Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

GPT-5 is behind schedule

wsj.com

Post reply on HN
Print view View original

911–920 of 1001 posts

Re: GPT-5 is behind schedule

#911

Post by heavyset_go »

fragmede wrote: post #904
heavyset_go wrote: post #891

Earlier quoted context omitted.

> Would you trust a ML self-driving algorithm trained on a "digital twin" of a city? I would. No, just as I wouldn't trust a surgeon who studied medicine by playing Operation. A gross approximation is not a substitute for real life.

Hope you don't need surgery then! Suture training kits like these are quite popular for surgeons to train on. https://a.co/d/3cAotZ0 I don't know about you, but I'm not a rubbery rectangular slab of plastic, so obviously this kit can't help them learn.

This is a reason I opted to have a plastic surgeon come in when I went to the ER with an injury.

I could've had the nurse close me up and leave me with a scar, which she admitted would happen with her practice, or I could have someone with extensive experience treating wounds so that they'd heal in cosmetically appealing way do it. I opted for the latter.

Re: GPT-5 is behind schedule

#912

Post by zifpanachr23 »

threeseed wrote: post #233
ramesh31 wrote: post #220

Earlier 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.

I agree, these are good points.

Re: GPT-5 is behind schedule

#913

Post by [deleted] »

fragmede wrote: post #906
kjkjadksj wrote: post #852

Earlier quoted context omitted.

What makes you assume your digital twin is actually capturing the factors that contribute to variation in the real data? This is a big issue in simulation design but for ml researchers its hand-waved off seemingly.

Probably due to reports like these where the digital twin is credited with gains in factory efficiency. https://www.forbes.com/sites/carolynschwaar/2024/12/09/schae...

[deleted]

Re: GPT-5 is behind schedule

#914

Post by scottLobster »

fragmede wrote: post #904
heavyset_go wrote: post #891

Earlier quoted context omitted.

> Would you trust a ML self-driving algorithm trained on a "digital twin" of a city? I would. No, just as I wouldn't trust a surgeon who studied medicine by playing Operation. A gross approximation is not a substitute for real life.

Hope you don't need surgery then! Suture training kits like these are quite popular for surgeons to train on. https://a.co/d/3cAotZ0 I don't know about you, but I'm not a rubbery rectangular slab of plastic, so obviously this kit can't help them learn.

The difference being that you have to do a little more than that to become a board-certified surgeon. If a VC gives you a billion dollars to buy and practice on every available surgery practice kit in the world, you will still fail to become a surgeon. And we enforce such standards because if we don't then people die needlessly.

Re: GPT-5 is behind schedule

#915

Post by zifpanachr23 »

sdwr wrote: post #112
ericskiff wrote: post #25

What we can reasonably assume from statements made by insiders: They want a 10x improvement from scaling and a 10x improvement from data and algorithmic changes The sources of public data are essentially tapped Algorithmic changes will be an unknown to us until they release, but from published research this remains a steady source of improvement Scaling seems to stall if data is limited So with all of that taken toge…

Great improvements and all, but they are still no closer (as of 4o regular) to having a system that can be responsible for work. In math problems, it forgets which variable represents what, in coding questions it invents library fns. I was watching a YouTube interview with a "trading floor insider". They said they were really being paid for holding risk. The bank has a position in a market, and it's their ass on the…

This is underdiscussed. I don't think people understand just how worthless AI is in a ton of fields until it is able to be held liable and be sent to prison.

There are a lot of moral conundrums that are just not going to work out with this. Seems like an attempt to just offload liability and it seems like pretty much everybody has caught onto that as being it's main selling point and probably main thing that will keep it from ever being accepted for anything important.

Re: GPT-5 is behind schedule

#916

Post by fragmede »

glenstein wrote: post #839
ben_w wrote: post #824

Earlier quoted context omitted.

> To your point, I have wondered whatever became of that massive initiative from Google to scan books, and whether that might be looked at as a potential training source, giving that Google has run into legal limitations on other forms of usage. Still around, doing fine: https://en.wikipedia.org/wiki/Google_Books and https://books.google.com/intl/en/googlebooks/about/index.htm... Given the timing, I suspect it was st…

I don't know what you mean by timing (relative to what?) or "simple indexing" (they scanned the complete contents of books), but I am, and was already aware, of the wiki article and the role of recaptcha. Maybe I wasn't clear, but I was interested in the consequences of the legal stuff. It's not clear from the wiki article what any of this means with respect to the suitability of scans for AI training.

Until such time as a lawsuit declares otherwise, Google's position is obviously that scanning books, OCRing them, saving that text in a database, and using that to allow searching is no different, legally, than scanning books, OCRing them, saving that text in to a database, and using that to train LLMs. Book publishers already went up against Google for the practice of scanning in the first place, we'll see if they try again with LLM training.

Re: GPT-5 is behind schedule

#917

Post by elfly »

pphysch wrote: post #840
cshores wrote: post #815

Earlier quoted context omitted.

