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In your example it fails at self knowledge, not math. Here’s a description of the capability and how it is distinct from the 4o model:


In my experience it works quite well. Like any of these tools, it doesn’t absolve one from reasoning and verification, but it certainly accelerates certain activities.

It is quite good at statistics and I am not. In that sense I find it to be beneficial.
Probability and Statistics is no joke, some of the dullest reading I have encountered.

I had to drop it on my first attempt.
 
In your example it fails at self knowledge, not math. Here’s a description of the capability and how it is distinct from the 4o model:


In my experience it works quite well. Like any of these tools, it doesn’t absolve one from reasoning and verification, but it certainly accelerates certain activities.

It is quite good at statistics and I am not. In that sense I find it to be beneficial.
To me is it seems Juice's argument is that it's not doing math the way we do math. It has a vast amount of knowledge so it can predict that 1+1 is equal to 2. it's not adding 1 on top of 1. It however has access to models that can help it do math and pull formulae so, same difference. I can see where if it hiccups a 'prediction' it will just throw a garbage result out there
 
Don't worry, I'll research for at least fifteen minutes before I order steroids.


Yep, I've been lurking since QSC went MIA. Created an account so I could react to posts and was sorely disappointed.
Give it some time and you'll be able to react.
I waited some time for that, I could react in other forum sections but NOT in the underground one, then one day it happened.
 
To me is it seems Juice's argument is that it's not doing math the way we do math. It has a vast amount of knowledge so it can predict that 1+1 is equal to 2. it's not adding 1 on top of 1. It however has access to models that can help it do math and pull formulae so, same difference. I can see where if it hiccups a 'prediction' it will just throw a garbage result out there

He is not wrong, in that sense. The only issue I have with that assertion is that each new model handles things differently. As he mentioned, some models would hand math off to a python interpreter, which is less the case recently. 4o, I think does math in the way that you and he described, by guessing at the result and doing pretty well. 4o1 implements “chain of thought” and has also undergone reinforcement learning specifically for math. As such, it’s quite good, pragmatically speaking and is unlikely to produce a hallucination as a result to a mathematical question.
 
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