Alex Wiltschko

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.

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

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

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.

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

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 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 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

So these machines are great. And what we're

not going to do is we're not going to change the hardware because there's about a there's 12 nobel prizes worth of advances inside of these machines they're fantastic what we've done is rip out the brains and we've replaced it with our own brain so a lot of what we've noticed is the hardware actually is already pretty good in the realm of scent and chemistry but the software or the maps that link the different pieces of hardware has been completely missing that's what we built this is kind of like an inner sanctum here um

not going to do is we're not going to change the hardware because there's about a there's 12 nobel prizes worth of advances inside of these machines they're fantastic what we've done is rip out the brains and we've replaced it with our own brain so a lot of what we've noticed is the hardware actually is already pretty good in the realm of scent and chemistry but the software or the maps that link the different pieces of hardware has been completely missing that's what we built this is kind of like an inner sanctum here um

So this is where we keep every AI-designed molecule that we've made, which is probably a significant fraction of all AI-designed molecules ever. And so this is just one slice of it. So in this room is 10,000, 20,000 molecules that have all been designed by AI. And we have a digital twin of each. So if we need to go back and access it, we know it's fridge one, shelf three, row column two, four.

So this is where we keep every AI-designed molecule that we've made, which is probably a significant fraction of all AI-designed molecules ever. And so this is just one slice of it. So in this room is 10,000, 20,000 molecules that have all been designed by AI. And we have a digital twin of each. So if we need to go back and access it, we know it's fridge one, shelf three, row column two, four.