Oscar-winning computer scientist on the physics of computer animation

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Hello, and welcome to the Physics World weekly

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podcast,

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the last episode of 2025.

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And it features Pat Hanrahan,

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who studied

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nuclear engineering and biophysics

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before becoming a founding employee

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of Pixar

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Animation Studios

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in the nineteen eighties.

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That conversation is coming up after this message

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about a webinar

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that we're presenting

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with Leo Cancer Care.

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It's called unlocking

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novel radiation beams for cancer treatment

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with upright patient positioning,

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and it will feature a panel of leading

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clinicians

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and experts.

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They will discuss how the shift in patient

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positioning

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is enabling the exploration

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of new treatment geometries

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and supporting

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the development

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of advanced

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future cancer therapies.

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The live event is aimed at medical physicists,

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radiation oncologists,

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radiotherapy

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planners,

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and researchers

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in the field.

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Participants will learn about this paradigm shift in

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radiation

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therapy,

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gain an understanding

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of emerging and novel

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radiation

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beam modalities,

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and discover

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how foundational

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radiation

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physics

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translates

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into real world impact

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in cancer care.

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The webinar is on the February 17

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at 4PM

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GMT.

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That's 11AM

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Eastern Standard Time.

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You can register for this free event

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on the Physics World website.

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Earlier this year, Physics World's Margaret Harris attended

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the Heidelberg

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Laureate

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Forum in Germany.

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This international event brings together early career researchers

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with some winners of the most prestigious

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awards in mathematics

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and computer science.

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There, she spoke to a laureate who's also

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won three academy awards. Here's that conversation.

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So I'm talking to Pat Hanrahan, who won

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the Association for Computing Machineries AM Turing Award

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in 2019

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for contributions to three d computer graphics or

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CGI.

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So you're best known for that type of

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work, but you actually started out, I think,

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in nuclear engineering Yes. And then you got

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a PhD in biophysics. Yes. So how did

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you get into those subjects? Tell me about

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nuclear engineering first. Well, when I was in

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school, I I really felt I wanted to

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become a physicist. Anyway, I like math too,

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and I like science in general, but I

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think physics was the field that was most

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interesting to me. And so, yeah, when I

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went to the University of Wisconsin actually, it

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was it was it was doubly nice because

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they had this really nice, what they call,

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honors program,

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where you have a lot of freedom in

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what classes you took and all that. So,

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you know, not just take physics, but do

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other things as well. Take chemistry, biology, other

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sciences.

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So yeah. So I was always interested in

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physic. I love my intro physics course. I

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can still

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remember the lectures and, you know, going through

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it all. And,

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yeah. So I just loved physics, you know,

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all the way through the undergraduate

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physics, mechanics,

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electrodynamics,

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quantum mechanics. I just loved all those courses,

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my favorite courses.

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But why nuclear engineering specifically? Why not? Well,

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I think it was mostly because of this

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honors program. I was actually I actually and

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I when I went there, the chairman of

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the department,

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offered me a job,

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and he was the chair of the nuclear

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regulatory commission at the time. So I ended

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up, you know, in in this department. But,

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you know, I was he was working for

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the nuclear regulatory commission. This was, you know,

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like, in the late seventies.

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You know, nuclear power was having you know,

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people were pretty down on that. Right? And

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when I was reading about all this stuff,

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I got pretty down on it too because

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they weren't really addressing a lot of the

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currents. I think that's maybe changing a little

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bit, but I was definitely

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not that interested especially at towards the end.

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So I wanted to work on other areas

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of physics.

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I did a lot of theoretical physics. You

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know? Like, when I was a graduate student,

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I I had to take, like, I don't

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know, five courses in quantum mechanics, you know,

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quantum field theory. You know? I was really

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headed towards the theoretical physics thing, but I

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don't know what you I I the the

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low level of physics just wasn't really exciting

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me. So I I wanted to be a

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physicist, but I

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wanted to work on sort of higher level

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problems.

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So I I admired, like, Francis Crick, and

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he was, like, a theoretical

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biologist in some sense.

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And I thought, well, maybe I could become,

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like, a theoretical biologist.

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And then I met this person,

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and I was, he had was one of

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the founders of the computational neuroscience program.

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Or well, I'm sorry. Not computational neuroscience. That

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didn't exist. Neuroscience program. And, he was working

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on neurobiology of nematodes. He had worked for

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Sydney Brenner.

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And so I thought, well, I could I

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could do you know, he and they weren't

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being very quantitative, and I thought I could,

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like, apply what I know about physics to

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help them, you know, build up models of

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the nervous system. And I I started doing

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some simulations and things like that. Yeah. And

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is that about the time that you got

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first involved in Pixar, the project that became

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the first Toy Story film? No. That took

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a little while. I mean, you know, you

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have to realize computer graphics didn't exist then.

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It really didn't exist. I mean, you know,

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it just did not exist. My advice so

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it turned out it's sort of funny story.

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Sydney Brenner, you know, Nobel laureate in biology.

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There was he had two a bunch of

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colleagues and students, Francis Crick. There was another

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guy named John White and another guy named

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John Sulston.

