Wheatman

I guess It is less haha funny, and more depressing funny.

Multi-billi9m industry sure, but it doesnt justify near trillions of spending and hype.

AI is slightly behond search engines/internet in terms of usefulness, and even that was bubble, and the sad thing is we already had a few AI wonters before simply due to the cost of research, if they end up losing money, or worse we end uo in a recession because of AI hype, research and funding are gonna dry up ridiculously fast, which wouod hurt not only AI but most of the tech industry short term.

Well at least the us has recovered enough to absorb that fall, i hope.

Well, apparently it has ended up being true.

The orion model underperformed expectations by a lot, and even fell beh8nd chatgpt-4 in programing tasks.

Why does your reply feel like it was edited by an llm?

Still, feels like we are at risk of another AI winter soon, especially with such a huge bubble being built around it this time.

Here to hoping the US wont hit a recession bceause of it.

Well uh, I dont know if this is bad news or good news but GPT-5 might never be released, their "Orion" model seems to be barely better if not worse than GPT-4.

Here:https://the-decoder.com/openais-new-orion-model-reportedly-s...

Interestingly enough, the new "Orion" model by OpenAI doesnt outperform, and even sometimes underperforms in programing tasks, when compared to GPT-4.

There is an interesing discussion about it here:https://news.ycombinator.com/item?id=42104964.

But why would you spend billions training an llm, when it barely shiws any improvement over the previous model.

Unless OpenAI is willing to do something desperate, the best they have right now is what llm are, and so the cost would be in maintaing them. If you already paid for a bunch of H100's to train, there is little incentive to move away unless you know TPU are going to be significantly cheaper to run, cheap enough to explain the new cost of buying them.

This is ignoring the giant bubble that has balooned out of AI hype, which if popped would be disastorous for the comapnies most invested in the industry. Nvidia has a P/E ratio of 60-70, if they dont get enough future growth to explain it, they could lose a third of their pricing if not more.

>Those GPUs also cost a bomb to run. LLMops isn't super easy, I am working with a large OEM manufacturer rn as a consultant and they are also experimenting internally with LLMs, but they have enough resources to run those models. I don't see smaller companies having enough resources to experiment with various models at scale like they are.

True, I sorta conflated running llama on your pc with what large comapnies.

Not to mention how I was somewhat conflating chat-gpt the product with OpenAI the company, What i argues was that soon enough ChatGPT itself won't be that special when comparing it to open source models.

OpenAI the company is in the weird position of both having a moat, and yet drowning in it: They have a huge advantage in skilled experts, engineers, and know-how to get a first mover advantage, especially now that they are practically another subsidiary of microsoft.

But they also have the notable disadvantage of spending billions upon billions of dollars developing a model that in the end is little to no better than what one could get for free from the internet.

A small company with a few dozen specialist could present a comparable product at a fraction of the cost, simply by not having to pay back the cost of developing their own model.

I feel like OpenAI would end up in a weird place in soon, maybe something like a cloud provider for companies, usefull for smaller ones where brand recognition and reliability matter, but having to compete with more specialised companies offering a similar service using llama, And at some point large companies could just build their own servers with open-source LLM's with their own servers and their own teams, bypassing OpenAI entirely.

The biggest winner here is those new small AI consulting teams that didn't have to spend nearly as much on finetuning the models that are already made.

You probably know way more about these things than me, what do you think of this prediction?

It doesnt sound as terrible for developers as I first thought, though it pains me to see how many people quit/never went into software development due to the AI hype, we lost a third of our class from 2023, and I assune things are even worse in america/developed countries.

Open AI is already running a huge loss currently, and it isnt like o1 is cheap to run either.

I wonder what price these llm's can be run in order to be profitable,and whether just running your own model would be worth it.

Maybe it could be even cheaper if youre willing to fall behind on R&D, but keep in my mind that everytime openAI invented something, it was quickly copied by its competitors.

While There is money to be made in further integrations, hell thats where i see most of thr priductivity increase from these tools coming from, OpenAI has already spent billions developing these tools, money which they have to pay back in some way soon.

This is also ignoring the giant elephant that is open models, soon enough models like Llama, would be able to match or even surpass what ChatGPT, by which point why would any sufficently large company pay for API when they can run their own model, especially when all those GPU used for training flood the market.

But then again, plenty of large comapnies still use aws, even when it makes no sense to go serverless, so they might have a market to capitalise on.

We live in interesting times for tech, moores law is dead, intel is falling, layoffs are everywhere...

