Earlier quoted context omitted.
AGI is the Sisyphean task of our age. We’ll push this boulder up the mountain because we have to, even if it kills us.
And when we get it there, it kills us.
[dead]
GPT-5 is behind schedule
261–270 of 1001 posts
Re: GPT-5 is behind schedule
#262Earlier quoted context omitted.
If their AGI dreams would come true it might be more than enough to have 3 months head start. They probably won't, but it's interesting to ponder what the next few hours, days, weeks would be for someone that would wield AGI. Like let's say you have a few datacenters of compute at your disposal and the ability to instantiate millions of AGI agents - what do you have them do? I wonder if the USA already has a secret p…
How many important problems are there where a 3 month head start on the data side is enough to win permanently and retain your advantage in the long run? I'm struggling to think of a scenario where "I have AGI in January and everyone else has it in April" is life-changing. It's a win, for sure, and it's an advantage, but success in business requires sustainable growth and manageable costs. If (random example) the bar…
Well that's the thought exercise. Is there something you can do with almost unlimited "brains" of roughly human capability but much faster, within a few days / weeks / months. Lets say you can instantiate 1 million agents, for 3 months, and each of them is roughly 100x faster than a human, that means you have the equivalent of 100 million human-brain-hours to dump into whatever you want, as long as your plans don't require building too many real world things that actually require moving atoms around, I think you could do some interesting things. You could potentially dump a few million hours into "better than AGI AI" to start off for example, then go to other things. If they are good enough you might be able to find enough zero-days to disable any adversary through software, among other interesting things.
Re: GPT-5 is behind schedule
#263Re: GPT-5 is behind schedule
#264Earlier quoted context omitted.
Laundry folding is an instructive example. Machines have been capable of home-scale laundry folding for over a decade, with two companies Foldimate and Laundroid building functional prototypes. The challenge is making it cost-competitive in a world where most people don't even purchase a $10 folding board. I would guess that most cooking and cleaning tasks are in basically the same space. You don't need fine motor co…
I think the problem of those is that they are special purpose, and probably too expensive and bulky for that single purpose. A single general-purpose robot that can do everything would be much easier to sell.
There's plenty of machines which are expensive, bulky, single purpose and yet commercially successful. The average American household has a kitchen range, refrigerator, dishwasher, laundry machine, dryer, television, furnace, and air conditioner. Automatic coffee machines and automatic vacuums are less universal but still have household penetration in the millions. I really think the household tasks with no widely available automation are simply the ones that nobody cares enough about doing to pay for automation.
A robot servant that does literally 100% of chores would be a game changer, and I expect we'll get there at some point, but it will probably have to be a one-shot from a consumer perspective. A clever research idea to reach 25% or 50% coverage still isn't going to lead to a commercially viable product.
Re: GPT-5 is behind schedule
#265Re: GPT-5 is behind schedule
#266One fundamental challenge to me is that if each training run because more and more expensive, the time it takes it to learn what works/doesn't work widens. Half a billion dollars for training a model is already nuts, but if it takes 100 iterations to perfect it, you've cumulatively spent 50 billion dollars... Smaller models may actually be where rapid innovation continues simply because of tighter feedback loops. O3…
O3 is not a smaller model. It's an iterative GPT of sorts with the magic dust of reinforcement learning.
I'm pretty sure that the parent implied that o3 is smaller in comparison to gpt5
Re: GPT-5 is behind schedule
#267Earlier quoted context omitted.
a) There is evidence e.g. private data deals that we are starting to hit the limitations of what data is available. b) There is no evidence that LLMs are the roadmap to AGI. c) Continued investment hinges on their being a large enough cohort of startups that can leverage LLMs to generate outsized returns. There is no evidence yet this is the case.
"There is no evidence that LLMs are the roadmap to AGI." - There's plenty of evidence. What do you think the last few years have been all about? Hell, GPT-4 would already have qualified as AGI about a decade ago.
>What do you think the last few years have been all about?
Next token language-based predictors with no more intelligence than brute force GIGO which parrot existing human intelligence captured as text/audio and fed in the form of input data.
4o agrees:
"What you are describing is a language model or next-token predictor that operates solely as a computational system without inherent intelligence or understanding. The phrase captures the essence of generative AI models, like GPT, which rely on statistical and probabilistic methods to predict the next piece of text based on patterns in the data they’ve been trained on"
Re: GPT-5 is behind schedule
#268Earlier quoted context omitted.
But if the scaling law holds true, more dollars should at some point translate into AGI, which is priceless. We haven't reached the limits yet of that hypothesis.
a) There is evidence e.g. private data deals that we are starting to hit the limitations of what data is available. b) There is no evidence that LLMs are the roadmap to AGI. c) Continued investment hinges on their being a large enough cohort of startups that can leverage LLMs to generate outsized returns. There is no evidence yet this is the case.
Have we really hit the wall?
Do they use GPS based data?
Feels like there’s data all around us.
Sure they’ve hit the wall with obvious conversations and blog articles that humans produced, but data is a by product of our environment. Surely there’s more. Tons more.
Re: GPT-5 is behind schedule
#269Earlier quoted context omitted.
"There is no evidence that LLMs are the roadmap to AGI." - There's plenty of evidence. What do you think the last few years have been all about? Hell, GPT-4 would already have qualified as AGI about a decade ago.
No, GPT-4 would have been classified as it is today: a (good) generator of natural language. While this is a hard classical NLP task, it's a far cry from intelligence.
GPT-4 is a good generator of natural language in the same sense that Google is a good generator of ip packets.
Re: GPT-5 is behind schedule
#270Earlier quoted context omitted.
At this point I think it's safe to say they have given up on custom GPTs.
What makes you say that?
They hyped them like crazy and haven't discussed them once since then. I agree that the inability to change the model is pretty absurd when the whole point was to "supercharge" specific tasks.
There was even talk of some sort of profit sharing with creators which clearly never happened. I just think the premise is too confusing for many and can still be served by using a custom system prompt via the API.