Like if you trained a machine learning algorithm to differentiate 10 samples of asbestos containing material from 10 non-asbestos containing materials I wouldn't believe it would work with all the many kinds of materials you would find out in the field in all the configurations that are out there.
All that talk of how the electromagnetic properties of asbestos-containing materials are different are pretty handwavy and lack a theoretical explanation of where the dividing line between different materials ought to be. Overall it strikes me as the kind of half-baked idea that people suddenly feel empowered to do thanks to AI.
Yes, it is half baked, we stopped because the quantity of data needed to continue was too expensive. Concerning the materials that were in the confusion matrix that you saw, it was only non asbestos materials (plexiglas doesn't ever contain asbestos for instance). The confusion matrix that you saw was made to prove you could identify different materials from one another, we never went as far as getting two same materials and one with asbestos minerals inside it.
About AI. Two things you learn in school : for centuries, we measured the world and modelled it using differential equations, and other mathematical concepts. Humans just have a certain limit to finding patterns, and this limit is covered by AI, which when you come to think of it is just a series of calculations to model statistical phenomenons.
Physics is a statistical phenomenon, therefore AI is now being used everywhere in physics to model the world.
It's a cool technology, but for it to gain commercial interest it needs to solve a problem better than the status quo. What problem is it solving and for who? If I was to buy that mmwave radar device it would probably cost more than the $60 test, and I would want assurances that it is as accurate as existing tests.
exact, if I was carrying a PhD (which I am not). I think I would have wanted to go out further and get more data to make this device pass regulatory tests.
What was the status quo we were solving for ? An asbestos analysis costs around 60€ per sample in Europe when you ask it to a professional asbestos diagnoser. One use of our radar cost litterally the cost of an API call, so we were definetly beating the status quo. The big challenge around this was actually who is the customer ? We initially wanted to sell it to the pro diagnoser, but in France there is some sort of tacit agreement between diagnosers and asbestos labs to keep prices high on purpose (because it advantages both of them), they protect their business well and put high regulatory gates around this. Building a tech startup isn't just about overcoming the tech barriers, but also regulatory barriers which are often really underestimated.
overtech for a problem that had a solution (asbestos sensing is pretty painful in Europe), but anyways the market was shrinking, and the TAM was totally not VC backable. Tested it out with : wood, copper, alumnium, paper (the book you saw), stone, PVC, plexiglas and air
Comments
Kinda crazy that it worked but got no commercial interest. Hopefully someone suitable here sees it and can intervene
Does it also work through other materials. i.e. through a drywall etc.
I can't say that I believe that it works.
Like if you trained a machine learning algorithm to differentiate 10 samples of asbestos containing material from 10 non-asbestos containing materials I wouldn't believe it would work with all the many kinds of materials you would find out in the field in all the configurations that are out there.
All that talk of how the electromagnetic properties of asbestos-containing materials are different are pretty handwavy and lack a theoretical explanation of where the dividing line between different materials ought to be. Overall it strikes me as the kind of half-baked idea that people suddenly feel empowered to do thanks to AI.
Yes, it is half baked, we stopped because the quantity of data needed to continue was too expensive. Concerning the materials that were in the confusion matrix that you saw, it was only non asbestos materials (plexiglas doesn't ever contain asbestos for instance). The confusion matrix that you saw was made to prove you could identify different materials from one another, we never went as far as getting two same materials and one with asbestos minerals inside it.
About AI. Two things you learn in school : for centuries, we measured the world and modelled it using differential equations, and other mathematical concepts. Humans just have a certain limit to finding patterns, and this limit is covered by AI, which when you come to think of it is just a series of calculations to model statistical phenomenons.
Physics is a statistical phenomenon, therefore AI is now being used everywhere in physics to model the world.
It's a cool technology, but for it to gain commercial interest it needs to solve a problem better than the status quo. What problem is it solving and for who? If I was to buy that mmwave radar device it would probably cost more than the $60 test, and I would want assurances that it is as accurate as existing tests.
exact, if I was carrying a PhD (which I am not). I think I would have wanted to go out further and get more data to make this device pass regulatory tests. What was the status quo we were solving for ? An asbestos analysis costs around 60€ per sample in Europe when you ask it to a professional asbestos diagnoser. One use of our radar cost litterally the cost of an API call, so we were definetly beating the status quo. The big challenge around this was actually who is the customer ? We initially wanted to sell it to the pro diagnoser, but in France there is some sort of tacit agreement between diagnosers and asbestos labs to keep prices high on purpose (because it advantages both of them), they protect their business well and put high regulatory gates around this. Building a tech startup isn't just about overcoming the tech barriers, but also regulatory barriers which are often really underestimated.
Looks like he succesfully pivoted: https://waves.black/ and he is building an OTA update framework apparently now : https://www.nanoforgeflow.com/
The guy is scrappy.
overtech for a problem that had a solution (asbestos sensing is pretty painful in Europe), but anyways the market was shrinking, and the TAM was totally not VC backable. Tested it out with : wood, copper, alumnium, paper (the book you saw), stone, PVC, plexiglas and air