I sure picked the best time to go to university for Computer Science T-T

The thing with AI isnt that it doesn't have a whole lot of use cases,it is thr fact that its use cases dont justify the hype or investment it has gotten.

It is somewhere in between Crypto and dot.com as far as bubbles go, and as open models catch up with closed source ones, it seems less and less likely that yhese companies are ever gonna make back the monry they spent, at least short term.

They are already bleeding money from what I'm aware, so they either have to jack up prices so much they could make up for 5bn in losses, or Sam Altman manages to convince investors to contribute to another funding round.

Considering he was willing and Delusional enough to ask for 7T USD for AI chips, Im sure he would try.

It is just the kind of scifi trope that wouod get investors invessting.

OpenAI barely has any moat, I Seriously wonder why no one is talking about hoq much open weighted models are getting to the closes source ones, they need invesotr cash to build something that would let them stabd out, otherwise no one would bither paying for OpenAI API when you can just run your own model.

How woukd you even put ads into an llm, especillay an open weighted one?

Maybe thats why they are talking about a fully AI generated feed, despite how unpopular that is with users.

Dont have to pay tge content creators a share if you produce all the content, lol

Another thing this paper mentions is how Open models like llama are quickly closing in on Closed source ones.

I wonder what kind of future llm have, since soon with a good enough GPU you can run your own model that is as good as the paid one(which i expect the price of to rise considerably once investment dries up)

One option is running ads i guess, though i question how that would even work.

This seems to be a prevalent problem that people bring up.

I remember there was a forum post about it that got a lot of flack, but maybe they were onto something.

Here it is: https://community.openai.com/t/did-chatgpt-4o-get-progressiv...

Cheked, it is True,I rarely see or hear about iphones, so i just heard they sold badly and made a connection.

Though why was that fact never mentioned in the adverts? Or did i just not notice?

My guess is that they changed it from our definition of AGI to their own:

Artificial.

Good enough.

Intelligence.

Besides, most people i know that use AI say they would get much more out of it with smaller more specifically trained models than the all knowing one we have now, but that depends.

It already is harming sales apparently, little to no of the reviews on the new iphone even mention AI even though they spent a lot of money marketing for it. It even seems to hurt its sales.

I wouldn't bet on a full-on ai wonter soon, but it starting to seem more and more likely the more hype companies are trying to build on it.

Note: This isn't to be confused with model collapse (the rapid deterioration of models trained on their own data), this paper talks about neural collapse (Read here:https://medium.com/ai-assimilating-intelligence/what-is-neur...)

My honest guess is that they want to use AI generated content to lie more truthfully.

I imagine 2 or 3 years from now, major social media companies are gonna keep claiming stuff like "Over 1 billion unique images uploaded each month" or "We have over a million new tweets per month", while most of that content is AI generated.

Advertisers would eat that shit proudly.

My guess is that they counted each line of code made by an engineer using AI coding tools.

Besides, even google employees write a lot of boilerplate, especially android IIRC, not to mention simple but essential code, so AI can prevent carpal tunnel for the junior devs working on that.

It is great for cheating at school, at least.

And maybe boilerplate.

2T is still ridiculous.

My guess is that since they are so sure of AGI being achievable soon, that they think they can squeeze out any amount of money they want out of investors.

After all, AGI would be worth way more thab 7T right?

>"Open AI CFO".

While i don't want to say completely ignore what she says based on her postion, the fact that she is the Chief "Financial" adviser should atleast raise a few red flags when considering her words on the matter.

[PS:Why does your comment feel like an SEO article? That hastag feels so random?]

While i somewhat agree, the real sad thing is that 10% is real and usefull, yet it gets overshadowed by that 90% hype based products.

Think of how mych money is being thrown at hype products that could have been allocated to the next Cancer detection AI, or AI prosthetic, but instead these things have to take 2nd place behind stuff like the Rabbit R1, or Devin, or the AI washing machine.

At least their is a somewhat usefull product this time, unlike with NFT.

Besides, i was like 3 when 2008 happened, and it dodnt really happen in my country, so it would be nice to experience what a real recession feels like :v

Interesting read.

I noticed something, you achieved near 100% accuracy on most domains in every domain but scientific which made me wonder, how much is that could be due to how "strict" and "profrssional" these papers could be, or maybe how a slightly disproportionate number of the training data for these LLM could be from science based articles and papers, as they are generally viewed to be "high quality"

Interesting read either way, best of luck on your project (: