The Magnitude of the AI Bubble
apolloacademy.com
apolloacademy.com
On the "AI is just a bubble" side we have: AI is not as good as claimed therefore its impact is not as significant as advertised - ergo it is a passing fad & market caps are inflated.
On the "AI is legit" side we have the counter: AI is as at least nearly as good as claimed and/or has potential to be - ergo the hype is warranted & it's here to stay & market caps are warranted.
I'm in the third camp: impact is not related to merit, and AI is impactful in not-necessarily-positive ways that are societally transformative & will reach far outside any bubble & persist. Probably to a more significant degree even than predicted. And I think this extends far beyond the impact of purely economic knock-ons as seen with some latent impacts of blockchain speculation.
Given that third thesis I don't think the market caps are significantly inflated (beyond any other comparable market caps outside AI): investment is not merit based, it's impact based.
Also, grouping the current "AI summer" in the "2005-" category seems questionable.
and all of this is assuming we don't see the AGI exponential model improvement a lot of the AI bros hype up. If we continue to see improvements on the level of GPT-2 to GPT-3 to GPT-4, then the economy as we know it changes forever. I've already seen research prototypes using LLMs to do automated reinforcement learning and optimization for robotics, so you could rapidly see automation there as well
maybe LLMs will change that: maybe it will help write all those "simple" shell scripts?
I for one look forward to the 737 Max on board flight critical LLM, it'll help with our emissions goals.
The more you play with these tools, the more you realize that they are not nearly as robust as they need to be to have a significant impact on society. We need much more reliability.
We will undoubtedly continue to see new generative AI tools rolling out, but I think the end result is going to be a lot less disruptive than many claimed when ChatGPT was initially released.
Of course if there is exponential improvement all bets are off, but we have had nearly a year of stagnation where GPT-4 hasn’t been beaten. This year we’ll see if this is an actual ceiling.
To hedge against the first possibility, I want to at least have some presence in the stock market. (A broad presence, not only "AI stocks"). If the current AI boom is a bubble, I will stay employed for another couple of decades, and don't need those savings yet.
It's perfectly possible to imagine an economy where most of the productivity goes into catering to the needs of those who hold capital, such as personal consumption, security and investment into activities that increase the value of their capital.
As an example, consider North Korea. Very little goes to the consumption of the regular citizens as most go into the regime and their police and military forces.
With AI, it potentially becomes easier for an elite to do this, as the police force can be robotized, meaning a handful of people (or none at all) can monopolize violence without relying on the support of a large group of humans.
For instance, if democracy collapses, the tech industry could step in as "saviors" and institute some kind of oligarchic republic or empire where the government is under the control of a wealthy elite (or an individual).
Even without a full collapse of democracy, I imagine it may be difficult for a government to fully control industry if AI becomes sufficiently powerful.
It is quite plausible to me that the result will be that international corporations will be able to protect 50% or more of value generation from taxation, by relocating to favorable markets, lobbying, clever lawyers, etc, just like today.
In both of the scenarios above, we may be seeing a massive increase in the gap between those who own capital and those who do not as labor is no longer needed to generate this value.
While it IS conceivable that at least some countries are able to adopt full socialism based on an AI economy, I wouldn't take that for granted.
As an abstract, I would wager AI will take off AND your job will stay relevant.
As an individual, the relevance of your skillset within the professional sphere is more variable - some jobs change more frequently than others, & I do think AI will change the nature of some jobs.
The most discussed example is graphic design: if you're a graphic designer "pre-AI take off", there's a reasonable chance you're balancing a more lucrative corporate slog with a less lucrative creative outlet. I'm banking on AI becoming favoured for the slog, but never approaching anything competitive in the creative space. That will lead to job losses or jobs becoming even more vacuous than before, but as an abstract it won't eliminate the actual creative role.
I suppose I'm in Camp Zero: If you want me to invest, tell me exactly what it does and what you think it can do.
If you have created a better probabalistic language generator, you may have created some business value. But calling it "A.I." and implying that it is "A.G.I." is the kind of deceit practised in a typical economic bubble.
No marketing team has yet had the audacity to claim that A.G.I. == M.L. but I am alas not aware of any robust long-term protection against marketing audacity. ^_^
A.I. remains a theoretical hypothesis, and that is not an opinion regardless of the marketing tactics and money thrown at the question. As for probablistic text generation, generating dubious text at scale isn't intelligence.
It's good enough for chat-bots but will not do for any task requiring serious responsibility.
It may nonetheless prove to be a viable business... or short-term pump-and-dump. ^_^
The AI Hype is boosting all large tech players because investors think they will be in a good position to benefit from it.
It's rumoured/estimated that their AI hardware spending will be over $4Billion next year [1].
I would guess that at some point Apple will release a better Siri or an iPhone with onboard hardware for local LLM capabilities, or whatever to compete with MS at some point.
[1] https://medium.com/@mingchikuo/how-much-does-apple-need-to-i...
Look at the 5 year trend. Please tell me where on that graph the AI investor hype starts. I'll wait.