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And John White is famous for

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determining,

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the structure of the nervous system of c

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l. So they all worked on C. Elegans,

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which is a a free living nematode.

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So, John White had, like, figured out the

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entire wiring grant by sectioning the words and

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worm and tracing all the neurons. And,

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John Solston had, worked on

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developmental biology, and he recorded, you know, how

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the cells

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divided, you know, from an egg all the

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way to a full grown one.

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And, anyways, the three of them all got

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really the same computers.

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And,

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and so, you know, my my adviser was

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in that group, and he was trying to

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convince me to work on computers.

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And I didn't have any background in computers.

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So I started simulating,

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this nervous system,

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and I had you, write these programs that

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simulated. I was, like, solving,

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like, basically cable equations for neurons because these

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neurons are, like, you know, electrical cables.

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But I needed to do visualization. I had

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to be able to see my result. Like,

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you just so my roommate introduced me to

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computer graphics. He said, oh, by the way,

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do you know about this graphic stuff?

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You know, I just sort of got enchanted

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by what I could do with it because

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I could take all my theories, like, whether

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it was simulation of neurons or whatever I

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was interested in and see it, you know,

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make it really concrete. And it just became

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even more fun. You know? Like, the the

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physics was suddenly

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infinitely more fun because I could see it.

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You know? Like, I could do animations,

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not much animation, but I could at least

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make pictures and so on. So I sort

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of got seduced by that idea, and it

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it was a wide open field. You know?

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Physics and, you know, biology was, you know,

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sort of slow paced. This was, like, completely

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wide open. So, like like like, the first

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week I worked on it, I, like, wrote

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a paper. I got accepted in the major

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conference. You know? Whereas in physics, you know,

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I'd been a grad student for a couple

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years, never written a paper. And so then

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I decided I had you go learn more

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about computer graphics,

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but, you know, because there was nobody there.

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There was only one or two places in

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the world that was doing computer graphics, and

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eventually, I ended up at Pixar a couple

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years later. Yeah.

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And a lot of your research on computer

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generated imagery focuses on getting the simulated world

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to display

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things in the way it's grounded in physics.

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Yeah. Yeah. You know, you literally wrote the

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book about physically based rendering. Yeah. What are

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the benefits of that approach, and what are

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some of the main challenges in it? That's

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a great question.

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You know, I love that question. I mean,

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you know, you know, we're we're creating a

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virtual world, and the world, you know, has

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physics in it. I mean, you know, and

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just imagine. I mean, what we did, we're

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just trying to create a world that, like,

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if somebody looked at it had all the

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phenomena that we think of in physics and

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even biology as well, but all these phenomena.

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So, you know, like, what are some of

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the found well, a cloud might move. Right?

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Wind will move the leaves of the tree.

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You know, you could have an object, a

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rock falling.

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You know, get out something a building kind

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of blowing apart. You could have, you know,

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cloth, you know, conforming to somebody's skin. You

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have the muscles moving the body. I mean,

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there's just physics everywhere in the world. Right?

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And so, you know, if we're trying to

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simulate all I mean, we're trying to make

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a picture of all this stuff. I mean,

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how else would you do it? I mean,

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you you have to in some sense, you

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have to somehow capture the physics of the

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everyday world. It's I I call it the

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everyday world because it's at the human scale.

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You know? It's what we see around us.

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And I mostly worked on,

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simulating the appearance of it, right, which is

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like, you know, you know, why does it

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look the way it does? Like, why how

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do, like, materials scatter light, and how does

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light get transported through the environment, and, you

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00:09:25,259 --> 00:09:27,899
know, even how cameras simulate cameras and simulate

272
00:09:27,899 --> 00:09:29,820
light sources. So, yeah, so if you look

273
00:09:29,820 --> 00:09:31,420
at the what we actually ended up doing,

274
00:09:31,420 --> 00:09:33,179
if you look at that book, you know,

275
00:09:33,179 --> 00:09:34,080
we write down

276
00:09:34,460 --> 00:09:36,700
a bunch of equations that describe the scattering

277
00:09:36,700 --> 00:09:39,279
of light off surfaces and off infinite media,

278
00:09:39,465 --> 00:09:41,245
and then we just solve this

279
00:09:42,024 --> 00:09:44,264
solve for the lightning distribution in the world.

280
00:09:44,264 --> 00:09:46,345
You know? And it's a just a giant

281
00:09:46,345 --> 00:09:47,725
computational science problem.

282
00:09:48,105 --> 00:09:49,945
But the challenge is you have all these

283
00:09:49,945 --> 00:09:50,925
real world materials,

284
00:09:52,345 --> 00:09:53,884
which are both complex.

285
00:09:54,529 --> 00:09:57,009
You know, they're not just like ideal mirrors

286
00:09:57,009 --> 00:09:58,929
and, you know, one type of cars where

287
00:09:58,929 --> 00:10:00,690
I just, like, opened up an optics book

288
00:10:00,690 --> 00:10:02,290
and said, how much is in this book

289
00:10:02,290 --> 00:10:04,389
that would help us do this? Almost nothing.

