Of course they don’t, that’s why they’re building bunkers. Thinking it’ll slow us down, as we’ll open their bunkers like cans of tuna. A bunker only works for so long, then the survivors start hunting for them like delicious shipwrecks.

And that's why they're trying underhanded tactics to inflate earnings and IPO directly into the index funds, so every American's 401K will legally have to rebalance and invest in them. They're racing to fleece retirement funds before the bubble bursts.

Not financial advice, of course :p but people should really consider getting their stuff out and into self-directed funds or whatever it is US people do to not depend on auto-allocated funds.

Money printer go brrrrrrr

That's simple, because the people making laws and overseeing the adherence to those laws are great buddies with those same CEOs.

So, corruption.

Though i do agree with you, there is no such thing as too big to fail. Government shouldn't have any handouts to corporations.

Both Uber and Spotify (and AWS too) had economics of scale going for them - the more users they have, the more the infrastructure could be leveraged. This does NOT work for LLMs. More users means using more compute, more advanced tasks (like coding) uses exponential amounts of compute. A single user running a complex task can make 8 Blackwell GPUs run full tilt, and you don't even have any guarantee that the output will be useable.

There are a few narrow areas where LLMs might be successful, like scanning for security vulnerabilities or searching large amounts of documents. The massive amount of money invested will never be recouped with these usage scenarios.

Although, most people aren't talking about Alphafold when they're talking about AI. They're usually specifically referring to the generative transformer models that are currently all the rage.

I doubt anyone would care too much about a linear regression model, or multi-layer peceptron , for example.

solving something like the Erdős unit distance conjecture

Tell me you listen to media news cycle without understanding what that actually mean without telling me that.

That's not exactly what happened, isn't it.

Not to bring up what’s also been accomplished in cyber security

Multiple new vectors of attacks, automation of attack pipelines...

Imagine having a streaming service so bad it fails twice

I love that nobody watched anything on Yahoo! Screen except for that one season of Community

Late to streaming? Netflix was the first big time streaming service that I ever heard of. The main reason their streaming service was able to take off like it did is that nobody else of significance thought that streaming was worth pursuing. What other companies were offering streaming services at anything approaching scale before Netflix?

late to streaming, but practically the first subscription based system to watch movies/tv online.

First years of Netflix were the best, the product began degrading quite early on. but that was mostly companies realizing that instead of licensing their content on Netflix, they can make their own platforms.

"I need a triple A cooking game with blackjack and hookers, all written in SQL."

"But that's a database langu-"

"Did I stutter?"

Agreed, but hey no need to pile the the hate on Pascal, modern ones like FPC/Lazarus are pretty cool actually :)

We need this in Esperanto and the lost languages of Lutruwita.

OpenAI and Anthropic aren’t less evil than Google.

They're all evil, so we just have to exploit the ones that offer us some value. If Google is cheaper, and has the ability to damage the others, then Google it is.

Google is shaping up to fare better than the others, but I dont think that means success. They, too, are spending more than its making, just at a less drunken rate than some competitors.

Anthropic is doing the same too. SpaceX over here providing the shovels and pans for the modern day gold rush, sheesh.

That's definitely costing them more than running it on their own hardware, but it doesn't mean AI is costing them more than the AI startups. Anthropic for example is already paying SpaceX 1.25 Billion a month for compute, and has agreed to pay Google 200 billion over the next 5 years for access to Google's compute and TPU chips.

Google's deal with xAI specifically lets them terminate the deal with 90 days notice after the end of the year. Google is also investing heavily in building new data centers with their hardware. I'm assuming this deal means they've eclipsed their current TPU capacity, and are just looking for a short term bandaid until they can catch up with their new constructions.

Claude just kills the other models, it's not close. Microsoft could ban claude extension from VSC tonight and ill start using command line Claude tomorrow. There's just no comparison right now. Itd be like Microsoft trying to ban NVidia gpus from Windows, they'll just lose.

