Thank you, Enrico, for this really, really kind introduction.

And I totally emphasize again what he was saying, that my lab employs biologists, but

we also employ physicists and mathematicians, because for those of you who might think that,

I mean, there's a bit of a trade-off that we don't actually necessarily produce interesting

mathematics for the mathematicians, kind of like for their eyes, but we do produce extremely

interesting applications in the biological sciences that change the way that biologists

even test their theories, and I hope to show a few examples of how we do this.

Now, I didn't put the title of my talk anymore onto this slide, because I promised to talk

both about sex and about death, and the death aspects, this evolution of aging and lifespan,

this is something that we work on a lot, but I only have one hour, or ideally even less,

and I thought, you know, there's so much to tell you about, you know, the sexual diversity

that is out there in nature that, you know, why don't I just focus on that?

So the alternative fun title of this talk could be Sex Education for Mathematicians,

but let's see how this goes.

So here's a picture of flamingos, and this is before artificial intelligence times.

As far as I know, this is not manipulated in any way, so there's these tiny little flamingos,

they're individuals, and they form a population of flamingos that looks like a flamingo just

by chance.

But I put this picture here to make you think how, if you are not a professional evolutionary

biologist, you often might phrase evolutionary ideas kind of like, oh, evolution is something

that promotes things that are good for the entire species.

And given that I already mentioned artificial intelligence, you can ask, I can't remember

which version of AI I used here, like how does evolution promote the survival of the

species?

And then whoa, all kinds of ideas come in there.

But I can also ask artificial intelligence, tell me why evolution does not always promote

the survival of the species, and then it also produces a lot of answers there.

So this is where you have to be a bit more scientific and actually know what stuff you're

talking about.

And generally I would say yikes to these kind of ideas here, because my entire career I

have been looking at things where evolution does not necessarily satisfy an optimality

criterion that at first sight you might think that it's a sensible one.

But more generally what we do in my lab is that we are really interested in the tension

between diversity and generalizability.

So we're scientists, we like to uncover some sort of general rules, general hypotheses,

theories even.

But at the same time, if you look at these different organisms, they obey different,

they have different challenges in their lives, and therefore sometimes you get different

answers if you change the rules of the game, so to say.

In other words, if you have a good theory, you should explain what is the norm.

This is a fruit fly, everybody has heard about fruit flies, genetics use that a lot, it's

kind of like your standard species.

But then if you shake a tree in a rainforest, you actually get this dropping out, so what

the hell is this antenna for?

And there's actually new research that it really seems to be sensing electricity, static

electricity out there, so there's quite new stuff that is not my research topic at all.

But this is general, just the nature is really diverse and therefore it's really fun to study it.

In other words, you set, from set A to set B, we change the rules of the challenges that

the organisms are facing, so what sort of behaviors or trait changes do you expect in nature?

And so this is a much better way to phrase the questions than the sort of naive expectations