290
00:10:04,690 --> 00:10:06,210
You know what I mean? Because, you know,

291
00:10:06,210 --> 00:10:07,889
how does light scatter off skin? How does

292
00:10:07,889 --> 00:10:10,085
light scatter off a rock? How does light

293
00:10:10,085 --> 00:10:12,565
scatter off a cloud? Just not detailed stuff

294
00:10:12,565 --> 00:10:14,644
in there. So we'd often have to come

295
00:10:14,644 --> 00:10:15,625
up with, you know,

296
00:10:16,004 --> 00:10:16,504
approximations

297
00:10:16,884 --> 00:10:17,784
and models

298
00:10:18,164 --> 00:10:20,325
for all these things. And I worked a

299
00:10:20,325 --> 00:10:22,164
lot. Like, I I worked on my papers

300
00:10:22,164 --> 00:10:23,464
as I'm modeling skin.

301
00:10:24,419 --> 00:10:26,339
Hair. How does light scatter from hair? How

302
00:10:26,339 --> 00:10:28,899
does light scatter from cloth? Stuff like that.

303
00:10:28,899 --> 00:10:30,339
But, anyways, when it all is said and

304
00:10:30,339 --> 00:10:31,940
done, you get, you know, like, a billion

305
00:10:31,940 --> 00:10:32,440
objects

306
00:10:32,820 --> 00:10:34,679
each with really complex materials,

307
00:10:35,059 --> 00:10:37,375
and then you have to solve for the

308
00:10:37,375 --> 00:10:38,115
lighting distribution,

309
00:10:38,574 --> 00:10:41,454
which is really complicated because the objects have

310
00:10:41,454 --> 00:10:44,274
complicated shape. So we use Monte Carlo techniques.

311
00:10:44,495 --> 00:10:46,174
You know? In fact, just like what they

312
00:10:46,174 --> 00:10:48,815
did up during the war to simulate the

313
00:10:48,815 --> 00:10:49,794
neutron transport,

314
00:10:50,110 --> 00:10:51,870
And that's actually was the connection back to

315
00:10:51,870 --> 00:10:54,509
my work in nuclear engineering. I had learned

316
00:10:54,509 --> 00:10:57,230
about transport theory and Monte Carlo techniques, you

317
00:10:57,230 --> 00:10:59,309
know, in school. And so, you know, I

318
00:10:59,309 --> 00:11:01,009
I sort of also just sort of gravitated

319
00:11:01,070 --> 00:11:02,590
towards those problems because those are the ones

320
00:11:02,590 --> 00:11:03,570
I knew to sell.

321
00:11:03,904 --> 00:11:06,144
So you actually won, one of your three

322
00:11:06,144 --> 00:11:08,544
Academy Awards, Oscars, in other words Yeah. Is

323
00:11:08,544 --> 00:11:11,585
specifically for developing that software that simulates the

324
00:11:11,585 --> 00:11:13,665
subsurface scattering of light Yes. Yeah. In in

325
00:11:13,665 --> 00:11:16,304
materials that are translucent. Yeah. Yeah. Why is

326
00:11:16,304 --> 00:11:18,144
that so difficult, and why is it so

327
00:11:18,144 --> 00:11:18,644
important

328
00:11:19,340 --> 00:11:21,980
for film and computer graphics? Yeah. Well, okay.

329
00:11:21,980 --> 00:11:23,980
Why is it important? Well, I'm looking at

330
00:11:23,980 --> 00:11:26,080
you, and your skin looks really healthy.

331
00:11:27,019 --> 00:11:28,300
I mean, you know, I mean, you know,

332
00:11:28,300 --> 00:11:30,940
in real people, skin is really important. Right?

333
00:11:30,940 --> 00:11:33,340
It has to look right. And until then,

334
00:11:33,340 --> 00:11:34,399
it looked like plastic.

335
00:11:34,715 --> 00:11:36,154
You know, it looked like, yeah, just were

336
00:11:36,154 --> 00:11:38,235
completely covered in makeup. You know? You know,

337
00:11:38,235 --> 00:11:40,554
makeup and things like that, you know, almost

338
00:11:40,554 --> 00:11:41,915
like pink. You know what I mean? They're

339
00:11:41,915 --> 00:11:43,915
just very matte and, you know, very I

340
00:11:43,915 --> 00:11:45,995
mean, you know, that's why they're matte. They're

341
00:11:45,995 --> 00:11:47,740
not they did not you know, don't have

342
00:11:47,740 --> 00:11:49,180
all the complexity of real skin, but real

343
00:11:49,180 --> 00:11:51,820
skin has oil. It has texture to it.

344
00:11:51,820 --> 00:11:52,480
It has

345
00:11:52,940 --> 00:11:54,700
a bunch of properties that are very different

346
00:11:54,700 --> 00:11:57,519
than these idealized plastic like, paint like material.

347
00:11:57,820 --> 00:11:59,899
So so, obviously, for the movies, they want

348
00:11:59,899 --> 00:12:02,559
people to look, you know, natural and appealing.

