Osmo

“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, like, we couldn't just buy that service from anybody. We had to build it from the ground up.”

“The idea here is you need to have all the ingredients together that can be mixed on the fly to create any experience. Not just like eight pre-programmed experiences. That's like a slideshow, right? We want an actual display that can show anything.”

“And it turned out that our AI predictions of what these smells were going to be were better than the average panelist. Meaning if you're going to add one more person to this panel, you'd actually prefer to ask our software what it smells like that doesn't have…”

“What we've been able to do with StockX is show that we can take those really big sensors that are in the lab. Cut the right corners. Make them smaller. So it's actually, the sensors are about the size of these two shoe boxes together. That's one right there. A…”

“Instead of CMYK, we actually use hundreds of scents as kind of our primary odors, and That's what allows us to create, ah, all the sense that we need to train the AI system. So this is the writing part of the AI training loop.”

“It was Polo Blue. It was Abercrombie and Fitch Fierce. Both fragrances that our master perfumer that we just passed designed, right, many years ago, so it's completely full circle now.”

“We have a building of people that label smells all day every day, right? We have a laboratory full of sensors that 24 seven are dissecting scent down to the molecular level. We have robots that are creating smell.”

“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?”

“Our map is not three-dimensional like RGB, it's about 300 dimensional, which is, I think, why scent had to wait for artificial intelligence to be digitized, because it's just more complicated.”

“So, and this is, by the way, this is a multi-month process that we're condensing down into, you know, minutes.”

“So this is kind of like a piece of history here, Plum One Point O. This was the first scent that was teleported. So the first scent to be digitized and then reconstituted in another place.”

“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 system.”

“So in this room is, you know, 10, 20,000 molecules. That have all been designed by AI, and we have a digital twin of each”

“The exit strategy is death. Right, like, this is the last thing I want to do.”

“We're launching a new kind of fragrance house called Generation, and the idea is to take all the technology that we've built, but also all the humanity, the people, the perfumers, the noses, and to combine that”

“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, right?…”

“Like, let me draw a molecule on the whiteboard, like we're in chemistry class. Can you look at that molecule and tell me what it's going to smell like? Will it smell like apple or cinnamon or? You know, Anis or what? So it turns out that's like a hundred year …”

“We went through a similar journey where we, I mean, if I could have sold the software here, and believe me, we've tried, like, yeah, we'd be selling software. We might not be talking but there's not that many fragrance houses, period”

“We have to take that down by a factor of like four to eight in order for this to be something you would really say is portable. Right now we can move it around. We could deploy it. I don't think you can say it's portable today.”