[LINK] OpenAI’s o3 Model: Breakthrough or Breakdown?

[Scott Howard]

On Mon, Apr 28, 2025 at 1:30 PM David <dlochrin at aussiebb.com.au> wrote:

> This seems to me to demonstrate a fundamental issue with AI machines: they
> are still very large correlation processors but have not been developed far
> enough to distinguish "empirical correlations" and logical rules.  Thus "2
> plus 2 usually makes 4" is an empirical correlation, but "2+2=4" in an
> appropriate mathematical context is a logical rule.  (And we understand "He
> added 2 and 2 and got 5" isn't an appropriate context!)


This is one of the many areas where the idea of 'agentic AI' comes in.  If
you ask a human to add two numbers, what would they do?  For a simple case
like the one you've mentioned they probably just do it in their head, but
in a more generic sense the easy answer is to outsource that calculation to
something designed explicitly to do that type of action - such as a
calculator.  In an agentic AI world, the role of the AI isn't to add those
2 numbers together, but to outsource it to an agent (such as a calculator,
via an API) that will do it for it.

Mix this with the newer reasoning models which are much better at working
out the best path to come to an answer, and the types of answers you get
from AI systems now days for this type of question is significantly better
than it was only a few months ago.  Instead of simply looking at "2 plus 2"
and trying to guess what comes next, the recent models are able to look at
that statement, determine it's a calculation, decide that the best way to
solve such a statement is by using a calculator, and then call a calculator
agent to actually do the work and get the answer.  If the calculation was
even more complex, then they might instead decide that the best option is
to write python or R code to solve it, run that code, and then return the
answer.

  Scott