349
00:12:03,144 --> 00:12:04,664
So that was one that was sort of

350
00:12:04,664 --> 00:12:06,985
a motivation for it. What was interesting, the

351
00:12:06,985 --> 00:12:08,365
discovery was that

352
00:12:08,825 --> 00:12:09,565
most materials

353
00:12:10,105 --> 00:12:13,225
are actually somewhat translucent, and subsurface scatter is

354
00:12:13,225 --> 00:12:15,929
actually more common than just normal surface scatter.

355
00:12:15,929 --> 00:12:17,690
So what happened in surface scatter, which you

356
00:12:17,690 --> 00:12:19,450
learn about in physics, you know, light ray

357
00:12:19,450 --> 00:12:21,769
hits the surface and just gets reflected off

358
00:12:21,769 --> 00:12:24,170
the interface between, say, the air and the

359
00:12:24,170 --> 00:12:26,809
the material itself. Yeah. Yeah. But in most

360
00:12:26,809 --> 00:12:28,809
materials, they're actually dielectric. And by the way,

361
00:12:28,809 --> 00:12:30,410
that's what happens in the metal. You know?

362
00:12:30,410 --> 00:12:32,334
Like, light can't go into a metal because

363
00:12:32,334 --> 00:12:32,995
it's conductive,

364
00:12:33,534 --> 00:12:34,914
so it has to get reflected.

365
00:12:35,294 --> 00:12:38,095
Okay? That's why metals are shiny. But most

366
00:12:38,095 --> 00:12:40,334
materials are dielectrics. You know? They have an

367
00:12:40,334 --> 00:12:42,815
index of refraction. And so most light goes

368
00:12:42,815 --> 00:12:44,815
into the materials. It doesn't get reflected. You

369
00:12:44,815 --> 00:12:46,589
know? You just look at it physically. And

370
00:12:46,589 --> 00:12:48,829
why are the dialectics? Well, they're rocks. You

371
00:12:48,829 --> 00:12:51,069
know? They're based on water. Like, we have

372
00:12:51,069 --> 00:12:53,009
a lot of water in our human body.

373
00:12:53,069 --> 00:12:54,929
You know? They're made of things like fibers,

374
00:12:55,149 --> 00:12:56,449
anything like biological.

375
00:12:57,149 --> 00:12:59,534
And most minerals are not metals. They're,

376
00:12:59,934 --> 00:13:02,095
you know, they're dielectric. So almost everything around

377
00:13:02,095 --> 00:13:03,634
us is a dielectric,

378
00:13:04,495 --> 00:13:06,815
and what happens is the light goes into

379
00:13:06,815 --> 00:13:09,134
the material and then it scatters around a

380
00:13:09,134 --> 00:13:11,054
little bit, and then it comes up. It

381
00:13:11,054 --> 00:13:13,294
looks like it's reflecting off it. Let's actually

382
00:13:13,294 --> 00:13:15,240
go on and scatter around, come out, And

383
00:13:15,240 --> 00:13:17,019
that's called subsurface reflection.

384
00:13:17,639 --> 00:13:19,320
You know, it's been studied, but it's never

385
00:13:19,320 --> 00:13:21,159
really been studied very much in natural no

386
00:13:21,159 --> 00:13:23,799
normal everyday materials like skin or whatever. So

387
00:13:23,799 --> 00:13:25,899
we we develop you know, like a physicist,

388
00:13:26,200 --> 00:13:28,600
you know, just, you know, we read models

389
00:13:28,600 --> 00:13:30,415
about how you might do that. I used

390
00:13:30,415 --> 00:13:33,075
to read books like people like in atmospheric

391
00:13:33,375 --> 00:13:36,254
sciences study that, meteorology study that, like, if

392
00:13:36,254 --> 00:13:38,035
you observe a planetary atmosphere

393
00:13:38,575 --> 00:13:40,335
from a distance, like, it's like you have

394
00:13:40,335 --> 00:13:43,554
this layer of gas around the planet,

395
00:13:43,879 --> 00:13:45,559
and so it's gonna be sort of like

396
00:13:45,559 --> 00:13:47,159
that. The light goes into the atmosphere and

397
00:13:47,159 --> 00:13:48,839
gets scattered. So there, you know, there's things

398
00:13:48,839 --> 00:13:50,039
known about it, but they were all like

399
00:13:50,039 --> 00:13:52,139
things like that, like, you know, planetary atmosphere.

400
00:13:52,519 --> 00:13:54,360
So we yeah. We we just took a

401
00:13:54,360 --> 00:13:56,200
lot of those ideas that they had developed

402
00:13:56,200 --> 00:13:58,085
and and, you know, sort of, you know,

403
00:13:58,085 --> 00:14:00,264
mod used them to model things like skin.

