alt Hacker NewsI find it interesting that we seem to have mastered what the human eye can do and even go beyond it with like infrared but somehow we still can't build a chip that can "taste" or "smell".
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Makes total sense to me. Detecting and measuring photons seems much simpler than accurately detecting whole molecules. When we need to detect if a sample contains a certain kind of molecule, it usually requires expensive chemical processes.
The human eye is still pretty difficult to beat on some metrics, especially dynamic range (I think top-of-the-line sensors are now competitive, but for a while there was not really any options)
I think at least _part_ of the reason why is that it's just a whole lot less useful? There's tons and tons of applications for image and video and the automated analysis of it (for art, documentation or business purposes), whereas taste/smell capture and the analysis of it doesn't have that many useful use-cases (the article points at one of course, I'm not saying there's no use-case but much fewer). So we put a whole lot of effort and money into developing it, which didn't happen for smell.
If you just want a histogram of all the chemicals that are present, that would probably be doable if not already done. But how would you even quantify/qualify the "sensations" of those senses?
Vision is "easy": What I see is what you see is what the machine sees.
A machine shows us what it sees and we can verify that it is working correctly, with a glance.
How would we verify that a machine smells or tastes "correctly"?
- "quantum mechanics are so hard to reason about since I have no senses where that plays a part"
- "oh, so you have no sense of smell?"
This is exactly the problem I've been obsessing over. The challenge is that olfaction isn't like vision. you're not detecting photons at discrete wavelengths, you're dealing with ~400 olfactory receptor types responding to millions of possible volatile molecules in combinatorial ways.
MOX sensors (like the SnO2 in this paper) have been around for decades but hit a fundamental ceiling—they require specific coatings to bind to specific VOCs. Want to detect a new substance? You're changing hardware.
The more promising path, IMO, is carbon nanotube (CNT) sensors that actually mimic how our nose works. Instead of measuring bulk resistance changes, you functionalize CNT arrays to respond to specific molecular binding events—much closer to how olfactory receptors operate. detection of new substances becomes a software/ML problem rather than a hardware redesign. That's how biology does it—your nose doesn't grow new receptors, your brain learns new patterns.
Full disclosure: I'm building in this space (https://nosy.network) Nosy is using CNT paired with transformer models to create what we call a "Large Essence Model" (LEM). LEM "GPT for smell" processes scent information similar to how LLMs process text.