Dr. Max Fomitchev-Zamilov

And every so often, she comes to me and say, curse this eye I was painting for so long, and now it's in a different place. And that's what we see here, you know. It's just what happens. Yeah, it's another vase, just for example, the other vase. It's not quite as precise as this one, but it's still pretty amazing.

So we have six, ten thousands of an inch centering error for the outer surface and little worse than, you know, one thousand of an inch for the inner surface. So it's on par, you know, with this vase, but I would say maybe like two times worse, roughly.

So we have six, ten thousands of an inch centering error for the outer surface and little worse than, you know, one thousand of an inch for the inner surface. So it's on par, you know, with this vase, but I would say maybe like two times worse, roughly.

So we have six, ten thousands of an inch centering error for the outer surface and little worse than, you know, one thousand of an inch for the inner surface. So it's on par, you know, with this vase, but I would say maybe like two times worse, roughly.

That was the main conclusion. So this is scatterplot on the horizontal axis. We have, I believe, the... So the vertical axis is the deviation from the center. It's the concentricity error. Yes. And the horizontal axis is the circularity error. it's a two-dimensional plot. We have circularity error horizontally and concentricity error vertically. And this is a logarithmic plot.

That was the main conclusion. So this is scatterplot on the horizontal axis. We have, I believe, the... So the vertical axis is the deviation from the center. It's the concentricity error. Yes. And the horizontal axis is the circularity error. it's a two-dimensional plot. We have circularity error horizontally and concentricity error vertically. And this is a logarithmic plot.

That was the main conclusion. So this is scatterplot on the horizontal axis. We have, I believe, the... So the vertical axis is the deviation from the center. It's the concentricity error. Yes. And the horizontal axis is the circularity error. it's a two-dimensional plot. We have circularity error horizontally and concentricity error vertically. And this is a logarithmic plot.

Logarithmic means it's not linear. Because it was linear, we would have just two dots in it. And because if we had two dots, we cannot see the points through individual vases, I chose a logarithmic plot. And a lot of scientists do it when you have data that's very different in size. You cannot fit it like on one page comfortably.

Logarithmic means it's not linear. Because it was linear, we would have just two dots in it. And because if we had two dots, we cannot see the points through individual vases, I chose a logarithmic plot. And a lot of scientists do it when you have data that's very different in size. You cannot fit it like on one page comfortably.

Logarithmic means it's not linear. Because it was linear, we would have just two dots in it. And because if we had two dots, we cannot see the points through individual vases, I chose a logarithmic plot. And a lot of scientists do it when you have data that's very different in size. You cannot fit it like on one page comfortably.

And I think this is good because green vases here are what, you know, I deem precise, and I'll explain why. And blue is what I deem imprecise. And you can see that the red dots are the vases that are made by Olga. They fall into the imprecise class. versus orange dots are the contemporary machine made in a vases that fall in the precise class.

And I think this is good because green vases here are what, you know, I deem precise, and I'll explain why. And blue is what I deem imprecise. And you can see that the red dots are the vases that are made by Olga. They fall into the imprecise class. versus orange dots are the contemporary machine made in a vases that fall in the precise class.

And I think this is good because green vases here are what, you know, I deem precise, and I'll explain why. And blue is what I deem imprecise. And you can see that the red dots are the vases that are made by Olga. They fall into the imprecise class. versus orange dots are the contemporary machine made in a vases that fall in the precise class.

And on this particular chart, I just show a broad grouping. That's out of all vases that I analyzed, just looking at this two particular subsets of quality metric, how concentric the slices are and how circular they are. You have two blobs, you know, two distinct blobs. One is I call precise and the other I call imprecise.

And on this particular chart, I just show a broad grouping. That's out of all vases that I analyzed, just looking at this two particular subsets of quality metric, how concentric the slices are and how circular they are. You have two blobs, you know, two distinct blobs. One is I call precise and the other I call imprecise.

And on this particular chart, I just show a broad grouping. That's out of all vases that I analyzed, just looking at this two particular subsets of quality metric, how concentric the slices are and how circular they are. You have two blobs, you know, two distinct blobs. One is I call precise and the other I call imprecise.

It doesn't because it's a logarithmic algorithm.

It doesn't because it's a logarithmic algorithm.

It doesn't because it's a logarithmic algorithm.

I would say 10 times.