404
00:14:00,644 --> 00:14:02,165
And in the same thing with hair, what

405
00:14:02,165 --> 00:14:03,625
happens is hair is mostly,

406
00:14:04,245 --> 00:14:06,325
translucent as well. It's like a little optical

407
00:14:06,325 --> 00:14:08,165
fiber. And so light goes into it, bounces

408
00:14:08,165 --> 00:14:10,085
around, and comes out. So these just lead

409
00:14:10,085 --> 00:14:12,264
to very different appearances than

410
00:14:12,629 --> 00:14:15,110
metals and things like that. So yeah. So

411
00:14:15,110 --> 00:14:16,230
I I did a lot of work on

412
00:14:16,230 --> 00:14:18,809
on, you know, just modeling different materials. And

413
00:14:18,870 --> 00:14:21,210
the subsurface scattering works, I mean, since everything

414
00:14:21,429 --> 00:14:23,750
looked like plastic, as soon as we wrote

415
00:14:23,750 --> 00:14:26,149
the paper, I mean, every studio in the

416
00:14:26,149 --> 00:14:27,210
world immediately,

417
00:14:28,414 --> 00:14:30,975
adopted them. And we we published the source

418
00:14:30,975 --> 00:14:34,095
code, and it was relatively simple model, so

419
00:14:34,095 --> 00:14:35,855
they could just, like, take it and put

420
00:14:35,855 --> 00:14:36,995
it into their system.

421
00:14:37,454 --> 00:14:39,294
And so yeah. So they like, within a

422
00:14:39,294 --> 00:14:41,389
year or two, everybody was using it sort

423
00:14:41,389 --> 00:14:43,230
of very quickly. And but, you know, it's

424
00:14:43,309 --> 00:14:44,669
it was I think it was the first

425
00:14:44,669 --> 00:14:47,870
time an academic paper had ever gotten an

426
00:14:47,870 --> 00:14:48,769
Academy Award.

427
00:14:50,829 --> 00:14:52,769
What would you say is the most difficult

428
00:14:53,115 --> 00:14:55,995
CGI problem either you've solved or you've seen

429
00:14:55,995 --> 00:14:58,875
someone else solve by some building on your

430
00:14:58,875 --> 00:14:59,375
work?

431
00:14:59,914 --> 00:15:01,455
Well, I I I think the

432
00:15:01,914 --> 00:15:04,095
I think the hardest thing to solve

433
00:15:04,794 --> 00:15:06,554
was not just, like, how to make, you

434
00:15:06,554 --> 00:15:08,940
know, skin look right. I mean, that's really

435
00:15:08,940 --> 00:15:10,160
insane, hard problem.

436
00:15:10,779 --> 00:15:12,639
It's how to build a system

437
00:15:13,259 --> 00:15:14,639
that would include everything.

438
00:15:15,179 --> 00:15:16,620
You know what I mean? Like, it's like

439
00:15:16,620 --> 00:15:18,620
this it's like sort of grand unified theory.

440
00:15:18,620 --> 00:15:21,519
Right? How can I build one rendering system

441
00:15:21,924 --> 00:15:23,625
that would handle any shape

442
00:15:23,925 --> 00:15:27,144
and any material and any light source,

443
00:15:27,605 --> 00:15:28,985
you know, and any kind of,

444
00:15:29,365 --> 00:15:32,165
you know, participating media and and just build

445
00:15:32,165 --> 00:15:34,325
a system that could do it all? And

446
00:15:34,325 --> 00:15:35,605
the problem is you if you if you

447
00:15:35,605 --> 00:15:37,259
can't do a bunch of stuff, like, say

448
00:15:37,259 --> 00:15:38,720
you couldn't do the atmosphere.

449
00:15:39,179 --> 00:15:40,700
I mean, it's just not gonna be useful.

450
00:15:40,700 --> 00:15:42,620
Right? And if you can't do people, it's

451
00:15:42,620 --> 00:15:44,559
not gonna be useful. You can't do plants.

452
00:15:44,860 --> 00:15:46,460
You know, like plants were a huge problem

453
00:15:46,460 --> 00:15:48,300
because there's so many leaves and they have

454
00:15:48,300 --> 00:15:50,460
such complicated scattering, but you have billions of

455
00:15:50,460 --> 00:15:52,559
them. You know? Billions of leaves and

456
00:15:53,035 --> 00:15:55,274
dandelions and stuff. So, you know, just having

457
00:15:55,274 --> 00:15:57,514
a system that could handle all this stuff

458
00:15:57,514 --> 00:15:59,615
and scale to the complexities,

459
00:16:00,475 --> 00:16:02,955
I mean, it's it's mostly an engineering problem,

460
00:16:02,955 --> 00:16:04,495
but it was it was a conceptualization

461
00:16:05,195 --> 00:16:07,610
problem. Like, how do you break down,

462
00:16:08,070 --> 00:16:09,929
you know, the world in some sense

463
00:16:10,389 --> 00:16:12,870
into all these what are some you know,

464
00:16:12,870 --> 00:16:14,070
you know, we sort of use, like, object

465
00:16:14,070 --> 00:16:16,070
oriented, but what are all the objects you

466
00:16:16,070 --> 00:16:18,389
need, and how are they all interrelated? How

467
00:16:18,389 --> 00:16:20,309
do they all work together? And then so

468
00:16:20,309 --> 00:16:22,605
that you can, like, plug in something new.

