How AI Learns to Smell with Alex Wiltschko - #771

AI has advanced primarily by learning from the digital world, text, images, audio, and increasingly video. But many of the problems people want AI to solve live outside these modalities in the physical world. Smell is one of the most interesting examples. It's how animals detect disease, identify food, navigate environments, and communicate through chemistry. Yet, scent has remained largely outside the reach of computing because, unlike language or images, there has never been a practical way to digitize it at scale. Alex Wolchko, founder and CEO of Osmo and a formal Google DeepMind researcher, is working to change this. His team is building what they call olfactory intelligence, AI systems that can model, predict, and design scents while creating the datasets and infrastructure needed to bring smell to the digital world. In this conversation, we explore what it takes to give computers a sense of smell, why scent is such a difficult AI problem, and what it teaches us about the next generation of foundation models. Here's Alex. 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. 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 Charrington, and this is the Twimble AI podcast. For over a decade, I've been exploring the ideas and innovation shaping the future of AI through conversations like this one that help you understand what's real, what's next, and what matters. Let's jump in. When I think about giving computers a sense of smell, 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. And the other, which is, I think, more along the lines of what you're working on at Osmo, at least initially, is to have the computer kind of grok 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 gotta read the world to, 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 it, and that's like JPEG and RGB. Right? And then you have to be able to write it back out again. Right? So, printer or a display or a speaker. 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 for representation of well, what to what thing? Exactly. …