Alex Wiltschko

You can put like anything into these vials and it will suck the smell from out of what you put in the vials. It will analyze it.

You can put like anything into these vials and it will suck the smell from out of what you put in the vials. It will analyze it.

Directly. So what it does is it pumps air into these vials with a needle syringe. So it'll get dropped in here. A needle will be pushed into it. So basically we'll suck the air and we'll concentrate it onto, you know, like Kodak film absorbs light. We have film that absorbs scent.

Directly. So what it does is it pumps air into these vials with a needle syringe. So it'll get dropped in here. A needle will be pushed into it. So basically we'll suck the air and we'll concentrate it onto, you know, like Kodak film absorbs light. We have film that absorbs scent.

And they basically concentrate the smell on that thin piece of film, and then you move that needle and you inject it into the spectrometer, and it uses a flash of heat to remove all those molecules. It kind of develops the film. And then the normal machine runs, we analyze the data with AI, and then we can pull back out what the scent actually was.

And they basically concentrate the smell on that thin piece of film, and then you move that needle and you inject it into the spectrometer, and it uses a flash of heat to remove all those molecules. It kind of develops the film. And then the normal machine runs, we analyze the data with AI, and then we can pull back out what the scent actually was.

So this means that we can analyze flowers and vegetables and people and fruits. And so what we did, the first scent that we fully teleported digitally was a fresh summer plum. So it was like kind of the purple plum, you know, like the really good ones have like a snap when you bite into it. It was like one of those fresh ones.

So this means that we can analyze flowers and vegetables and people and fruits. And so what we did, the first scent that we fully teleported digitally was a fresh summer plum. So it was like kind of the purple plum, you know, like the really good ones have like a snap when you bite into it. It was like one of those fresh ones.

So we sliced it, we put it into one of these vials, we analyzed the smell, and then we actually reprinted the smell on the other side of the lab, which I'll show you. The other thing you can do with this machine, which is really cool, is you can pause the smell at any point in time and you can just sniff molecule by molecule.

So we sliced it, we put it into one of these vials, we analyzed the smell, and then we actually reprinted the smell on the other side of the lab, which I'll show you. The other thing you can do with this machine, which is really cool, is you can pause the smell at any point in time and you can just sniff molecule by molecule.

So a scent will be like 30 molecules, 100 molecules all blended together, different types. You can smell them one by one by putting your nose on here. It's kind of like a debugger for software. Wow. So this is called a GCO or gas chromatograph olfactometer.

So a scent will be like 30 molecules, 100 molecules all blended together, different types. You can smell them one by one by putting your nose on here. It's kind of like a debugger for software. Wow. So this is called a GCO or gas chromatograph olfactometer.

But when we really want to understand the smell and kind of like build our intuition when we're building new protocols, we'll actually sit here and sniff stuff that comes off the machine.

But when we really want to understand the smell and kind of like build our intuition when we're building new protocols, we'll actually sit here and sniff stuff that comes off the machine.

Exactly. And if you can read and write, then you can create this virtuous cycle where you're creating data at every run of the loop. And so if you actually can create new smells and then you can turn those smells into data readings of some kind, you're training AI.

Exactly. And if you can read and write, then you can create this virtuous cycle where you're creating data at every run of the loop. And so if you actually can create new smells and then you can turn those smells into data readings of some kind, you're training AI.

And then if you can tilt that process so the next smells that you create the next day teach the system even more, that's when you're doing what's called active learning. And that's how you get AI systems to get smart really fast. And that's what we do.

And then if you can tilt that process so the next smells that you create the next day teach the system even more, that's when you're doing what's called active learning. And that's how you get AI systems to get smart really fast. And that's what we do.

There's more nuance to how we do that to create data that can actually be fed into a machine learning system. But that's effectively it, which is like, do these things match? And there's a few tricks that you use to help de-bias people and get reliable data. But like, you're the arbiter, right?

There's more nuance to how we do that to create data that can actually be fed into a machine learning system. But that's effectively it, which is like, do these things match? And there's a few tricks that you use to help de-bias people and get reliable data. But like, you're the arbiter, right?