LLMs have absolutely put us in a similar place. People are getting customers/money by saying "Look at our AI-driven features!" But give it 5-10 years, or maybe less, and that will seem silly. People will be using LLMs for focused use cases and making sure they help the end users. You will be evaluated with a higher standard - of what you actually accomplish with your products. Saying your product is "AI-driven..." will be as stilly as saying your product is "RDBMS-driven..." would be today. Because it will be a foundational piece of the tech stack, not a marketing blurb.
I doubt it will be as big of a bubble as the dotcom crash, though. We may all still fall victim to hype cycles, but it is hard to explain just how low the bar was for investment during the original dotcom bubble. We are collectively wiser now, even as we stumble along the way.
End users don't care whether you solved a problem with clever algorithms, a cluster of hardware, or actual black magic. Just like they don't care if their software is written in Python or JavaScript. Why does anyone think customers care that their product is "AI powered"? Customers don't care, but for some reason, investors do care. Wacky.
https://www.theverge.com/24173858/ai-cohere-aidan-gomez-mone...
The host is clearly trying to push the CEO of Cohere on how all this is going to make money (or just be economic). The CEO is confident, but not in a very specific way. There is a great moment where he is like "we did some proof of concepts with 5 users, and they were pretty good, but when you tell CFOs about the running costs for a full user base, its not viable."
What fascinates me about AI right now is that it seems to have very different economics from traditional software/internet/SaaS businesses. Those business scale super-efficiently. They have some initial startup costs (but still relatively low, especially with cloud providers) and low running costs.
With AI, the initial capital costs to build the model are quite high. And, the running costs to handle queries are also quite high. These companies need to find use cases that generate value significantly in excess of those costs. If those use cases are out there, they must either involve really significant productivity improvements, or the costs have to come down a lot, or both.
All that said, I remember going to a talk by Adobe's founders, in which they pointed out that when they introduced Postscript, the first Apple printer that ran it was only viable because of a last minute drop in memory prices, and when they started building Photoshop, you could fit six (6!) digital images on a powerful computer.
So, I see why the investment is happening, but its a high risk investment right now hoping to identify both high-value use cases and significant cost savings simultaneously.
https://x.com/rao2z/status/1795595801177260311
https://www.youtube.com/watch?v=hGXhFa3gzBs
This Nikhil Suresh article can also be very enlightening:
https://ludic.mataroa.blog/blog/i-will-fucking-piledrive-you...
I think genAI is different as most of the use cases aren't really all that valid for individuals, and it's yet to be seen if companies actually derive benefits from it beyond just growing their ability to spam you with on-demand video, podcast and image generation. I'm not saying Copilot and the like aren't helpful, just that there probably isn't room for more than one Copilot scale product.
Mostly however, I feel that the AI hype is being driven by VCs and companies themselves, and there isn't a network effect to catalyze its growth among consumers, like there was with email.
But chatbots in all the things? That will definitely collapse. I am interested to see what cream rises to the top out of all this and if we'll see an actual bubble burst like we did then.
Even the company I work for, which makes and sells ERP software, literally changed its main domain from .com domain to .ai
There are lots of potential applications for _some_ LLM models. However, if your business is dependent on openai to differentiate you from another business, you're probably fucked.
I don't think nvidia is going to be the only shop in town for much longer. The GPUs are too expensive and too power hungry.
Meta and Amazon are going headlong into AI. Most of the stuff they are embedding into product are _shit_ despite meta accidentally seeding self hosted LLMs with llama "leaking"
Google are probably dead in the water. They have the talent, but not the vision or the leadership structure to drive meaningful change in their products.
Meta is slightly better placed. but they also have no real internal product leadership (shrimp jesus, and all the utter shit changes they've made to the facebook app, and the poison they've been pissing into Instagram. ) However they have got distracted from AR by Mixed reality, and even more recently by AI (ooo I can ask generic questions about a photo, and get a bullshit answer, how great!)
Search and generative AI are eerily similar in my eyes. Most of the best (aka higher quality) responses from ChatGPT are when it is assembling "answers" to things it is just looking up. I remember when a ton of companies were touting their "search" or being adjacent to search, selling search engines, etc.
At some point the tide will go out for companies doing BS "AI" and the capital will have a $0 ROI. Some of this will have downstream effects on underlying APIs and hardware companies much like the dot com era had impacts on companies like Cisco. There will be major players that come out of this with transformative tech that will be useful.
Tech stocks has always had a larger risk than traditional companies so there could be corrections but in general its not like MSFT is going to go bankrupt. Investing in ETFs should insulate against any single company fails. I would be wary of startups promising equity and some IPO, take over the world type of thing, etc.
1 software engineer can become 10x with a better ai.
In the further future 20x.
People are worried about the investment bubble. I’m worried about the employment bubble.
It’s sort of opposing metrics if ai does pan out your job is at risk. If it doesn’t, your ai investments are at risk. I think ultimately it’s your job that will be obsolete.
If one of the AI companies use their windfall investment funds wisely they'd invest in getting fusion power working, something that small scale crypto power wasters don't have the organisation for.