469
00:16:22,605 --> 00:16:24,205
Like, when we had that skin model, like,

470
00:16:24,205 --> 00:16:25,565
you just plug it in. You know, the

471
00:16:25,565 --> 00:16:27,804
system had the design. So that was actually

472
00:16:27,804 --> 00:16:29,485
my first academy where we had this system

473
00:16:29,485 --> 00:16:30,705
we called Reyes,

474
00:16:31,165 --> 00:16:33,585
R E Y E S, for the California.

475
00:16:33,725 --> 00:16:35,825
There's this park called Point Reyes.

476
00:16:36,740 --> 00:16:38,339
It's a very beautiful place. It was near

477
00:16:38,339 --> 00:16:41,779
Lucasfilm, so everybody knew about it. But it

478
00:16:41,779 --> 00:16:44,259
it was the acronym for renders everything you

479
00:16:44,259 --> 00:16:46,419
ever saw. So, you know, the first thing

480
00:16:46,500 --> 00:16:48,259
what I mostly worked on at Pixar was

481
00:16:48,259 --> 00:16:50,024
just how to build this system. You know?

482
00:16:50,105 --> 00:16:52,105
How how to build a system that renders

483
00:16:52,105 --> 00:16:54,264
everything you ever saw. And, you know, it's

484
00:16:54,425 --> 00:16:55,404
it was very,

485
00:16:56,024 --> 00:16:58,264
very challenging and non trivial to think of

486
00:16:58,264 --> 00:17:00,264
how to design this thing so it would

487
00:17:00,264 --> 00:17:01,705
work. And it's still being used. I mean,

488
00:17:01,705 --> 00:17:03,144
I did this many, many years ago. But,

489
00:17:03,144 --> 00:17:04,904
you know, once you get the basic framework

490
00:17:04,904 --> 00:17:05,549
in place,

491
00:17:06,110 --> 00:17:07,869
you know, you can just keep enhancing it

492
00:17:07,869 --> 00:17:09,630
because you can add stuff to it and

493
00:17:09,630 --> 00:17:11,070
they it just sort of you know, you

494
00:17:11,070 --> 00:17:13,309
have the right design when something new comes

495
00:17:13,309 --> 00:17:15,070
along and just sort of clicks into place.

496
00:17:15,070 --> 00:17:16,670
You know what I mean? So that that

497
00:17:16,750 --> 00:17:18,190
I think that was the hardest part. I

498
00:17:18,190 --> 00:17:20,194
mean, you know, maybe not quite as mathematical,

499
00:17:20,335 --> 00:17:22,515
but just how to conceive of this thing

500
00:17:22,654 --> 00:17:24,595
in a way that, you know, was both

501
00:17:24,654 --> 00:17:27,214
conceptually elegant, but also worked. You know what

502
00:17:27,214 --> 00:17:29,315
I mean? It could be efficient and and

503
00:17:29,454 --> 00:17:30,815
and so on. So that I think that

504
00:17:30,815 --> 00:17:32,759
was the hardest problem. Yeah. What would you

505
00:17:32,759 --> 00:17:35,559
say then is the the most difficult unsolved

506
00:17:35,559 --> 00:17:37,400
problem? What what can't you do now that

507
00:17:37,400 --> 00:17:38,680
you really like to be able to do

508
00:17:38,680 --> 00:17:39,740
in computer graphics?

509
00:17:40,519 --> 00:17:41,880
Well, I think that I have a couple

510
00:17:41,880 --> 00:17:43,400
of opinions. I mean, you know, on the

511
00:17:43,400 --> 00:17:45,340
on the so we would call this photorealistic

512
00:17:45,720 --> 00:17:47,545
rendering and so on. I mean, I don't

513
00:17:47,625 --> 00:17:49,144
I mean, pretty much, you know, we've been

514
00:17:49,144 --> 00:17:50,825
working on it so long. I mean, I

515
00:17:50,825 --> 00:17:52,424
don't know if you go to movies. Some

516
00:17:52,424 --> 00:17:53,705
of the people do, but, you know, the

517
00:17:53,705 --> 00:17:55,865
movies are pretty convincing at this point. You

518
00:17:55,865 --> 00:17:57,464
know? And even like Toy Story was the

519
00:17:57,464 --> 00:17:59,224
first one that we did. It was a

520
00:17:59,224 --> 00:18:00,365
cartoon movie.

521
00:18:00,664 --> 00:18:02,205
Now, you know, you see movies

522
00:18:02,920 --> 00:18:04,380
routinely that just

523
00:18:04,920 --> 00:18:05,900
is completely indistinguishable

524
00:18:06,519 --> 00:18:07,019
from,

525
00:18:07,320 --> 00:18:09,640
you know, from things like Avatar and, you

526
00:18:09,640 --> 00:18:12,119
know, all these movie. So it's pretty hard.

527
00:18:12,119 --> 00:18:13,240
I mean, I don't know if I can

528
00:18:13,240 --> 00:18:14,059
think of really,

529
00:18:14,599 --> 00:18:17,559
one thing. I find natural scenes, outdoor scenes,

530
00:18:17,559 --> 00:18:19,305
sort of still somewhat unsatisfying.

