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AI should be trained on the chemical 'language' that 99% of species — bacteria, fungi, plants, insects — use to communicate, treating it as an alien form of intelligence worth adding to our models.

Alex Wiltschko argues that since most life on Earth communicates only through chemistry, AI should be trained on that 'alien' chemical intelligence, not just human-generated text and images. ✦ AI generated

Alex Wiltschko · The TWIML AI Podcast · 2026-07-08 · original ↗

starts at this moment · 1:19

99% of species on this planet can only speak with chemistry, right? Thinking of bacteria and fungi and and plants and insects, like they just only can talk with molecules. And I think that it's really worth adding other kind of alien forms of intelligence to our AI models. And the way to do that is to train it on the intellectual output of those other intellects, which is that's chemistry.

verbatim transcript · starts at 1:19

Transcript · around this moment

1:19models. And the way to do that is to train it on the intellectual output of those other intellects, which is that's chemistry. That's the sense that's in the air. They're produced by living things for reasons to talk to each other. I'm Sam Chington and this is the Twimmel AI podcast. For over a decade, I've been exploring the ideas and innovations shaping the future of AI through conversations like this one that

1:40help you understand what's real, what's next, and what [music] matters. Let's jump in. When I think about giving computers a sense of smell, uh there's kind of two angles to this. One is, you know, there's some scent out in the world and I want my computer to be able to recognize it the same way I do. Uh, and the other, which is, I think, more along the lines of what you're working on at

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

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