They have big plans to build more data centers for themselves, so they definitely want more compute than the have access to right now. But even if they're paying more to rent xai compute, they're still paying less overall for hardware/access than their direct AI competition.

The thing is this really depends on the speed of some financial events, not some technical failing.

Notably, if OpenAI has to cancel any of their commitments to buy hardware because they find they have neither the money nor can secure even more debt to cover, that event would potentially cause the bubble to pop, even for hypothetical companies that may have been more responsible and might have a viable business approach. Those commitments are coming up, and a lot of analysis struggles to see how they will fund those commitments.

The thing with this bubble is that the investors don't get the nuance and will flee at signs of trouble in any of OpenAI, Anthropic, or a handful of others, and Altman's leadership has made trouble at OpenAI very likely, but the investors don't believe it and won't believe it's unique to OpenAI, even if it would be.

The bubble will pop, I think a lot of people are just baffled by how big it's getting.

What people? All the credible people I read say that things fall apart Q2/Q3 2027 as debt and profit obligations are due.

The only thing that changed is now there is an energy crisis coming, so it's possible that might force the bubble to pop sooner if all the systemic risk aligns.

Only because the hype has lasted longer than expected. Now that IPOs have been filed, the AI companies (Anthropic, OpenAI) released statements about slowing down to protect us. They're setting the stage for lower growth. But I think you should invest every penny you have into "SpaceXMegaTwitterSuperCarAI".

To break even on operating expenses, not even counting debt payments, depreciated capital value, or future recapitalization costs.

This is why IMO blitz scaling is dumb when your service is a commodity. I'm not any more loyal to Uber than Skip. If more investor money goes into making a cheaper meal or ride on Skip I use that. Consumers are mercenaries about that stuff.

The "blitz" part of blitz scaling assumes your customers can't move.

An older co-worker seems to ask AI for help during work, we are blue collar. But the Owner of the company does not seem to use it whatsoever.

I ask Claude on occasion, to see if it will say something smart (it was mostly useless as fuck).

Exactly, these companies will keep leveraging more and more because they know the govt will step in and print whatever number of trillions of dollars needed to fix the accounting. Then they'll tell us "core" inflation is only 2.8%.

Would be nice to see that used hardware for sale rather than it being junked as a writeoff.

I find that hard to believe, I recently had to uninstall co-pilot after it weaseled its way into my search bar. Its not an exageration to say that my PC literally ran cyberpunk 2077 with pathtracting better than it ran the fucking windows search bar with co-pilot.

It is sorta. Training is orders of magnitudes more intensive than inference, but we infer billions of times within a model generation.

ax+c

You just need a better prompt, bro

I was using a set of template files designed for LLMs to review that project. It is absolutely the fault of Claude that it tools me to do something one way, then told me to try another and when I reverted it said it was the optimal approach.

Where I find it helps is in getting initial starts and as a start to code review. But in both cases they aren't ever operating on their own and their feedback is filtered through myself or another senior dev.

Lots of anti-ai people in this thread it seems. I get it - personally I HATE the fake image generation! But I have to agree with you in terms of coding that using LLM's correctly can offer huge benefits.

Modern harnesses are getting more and more sophisticated and your milage varies depending on how well you use them (like any complex tool). At the end of the day it's still up to the developer to take the code and make sure it's correct - no different from before where we used to copy code from Stack Overflow or other examples and modify them for our own use.

One thing I have to add - I honestly don't understand why anyone would use Claude or chatgpt at their ridiculous prices when DeepSeek exists..

I have found the opposite. Codex spits back mostly useless code that is twice the length it needs to be with a bunch of unessesary stuff and Claude is the only thing I get useful output from.

You're right if we're talking about the entire population of Earth. With these local models though, other people have already done all the hard stuff. Anyone with an RTX card and just a minimum level of patience can get going.

If you were paying the real price it would be 2 grand a year though. And in 5 years that 15k graphics card will be $200 and sip on electricity by comparison.

