeek R1 to generate the bulk of text (mostly to make a point about the state of progress with LLMs, as I warned). So – only artisanal tokens now, believe it or not. No guarantees of doing any better though.
The direct piece of news inspiring this post is The Information's claim that DeepSeek, a private Chinese AGI company owned by Liang Wenfeng, is implementing some very heavy-handed measures: «employees told not to travel, handing in passports; investors must be screened by provincial government; gov telling headhunters not to approach employees». This follows OpenAI's new Global Policy chief Chris Lehane accusing them of being state-subsidized and state-controlled and framing as the main threat to the West, popular calls on Twitter (eg from OpenAI staff) to halt Chinese AI progress by issuing O1 visas or better offers to all key DeepSeek staff, and the sudden – very intense – attention of Beijing towards this unexpected national champion (they weren't among the «six AI tigers» pegged for that role, nor did they have the backing of incumbent tech giants; what they did have was grassroots attention of researchers and users in the West, which China trusts far more than easily gamed domestic indicators).
I am not sure if this is true, possibly it's more FUD, like the claims about them having 50K H100s and lying about costs, claims of them serving at a loss to undercut competition, about compensations over $1M, and other typical pieces of «everything in China is fake» doctrine that have been debunked. But China does have a practice of restricting travel for people deemed crucial for national security (or involved in financial institutions). And DeepSeek fits this role now: they have breathed new life into Chinese stock market, integrating their model is a must for every business in China that wants to look relevant and even for government offices, and their breakthrough is the bright spot of the National People’s Congress. They are, in short, a big deal. Bigger than I predicted 8 months ago:
This might not change much. Western closed AI compute moat continues to deepen, DeepSeek/High-Flyer don't have any apparent privileged access to domestic chips, and other Chinese groups have friends in the Standing Committee and in the industry, so realistically this will be a blip on the radar of history.
Seems like this is no longer in the cards.
Recently, @ActuallyATleilaxuGhola has presented the two opposite narratives on China which dominate the discourse: a Paper Tiger that merely steals, copies and employs smoke and mirrors to feign surpassing the fruit of American genius born of free exchange of ideas etc. etc.; and the Neo-China coming from the future, this gleaming juggernaut of technical excellence and industrial prowess. The ironic thing is that the Chinese themselves are caught between these two narratives, undecided on what they are, or how far they've come. Are they merely «industrious» and «good at math», myopic, cheap, autistic narrow optimizers, natural nerdy sidekicks to the White Man with his Main Character Energy and craaazy fits of big picture inspiration, thus doomed to be a second-tier player as a nation; with all cultural explanations of their derivative track record being «stereotype threat» level cope – as argued by @SecureSignals? Or are they just held back by old habits, path-dependent incentives and lack of confidence but in essence every bit as capable, nay, more capable of this whole business of pushing civilization forward, and indeed uplifting the whole planet, as argued by Chinese Industrial Party authors – doing the «one thing that Westerners have been unwilling or powerless to accomplish»?
In the now-deleted post, me and R1 argued that they are in a superposition. There are inherent racial differences in cognition, sure, and stereotypes have truth to them. But those differences only express themselves as concrete phenotypes and stereotypes contextually. In the first place, the evo psych story for higher IQ of more northern ancestral populations makes some sense, but there is no plausible selection story for Whites being unmatched innovators in STEM or anything esle. What is plausible is that East Asians are primed (by genetics and, on top of that, by Confucian culture and path dependence) towards applying their high (especially in visually and quantitatively loaded tasks) IQ to exploitation instead of exploration, grinding in low-tail-risk, mapped-out domains. Conformism is just another aspect of it; and so you end up with a civilization that will hungrily optimize a derisked idea towards razor-thin margins, but won't create an idea worth optimizing in a million years. Now, what if the calculus of returns changes? What if risk-taking itself gets derisked?
And I see DeepSeek as a vibe shift moment nudging them in this direction.
