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The Crash Everyone Saw Coming
The ubiquity of AI bubble narratives and, more to the point, the incisiveness with which they're oft
cue catalyst to reset the positioning cycle
Here’s something to consider. I asked AI how I could build my own home cluster of LLM’s that would facilitate a bunch of different work tasks. Research, coding, project management, and then a generalist. To build this out at home would cost me roughly $25k in hardware and then it would be a matter of downloading and installing the open source LLM’s that are suited to those specific tasks. I would then be able to leverage those LLM’s without a subscription, at will, on a pretty robust scale. If you properly monetize the use of such a network the returns would justify further investment or a refresh of hardware as needed and still generate profit.
If I can build this for such a low entry cost, anyone else can. So where is the need for trillions in investment to these big players for incrementally better tools? AI is the next iteration of technological advancement it’s railroads, radio, television, the home computer, the internet; all revolutionary technologies, all over invested in, all not worth as much as originally projected when it was all said and done.
But why would you go to all this effort? And the expense isn’t just the hardware but also the expertise to set all this up, which you may or may not have access to. Why do this when you can buy the same thing off an OpenAI type company for $200 a month.
You may want control over your LLMs, the ability to be independent of the big vendors I suppose. Or even because you suspect the costs of subscribing to these services will increase over time.
Will OpenAI ever make money? probably not. So like a lot of railroad, radio, home computer and internet companies in the past it will fold and any residual value absorbed by a survivor. The real questions are: were these tools worth it? can they replace people? If no one has a job any more how does the economy work?
Either this enormous AI investment goes bust and crashes the market, maybe the economy. Or it is useful and everyone is out of work and it crashes the economy. Seems like a lose – lose proposition to me.
Great questions! I have expertise, I have existing LLM subscriptions, and I for some reason enjoy toiling on projects like this so I understand the mechanics of how things work better.
I do suspect that at some point the cost of subscriptions will go up. I view the business model similar to how Uber and Lyft started out and I suspect that the LLM’s will collaboratively raise prices to generate profit. I could also see them exploiting some surge pricing models to help shore up the deficit. I expect the flat rate pricing will go extinct in the next year and then everyone will start getting surprise bills having no idea how many tokens they were actually consuming under the covers of that flat rate.
So I’m not building this yet, but I want to know how to build it so when this announcement comes I can continue to operate my businesses without a sudden surprise in upstream costs taking them out.
Check out Ollama. I haven’t set anythying up yet but was also interested in the idea of creating a local LLM.
For the applications where money can be made (augmenting/replacing human labor, e.g., coding assistant or automated bug fixing, automated handling complaints) accuracy, response quality and hallucinations are critical. Top of the line models have significant quality advantages to open source.
There’s a super bull case of significant replacement of human labor, bull case of increasing adoption and revenue, bear case of resource constraints or slow adoption, super bear case of earnings failing to show up or regulatory issues leading to bust. When your barber could tell you the bear case, shouldn’t all other things equal that be already reflected in the price?
The argument for top of line models holds true for as long as they are able to continue iterating and improving. The reality is that the ceiling on that iterating is closing in faster than they projected. AGI is not going to happen in this iteration of AI so it’s about optimizing accuracy and costs. Those limitations argue against the massive investments being made and at some point future improvement will be shelved to prioritize profit.
It is at this point where open source will once again show its superiority. Open source doesn’t care about profit, it’s community driven and about making the solution better for the community of users. While the private LLM’s will focus on profit extraction, the open source LLM’s will surpass them in accuracy and cost optimizations. Then I expect the cloud providers will take advantage of the open source tools and begin providing access to those LLM’s via a service offering that competes directly with Open AI and Anthropic. This is effectively how AWS built its entire business.
Human labor can’t ever be fully replaced by AI, it can be augmented but I doubt AI will ever be reliable enough to be trusted without human supervision. That and AI has no ambition, it doesn’t care about or understand the problems we are trying to solve with it. Humans still need to direct AI to do something otherwise it will do nothing.
Finally, data is not reliably consistent. Parameters change, schemas adapt, new and unforeseen iterations occur. AI is terrible at managing change, it often ignores things that are blatantly problematic. It over confidently declares victory without ever validating that a problem has been solved. If you think that you can eliminate headcount in favor of operating with this resource as your sole business support staff, you’re in for some major headwinds.
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meant to be a happy face emoji
The music will stop eventually and when it does the only question is how many chairs (safe invests) are left? Possibly only cash, but if inflation reignites (and everything is aligning that it will) even cash will have issues.
That said, there very well may be 10-50% left in the blow off top. Can’t miss that.
The big question to me is: when is peak Nvidia. 63x earnings, on a company that big? Could drop 60% to a “normal” 22x. My guess is Meta will be the first to lower Capex plans which will lead to others backing off as well. Watching for a pre-reporting announcement the days leading up to Metas next few earnings reports. I also have Meta as my most likely to have a Global Crossing style accounting scandal. I don’t believe their earnings. Late stage cockroaches, etc.
This is but the first Tremor!
I was asking an AI what exactly gaining AGI means, it then listed the capabilities that AIs lack. I thought it amusing the 3rd one was Common Sense. That reminded me of an instance where a user asked an AI what they could eat that was high on minerals and the AI suggested a rock. While i believe they will solve a lot of the issues with AI, I think we are still years away from AGI. They are great as assistants, and they will make us a lot more productive, but they are not going to provide the kinds of ROI currently expected because they’re not ready.