It ultimately doesn't matter because a fairly current snapshot of all of the world's information is already housed in their data lakes. The next stage for AI training is to generate synthetic data either by other AI or by simulations to further train on as human generated content can only go so far.

How is synthetic data supposed to work? Broadly speaking, ML is about extracting signal from noisy data and learning the subtle patterns. If there is untapped signal in existing datasets, then learning processes should be improved. It does not follow that there should be a separate economic step where someone produces "synthetic data" from the real data, and then we treat the fake data as real data. From a scientific…

Synthetic data works as long as it is directed towards a clear objective and curated.

At one point someone generated a Python teaching book from a LLM, took that, trained a second LLM with that, and the new LLM knew Python.

If you are just dragging random content from the web and you don't know what's synthetic and what's human, that data may be contaminated and a lot less useful, but if someone wanted to whitewash their training data by replacing a part of it with synthetic data, it can be done.

Re: GPT-5 is behind schedule

#918

Post by Nevermark »

cshores wrote: post #882
pphysch wrote: post #840

Earlier quoted context omitted.

How is synthetic data supposed to work? Broadly speaking, ML is about extracting signal from noisy data and learning the subtle patterns. If there is untapped signal in existing datasets, then learning processes should be improved. It does not follow that there should be a separate economic step where someone produces "synthetic data" from the real data, and then we treat the fake data as real data. From a scientific…

As others have mentioned, Tesla is already implementing similar advancements. More broadly, a new AI framework called Genesis has emerged, capable of training robots in just minutes using purely synthetic data. It generates a virtual environment for the robot to "perceive" and train within, even though this environment doesn't physically exist. This is just one example. Another could involve an AI specifically traine…

Competition between AI’s to solve problems better or faster than each other, but learning from each other, is another way to start with simple problems and naturally bootstrap increasing difficulty.

Re: GPT-5 is behind schedule

#919

Post by Nevermark »

scottLobster wrote: post #902
RationPhantoms wrote: post #848

Earlier quoted context omitted.

Would you trust a ML self-driving algorithm trained on a "digital twin" of a city? I would. I view synthetic training data like a digital twin in which it can provider further control or specified noise to understand from.

No, because right now I'm working closely with some EEs to troubleshoot electrical issues on some prototype boards (I wrote the firmware). They're prototypes precisely because we know the limits of our models and simulations and need real world boards to test our electronics design and firmware on. You're suggesting the new, untested models in a new, untested technological field are sufficient for deployment in real…

Both are likely to be much better.

Simulations may not be good enough alone, but still provide a significant boost.

Simulations can cheaply include scenarios that would be costly or dangerous to actually perform in the real world. And cover many combinations of scenario factors to improve combinatorial coverage.

Another way is to separate models into highly real world dependent (sensory interpretation) and more independent (kinematics based on sensory interpretation) parts. The latter being more suited to training in simulation. Obviously full real world testing is still necessary to validate the results.

Re: GPT-5 is behind schedule

#920

Post by heavyset_go »

zifpanachr23 wrote: post #903
heavyset_go wrote: post #900

Earlier quoted context omitted.

> I am betting hundreds of thousands, rising to millions more little sites, will start blocking/gating this year. AI companies might license from big sources (you can see the blocking percentage went down), but they will be missing the long tail, where a lot of great novel training data lives. This is where I'm at. I write content when I run into problems that I don't see solved anywhere else, so my sites host novel…

I don't think it is at all selfish to want to get some credit for going to the trouble of publishing novel content and not have it all stolen via an AI scraping your site. I'm totally on your side and I think people that don't see this as a problem are massively out of touch. I work in a pretty niche field and feel the same way. I don't mind sharing my writing with individuals (even if they don't directly cite me) be…

Agree with your assessment. I enjoy the little networks of people that develop as others use and share content. I enjoy the personal messages of thanks, the insights that are shared with me and seeing how my work influences others and the work they do. It's really cool to learn that something I made is the jumping off point for something bigger than I ever foresaw. Hell, just being reached out to help out or answer questions is... nice? I guess.

It's the little bits of humanity that I enjoy, and divorcing content from its creators is alienating in that way.

I'm not a musician, but I imagine there are similar motivations and appreciations artists have when sharing their work.

> I work in a pretty niche field and feel the same way. I don't mind sharing my writing with individuals (even if they don't directly cite me) because then they see my name and know who came up with it, so I still get some credit. You could call this "clout farming" or something derogatory, but this is how a lot of experts genuinely get work...by being known as "the guy who gave us that great tip on a blog once".

Yup, my writing has netted me clients who pointed at my sites as being a deciding factor in working with me.

> I honestly think we should just be done with writing content online now, before it's too late. I've thought a lot about it lately and I'm leaning more towards that option.

The rational side of me agrees with you, and has for a while now, but the human side of me still wants to write.

Post reply on HN