Detecting diseases like cancer or malaria from scent will require assembling a massive, ground-up olfactory dataset by sniffing thousands of people and everyday objects, because you can never collect enough subjects to statistically learn the subtle, distributed molecular signal directly.
Wiltschko argues scent-based disease detection can't be cracked by collecting data only from sick versus healthy people, since sample sizes will never be large enough to isolate the subtle multi-molecule signal — instead it requires a massive, general-purpose olfactory data-collection effort across thousands of people and objects. ✦ AI generated
Alex Wiltschko · The TWIML AI Podcast · 2026-07-08 · original ↗
starts at this moment · 41:17
“Meaning because there's not enough signal and the correlation between scent and disease or some other factor. Are you speaking?”
You can go directly after that and like collect uh scent data from people with or without those conditions and try to build models, you're never going to get enough people to build a great model, right? And like there's just it's just hard to go get that much data.
verbatim transcript · starts at 41:17
41:17those as data collection problems. >> But so here's here's the deal. You can go directly after that and like collect uh scent data from people with or without those conditions and try to build models, you're never going to get enough people to build a great model, right? And like there's just it's just hard to go get that much data. >> Meaning because there's not enough signal and the correlation between scent
41:42and disease or some other factor. Are you speaking? just low numbers. It's just just from a pure statistics and machine learning problem. You know, I think basically there's not an obvious obvious obvious signal that says this person has, you know, a disease and then dozen. There are subtle changes across like many, you know, hundreds or potentially thousands of molecular signals. We just don't know. Um, but we
42:04know dogs can do it. Like animals can actually detect these patterns. So there's something, >> right? That's what I was thinking of when you raised. >> It's for sure there. It's for sure there. Um, but we can't get computers to do it. >> We just need to go get a ton of data, right? Like we need to like band together and build a huge effort where we just like let's go sniff 10,000
42:21people. I don't care if they're healthy or sick. I don't care how old they are. I don't care. I mean, let's record all that information, of course, but like let's just go get a ton of data. Let's go to the grocery store and get cucumbers and bananas, flowers, and like steaks and whatever. Um, and let's just go smell everything and then build a huge oldactory data set of what the
42:41world smells like. And if we can do that, then then >> it sounds a lot harder than scraping Reddit one more time. [laughter] >> Whole lot harder than scraping Reddit. But it's worth it because literally nobody's going to do it unless we pull pull ourselves together. So like but this it's like worth doing, right? Like you know this is the thing that maybe as an aside but like I have a lot of
43:02friends in the world of AI and ML and you know I came in through this as a biologist and as a biologist like you go do experiments and it's like hard and like you got to go to the bench and get your own data and you know it's gritty. Um and in the world of AI like you kind of just assume the data is out there and