Giving computers a sense of smell requires three steps: reading the world (turning atoms into bits), mapping it (encoding and manipulating it digitally, the way JPEG and RGB do for images), and writing it back out (through something like a printer or speaker) — and the piece that's been missing for scent, which Osmo focused on, is the map.
Alex frames the problem of computerizing smell as analogous to color and sound digitization, breaking it into read/map/write stages, and identifies the missing 'map' as Osmo's founding technical focus. ✦ AI generated
Alex Wiltschko · The TWIML AI Podcast · 2026-07-08 · original ↗
starts at this moment · 2:10
“When I think about giving computers a sense of smell, there's kind of two angles to this. One is there's some scent out in the world and I want my computer to be able to recognize it the same way I do. And the other, which is more along the lines of what you're working on at Osmo, is to have the computer kind of grock the idea of scent so that it can create new ones.”
Any scent that's been given to computers, there's three kind of broad steps. You got to read the world. So, like turn atoms into bits and information. You have to map it, like understand it... and then you have to be able to write it back out again... the thing we focused on at Google Brain was the missing piece, which is for scent is the map.
verbatim transcript · starts at 2:10
2:10Osmo, at least initially, is to have the computer kind of grock the idea of scent so that it can create new ones. >> Any scent that's been given to computers, there's three kind of broad steps. You got to read the world. So, like turn atoms into bits and information. you have to map it, like understand it. So, you know, be able to manipulate it digitally, encode it, send
2:31it, and that's like JPEG and RGB, right? Um, and then you have to be able to write it back out again, right? So, a printer or a display or a speaker. Um, and so the thing we focused on at Google Brain was the missing piece, which is for scent is the map. So, color has had a map, >> sort of representation of well, what to what though?
2:53>> Exactly. Exactly. So like let's let's approach it from the side like how did this work for vision? How did this work for hearing? Right? We've had maps for a long time, right? So the map for sound is just one dimension. It's low to high frequency. Really simple to say. Uh and then for color it's it's three numbers. It's RGB, right? Or whatever your preferred color space is. But those
3:12three numbers like tell you how to deal with color. There's three channels of color information in our eye. But of of course you're simplifying a lot because for each of those other modalities, there's lots of different maps. Totally. >> Those are just examples of >> they're examples and they can kind of be translated into each other, but I'm like I'm papering over like centuries of psychopysics here and anybody who knows
3:33anything about those things is going to come screaming at me. Um, but you'll have to forgive the simplifications. [laughter] I'm going to simplify sense stuff, too. And if people talked the way that I'm going to talk, I would come after them, too. Um, so yeah, there's CMYK, there's Lab, there's HSV, there's many different maps. And then there's more complex maps. >> I was scarred by a DSP class in grad
3:51school. It all came back in. Exactly. You know, and like there's filter sets, there's Gabbor [clears throat] filter sets, there's, you know, all kind there's huff trans like there's all kinds of ways of representing images and I'm super simplifying it, right? But like maps, they for certainly they're there and and we know them. We've known them for a while and the notion that like we can map color has been