Comment by matthewaveryusa
13 hours ago
I'll offer two counter-points. Weak but worth mentioning. wrt China there's no value to extract by on-shoring manufacturing -- many verticals are simply uninvestable in the US because of labor costs and the gap of cost to manufacture is so large it's not even worth considering. I think there's a level of introspection the US needs to contend with, but that ship has sailed. We should be forward looking in what we can do outside of manufacturing.
For AI, the pivot to profitability was indeed quick, but I don't think it's as bad as you may think. We're building the software infrastructure to accomodate LLMs into our work streams which makes everyone more efficient and productive. As foundational models progress, the infrastructure will reap the benefits a-la moore's law.
I acknowledge that this is a bullish thesis but I'll tell you why I'm bullish: I'm basically a high-tech ludite -- the last piece of technology I adopted was google in 1996. I converted from vim to vscode + copilot (and now cursor.) because of LLMs -- that's how transformative this technology is.
> many verticals are simply uninvestable in the US because of labor costs and the gap of cost to manufacture is so large it's not even worth considering.
I think this is covered in a number of papers from think tanks related to the current administration.
The overall plan, as I understood it, is to devalue the dollar while keeping the monetary reserve status. A weaker dollar will make it competitive for foreign countries to manufacture in the US. The problem is that if the dollar weakens, investors will fly away. But the AI boom offsets that.
For now it seems to work: the dollar lost more than 10% year to date, but the AI boom kept investors in the US stock market. The trade agreements will protect the US for a couple years as well. But ultimately it's a time bomb for the population, that will wake up in 10 years with half their present purchasing power, in non dollar terms.
I think an interesting way to measure the value is to argue "what would we do without it?"
If we removed "modern search" (Google) and had to go back to say 1995-era AltaVista search performance, we'd probably see major productivity drops across huge parts of the economy, and significant business failures.
If we removed the LLMs, developers would go back to Less Spicy Autocomplete and it might take a few hours longer to deliver some projects. Trolls might have to hand-photoshop Joe Biden's face onto an opossum's body like their forefathers did. But the world would keep spinning.
It's not just that we've had 20 years more to grow accustomed to Google than LLMs, it's that having a low-confidence answer or an excessively florid summary of a document are not really that useful.
Chatting with Claude about a topic is in another universe to google search.
I default to Claude for almost everything where I want to know something. I don’t trust Google’s results because of how weighted they are to SEO. Being good at SEO is a separate skill set.
The answers are not low confidence, cite sources, and can do things that Google cannot. For example: I used Claude to design a syllabus to learn about a technical domain along with quizzes and test suites for verification. It linked to video series, books, and articles grouped by an increasingly complex knowledge set.
You are putting too much hope on a glorified parrot.
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Is this really true re: "modern search"? Genuine question because this is probably outside of my domain. I'm just trying to think of industries that would critically affected it we went from modern search to e.g. AltaVista/Yahoo/DogPile and kind of coming up empty except in that it might be more difficult for companies that have perfected modern SEO/advertising to maintain the same level of reach, but I don't think that's what you're alluding to?
you can say something similar about google search about 5 years after release too
I think there's a bubble around AI, but I don't think I agree with this argument. Google search launched in 1998, and ChatGPT launched in 2022.
In 2001, if Google had gone under like a lot of .com bubble companies, I think the economic impact visible to people of the time would have been marginal. There was no Google News, Gmail, Android, and the alternatives (AltaVista, Ask Jeeves, MSN Search) would have been enough. Google was a forcing function for the others to compete with the new paradigm or die trying. It wasn't itself an economic behemoth the way it is today.
I think if OpenAI folded today, you'd still have several companies in the generative AI space. To me, OpenAI's reminiscent of Google in the late 90s in its impact, although culturally it's very different. It's a general purpose website anyone with an internet connection can visit, deep industry competitors are having to adapt to its model to stay alive, and we're seeing signs of a frothy tech bubble a few years after its founding. People across industry verticals, government, law, and NGOs are using it, and students are learning with it.