531
00:18:20,085 --> 00:18:21,765
I mean, remember, they still fake a lot

532
00:18:21,765 --> 00:18:23,465
of stuff. They don't model everything

533
00:18:24,085 --> 00:18:25,924
and so on, so they can avoid, you

534
00:18:25,924 --> 00:18:27,865
know, showing you things that they can't do.

535
00:18:27,924 --> 00:18:30,005
But I find, you know, really if I

536
00:18:30,005 --> 00:18:31,865
take a walk in the forest or something,

537
00:18:32,119 --> 00:18:33,960
you know, there's something about it that I

538
00:18:33,960 --> 00:18:35,880
don't I don't see in the computer, but

539
00:18:35,880 --> 00:18:37,240
I can't quite pin it down. That's the

540
00:18:37,240 --> 00:18:39,160
other problem. What? You're you're looking at this

541
00:18:39,160 --> 00:18:40,940
stuff. Like, you look I'm looking at skin.

542
00:18:41,240 --> 00:18:43,240
Like, what are we not getting about it?

543
00:18:43,240 --> 00:18:45,480
You know? There's something underlying the phenomena of

544
00:18:45,480 --> 00:18:47,734
the scattering. So I don't quite know exactly

545
00:18:47,795 --> 00:18:48,615
for these

546
00:18:48,994 --> 00:18:49,494
natural,

547
00:18:50,195 --> 00:18:53,234
environments what we're getting wrong. But, anyway, I

548
00:18:53,234 --> 00:18:54,994
think that's one. But I actually think, you

549
00:18:54,994 --> 00:18:55,494
know,

550
00:18:55,955 --> 00:18:58,615
a more interesting thing is not just photorealistic

551
00:18:59,154 --> 00:19:01,029
effects, but, you know, how to make it

552
00:19:01,029 --> 00:19:02,710
easy. You know, like, I gave a talk

553
00:19:02,710 --> 00:19:05,589
once about starting with Leonardo, how, you know,

554
00:19:05,589 --> 00:19:08,970
we sort of reproduced what Leonardo had discovered,

555
00:19:09,029 --> 00:19:11,349
right, like perspective and shading and all that

556
00:19:11,349 --> 00:19:13,289
stuff, and we just computerized it.

557
00:19:13,865 --> 00:19:15,465
But then the event art sort of went

558
00:19:15,465 --> 00:19:17,785
in lots of different directions. It wasn't just

559
00:19:17,785 --> 00:19:19,865
about realism. You know? So, like, maybe how

560
00:19:19,865 --> 00:19:21,485
to make other kinds of pictures,

561
00:19:22,105 --> 00:19:24,424
like, either more abstract kind of pictures like

562
00:19:24,424 --> 00:19:26,930
an artist might do, or more functional kind

563
00:19:26,930 --> 00:19:28,390
of pictures, like, in visualizations

564
00:19:28,690 --> 00:19:30,529
of things. You know, just how you know,

565
00:19:30,529 --> 00:19:32,609
because there you're not just simulating the physics.

566
00:19:32,609 --> 00:19:34,130
You have to ask but you still you

567
00:19:34,130 --> 00:19:36,049
know, it might be some formal technique. Let's

568
00:19:36,049 --> 00:19:37,589
say we had some theory of aesthetics

569
00:19:38,265 --> 00:19:40,345
or something like that. Maybe we could formalize

570
00:19:40,345 --> 00:19:42,025
that and have a computer do that kind

571
00:19:42,025 --> 00:19:43,384
of stuff. Yeah. You see some of that

572
00:19:43,384 --> 00:19:45,785
generated by AI right now. But, yeah, just,

573
00:19:45,785 --> 00:19:47,465
you know, other there are different kinds of

574
00:19:47,465 --> 00:19:47,965
picture.

575
00:19:48,585 --> 00:19:50,505
And I think we could make a lot

576
00:19:50,505 --> 00:19:52,904
of other interesting pictures besides just sort of

577
00:19:52,904 --> 00:19:53,404
photographic,

578
00:19:53,750 --> 00:19:55,529
You know, sort of a classic thing, like,

579
00:19:55,830 --> 00:19:57,509
first we once we had a camera, like,

580
00:19:57,509 --> 00:19:58,789
you know, what do we why do we

581
00:19:58,789 --> 00:20:00,710
need to you know, we don't want it

582
00:20:00,710 --> 00:20:02,950
to we have cameras to take realistic pictures.

583
00:20:02,950 --> 00:20:05,109
We don't need, you know, artists to draw

584
00:20:05,109 --> 00:20:07,634
perfectly realistic pictures. Yeah. So you're still looking

585
00:20:07,634 --> 00:20:10,115
for the Pixar version of Picasso. Yeah. Yeah.

586
00:20:10,115 --> 00:20:12,455
Exactly. Yeah. Yeah. Yeah. Exactly. Exactly.

