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GPT-5 is behind schedule

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Re: GPT-5 is behind schedule

#101

Post by nialv7 »

dartos wrote: post #50
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…

I’m curious how, if at all, the plan to get around compounding bias in synthetic data generated by models trained in synthetic data.

synthetic data is fine if you can ground the model somehow. that's why the o1/o3's improvements are mostly in reasoning, maths, etc., because you can easily tell if the data is wrong or not.

Re: GPT-5 is behind schedule

#103

Post by OutOfHere »

simondotau wrote: post #44
PittleyDunkin wrote: post #21

Everyone's comparing o1 and claude, but neither really work well enough to justify paying for them in my experience for coding. What I really want is a mode where they ask clarifying questions , ideally many of them, before spitting out an answer. This would greatly improve utility of producing something with more value than an auto-complete.

Just today I got Claude to convert a company’s PDF protocol specification into an actual working python implementation of that protocol. It would have been uncreative drudge work for a human, but I would have absolutely paid a week of junior dev time for it. Instead I wrote it alongside AI and it took me barely more than an hour. The best part is, I’ve never written any (substantial) python code before.

It would seem you don't care too much about verifying its output or about its correctness. If you did, it wouldn't take you just an hour. I guess you'll let correctness be someone else's problem.

Re: GPT-5 is behind schedule

#105

Post by h_tbob »

onemoresoop wrote: post #43
h_tbob wrote: post #36

It seems google has a massive advantage here since they can tap all of YouTube to train. I wonder what openai is using for its video data source.

Train for what? For making videos? Train from people’s comments? There’s a lot of garbage on AI slop on youtube, how would this be sifted out? I think there’s more value here on HN in terms of training, but even that, to what avail?

From what I read openai is having trouble bc not enough data.

If u think about it, any videos on YouTube of real world data contribute to its understanding of physics at minimum. From what I gather they do pre training on tons of unstructured content first and that contributes to overall smartness.

Re: GPT-5 is behind schedule

#106

Post by nradov »

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…

There is an enormous "iceberg" of untapped non-public data locked behind paywalls or licensing agreements. The next frontier will be spending money and human effort to get access to that data, then transform it into something useful for training.

Re: GPT-5 is behind schedule

#107

Post by tshadley »

Stevvo wrote: post #31
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…

"With o3 now public knowledge, imagine how long it’s been churning out new thinking at expert level across every field." I highly doubt that. o3 is many orders of magnitude more expensive than paying subject matter experts to create new data. It just doesn't make sense to pay six figures in compute to get o3 to make data a human could make for a few hundred dollars.

Seems to me o3 prices would be what the consumer pays, not what OpenAI pays. That would mean o3 could be more efficient in-house than paying subject-matter experts.

Re: GPT-5 is behind schedule

#108

Post by shepherdjerred »

beacon294 wrote: post #19
jsheard wrote: post #13

Earlier quoted context omitted.

[flagged]

There's someone with this comment in every thread. Meanwhile, no one answers this because they are getting value. Please take the time to learn, it will give you value.

For my mental health I’ve stopped replying to comments where it’s clear the author has no intention of having a discussion and instead wants their share their opinion and have it reinforced by others.

No, we don’t have AGI or anything close to it. Yes, AI has come a long way in the past decade and many people find it useful in their day-to-day lives.

It’s difficult to know where AI will be in 10 years, but the current rate of improvement is staggering.

Re: GPT-5 is behind schedule

#109

Post by lalalali »

tshadley wrote: post #107
Stevvo wrote: post #31

Earlier quoted context omitted.

"With o3 now public knowledge, imagine how long it’s been churning out new thinking at expert level across every field." I highly doubt that. o3 is many orders of magnitude more expensive than paying subject matter experts to create new data. It just doesn't make sense to pay six figures in compute to get o3 to make data a human could make for a few hundred dollars.

Seems to me o3 prices would be what the consumer pays, not what OpenAI pays. That would mean o3 could be more efficient in-house than paying subject-matter experts.

What is open ai margin on that product?

Re: GPT-5 is behind schedule

#110

Post by mrshadowgoose »

Stevvo wrote: post #31
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…

"With o3 now public knowledge, imagine how long it’s been churning out new thinking at expert level across every field." I highly doubt that. o3 is many orders of magnitude more expensive than paying subject matter experts to create new data. It just doesn't make sense to pay six figures in compute to get o3 to make data a human could make for a few hundred dollars.

Can SMEs deliver that data in a meaningful amount of time? Training data now is worth significantly more than data a year from now.
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