Charan Ranganath
๐ค SpeakerAppearances Over Time
Podcast Appearances
And then things start to get really complicated.
And then things start to get really complicated.
Yeah, yeah. I mean, well, even if we want to go super simple, right? Like Tyler Bonin, who's a postdoc who's collaborating with me, he actually studied a lot of computer vision at Stanford. And so one of the things he was interested in is some people who have brain damage in areas of the brain that were thought to be important for memory.
Yeah, yeah. I mean, well, even if we want to go super simple, right? Like Tyler Bonin, who's a postdoc who's collaborating with me, he actually studied a lot of computer vision at Stanford. And so one of the things he was interested in is some people who have brain damage in areas of the brain that were thought to be important for memory.
Yeah, yeah. I mean, well, even if we want to go super simple, right? Like Tyler Bonin, who's a postdoc who's collaborating with me, he actually studied a lot of computer vision at Stanford. And so one of the things he was interested in is some people who have brain damage in areas of the brain that were thought to be important for memory.
But they also seem to have some perception problems with particular kinds of object perception. And this is super controversial. Some people found this effect, some didn't. And he went back to computer vision and he said, let's take the best state-of-the-art computer vision models and let's give them the same kinds of perception tests that we were giving to these people. Mm-hmm.
But they also seem to have some perception problems with particular kinds of object perception. And this is super controversial. Some people found this effect, some didn't. And he went back to computer vision and he said, let's take the best state-of-the-art computer vision models and let's give them the same kinds of perception tests that we were giving to these people. Mm-hmm.
But they also seem to have some perception problems with particular kinds of object perception. And this is super controversial. Some people found this effect, some didn't. And he went back to computer vision and he said, let's take the best state-of-the-art computer vision models and let's give them the same kinds of perception tests that we were giving to these people. Mm-hmm.
And then he would find the images where the computer vision models would just struggle, and you would find that they just didn't do well. Even if you add more parameters, you add more layers, on and on and on, it doesn't help, right? The architecture didn't matter, it was just there, the problem.
And then he would find the images where the computer vision models would just struggle, and you would find that they just didn't do well. Even if you add more parameters, you add more layers, on and on and on, it doesn't help, right? The architecture didn't matter, it was just there, the problem.
And then he would find the images where the computer vision models would just struggle, and you would find that they just didn't do well. Even if you add more parameters, you add more layers, on and on and on, it doesn't help, right? The architecture didn't matter, it was just there, the problem.
And then he found those were the exact ones where these humans with particular damage to this area called the perirhinal cortex, that was where they were struggling. So somehow this brain area was important for being able to do these things that were adversarial to these computer vision models. So then he found that it only happened if people had enough time they could make those discriminations.
And then he found those were the exact ones where these humans with particular damage to this area called the perirhinal cortex, that was where they were struggling. So somehow this brain area was important for being able to do these things that were adversarial to these computer vision models. So then he found that it only happened if people had enough time they could make those discriminations.
And then he found those were the exact ones where these humans with particular damage to this area called the perirhinal cortex, that was where they were struggling. So somehow this brain area was important for being able to do these things that were adversarial to these computer vision models. So then he found that it only happened if people had enough time they could make those discriminations.
But without enough time, if they just get a glance, they're just like the computer vision models. So then what he started to say was, well, maybe let's look at people's eyes, right? So a computer vision model sees every pixel all at once, right? It's not, you know, and we don't, we never see every pixel all at once. Even if I'm looking at a screen with pixels, I'm not seeing every pixel at once.
But without enough time, if they just get a glance, they're just like the computer vision models. So then what he started to say was, well, maybe let's look at people's eyes, right? So a computer vision model sees every pixel all at once, right? It's not, you know, and we don't, we never see every pixel all at once. Even if I'm looking at a screen with pixels, I'm not seeing every pixel at once.
But without enough time, if they just get a glance, they're just like the computer vision models. So then what he started to say was, well, maybe let's look at people's eyes, right? So a computer vision model sees every pixel all at once, right? It's not, you know, and we don't, we never see every pixel all at once. Even if I'm looking at a screen with pixels, I'm not seeing every pixel at once.
I'm grabbing little points on the screen by moving my eyes around and getting a very high resolution picture of what I'm focusing on and kind of a lower resolution information about everything else.
I'm grabbing little points on the screen by moving my eyes around and getting a very high resolution picture of what I'm focusing on and kind of a lower resolution information about everything else.
I'm grabbing little points on the screen by moving my eyes around and getting a very high resolution picture of what I'm focusing on and kind of a lower resolution information about everything else.