Great writeup. This focuses heavily on the fragrance/perception side of digital olfaction, but there's a whole other dimension here: detection. Think of it as speaker vs microphone — most of the hype (Osmo, Givaudan) is on generating and designing scents, but detecting and identifying chemical signatures in real-world environments is an equally hard problem.
The article nails the core challenge: the structure-odor relationship is messy and there's no "RGB of smell." We're hitting the same wall from the detection side. Getting to parts-per-trillion sensitivity is one thing; making sense of complex, noisy molecular signatures in the wild is another. The DREAM challenge benchmarks are encouraging, but the gap between lab conditions and real-world deployment is enormous.
Curious if anyone else is working on the detection and safety rather than fragrance. Feels underrepresented relative to the urgency.
Disclosure: I work in the scent detection space.
Rendered at 06:36:35 GMT+0000 (UTC) with Wasmer Edge.
The article nails the core challenge: the structure-odor relationship is messy and there's no "RGB of smell." We're hitting the same wall from the detection side. Getting to parts-per-trillion sensitivity is one thing; making sense of complex, noisy molecular signatures in the wild is another. The DREAM challenge benchmarks are encouraging, but the gap between lab conditions and real-world deployment is enormous.
Curious if anyone else is working on the detection and safety rather than fragrance. Feels underrepresented relative to the urgency.
Disclosure: I work in the scent detection space.