There is a middle ground. Crypto farmers have transitioned into running AI workloads for money. There are things sort of like folding@home but you can let people use your GPU and you earn tokens which are used to buy compute or sold to people who want to buy compute on the network. So you can setup a bigass open source model for private on demand use it's still not cheap but a lot closer to reality for a lot of people than a 15k initial purchase.

I've got an old 1060ti in my server. Ollama shares it with just a couple other containers. Electricity here is majority hydro with some natural gas, $0.08/kWh.

It's a little slow, but I can comfortably run qwen3:14b. Of course that's not all done on the GPU, a large part is offloaded to server ram (generally 32GB available so more than enough headroom)

My server and my gaming PC combined last month came out to $13.32

lfm2 works like greased lightning on the NPU built into the current macbook M5.

I remember my computer not being fast enough to even play an MP3 file. Two years later, my computer was capable of running 3D accelerated games, browsing the internet at broadband speeds and playing videos.

Sometimes technology advances fast. We could be entering such an era as there are major investments taking place and global competitors will rise to the occasion to market these to a broader audience.

I think it will be entirely possible for consumers to use a decent LLM on their computer in a few years time.

Profit ≠ success

Edit: to clarify, even if profitable it will still be a failure of society in some way/shape/form.

A large majority definitely hate it to the point of having blinders on for sure.

On one side you have corpo hype/lies, and the other is LLM is slop garbage and terrible for anything, also developers wrote perfect code before LLMs and now everything that breaks is AI slop caused.

Why not? Why Microsoft develops it's .NET ecosystem? Why Google develops Go/Dart? It costs them lots of money and they give it for free.

The answer is: they don't earn money on it directly, but these tools are a way to tie programmers to their cloud services. If you use .NET you'll probably end up on Azure. If Go - probably you'll use GCP.

So I suspect the same will be with LLMs. At some point they will say: "hey, you can use this LLM however you want, but as you are already using it, then you may want to know our platform is optimized for it"

Because when you're old enough to remember what AIM chat it's could do 25 years ago, it stops being impressive what today's chatbots can do...

C’mon, that’s just silly.

You're right that people can and do max out the expensive plans. Its very difficult to say how often. I just think a majority of anthropics customers are businesses, who often pay per token for easier scaling etc. According to the company, enterprise employees use about $150-$250 per month, (possibly max plans have similar use, which would support your view) but thats in API tokens which they probably have big margins on, so it's less likely anthropic are burning money on inference. If you want to convince me otherwise, its not enough to say that it can happen, it has to be frequent enough to outweigh the B2B sales. They are however likely losing money overall due to training costs etc.

I mean it's not very hard to use up your Claude Max plan, but I find it hard to believe a majority of users do so consistently.

The anecdotal evidence does point toward folks using up their plan, every month.

I see plenty of script kids post "development on X is paused until next month when my tokens reset".

Of course, I have no way to tell what percentage of script kids are running out of their token limit every month.

All I can conclude is that using the full allowed amount is pretty common.

Then they will go bankrupt, their assets and IP will be sold for pennies on the dollar, and those that follow them will be able to make a profit serving the established demand without the debt burden of the R&D that created it. It's a common pattern for first-movers to not benefit from the industries they create.

I think a lot of people just want to conclude that AI is going to "go away", and latch on to beliefs that lead to this conclusion.

I think a lot of AI companies are likely to "go away." That's what happened when the dot com bubble popped, if there is indeed an AI bubble then we'll see a similar massacre at the stock market. But the technology itself is sound, just like how the basic idea of e-commerce didn't vanish with the dot-coms.

I've been doing a lot of fiddling with locally-run AI models and I'm thinking that the local open-weight models will be good enough to perform 90% of the tasks that most of us are currently depending on those big companies like Anthropic and OpenAI for. That's going to let a lot of the air out of them when the applications catch up and start using those cheaper commodity-level models instead. For now it's easier to just throw an OpenAI API key into your application and let it use the heavyweight models for everything, a powerful model can do simple tasks just as well as a simple model. Most tasks are simple but adding the ability to distinguish those tasks from the complicated ones is hard.