I don't know what the Y-axis is supposed to be on that Wharton AI capabilities graph, but I am not really convinced that Opus 4.6 has more than double the intelligence/capability/whatever of GPT 5.1 Max.
IIRC that graph tracks capabilities as time_to_solve a task for humans (i.e. the model can now handle tasks that usually take a human ~8h). Which, depending on what tasks you look at, could be a reasonable finding. I could see Opus 4.6 handling tasks that take ~8h for humans, and that 5.1 couldn't previously handle (with 5.1 being "limited" at 4h tasks let's say). It is a bit arbitrary, but I think this is what they're tracking.
Without knowing more about their methodology, it seems like a lot of the recent improvements have involved the AI itself taking time to complete the task.
At first the models turned a 5 minute task into a 5 second task (by 5 seconds I mean a very short amount of time, not precisely 5 seconds). Then they turned a 15 minute task into a 5 second task.
Opus 4.6 completes 8 hour tasks all the time but (at least in my experience) it isn't spitting the answer out in 5 seconds anymore. It's using chain of thought and tools and the time to completion is measured in minutes or maybe hours.
In my experiments with local LLMs, a substantial part of the gap between frontier and local (for everyday use) is in tooling and infrastructure.
That is why I am sympathetic to the idea we are leveling off. But to bring in the air speed example from the article, I don't think we've reached the equivalent of the ramjet yet. I suspect in the coming years there will be new architectures, new hardware, and new ways to get even more capable models.
It measures ability to complete (with a given success rate) a task with a known human benchmark time to complete. I.e., they set the task to human volunteers and timed how long they took the complete that task.
It also measures task coherence—ability to plan, form contingencies, recover from errors, mitigate accumulation of errors, and reconcile findings across a long context window.
Have you used the models, out of interest? They routinely do things autonomously that are not in the training set that would take me 8h, and I wouldn't say I'm slow. The profile of tasks they can do this way is jagged, and maintaining architectural coherence ("months, not hours") is still beyond them, but they're perfectly capable of writing plans and sticking to them.
Yeah, I use them all the time. I just don't see any good argument that it's anything other than statistical pattern matching plus some sort of logic encoded in language.
My overfitted LLM obviously didn't arrive at Harry Potter the same way JK Rowling did, so the amount of time she spent writing it is completely irrelevant to any discussion about whether or not the LLM should be able to reproduce it. discussions of AGI if it took her an hour or a decade to write it, it has seen the result, so it can reproduce it.
I don't think you've addressed the fact that they can do long tasks that aren't in the training set? (And the fact that they're just statistical models isn't very relevant. So am I!)
Yeah, what about them? As far as I read it the tasks are fixed. The AI companies should know the tasks by now, and have overfitted their models on the tests by now, in the same way I'm implying I overfitted my model to reproduce Harry Potter.
The tasks are obviously all of the form "Go do this, and if you get the following output you passed". Setting up a web server apparently takes 15 minutes for a human, which is news to me since I'm able to search for https://gist.github.com/willurd/5720255, find the python one-liner, and copy it within about ten seconds.
Anyway, this is cool but it does not mean Claude can perform any human tasks that take less than 8 hours and are within its physical capabilities.
> more than double the intelligence/capability/whatever
I'm curious what people really mean when they say this. Intelligence is famously hard to define, let alone measure; it certainly doesn't scale linearly; it only loosely correlates to real-world qualities that are easy to measure; etc. Are you referring to coding ability or...?
According to this article: whenever someone games a benchmark to make an upward chart on some y-axis, it's YOUR responsibility to prove how and why that trend can't continue indefinitely.