Oct 9, 2026 · 9 min · 5 segments
Stephen Wolfram talks about how he knows what he knows, the interplay between theory and experiment, and the importance of building towers of knowledge on solid ground. — Stephen Wolfram…
When the theory is strong enough, you've got to believe the theory, even if the experiment doesn't initially agree with you.
[instrumental music] You talked about developing that judgment of when an idea is a good idea and not a good idea.
How do you get better at that over time? Is, is it because you have more knowledge? Is it because you just have more experience and pattern matching, or can you actually get better at the process of judging ideas? Is, is there some key there to, to know-
I've ended up, you know, having a, a strange forcing function that's kind of unique, which is I've been building this computational language that, you know, tries to cover all these different areas.
And so even though I knew nothing about control theory, let's say, I had to learn something about it, 'cause I was kind of trying to validate the design we had for implementing it in our computational language.
So I've had this kind of strange, unexpected, unplanned, unique experience of kind of having to broaden my knowledge, uh, in a, in a prac- very practical way across all these different fields.
I mean, it really means that, that, for example, it gives me a bit of confidence when I'm thinking about something.
It's like, well, is this obvious to somebody? Right? I'll typically know the answer to that.
Somebody will say, you know, "Is this known?" And I will have a pretty decent idea of whether, you know, if it's known, this will be the subcommunity that has discovered that, et cetera, et cetera, et cetera.
And it's-- that's useful, because otherwise you're, you're ending up kind of you're always kind of avoiding, "Oh, I shouldn't think about that because somebody must already know that."
And therefore, it's a lot easier to kind of feel like, oh, it's worth me thinking about that, 'cause I know nobody knows that.
When the theory is strong enough, you've got to believe the theory, even if the experiment doesn't initially agree with you.
[instrumental music] You talked about developing that judgment of when an idea is a good idea and not a good idea.
How do you get better at that over time? Is, is it because you have more knowledge? Is it because you just have more experience and pattern matching, or can you actually get better at the process of judging ideas? Is, is there some key there to, to know-
I've ended up, you know, having a, a strange forcing function that's kind of unique, which is I've been building this computational language that, you know, tries to cover all these different areas.
And so even though I knew nothing about control theory, let's say, I had to learn something about it, 'cause I was kind of trying to validate the design we had for implementing it in our computational language.
So I've had this kind of strange, unexpected, unplanned, unique experience of kind of having to broaden my knowledge, uh, in a, in a prac- very practical way across all these different fields.
I mean, it really means that, that, for example, it gives me a bit of confidence when I'm thinking about something.
It's like, well, is this obvious to somebody? Right? I'll typically know the answer to that.
Somebody will say, you know, "Is this known?" And I will have a pretty decent idea of whether, you know, if it's known, this will be the subcommunity that has discovered that, et cetera, et cetera, et cetera.
And it's-- that's useful, because otherwise you're, you're ending up kind of you're always kind of avoiding, "Oh, I shouldn't think about that because somebody must already know that."
And therefore, it's a lot easier to kind of feel like, oh, it's worth me thinking about that, 'cause I know nobody knows that.
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