That is, in fact, the only thing I can figure out what Sam Altman needs $7 trillion for.
At least then when it bursts we'd have something to show. And he'd get some place in history.
Do you personally have a job because employers and investors threw money at AI?
When no-one uses or pays for your AI features, will your employer lay you off?
I'm sure the hype bubble will pop, and investments will cool off, but I don't think that will translate to the average CRUD developer being laid off.
Whatever GPT-5 turns out to be will set the tone. If there is a clear increase in intelligence over GPT-4, I don’t think it’s a bubble. If it turns out to be a modest improvement in capabilities (like a GPT-4.5), then it’s probably a bubble.
In other words, if the exponential gains continue as AGI/ASI proponents expect, then there is every reason for these crazy valuations to be real.
That said, I think most these AI startups which are simply wrappers around an LLM are obviously going to die either way.
- The current "AI" stuff is truly useful. So it isn't just hot air, like "web3" was, for example. - Does that justify Nvidia's crazy market cap? I don't think so.
> "It's just money; it's made up. Pieces of paper with pictures on it so we don't have to kill each other just to get something to eat. It's not wrong. And it's certainly no different today than it's ever been. 1637, 1797, 1819, 37, 57, 84, 1901, 07, 29, 1937, 1974, 1987—Jesus, didn't that fucker fuck me up good—92, 97, 2000 and whatever we want to call this. It's all just the same thing over and over; we can't help ourselves. And you and I can't control it or stop it, or even slow it, or even ever-so-slightly alter it. We just react. And we make a lot of money if we get it right. And we get left by the side of the road if we get it wrong. And there have always been and there always will be the same percentage of winners and losers, happy fuckers and sad suckers, fat cats and starving dogs in this world. Yeah, there may be more of us today than there's ever been, but the percentages—they stay exactly the same."
See:
* https://en.wikipedia.org/wiki/Technological_Revolutions_and_...
* https://www.pwlcapital.com/investing-technological-revolutio...
Let's say AI isn't as revolutionary as we thought, but it does make the average office worker %15 more productive. Surely that's worth a lot. And surely that means every single company with office workers will be spending money on it, no?
Maybe it's a bit like the bubble of the PC market, in that there is real value, and money to be made, but when it all shakes up there will only be a handful of big winners.
How long it continues is anyone's guess.
However like any boom and bust cycle, the losers could be AI startups building thin layers on top of apis.
When OpenAI becomes Google and loses product sense, they'll be bust.
Mobile and smart phones put the internet in our pocket.
I dont see how gen-ai is going to change any of our day-to-day workflows. Hence I believe it to be a giant bubble. It will help some small sectors (education, customer support) but the overall impact will be much smaller than dotcom or mobile.
Just like those here are old enough to remember the Cisco stock price and Intel's stock price in the 1990 when the internet was hyped up.
It is unsustainable and insiders will start or already have been taking profits out to derisk and anticipate any outside market forces that will correct these prices such as; for example: A declaration of war and an invasion.
This will be no different. Even the Nvidia CEO is taking out profits. Soon employees will do the same (and are already doing so), then Pelosi will do that ahead of the event.
Look at the performance of th qqq certificate, which invests in the largest 100 non-tech companies in the Nasdaq:
https://www.google.com/search?q=qqq
And click on "max". It goes from $52.97 in May 1999 to $485.51 today.
That is an annualized ROI of 9.21%. A better performance than many other market indices had over the same time.
Something which I'm kind of convinced about though is that I think after this we're going to see an end of an era in tech in that I don't foresee another "next big thing". Feels like we've kind of played all of them out, they've all more-or-less matured. Like, maybe there will be another hype cycle in AR/VR, but unless Apple really outdoes itself with the next Vision Pro launch I don't foresee it being all that buzzy. Hell, even if Apple launches a headset that's both affordable and ridiculously good, I still don't foresee AR/VR being all that buzzy.
And if AI really does live up to the hype, well, there still won't be a "next big thing", just for an entirely different reason.
I'm not personally upset about it. There's still a wealth of good ideas out there to chase that don't have the scaling potential to attract VC interest but nonetheless could potentially make a decent chunk of people rich and employ a lot of people. Perhaps society will give more of its collective attention to the problems that aren't so easily solved with a mobile app.
But AI hype in 2024 is not even close to dotcom hype in early 2000.
During the dotcom bubble, companies IPOed with no revenue and no profit. In 2024, OpenAI is probably at $2 - $3 billion in revenue right now. All the companies benefiting the most from AI are established companies such as Microsoft, Apple, Nvidia, TSMC. We haven't had any pure AI companies IPO with no revenue in 2024 as far as I know. Heck, I'm not even sure if there is an AI company that IPOed in 2024.
I think AI hype is in the 1996 equivalent of hype - not 1999.
We're at the baby steps of the LLM revolution. There are so many things I want an LLM to do but it hasn't been done yet. I want Slack to be integrated with an LLM so I can ask it business logic discussions that I can't find using its search engine. I want Outlook to summarize long email chains that I just got cc'ed into. I want an powerful but private LLM to ingest all my digital data so it takes into account all those things before doing things for me or answering my requests.