4 ms·

I 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 t

I 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".

lopis 9mo ago
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.
- throwaway198846 9mo ago
  Or Mass spectrometry
  - Terr_ 9mo ago
    Pretty sure that relies on a lot of assumptions about how the pieces being detected originally fit together, or extremely pure samples.
    - Latitude7973 9mo ago
      Mass spectrometry is a multi-faceted beast, and has many applications. One that comes to mind is ion mobility spectrometry. I am most familiar with FAIMS which is an extremely selective method and can detect trace amounts of specific molecules. The challenge is piecing together what you have detected to draw conclusions about the sample - in this instance you might detect a specific molecule, but to definitively conclude that it's caused by a particular fungus requires lots of prior testing.
Razengan 9mo ago
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"?
- sschueller 9mo ago
  The machine would need to reproduce the smell just like it reproduces what it sees on a screen. What the sensor "sees" isn't what our eye sees either.
- deleted 9mo ago
  [deleted]
- Terr_ 9mo ago
  > a histogram of all the chemicals that are present, that would probably be doable if not already done. I'm no olfactory biochemist, but that sounds like science-fiction to me. The, er, reference implementation we're talking about is advanced nanotechnology we don't fully understand. While we can do stuff like mass-spectrography, that involves destroying complex chemicals and converting them to smaller fragments we can tally, and then guessing at possible configurations they might have originally had. If someone had a device that could simply tell you the exact chemical formulas of all molecules of any kind in a sample, it would be used everywhere and they would be very rich.
  - sumea 9mo ago
    You are right that such device does not exist, but in theory you could combine many analytical techniques to a single black box that could analyze practically all of molecules and particles in the air or even in more complicated samples. It would contain at least some sort of chromatography, nmr, mass spectrometer, infrared spectrometer and various special analytical techniques for some compounds. Also some kind of sample preparation system would be needed. This would be a very large machine and you would need to provide a sample to it in a test tube or similar manner. Automated blood analyzers in hospitals are maybe the closest thing to a such device.
- luz666 9mo ago
  The machine smells correctly, when the same numbers (or similar when using some norm, e.g. the L2) appear for the same smell (reproducibility) and therefore a mapping (numbers -> smell) can be created. When this starts to exist (practically usable), there can be a database to store the mappings, allowing classification. E.g., the machine says "this tastes like banana". The machines/algorithms/products could itself be rated for precision. I dont say such machines don't exist, but for my taste (pun intended) the solutions all lack something, either long term stability or having a second source supplier or being able to classify a reasonable amount of tastes or being able to distinguish between two tastes (or lacking all those things together).
ptman 9mo ago
- "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?"
williamdclt 9mo ago
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.
- praptak 9mo ago
  Dog level smell is pretty useful, as evidenced, well, by actual dog usage. OTOH maybe dogs are cheap enough not to create strong incentive for automation.
  - red-iron-pine 9mo ago
    can't cuddle my laptop the same way I can a goofy-but-well-trained golden retriever
    - praptak 9mo ago
      Maybe programmers should become cuddly to avoid being replaced by AI.
rcxdude 9mo ago
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)
- jeremyscanvic 9mo ago
  Any reference you can share on this? I'm genuinely curious speaking as a PhD student in image processing for computer vision
vjanma 9mo ago
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 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.

I 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".

lopis 9mo ago

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.

throwaway198846 9mo ago
Or Mass spectrometry
- Terr_ 9mo ago
  Pretty sure that relies on a lot of assumptions about how the pieces being detected originally fit together, or extremely pure samples.
  - Latitude7973 9mo ago
    Mass spectrometry is a multi-faceted beast, and has many applications. One that comes to mind is ion mobility spectrometry. I am most familiar with FAIMS which is an extremely selective method and can detect trace amounts of specific molecules. The challenge is piecing together what you have detected to draw conclusions about the sample - in this instance you might detect a specific molecule, but to definitively conclude that it's caused by a particular fungus requires lots of prior testing.

Razengan 9mo ago

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"?

sschueller 9mo ago
The machine would need to reproduce the smell just like it reproduces what it sees on a screen. What the sensor "sees" isn't what our eye sees either.
deleted 9mo ago
[deleted]
Terr_ 9mo ago
> a histogram of all the chemicals that are present, that would probably be doable if not already done. I'm no olfactory biochemist, but that sounds like science-fiction to me. The, er, reference implementation we're talking about is advanced nanotechnology we don't fully understand. While we can do stuff like mass-spectrography, that involves destroying complex chemicals and converting them to smaller fragments we can tally, and then guessing at possible configurations they might have originally had. If someone had a device that could simply tell you the exact chemical formulas of all molecules of any kind in a sample, it would be used everywhere and they would be very rich.
- sumea 9mo ago
  You are right that such device does not exist, but in theory you could combine many analytical techniques to a single black box that could analyze practically all of molecules and particles in the air or even in more complicated samples. It would contain at least some sort of chromatography, nmr, mass spectrometer, infrared spectrometer and various special analytical techniques for some compounds. Also some kind of sample preparation system would be needed. This would be a very large machine and you would need to provide a sample to it in a test tube or similar manner. Automated blood analyzers in hospitals are maybe the closest thing to a such device.
luz666 9mo ago
The machine smells correctly, when the same numbers (or similar when using some norm, e.g. the L2) appear for the same smell (reproducibility) and therefore a mapping (numbers -> smell) can be created. When this starts to exist (practically usable), there can be a database to store the mappings, allowing classification. E.g., the machine says "this tastes like banana". The machines/algorithms/products could itself be rated for precision. I dont say such machines don't exist, but for my taste (pun intended) the solutions all lack something, either long term stability or having a second source supplier or being able to classify a reasonable amount of tastes or being able to distinguish between two tastes (or lacking all those things together).

ptman 9mo ago

- "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?"

williamdclt 9mo ago

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.

praptak 9mo ago
Dog level smell is pretty useful, as evidenced, well, by actual dog usage. OTOH maybe dogs are cheap enough not to create strong incentive for automation.
- red-iron-pine 9mo ago
  can't cuddle my laptop the same way I can a goofy-but-well-trained golden retriever
  - praptak 9mo ago
    Maybe programmers should become cuddly to avoid being replaced by AI.

rcxdude 9mo ago

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)

jeremyscanvic 9mo ago
Any reference you can share on this? I'm genuinely curious speaking as a PhD student in image processing for computer vision

vjanma 9mo ago

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 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.