GPT-5 is behind schedule

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.

People who say „it’s bullshit” are the ones that push the technological advance forward.

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 together, the logical step is to figure out how to turn compute into better data to train on. Enter strawberry / o1, and now o3

They can throw money, time, and compute at thinking about and then generating better training data. If the belief is that N billion new tokens of high quality training data will unlock the leap in capabilities they’re looking for, then it makes sense to delay the training until that dataset is ready

With o3 now public knowledge, imagine how long it’s been churning out new thinking at expert level across every field. OpenAI’s next moat may be the best synthetic training set ever.

At this point I would guess we get 4.5 with a subset of this - some scale improvement, the algorithmic pickups since 4 was trained, and a cleaned and improved core data set but without risking leakage of the superior dataset

When 5 launches, we get to see what a fully scaled version looks like with training data that outstrips average humans in almost every problem space

Then the next o-model gets to start with that as a base and reason? Its likely to be remarkable

have you tested that this helps? seems pretty simple to script with an agent framework

I’m a consultant. Having looked at several enterprises, there’s a lot of work being done to make a lot of things that don’t really work.

The bigger the ambition, the harder they’re failing. Some well designed isolated use cases are ok. Mostly things about listening and summarizing text to aid humans.

I have yet to see a successful application that is generating good content. IMO replacing the first draft of content creation and having experts review and fix it is, like, the stupidest strategy you can do. The people you replace are the people at the bottom of the pyramid who are supposed do this work to upskill and become domain experts so they can later review stuff. If they’re no longer needed, you’re going to one day lose your reviewer, and with it, the ability to assess your generated drafts. It’s a foot gun.