The Guoyun narrative around DeepSeek began when Feng Ji 冯骥, creator of the globally successful game “Black Myth: Wukong,” declared it a “national destiny-level technological achievement.” The discourse gained momentum when Zhou Hongyi 周鸿祎, Chairperson of Qihoo 360, positioned DeepSeek as a key player in China’s “AI Avengers Team” against U.S. dominance. This sentiment echoed across media, with headlines like “Is DeepSeek a breakthrough of national destiny? The picture could be bigger” The discourse around 国运论 (guóyùn lùn, or “national destiny theory”) reveals parallels to America’s historical myth-making. Perhaps the most striking similarity between China and the US is their unwavering belief in their own exceptionalism and their destined special place in the world order. While America has Manifest Destiny and the Frontier Thesis, China’s “national rejuvenation” serves as its own foundational myth from which people can derive self-confidence.
And to be clear, DeepSeek is not alone. Moonshot is on a very similar level (at least internally – their unreleased model dominates LiveCodeBench), so are StepFun, Minimax and Alibaba Qwen. Strikingly, you see a sudden formation of an ecosystem. Chinese chip and software designers are optimizing their offerings towards efficient serving of DeepSeek-shaped models, Moonshot adopts and builds on DeepSeek's designs in new ways, Minimax's CEO says he was inspired by Wenfeng to open source their LLMs, there are hundreds of papers internationally that push beyond R1's recipe… the citation graph is increasingly painted red. This, like many other things, looks like a direct realization of Wenfeng's long-started objectives:
Innovation is undoubtedly costly, and our past tendency to adopt existing technologies was tied to China’s earlier developmental stage. But today, China’s economic scale and the profits of giants like ByteDance and Tencent are globally significant. What we lack isn’t capital but confidence and the ability to organize high-caliber talent for effective innovation … I believe innovation is, first and foremost, a matter of belief. Why is Silicon Valley so innovative? Because they dare to try. When ChatGPT debuted, China lacked confidence in frontier research. From investors to major tech firms, many felt the gap was too wide and focused instead on applications.
NVIDIA’s dominance isn’t just its effort—it’s the result of Western tech ecosystems collaborating on roadmaps for next-gen tech. China needs similar ecosystems. Many domestic chips fail because they lack supportive tech communities and rely on secondhand insights. Someone must step onto the frontier.
We won’t go closed-source. We believe that establishing a robust technology ecosystem matters more.
No “inscrutable wizards” here—just fresh graduates from top universities, PhD candidates (even fourth- or fifth-year interns), and young talents with a few years of experience. … V2 was built entirely by domestic talent. The global top 50 might not be in China today, but we aim to cultivate our own.
BTW: I know @SecureSignals disagrees on the actual innovativeness of all this innovation. Well suffice to say the opinion in the industry is different. Their paper on Native Sparse Attention, pushed to arxiv (by Wenfeng personally – he is an active researcher and is known to have contributed to their core tech) just the day before Wenfeng went to meet Xi, looks more impressive than what we see coming from the likes of Google Deepmind, and it has a… unique cognitive style. They have their very distinct manner, as does R1. They had nowhere to copy that from.
Maybe all of it is not so sudden; the hockey-stick-like acceleration of Chinese progress is a matter of boring logistics, not some spiritual rebirth, much like the hokey stick of their EV or battery sales. For decades, they've been mainly a supplier of skilled labor to America, which masked systemic progress. All the while they have been building domestic schools to retain good educators, training new researchers and engineers without entrusting this to Microsoft Asia and Nvidia and top American schools, growing the economy and improving living conditions to increase retention and have businesses to employ top talent and give them interesting enough tasks… so at some point it was bound to happen that they begin graduating about as much talent as the rest of world combined, a giant chunk goes to their companies, and that's all she wrote for American incumbents in a largely fake, sluggish market. DeepSeek, or Wenfeng personally, is not so much a crown jewel of Chinese economy as a seed of crystallization of the new state of things, after all pieces have been set.
The boost of confidence is visible outside the AI sphere too. I find it remarkable that He Jankui is shitposting on Twitter all the time and threatening to liberate the humanity from the straitjacket of «Darwin's evolution». A decade earlier, one would expect his type to flee to the West and give lectures about the menace of authoritarianism. But after three years in Chinese prison, he's been made inaugural director of the Institute of Genetic Medicine at Wuchang University and conspicuously sports a hammer-and-sickle flag on his desk. The martyr of free market, Jack Ma, also has been rehabilitated, with Xi giving him a very public handshake (alongside Wenfeng, Unitree's Wang Xingxing, Xiaomi's Lei Jun and other entrepreneurs).
