Posted by saigrandhi 1 day ago
In the case of AI coding, yes: AI does exceptionally well at search (something we have known for quite some time, and have a variety of ML solutions for).
Large codebases have search and understanding as top problems. Your ability to make horizontal changes degrades as teams scale. Most stability, performance, quality, etc., changes are are horizontal.
Ironically, I think it's possible that AI's effectiveness at broad search give software engineers additional effectiveness, by being their eyes. Yes, I still review every claude code PR I submit, and yes, I typically take longer to create a claude code PR than a manual one. But I can be more satisfied that the parallel async search agents and massive grep commands are searching more locations, more quickly, and more thoroughly than I would.
Yes, it probably is a bubble (overvalued). No, that doesn't mean it's going to go away. The market is simply overcorrecting as it determines how to price it. Which--net net, is a positive effect, as it encourages economic growth within a developing sector.
Bubble is also not the most important concern--it's rather a concern that the bubble is in the one industry that's not in the red. More important to worry about are other economic conditions outside of AI and tech, which are causing general instability and uncertainty rather than investor appetite. Market recalibrating on a developing industry is fine, as long as it's not your only export.
Before ChatGPT, I'd guess that the amounts of money poured in both of these things were about the same.
All nondeterministic AI is a demo. They only vary in the duration until you realize it’s a demo.
AI makes a hell of a demo. And management eats up slick demos. And some demos are so good it takes months before you find out how that particular demo gets stuck and can’t really do the enterprise thing it claimed to do reliably.
But also some demos are useful.
Fusion power on the other hand has to work as it doesn't make money until it does. You can't sell futures to people on a fusion technology today that you haven't yet built.
You will get a different result if you revolutionize some related area (like making an extremely capably superconductor), or if you open up some market that can't use the cheapest alternatives (like deep space asteroid mining). But neither of those options can go together with "oh, and we will achieve energy positive fusion" in a startup business plan.
Investment in fusion is huge and rising. ITER's total cost alone will be around $20b. And then there's Commonwealth Fusion, Helion, TAE and about a dozen others. Tens of billions are going into those efforts too.
See, every fab costs double what the previous generation did (current ones run roughly 20 gigadollars per factory). And you need to build a new fab every couple of years. But, if you can keep your order book full, you can make a profit on that fab- you can get good ROI on the investment and pay the money people back nicely. But you need to go to the markets to raise money for that next generation fab because it costs twice what your previous generation did and you didn't get that much free cash from your previous generation. And the money men wouldn't want to give it to you, of course. But thanks to Moore's Law you can pitch it as inevitable, if you don't borrow the money to build the new fab, then your competitors will. And so they would give you the money for the new fab because it says right on this paper that in another two years the transistors will double.
Right now, that "it's inevitable, our competitors will get there if we don't" argument works on VCs if you are pitching LLM's or LLM based things. And it doesn't work as well if you are pitching battery technology, fusion power, or other areas. And that's why the investments are going to AI.
Just because YOU find the technology helpful, useful, or even beneficial for some use cases does NOT mean it has been overvalued. This has been the case for every single bubble, including the Dutch Tulip mania.
> during the internet bubble of 1998-2000, the p/e ratios were much higher
That is true, the current players are more profitable, but the weight in SPX percentages looks to be much higher today.
(I think a reasonable argument can be made that P/E ratios today should be higher than the historical mean, or rather that they should have trended up over time, based on fundamental changes in how companies compensate their shareholders.)
If Elon tried to sell every share of Tesla tomorrow, he would get a lot less than the face value of all his shares.
So in other words, there doesn't need to be that much currency, just that much hype.
AI's potential isn't defined by the potential of the current crop of transformers. However, many people seem to think otherwise and this will be incredibly damaging for AI as a whole once transformer tech investment all but dries out.
We're too easily fooled by our mistaken models of the problem, it's difficulty, and what constitutes progress, so are perpetually fooled by the latest, greatest "ladder to the moon" effort.
Looking at your history it's something like "I tried them and they hallucinate" and, possibly, you've read an article that talks about inevitability of hallucinations. Correct? What's your reason for thinking that hallucination rate can't be lowered to or below the human rate ("Damn! What I was thinking about?").
It's no wonder that the "AI optimists", unless very tendentious, try to focus more on "not needing to work because you'll get free stuff" rather than "you'll be able to exchange your labor for goods".
How about when offices went digital? All the file runners, calculators, switchboard operators, secretaries, transcribers, etc. Where are they now? Probably not working good jobs in IT. Maybe you will find them bagging groceries past retirement age today.
But this is only if the trend-line keeps going, which is a likely possibility given the last couple of years.
I think people are making the mistake that AI is a bubble and therefore AI is completely bullshit. Remember: The internet was a bubble. It ended up changing world.
Or, you skip all that and just put it all in an S&P 500 fund.
Because of the way the AMT (Alternative Minimum Tax) worked at the time they bought the stock, did not sell, but owed taxes on the gain on the day of purchase. They had tax bills of over $1 million but even if they sold it all they couldn't pay the bill. This dragged on for years.
https://www.latimes.com/archives/la-xpm-2001-apr-13-mn-50476...
That lesson is part of why I dump my company's shares the first chance I get.
The bubble burst in 2000-2001, Google IPO was in 2004.
The S&P500 also did not do very well at the time.
That is the problem with bubbles.
Let's just say the AI bubble started in 2023. We still have about 3 years, more or less, until the AI bubble pops.
I do believe we are in the build out phase of the AI bubble, much like the dotcom bubble, where Cisco routers, Sun Microsystems servers... etc. sold like hotcakes to build up the foundation of the dotcom bubble
Minimum 3 years and at a hard maximum of 6 years from now.
We'll see lots of so called AI companies fold and there will be a select few winners that stay on.
So I'd give my crash timelines at around 2029 to 2031 for a significant correction turned crash.