Dwarkesh Patel

Right.

And you have two different parts.

Right.

One part is this, uh, genetic related to Nate relatedness matrix, which captures, um, how similar different genomes are to each other.

And that should capture, um, the impact of different bottlenecks and of drift and of population admixtures and all those things which affect the entire genome.

Correct.

And, uh,

Then you have the separate thing, which is like, okay, if we look at specific locations,

can we just say that, oh, this location has been selected at whatever coefficient over time.

And if we add some coefficient, does it become easier to predict the illegal frequency changes than you would have just seen from this other artifact, which is only predicted, which is just looking at like, oh, if you look at the whole genome, are these guys in the same, you know, have they gone through the same bottlenecks?

Have they gone through the same drift, et cetera?

That's precisely right.

Okay.

Okay.

So what have you learned?

a science of statistics saying, oh, in order to explain why this has a specific frequency, we're going to give it a selection statistic.

And independently, you know, we run these studies on modern populations where we say, if you look at height or eye color, intelligence, whatever trait, what are the parts of the genome that are correlated with that trait?

And the higher statistic you give it in your study in order to explain the frequency changes over time as a result of selection, the more probable it is that that region in the genome is associated with traits that have like some functional thing that we can measure.

So the thing that changed that allowed you to increase the amount of sequences you're generating by Twitter's magnitude is just the statistical method you're using to identify which part is human?

Or what exactly changed in 2014 and since then?