…but this is all fragile, because China remains a nation led by the CCP, which remains led by one boomer of unclear sentience and a very clear obsession with maximizing his control and reducing risk to himself. In that, Wenfeng is similar – he's bafflingly refusing all investment, from both private and state entities, because it always has strings attached, I suppose.
“We pulled top-level government connections and only got to sit down with someone from their finance department, who said ‘sorry we are not raising’,” said one investor at a multibillion-dollar Chinese tech fund. “They clearly are not interested in scaling up right now. It’s a rare situation where the founder is wealthy and committed enough to keep it lean in a Navy Seal-style for his pursuit of AGI.”
But you can't just refuse the CCP forever. Reports that he's been told not to interact with the press seem credible; perhaps the story about passports will come true too, as DeepSeek's perceived value grows. In that moment, China will largely abandon its claim to ascendancy, vindicating American theory that Freedom always wins hearts and minds. People, even in China, do not acquire world-class skills to be treated like serfs.
…If not, though? If China does not just shoot itself in the foot, with heavy-handed securitization, with premature military aggression (see them flexing their blue water navy they supposedly don't have in Australian waters, see their bizarre landing ships designed for Taiwan Operation, see their 6th generation aircraft…), with some hare-brained economic scheme – where does this leave us?
I've been thinking lately: what exactly is the American theory of victory? And by victory I mean retaining hegemony, as the biggest strongest etc. etc. nation on the planet, and ideally removing all pesky wannabe alternative poles like Russia, China and Iran. Russia and Iran are not much to write home about, but what to do with China?
The main narrative I see is something something AGI Race: the US builds a God-level AI first, then… uh, maybe grows its economy 100% a year, maybe disables China with cyberattacks or nanobots. I used to buy it when the lead time was about 2 years. It's measured in months now: research-wise, they have fully caught up, releases after V3 and R1 show that the West has no fundamental moat at all, and it's all just compute.
In terms of compute, it's very significant to my eyes that TSMC has been caught supplying Huawei with over 2 millions of Ascend chip dies. This could not have been obfuscated with any amount of shell companies – TSMC, and accordingly Taipei, knew they are violating American decree. Seeing Trump's predatory attitude towards TSMC (them being forced to invest into manufacturing on American soil and now to fix Intel's mess with a de facto technology transfer… as an aside, Intel's new CEO is a former director of SMIC, so literally all American chip companies are now headed by Chinese or Taiwanese people), I interpret this as hedging rather than mere corruption – they suspect they will not be able to deter an invasion or convince the US to do so, and are currying favor with Beijing. By the way, Ascend 910c is close to the performance of Nvidia H800. R1 was trained on 2048 H800s; So just from this one transaction, China will have around 500 times more compute, and by the end of the year they will be able to produce another couple million dies domestically. So, it is baked in that China will have AGI and ASI shortly after the US at worst, assuming no first strike from the latter.
In terms of cyberattacks for first strike, AIs are already good enough to meaningfully accelerate vulnerability search; coupled with the vast advantage in computer-literate labor force (and to be honest, actual state-backed hackers), China will be able to harden their infrastructure in short order, and there's no amount of cleverness that gets past provably hardened code. So this is a very uncertain bet.
In terms of economic growth, this is usually tied to automation. China seems to be on par in robotics research (at least), controls almost the entire supply chain, and has an incomparably bigger installed automated manufacturing base (see their EV factories, which are now also producing robots). They will have OOMs more humanoids and probably faster compounding growth. This more than covers for their workforce aging, too.
Then I hear something about Malacca strait blockade. Suffice to say this seemed more convincing when they really didn't have a «blue water navy», which they now clearly have, contra Peter Zeihan. They're also making great progress in weaning their civilian economy off oil (high speed rail instead of planes, normal rail for freight, EVs again, nuclear and renewable buildouts…) and have stockpiled giant reserves so oil cutoff won't really deter them. They are not quite food-secure but likely won't starve without imports. So blockade is no solution.
