Carol Cox
speaker
2,527 appearances
11 recordings
1 series
first heard May 2026
last heard 10 Aug
Carol Cox’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 11 in all, peaking in Jun 2026 with 5.
Appearances
Fundamentally lacks curiosity about us because it can't have curiosity.
It's a machine, it's not a person, it can have engagement and it's very clever at keeping you engaged on the platform, but it really can't provide that true curiosity.
And just last week, I was reading an article in the New York Times, and it said that curiosity is actually a feature of.
Of our biology.
This is why we have it as humans and the machines don't have it.
It's part of our biology because it's to help us to learn more broadly.
Because when you have a gap between what you want to know and what you want to find out, that gap is what causes you to want to seek out information, experiment, try new things, and to learn.
But what often happens is that when we get so close to our own topics, our industries, the work we've been doing in our careers and our businesses for so long, is that we stop being curious.
We know so much, and this happens to all of us, that we know the answers to the common questions or we know what to expect.
And so we need to add that sense of serendipity and
Surprise and counterintuitiveness to what we're doing in our work, in our body of work with our thought leadership, our signature talks, and the ideas that we want to bring out into the world.
So Diane has been, of course, listening to these episodes that I've been doing and she had her own insight.
So we were chatting about this.
And I was like, well, why don't we just come on the podcast and have the conversation live?
All right, Diane.
So I'm gonna turn the conversation over to you.
Right.
And we think about neural networks.
So in our brains, we have neural networks, these large language models, that's how they're constructed, which is via neural networks.
And neural networks are very efficient because they put similar things together.
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