Alex Wiltschko

speaker

1,050 appearances 3 recordings 3 series first heard Mar 2025 last heard 21 Apr

Alex Wiltschko’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

Recordings per month over the last 12 months — 2 in all, peaking in Apr 2026 with 1.

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The Neuron: AI Explained · Teaching Computers to Smell?! The AI That's Digitizing Scent · 7 Nov 2025 podcast

And we're going to have some great announcements soon.

But we've got a private beta program.

So if you Google around for how to create scent with Osmo Studio, I think you'll be able to find that.

And then stay tuned for not too long in the future when we have an amazing tool that anybody can use to create their own scents using olfactory intelligence.

Invest Like the Best with Patrick O'Shaughnessy · Alex Wiltschko - Giving Computers A Sense Of Smell - [Invest Like the Best, EP.415] · 18 Mar 2025 podcast

So we smell a lot of stuff. Twice a day we run sensory panels where we just sniff stuff and label stuff. So it's just like Scale.ai has people labeling images all over the world. Turns out we couldn't just buy that service from anybody. We had to build it from the ground up. So this is where things get tested and low latency work happens. And then when we scale it, that happens elsewhere.

smelling stuff are they like notably talented smellers we we actually have literal rankings and so like when we need really accurate data of a certain kind we will call on our like top dogs you know so in there is synthetic chemistry just like a drug company to create a new molecule to affect human health, we create new molecules that affect human perception.

And we design those on spec for customers that like a large customer might say, all right, we're having this problem making our detergent smell this way, or the regulatory landscape is changing. We can't use this molecule. Can you please help us? So we take all those requirements. We go back into the lab and we use AI, but when it's applied to olfaction, we call it OI or olfactory intelligence.

So we use OI to design new molecules, which we then synthesize with our synthetic chemistry team, smell them, they work, we launch them.

So it's like a little bit maple syrupy today. So I don't know what they're making. I guess they're going through a lot of commercial fragrances right now. So you're smelling kind of the sum total of our work. So behind you is what's called the perfumer's organ. Each bottle there is like kind of a key on a piano. And instead of 88 keys, it's about 1200 keys. So a perfumer will be able to

pull any of these ingredients together and mix them in the right ratios to recreate your scent memories. So like the smell of fresh laundry was made by a person, right, from some of these ingredients. The smell of, you know, a clean kitchen was created from some of these ingredients.

So 90% of the products in your home have a fragrance and every single one of those fragrances was crafted by an individual and they were crafted by combining these ingredients together.

So what we're doing at Osmo is teaching AI about these ingredients and how to work with them in a safe way, to do it super fast, to do it super affordable, and to be able to launch new beautiful scents that were possible.

This is a machine called a GCMS. This is basically a camera for the molecular world. I'll just show you kind of how it works. So this is a robotic autoloader. And so each one of these has a smell that we want to analyze at the molecular level. So this thing can run 24-7. So we load this thing up. We just let it run.

What happens is you suck up a little bit of the smell as a liquid and you inject it and it goes into this half of the device, which is basically an oven with a 50 meter long, very thin cable. And you're shoving the smell through that cable. And what you're trying to make the smell do is like runners in a marathon. So every molecule in that

scent is all clumped together and you experience that as one kind of unified sensation as a smell you got to separate them to analyze them and so what you do first is you run them through a race and the light molecules make it through the race first and so they can be analyzed one by one here and heavy molecules come out later and later and later so this basically separates the scent into each individual molecule that's in the smell and then this side weighs them so the molecules enter the mass spectrometer after being separated and you basically hit it with a

an electron gun and it shatters the molecule into pieces and you very carefully weigh those pieces. And then you play kind of like a Sudoku puzzle to figure out, okay, given the weights of these fragments, given how long it took to run this race, what was that molecule? And typically this interpretation is done part by software, part by people.

And what we've done at Osmo is make that happen entirely by software. So that's a part of our OI

So nobody knows, but we're teaching the machines to figure that out. So that has been the core, core issue of why scent hasn't been digitized is because exactly what you're saying is- You don't know what maple syrup breaks down into as primary smells. Exactly. So people have been analyzing the molecular content of these smells for a long time.

So you can go look up in some textbook what the molecules in maple syrup are. but the ability to say, okay, I want maple syrup with a little bit more cherry, or I want maple syrup, but don't use that molecule because we know it's not safe. Use this other molecule. That requires tons of trade craft. That is what we're automating.

So these machines are great. And what we're

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