They tend to lag the hypewave, letting the dust settle, before they move in.
I wonder if it's worth it. Some here will say privacy but in my experience most users outside HN don't really care about that.
In my experience, they very much do care, but don’t understand the ramifications of the convenience, pushed by … um … HN users.
In my experience, once I explain to them, what kinds of risks they take, they tend to batten down the hatches.
I basically fill them in on the kinds of stuff that we all take for granted.
But the folks I Serve, with my software, tend to be a wee bit more tinfoil than most. It's a long story, and not one for this venue.
I'm usually careful to couch things in terms of "It has been my experience," etc.
When some of the best models are open source and allow commercial use (llama 2, Mistral), assuming there is economic value here [1], apple will be in the conversation
[1] feels like a big assumption, maybe! Isn't this just autocomplete? I think good semantic search is pretty valuable (as are other high level semantic concepts beyond similarity), but this is the part that needs more evidence for sure
ok but most companies stand to benefit significantly as soon as they do things that are beneficial to their bottom line that they have not yet managed to do. Sure AI is probably totally a thing that they will do and benefit from but it seems like they have wanted to do and benefit without success for a long time now.
Some artist's works have an interesting dynamic. One such is Andy Warhol.
A great number of his works were bought by a few families in the USA. These were then used as collateral for loans that underpin empires of real estate & businesses. The value of the collateral can never be allowed to sink, and obviously - if it rises further leverage can be created.
Should a Warhol hit the market it will have a bottom price set by these investors. No matter what it will sell for £300k or £1m or whatever, depending on what category it falls into. If the families have to buy it it will enter the collateral pool, if they don't their collateral remains good, and potentially grows.
So Warhol's, at least are just disconnected from their value as anything but a token. I suspect, very strongly, that at least some of these stocks have been given similar dynamics by their ownership and control structures. That's sort of ok while it lasts, but at some point someone may drop the ball and if they do then the extent of the pretend value will become very apparent very quickly.
I'm not saying that the models will make workers obsolete right now, but there are many white-collar jobs/tasks that will be seriously affected the next 5-10 years, all while the workers themselves envision a 20-30 year career doing the same stuff they do today.
If someone had asked me 5 years ago, if these things were possible, I'd react the same way - and say "Yeah, maybe 10-20 years from now", but for me that timespan has effectively been halved after all the progress of 2023.
LLMs give me a similar feeling to some of the car ADAS or Voice Assistant stuff. The first time you interact with the state of the art it is startling and impressive, going to change everything. The rate of change however is not that dramatic on an annual time scale, the rough edges become more obvious and you understand the product is actually quite limited, interest fades.
So, I think a lot of the 1-3 year time frame forecasts are extremely optimistic. However in a 10 year time frame I think we'll have some very interesting viable products. We probably have no idea today what those viable products will look like.
People that think brains are fueled by magic tend to assume AI will never fully take off.
> The dot com bubble was a bubble
There is not a 1:1 relationship between how big an impact AI will have in the coming years and how it will impact the valuation of "AI companies". Even if the progress slows down, it's possible that some companies will find ways to monetize it in ways that generate immense profit, if they can create some moat.
On the other hand, even if AI development takes off beyond expectation, it may be hard for companies like OpenAI or even Nvidia to continue to extract profit if they lose their moat.
In fact, AI itself can potentially cause this, as a sufficiently strong AI may be able to remove most of the costs associated with developing new chips or AI models, to the point where the marginal value of intelligence and compute becomes really low.
Like any bubble/hype wave there’s a lot of low value-add stuff that needs to get washed out of the system before a small number of long term winners are established.
nVIDIA - clearly riding the AI wave
Alphabet/Google - supposedly a mortal risk to their current model (search) so negative for them
Microsoft - Depending on the drama of the week with OpenAI, either the biggest beneficiary or biggest loser
Apple - supposedly not a player but again maybe will do something on-device and leapfrog everyone
Tesla - Depends on the moods of Musk that week and what he blurts out with Cathie Wood
Amazon/Meta - not clear
More like "the ones selling shovels during the Gold Rush", in my opinion.
Google will hopefully reinvent search for post-AI. IF AI is search, AI is indexing. and they are good at it. All the others are using stale data, which won't cut it besides lame limited assistants for specific use cases.
but yeah, more likely they won't do anything good in the end.
Then there are a good number of occupations that require so much memory that even the best of humans are a poor fit. I cant wait for a help desk "employee" who answers the phone immediately, knows who I am, is familiar with all my previous interactions with the company, is able to guess why I would be calling and is allowed to make decisions. It seems much better than having 100 employees who know very little trying very hard to deal with 300 calls with poor results while it costs $1500 per hour * 90 hours per week (135 000)
The topic reminds me of early computers. People could imagine games and some niche company archives. The idea that it would touch everything didn't sound very likely to most.
As for Tesla, I thought the general consensus was that they are behind cruise, who are far behind Waymo on self-driving?
It's a decade ahead of Tesla or Cruise (which just had some drama with their permits to operate because their software is crap.)