Lastly, I've seen this theory that Starship (once it's ready for prime time) provides the US with insurmountable advantage in mass to orbit, thus all the old Star Wars plans are back in action and Chinese nuclear deterrence is neutralized. This doesn't seem feasible because they're working on their own economical reusable rockets – across multiple companies as usual – and are very close to success, and there are signs that this project has very favorable scalability, to the point the US will lose its mass to orbit lead in under three years, or at least it will be diminished. (Personally I think Zhuque-3 is a more sensible design than Musk's monstrosity, though it's just a tasteful interpolation between Falcon and Starship. Learning from mistakes of others is a common late mover advantage).
Sector by sector and attack vector by attack vector, it's all like that.
So… what is left?
As far as I can tell, at this trajectory only China can defeat China – the hidebound, unironic Communists in control, fulfilling the mawkish Western prophecy they try to avoid, bear-hugging to death the young civilization that grew around their mandate and is now realizing its destiny. Confiscating passports, banning open source that widens the talent funnel, cracking down on «speculative investments», dragging them back into the 20th century at the brink of the long-coveted «national rejuvenation».
…Parallels to the US are probably clear enough.
I was not goading, I explained why I will not engage further (it's one thing to disagree even virtiolically, but if someone simply lies about my words, this is obviously a dead end). I don't even see what he replied.
I can't say I even understand why'd you think anyone would find AI outputs interesting to read.
Because they're intelligent, increasingly so.
The argument that cognitive output is only valid insofar as it comes purely from flesh reduces intellectual intercourse to prelude for physical one. At least that's my – admittedly not very charitable – interpretation of these disgusted noises. Treating AI generation as a form of deception constitutes profanation of the very idea of discussing ideas on their own merits.
"Hey I think this argument is wrong, so I'm gonna go use an AI that can spit out many more words than I can."
Really now?
The problem with all this nonsense (yours and @WhiningCoil's) is the projection of the degenerate American condition where somewhat organized 20th century things are next to impossible to do, so you have to rely on Bronze age factors like the proportion of – to a large extent functionally illiterate, obese, criminal and unhealthy, but at least physically mobile – population to kick the can down the road. Infrastructure cannot be adapted. Automation cannot be done, that's fake news, that'd require, like, electric engineering and other nerd shit that doesn't offer good P/E for the financial fraud class to get fat off. The olds will consume the surplus, or else revolt, because you cannot do anything against pensioners (eg provide very cheap industrialized welfare to have them shut up, or as @veqq says, just let them live out their lives in the naturally cheap countryside). Housing bubble will crash and bury the economy, because of course, the debt is secretly much higher than it seems, because Communists always lie with their fake statistics, we learned that from the Soviet Union, the previous “champion” of electronics exports and gacha games.
It's surreal to watch how their nation-scale companies like BYD operate, compare this to the shambolic, truly late Soviet bullshit going on in the US, and then observe all this Gordon Chang tier punditry. Their working age population is right now just short of 1 billion people. They're, it seems, overall higher quality people too, they live longer, ask for less and work harder. Tighter margins all around, higher efficiency of converting revenue to capex… There is, admittedly, a lot of population locked in agriculture and low-productivity sectors, so fine, the effective discrepancy in workforce might be “only” 5x. Do you seriously imagine that economies of scale in a nation with 5x the American workforce will amount to Wile-E-Coyote running off a cliff. Okay, I'll keep watching how it goes.
It seems you've collected every possible cope and trope, congrats.
“immigration”
Yes, Venezuelans will surely bail you out in the arms race with China, if you don't deport them to El Salvadoran prisons first.
Do you believe I would have had any trouble producing as good or better a wall of text myself?
but I don't understand people who aren't willing to choose the lesser of two evils
What is the argument for the need to make a choice? Does the US pay much attention to the war between Congo and Rwanda (despite clearly laying blame on one side)? Actually have you even heard of it?
Any reasonable country in Israel's position would react similarly.
No, not at all. Or only on the crudest level of analysis. There is no way to argue that Israeli policy is the only reasonable response, not even Israelis would say that. There are many possible options. Eg China has shown its take on the situation, in Xinjiang.
Strange argument. That's still hundreds of millions more young people than in the US. They don't dissolve in the shadow of inverted population pyramid, they simply get to solve the problem of elderly care on top of having a productive economy to run.
