[shmatt]

Im old enough to remember the mystery and hype before o*/o1/strawberry that was supposed to be essentially AGI. We had serious news outlets write about senior people at OpenAI quitting because o1 was SkyNet

Now we're up to o4, AGI is still not even in near site (depending on your definition, I know). And OpenAI is up to about 5000 employees. I'd think even before AGI a new model would be able to cover for at least 4500 of those employees being fired, is that not the case?

[pants2]

Remember that Docusign has 7,000 employees. I think OpenAI is pretty lean for what they're accomplishing.

[steamrolled]

I don't think these comparisons are useful. Every time you look at companies like LinkedIn or Docusign, yeah - they have a lot of staff, but a significant proportion of this are functions like sales, customer support, and regulatory compliance across a bazillion different markets; along with all the internal tooling and processes you need to support that.

OpenAI is at a much earlier stage in their adventures and probably doesn't have that much baggage. Given their age and revenue streams, their headcount is quite substantial.

[shmatt]

If we're making comparisons, its more like someone selling a $10,000 course on how to be a millionaire

Not directly from OpenAI - but people in the industry is advertising how these advanced models can replace employees, yet they keep on going on hiring tears (including OpenAI). Lets see the first company to stand behind their models, and replace 50% of their existing headcount with agents. That to me would be a sign these things are going to replace peoples jobs. Until I see that, if OpenAI can't figure out how to replace humans with models, then no one will

I mean could you imagine if todays announcement was - the chatgpt.com webdev team has been laid off, and all new features and fixes will be complete by Codex CLI + o4-mini. That means they believe in the product theyre advertising. Until they do something like that, theyll keep on trusting those human engineers and try selling other people on the dream

[scarface_74]

Yes and Amazon has 1.52 million employees. How many developers could they possibly need?

Or maybe it’s just nonsensical to compare the number of employees across companies - especially when they don’t do nearly the same thing.

On a related note, wait until you find out how many more employees that Apple has than Google since Apple has hundreds of retail employees.

[fsndz]

True.

Deep learning models will continue to improve as we feed them more data and use more compute, but they will still fail at even very simple tasks as long as the input data are outside their training distribution. The numerous examples of ChatGPT (even the latest, most powerful versions) failing at basic questions or tasks illustrate this well. Learning from data is not enough; there is a need for the kind of system-two thinking we humans develop as we grow. It is difficult to see how deep learning and backpropagation alone will help us model that. https://medium.com/thoughts-on-machine-learning/why-sam-altm...

[stavros]

> Im old enough to remember the mystery and hype before o*/o1/strawberry

So at least two years old?

[throwanem]

Honestly, sometimes I wonder if most people these days kinda aren't at least that age, you know? Or less inhibited about acting it than I believe I recall people being last decade. Even compared to just a few years back, people seem more often to struggle to carry a thought, and resort much more quickly to emotional belligerence.

Oh, not that I haven't been as knocked about in the interim, of course. I'm not really claiming I'm better, and these are frightening times; I hope I'm neither projecting nor judging too harshly. But even trying to discount for the possibility, there still seems something new left to explain.

[bananaflag]

I think people expected reasoning to be more than just trained chain of thought (which was known already at the time). On the other hand, it is impressive that CoT can achieve so much.

[irthomasthomas]

Yeah, I don't know exactly what at an AGI model will look like, but I think it would have more than 200k context window.

[doug_durham]

Do you have a 200k context window? I don't. Most humans can only keep 6 or 7 things in short term memory. Beyond those 6 or 7 you are pulling data from your latent space, or replacing of the short term slots with new content.

[boznz]

I'm not quite AGI, but I work quite adequately with a much, much smaller memory. Maybe AGI just needs to know how to use other computers and work with storage a bit better.

[kurthr]

I'd think it would be able to at least suggest which model to use rather than just having 6 for you to choose from.

[chrsw]

I’m not an AI researcher but I’m not convinced these contemporary artificial neural networks will get us to AGI, even assuming an acceleration to current scaling pace. Maybe my definition of AGI is off but I’m thinking what that means is a machine that can think, learn and behave in the world in ways very close to human. I think we need a fundamentally different paradigm for that. Not something that is just trained and deployed like current models, but something that is constantly observing, constantly learning and constantly interacting with the real world like we do. AHI, not AGI. True AGI may not exist because there are always compromises of some kind.

But, we don’t need AGI/AHI to transform large parts of our civilization. And I’m not seeing this happen either.

[BosunoB]

You are absolutely right that AGI will probably barely resemble LLMs, but this is kind of beside the point. An LLM just has to get good enough to automate sufficiently complicated coding tasks, like those of coding new AI experiments. From there, researchers can spin off new experiments rapidly and make further improvements. An AGI will likely have vastly different architecture from an LLM, but we will only discover that through likely hundreds of thousands of experiments with incremental improvements.

This is the ai-2027.com argument. LLMs only really have to get good enough at coding (and then researching), and it's singularity time.

[chpatrick]

I feel like every time AI gets better we shift the goalposts of AGI to something else.

[MoonGhost]

> Now we're up to o4, AGI is still not even in near site (depending on your definition, I know)

It's not only definition. Some googler was sure their model was conscious.

[actsasbuffoon]

Meanwhile even the highest ranked models can’t do simple logic tasks. GothamChess on YouTube did some tests where he played against a bunch of the best models and every single one of them failed spectacularly.

They’d happily lose a queen to take a pawn. They failed to understand how pieces are even allowed to move, hallucinated the existence of new pieces, repeatedly declared checkmate when it wasn’t, etc.

I tried it last night with Gemini 2.5 Pro and it made it 6 turns before it started making illegal moves, and 8 turns before it got so confused about the state of the board before it refused to play with me any longer.

I was in the chess club in 3rd grade. One of the top ranked LLMs in the world is vastly dumber than I was in 3rd grade. But we’re going to pour hundreds of billions into this in the hope that it can end my career? Good luck with that, guys.

[JFingleton]

I'm not sure why people are expecting a language model to be great at chess. Remember they are trained on text, which is not the best medium for representing things like a chess board. They are also "general models", with limited training on pretty much everything apart from human language.

An Alpha Star type model would wipe the floor at chess.

[schindlabua]

Chess is not exactly a simple logic task. It requires you to keep track of 32 things in a 2d space.

I remember being extremely surprised when I could ask GPT3 to rotate a 3d model of a car in it's head and ask it about what I would see when sitting inside, or which doors would refuse to open because they're in contact with the ground.

It really depends on how much you want to shift the goalposts on what constitutes "simple".

[code_biologist]

Claude can't beat Pokemon Red. Not even close yet: https://arstechnica.com/ai/2025/03/why-anthropics-claude-sti...

[famouswaffles]

LLMs can play chess fine.

The best model you can play with is decent for a human - https://github.com/adamkarvonen/chess_gpt_eval

SOTA models can't play it because these companies don't really care about it.

[LinuxAmbulance]

> We had serious news outlets write about senior people at OpenAI quitting because o1 was SkyNet

I wonder if any of the people that quit regret doing so.

Seems a lot like Chicken Little behavior - "Oh no, the sky is falling!"

How anyone with technical acumen thinks current AI models are conscious, let alone capable of writing new features and expanding their abilities is beyond me. Might as well be afraid of calculators revolting and taking over the world.