When you give it a large math problem and the answer is "seven point one three five ... ", and it shows a plot of the result v some randomly selected domain, well there could be more I'd like to know.
You can unlock a full derivation of the solution, for cases where you say "Solve" or "Simplify", but what I (and I suspect GP) might want, is to know why a few of the key steps might work.
It's a fantastic tool that helped get me through my (engineering) grad work, but ultimately the breakthrough inequalities that helped me write some of my best stuff were out of a book I bought in desperation that basically cataloged linear algebra known inequalities and simplifications.
When I try that kind of thing with the best LLM I can use (as of a few months ago, albeit), the results can get incorrect pretty quickly.
> [...], but what I (and I suspect GP) might want, is to know why a few of the key steps might work.
It's been some time since I've used the step-by-step explainer, and it was for calculus or intro physics problems at best, but IIRC the pro subscription will at least mention the method used to solve each step and link to reference materials (e.g., a clickable tag labeled "integration by parts").
Doesn't exactly explain why but does provide useful keywords in a sequence that can be used to derive the why.
Its understanding of problems was very bad last time I used it. Meaning it was difficult to communicate what you wanted it to do. Usually I try to write in the Mathematica language, but even that is not foolproof.
Hopefully they have incorporated more modern LLM since then, but it hasn’t been that long.
Wolfram Alpha's "smartness" is often Clippy level enraging. E.g. it makes assumptions of symbols based on their names (e.g. a is assumed to be a constant, derivatives are taken w.r.t. x). Even with Mathematica syntax it tends to make such assumptions and refuses to lift them even when explicitly directed. Quite often one has to change the variable symbols used to try to make Alpha to do what's meant.
What's surprising to me is that this would surely be in OpenAI's interests, too -- free RLHF!
Of course there would be the risk of adversaries giving bogus feedback, but my gut says it's relatively straightforward to filter out most of this muck.
