David HelmerGuestChris KeeferHost
So, uh, before I was a jet engine guy, my dissertation was actually about validating uncertainty quantification for computational models.

So how do we decide if these big fancy models are right? Because, uh, in fluid mechanics world, it's really expensive to do testing, as we talked about.


Uh, since I have the background in engineering and I understand the math, but also could understand the big picture, I've done a lot of work advising the government, uh, on things like whether autonomous systems should be invested in or different AI capabilities.

Uh, I've led teams that develop these kind of capabilities, uh, for the government.

Uh, and then, uh, I also taught, uh, introductory AI and some other topics in that space, uh, at the academy.

Uh, you're not gonna hear me rambling about, uh, details of mathematical methods.

Um, but a lot of my conversation, uh, tends to be about the fundamental principles.

Uh, and my company now advises, uh, generally non-technical experts, although technical experts as well, on what these systems can really do.

So I do legal education, senior leader education, uh, diligence activities for, for, uh, investments and things like that.
Uh, you know, I was, uh, being interviewed by Oliver Stone's team for a, uh, part two of their Nuclear Now movie.
Um, and one of the things I was reflecting upon was, you know, as a, uh, bright-eyed, bushy-tailed nuclear advocate, I sort of got into nuclear out of, you know, these really profoundly sort of humanistic concerns, uh, partially around things like climate change, you know, air quality.
Um, we had a big coal phase out in my province, uh, which was accomplished through nuclear power.
You know, good, solid, you know, working class jobs that could, you know, a single income could support a family, sort of that Homer Simpson ideal.
God, I don't know what else, but it was a really sort of idealistic, you know, in retrospect, slightly naive.

So, uh, before I was a jet engine guy, my dissertation was actually about validating uncertainty quantification for computational models.

So how do we decide if these big fancy models are right? Because, uh, in fluid mechanics world, it's really expensive to do testing, as we talked about.


Uh, since I have the background in engineering and I understand the math, but also could understand the big picture, I've done a lot of work advising the government, uh, on things like whether autonomous systems should be invested in or different AI capabilities.

Uh, I've led teams that develop these kind of capabilities, uh, for the government.

Uh, and then, uh, I also taught, uh, introductory AI and some other topics in that space, uh, at the academy.

Uh, you're not gonna hear me rambling about, uh, details of mathematical methods.

Um, but a lot of my conversation, uh, tends to be about the fundamental principles.

Uh, and my company now advises, uh, generally non-technical experts, although technical experts as well, on what these systems can really do.

So I do legal education, senior leader education, uh, diligence activities for, for, uh, investments and things like that.
Uh, you know, I was, uh, being interviewed by Oliver Stone's team for a, uh, part two of their Nuclear Now movie.
Um, and one of the things I was reflecting upon was, you know, as a, uh, bright-eyed, bushy-tailed nuclear advocate, I sort of got into nuclear out of, you know, these really profoundly sort of humanistic concerns, uh, partially around things like climate change, you know, air quality.
Um, we had a big coal phase out in my province, uh, which was accomplished through nuclear power.
You know, good, solid, you know, working class jobs that could, you know, a single income could support a family, sort of that Homer Simpson ideal.
God, I don't know what else, but it was a really sort of idealistic, you know, in retrospect, slightly naive.
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