One counterpoint to this would be that companies like Google reacted to the rise of social media with stuff like Google+, but to me the level to which "AI" is baked into every product at Google exceeds that play by a great margin. At most I remember a "post to plus" link at the top of GMail and a few hooks within the contact/email management views. In contrast, they are injecting AI results into almost every search I make and across almost every product of theirs I use today.
If you fast forward 20 years, I would be surprised if companies specializing in LLMs were not major players the way today's tech giants are. Some of the companies might have the same names, but they'll have changed.
> At most I remember a "post to plus" link at the top of GMail and a few hooks within the contact/email management views.
Google probably could have been whatsapp but to push Google+ scrapped a successful gmail chat for hangouts, which you had to visit Google+ feed each time to open at first.
> We should be forward looking in what we can do outside of manufacturing.
For example?
Another thing to note about China: while people love pointing to their public transit as an example of a country that's done so much right, their (over)investment in this domain has led to a concerning explosion of local government debt obligations which isn't usually well-represented in their overall debt to GDP ratios many people quote. I only state that to state that things are not all the propaganda suggests it might be in China. The big question everyone is asking is, what happens after Xi. Even the most educated experts on the matter do not have an answer.
I, too, don't understand the OP's point of quickly pivoting to value extraction. Every technology we've ever invented was immediately followed by capitalists asking "how can I use this to make more money". LLMs are an extremely valuable technology. I'm not going to sit here and pretend that anyone can correctly guess exactly how much we should be investing into this right now in order to properly price how much value they'll be generating in five years. Except, its so critical to point out that the "data center capex" numbers everyone keeps quoting are, in a very real (and, sure, potentially scary) sense, quadruple-counting the same hundred-billion dollars. We're not actually spending $400B on new data centers; Oracle is spending $nnB on Nvidia, who is spending $nnB to invest in OpenAI, who is spending $nnB to invest in AMD, who Coreweave will also be spending $nnB with, who Nvidia has an $nnB investment in... and so forth. There's a ton of duplicate-accounting going on when people report these numbers.
It doesn't grab the same headlines, but I'm very strongly of the opinion that there will be more market corrections in the next 24 months, overall stock market growth will be pretty flat, and by the end of 2027 people will still be opining on whether OpenAI's $400B annual revenue justifies a trillion dollars in capex on new graphics cards. There's no catastrophic bubble burst. AGI is still only a few years away. But AI eats the world none-the-less.
[1] https://www.sciencedirect.com/science/article/abs/pii/S09275...
My point is not that value extraction wouldn't happen, my point is simply that in addition to the value extraction we also made other huge shifts in economic policy that taken together really seem to put us on a path towards an "AGI or bust" situation in the future.
Is that a bit hyperbolic? isn't this just the same as dotcom and housing bubbles before where we pivoted a bit too hard into a specific industry? maybe... but I also am not sure it would be wise to assume past results will indicate future returns with this one.
AI is appealing to the investors not because it solves human problems, but because it solves some of the problems of previous bubbles.
When we wired the world for the Internet in the 1990s, or built railways across the continent in the 1800s, we eventually reached a point where even the starriest-eyed investors could see they've covered effectively the entire addressable market. Eventually AOL ran out of new customers no matter how many CDs they mailed out, or we had connected every city of more than 50 people with steel rail, and you could hear the music was slowing down.
By dangling the AGI brass ring out there, they can keep justifying the expenditure past many points of diminishing returns, because the first thing we'll ask the Omnipotent AGI is how to earn the quadrillions spent back, with interest.
It also has the benefit of being a high-churn business. The rails laid in 1880, or the fiber pulled in 2000, were usable for decades, but in the AI bubble, the models are obsolete in months and the GPUs in years. It generates huge looking commercial numbers just to tread water.
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