587
00:20:13,075 --> 00:20:14,994
So final question. How if you could just

588
00:20:14,994 --> 00:20:16,275
sum it up, how do you think your

589
00:20:16,275 --> 00:20:18,835
training in physics has helped you in your

590
00:20:18,835 --> 00:20:19,335
career?

591
00:20:19,759 --> 00:20:21,359
Well, I certainly learned a lot of phys

592
00:20:21,519 --> 00:20:23,619
you know, physical phenomena, you know,

593
00:20:24,240 --> 00:20:25,059
like transport,

594
00:20:25,519 --> 00:20:26,339
light optics,

595
00:20:26,960 --> 00:20:28,980
and mechanics, classical mechanics.

596
00:20:29,440 --> 00:20:32,085
You know, lots of, particular things I learned.

597
00:20:32,325 --> 00:20:33,924
But the best thing I learned was how

598
00:20:33,924 --> 00:20:34,825
to solve problems.

599
00:20:36,085 --> 00:20:37,684
I mean, you know, I mean, you just

600
00:20:37,845 --> 00:20:39,365
you know, the problems they gave you to

601
00:20:39,365 --> 00:20:40,804
solving, you just had to solve. And there

602
00:20:40,804 --> 00:20:42,404
was a certain way of solving them. You

603
00:20:42,404 --> 00:20:44,404
know? How do you like, you notice I

604
00:20:44,404 --> 00:20:46,484
use the word modeling and simulation a lot.

605
00:20:46,484 --> 00:20:48,849
You know? Like, you have physical models and,

606
00:20:49,230 --> 00:20:51,230
you know, models are useful, but they're not

607
00:20:51,230 --> 00:20:52,509
the whole thing. You have to, you know,

608
00:20:52,509 --> 00:20:54,049
you have to pick the right model

609
00:20:54,509 --> 00:20:56,269
for, you know, you know, like, start out

610
00:20:56,269 --> 00:20:57,649
with really phenomenological

611
00:20:57,950 --> 00:20:59,470
like models, but they can still be super

612
00:20:59,470 --> 00:21:02,049
useful when you also want more fundamental models.

613
00:21:02,174 --> 00:21:03,855
But there's many models, and you have to

614
00:21:03,855 --> 00:21:05,695
pick the right one. And then and so

615
00:21:05,695 --> 00:21:07,394
you just have to pick the right one.

616
00:21:07,695 --> 00:21:08,975
And, you know, a lot of people, they

617
00:21:08,975 --> 00:21:10,735
they just they don't know how to pick

618
00:21:10,735 --> 00:21:12,414
the right model. You know what I mean?

619
00:21:12,414 --> 00:21:13,775
And then you and then you have to

620
00:21:13,775 --> 00:21:14,755
crank through whatever

621
00:21:15,089 --> 00:21:17,569
it takes to sort of make it solvable.

622
00:21:17,569 --> 00:21:19,169
You know what I mean? Like, you know,

623
00:21:19,169 --> 00:21:21,169
it might involve spherical harmonics or it might

624
00:21:21,169 --> 00:21:22,690
involve a bunch of stuff. And then some

625
00:21:22,690 --> 00:21:24,690
of that stuff sort of just difficult. Right?

626
00:21:24,690 --> 00:21:26,769
You just gotta have the the you have

627
00:21:26,769 --> 00:21:29,410
to be, like, powerful problem solver to actually

628
00:21:29,410 --> 00:21:31,434
turn that into, like, something that works. So

629
00:21:31,434 --> 00:21:32,875
I think that's what I learned in physics.

630
00:21:32,875 --> 00:21:34,575
And, you know, that skill,

631
00:21:35,674 --> 00:21:37,674
it was I just think that's why physicists

632
00:21:37,674 --> 00:21:39,434
are so successful when they go to other

633
00:21:39,434 --> 00:21:41,434
fields, is they just have this magical ability

634
00:21:41,434 --> 00:21:43,615
to solve problems in other fields. Yeah.

635
00:21:44,179 --> 00:21:45,700
That kind of fun. Thank you very much.

636
00:21:45,700 --> 00:21:46,679
Yeah. Thank you.

637
00:21:53,859 --> 00:21:57,220
That was Margaret Harris in conversation with Pat

638
00:21:57,220 --> 00:21:57,720
Hanrahan,

639
00:21:58,515 --> 00:22:00,375
who has won three Oscars

640
00:22:00,755 --> 00:22:02,775
in addition to the ACM's

641
00:22:03,154 --> 00:22:04,855
AM Turing Award.

642
00:22:05,154 --> 00:22:07,414
Thanks to both of them for a fascinating

643
00:22:07,634 --> 00:22:08,134
conversation.

644
00:22:08,994 --> 00:22:11,875
And thank you for listening to the Physics

645
00:22:11,875 --> 00:22:13,335
World weekly podcast

646
00:22:13,909 --> 00:22:15,529
in 2025.

647
00:22:16,150 --> 00:22:17,450
I'm Hamish Johnston,

648
00:22:17,750 --> 00:22:20,409
and our producer is Fred Iles.

649
00:22:20,950 --> 00:22:22,089
We'll be back again

650
00:22:22,390 --> 00:22:24,089
in 2026.