We are in a world where self-driving is already a reality. It's just missing the scale aspect.
Meanwhile Cruise use lidars which simplify a lot, because Lidars give out better data. It's still crap compared to Waymo, which can actually drive a car very well. Waymo has already won this battle.
Ride a Tesla using FSD, Cruise and then Waymo, I'm sure you'll be surprised by how good Waymo is.
Tesla's Data faces a similar situation to training a LLM with data from the internet, it will be utter garbage. But if you use less data, but good data + RLHF, you get better results.
They finally found a case where this matters and that’s all that mattered, it’s gonna saturate them for years to come.
Amazon:
- currently hosting AI/ML generated reviews submitted by users of the site[0]
- Using AI-generated review summaries (search for "AI-generated from the text of customer reviews" on any product page)
Meta:
- Currently funneling AI generated propaganda to their users
- Attempting to help funnel AI generated propaganda for their users [1]
- Attempting to help funnel AI generated propaganda for their customers [2]
[0] https://www.cnbc.com/2023/04/25/amazon-reviews-are-being-wri... [1] https://about.fb.com/news/2023/09/introducing-ai-powered-ass... [2] https://www.facebook.com/business/news/generative-ai-feature...
https://eckertzhang.github.io/Text2NeRF.github.io/ + 3d gaussian splatting + time-varying flow on spats (for which transformers would be quite apt, to ground changes based on prompt) is my bet how they could do it.
It helps to think of AI as a discovery, a feat of science we now are unlocking using experimentation rather than a traditional engineering product.
Once you make that shift, the expectations we project on it start being silly. It’s marginally useful as a search engine but discussed like one primarily because Microsoft used they framing as the most business model advantageous they saw hurting google - not because it’s a particularly good fit for that usecase.
Once you understand it as a discovery you understand how silly much of the framing and opinionation really is - the “flaws” usually being projection of expectations used by the companies trying to monetize it.
Just because the technology isn’t fitting their business model framing doesn’t mean it can’t be phenomenally transformative to society and wreck a whole bunch of stuff.
Scientific discovery this year has been breathtaking on every dimension - not even taking hardware into account. And we don’t have a sense of where it ends beyond - not going on forever and not stopping tomorrow. Most people arguing about the technology is from a perspective of todays limitations in regards to todays usecases. And that’s not a good way to approach the problem.
These companies are richly valued primarily because they make massive sums of money and all seem to have bright futures. It's hard to find companies with characteristics like that (if they exist at all) outside of the US.
I don't think so. The mentality in most of Europe is completely different. Most people don't strive for the extreme levels of success of companies like Google, Tesla or Apple, but are happy to merely get rich. Also, most gain beyond "merely rich" tends to be absorbed by governments here, not the founders. That severely hinders rapid growth.
The few people with a similar mindset to Americans either migrate there or end up selling to some American company before scaling.
This is simply a chart of the frothiness of the Magnificent 7 post-COVID in what has been an AI sentiment driven tech rally.
The tech market rolled over after the initial COVID recovery WFH/remote tech rally as money tightened & rates went up. We then rotated into this AI sentiment rally about a year ago.
Whatever you think about about AI it is often important to understand the sentiments driving broad stock movements and when they turn..
3 years ago, these same 7 companies combined were worth… 4 times the Russel 2000 *[0].
So the only story here is that stocks have managed to mostly keep pace with each other before and during the current AI hype cycle.
[0] https://edition.cnn.com/2020/08/20/investing/faang-microsoft...
Not to dunk on the author, but after reading a bunch of literature on it and experimenting with 2 asset bubbles myself, it's quite bad that people dilute the word/economic phenomena without any further research from the past.
What is happening is that we have a great fragmentation of technology due to its many barriers of adoption and commoditization, where everyone will surely try to ride their R&D teams and investments.
At the end of the day markets will pursuit the maximum edge with the cheapest price available (in this case Open Source models, libs, and data(?), and consumers will converge to the cheapest of the best network; so the most rational movimento for a lot of businesses is to bet in something that can give some positive returns instead to miss out and be eaten.
OK, Apple and Tesla are overvalued. They're both struggling with growth. But Microsoft has a market cap of 2.8 trillion and it's still growing at 15% year over year. It's absolutely unreal. Amazon, Meta and NVIDIA are also doing great.
It's easy to yell "bubble!" and certainly it's not hard to find stocks that are overvalued. But it's nothing like yesterday's zaniness of NFTs and DAOs.
I think the primary issue is that during the pandemic we printed a bunch of dollars, and those dollars have been chasing a productive position ever since. AI is clearly a tech that is going to change the world, that much should be clear. But how do you invest in it? I guess throw it in Microsoft and Nvidia.
AI is just a tailwind for these fantastic companies (regardless of your opinion on how they make the money, they ARE fantastic companies, at least in the brutal capitalistic sense - they make a boat load of money!)
I mean these companies have been going up since the 90s. Obviously the author doesn't understand the geometric nature of markets - especially in the case of market leaders.