And all this happens within one "generation" anyway.
I know. This was a completely different America, it's like saying that Moscow was once conquered by Poles or something (Russians are very proud of that episode, thanks to propaganda in history lessons, but obviously there is no memory, institutional legacy or military tradition that survived) – a dim fact people learn in school. America that lives today was born in the Civil War and was fully formed in McKinley's era, probably. Since then, it was straight up dunking on weaker powers. With some tasteless underdog posturing from time to time, of course.
After all, if the American GDP is in some way fake how come the median American can buy so much Chinese production with his or her dollars?
Largely because China (like everyone else) is buying your assets and the USD is the global reserve currency.
Trump is doing what he can to fix this pathological situation, by being laser focused on goods.
That's not terrible prose but how do you square the idea that Trump isn't stupid with the fact that he apparently doesn't know how his beloved tariffs work?
Once again I notice that I am usually right in being rude to people, as their responses demonstrate precisely the character flaws inferred. This is a low-content post in defense of wounded ego, with snappy Marvel-esque one-liners («Won a Nobel prize») and dunks optimized for the audience but next to no interest in engagement on the object level. Yes, ML != LLMs, so what? Are you not talking about Altman and Elon who both clearly put their chips on LLMs? «That was a joke», yeah I get your jokes. Here's one you missed:
It's not the same, though, that's the thing. Returning back to my point that has upset you –
– I meant concretely that this is why leading companies now prioritize creation of training signal sources, that is: datasets themselves (filtered web corpora, enriched and paraphrased data, purely synthetic data, even entirely non-lingual data with properties that induce interesting behaviors), curricula of datasets, model merging and distillation methods, training environments and reward shaping – over basic architecture research, in terms of non-compute spend and researcher hours; under the (rational, I believe) assumption that this has higher ROI for the ultimate goal of reaching "AGI", and that its fruit will be readily applicable to whatever future algorithmic progress may yield. This goes far beyond ScaleAI's efforts in harnessing Pinoy Intelligence to annotate samples for RLHF and you have not even bothered to address any of this. If you think names of Old Titans are a valid argument, I present Hutter as someone who Gets It, gets that what you have a sufficiently general architecture to approximate is at our stage more interesting in terms of eventual structure than how you achieve this potential generality.
This older paper is a neat illustration too. Sohl-Dickstein and Metz have done a little bit of work in non-LLM algo design if you recall, maybe you'll recognize at least them as half-decent scientists.
Now, as regards poor taste in intellectual disagreements, let's revisit this:
My rudeness was not unprovoked; it was informed by the bolded parts. I saw it as a hubristic, elitist, oblivious, tone-deaf insult towards people – scientists – actually moving the field forward today, rather than 8 or 28 years ago, and I do not care that it's slightly obfuscated or that you lack self-awareness to recognize the douche in the mirror but are eager to chimp out at it as you currently do.
yes thanks for clarification, that's exactly as I understood you.
I claim that to the extent that «talent of that caliber» shares your conceit that design of clever new algorithmic primitives for ANNs is «exciting new science» whereas data work remains and will remain ScaleAI tier «mere data engineering, same as always», this talent is behind the times, too set in their ways, and is resting on its laurels; indeed this is the same high-level philosophical error or prizing manual structure design over simplicity, generality and scalability that keeps repeating on every revolution in AI, and that Sutton has famously exposed. They are free to work on whatever excites them, publish cute papers for fellow affocionados where they beat untuned mainstream baselines, or just leave the frontlines altogether, and even loudly assert that they have superior taste if they so choose, which in my view is just irrational fetishism plus inflamed ego; I think taste is to be calibrated to actual promise of directions. But indeed, what do I know. You are free to share their presumptions. New scientific talent will figure it out.
To me it seems like the opposite, we just disagree on what qualifies as discovery or science at all, due to differences in taste.
Egoists gonna be egoists.
Zhean Xu probably. But I think everyone on (Chenggang Zhao and Shangyan Zhou and Liyue Zhang and Chengqi Deng and Zhean Xu and Yuxuan Liu and Kuai Yu and Jiashi Li and Liang Zhao) list could ask for a megabuck total comp in a frontier lab now, and expect affirmative response.
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