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It's a little surprising to me (not necessarily bad, just unexpected) that Google is researching this. Yes, it's good for companies to do some R&D, and sometim

It's a little surprising to me (not necessarily bad, just unexpected) that Google is researching this. Yes, it's good for companies to do some R&D, and sometimes the R part of the R&D gets pretty theoretical, which is usually a good sign that a company is trying to really innovate. But usually also there's some indirect way to tie it back to some kind of application that could possibly somehow make the company money in the long term. Otherwise, you're just a for-profit company spending money on something because it's interesting. So what's the application here? Are there novel ideas or techniques here that can be applied to other AI problems? Is there some kind of application for smell in a Google product?

phonebucket 7y ago
The backbone of this work is graph convolutional neural networks. These have wide spread applicability in predicting molecular properties (useful to Google Health), building recommendation systems (useful in many obvious ways to Google), and modelling phenomena in social networks, to name a few off the top of my head. So while the scent identifying doesn’t seem directly relevant, nailing the underlying techniques is valuable.
Jabbles 7y ago
Google Cloud wants to be known as the best place for all kinds of machine learning. Google may not want to get into perfume manufacturing, but it wants Unilever (?) to run all their ML research on their cloud. This kind of research strengthens that part of their brand. (complete speculation, but seems plausible)
pharrington 7y ago
This is building a fundamental component for automated generalized molecule detectors.
dekhn 7y ago
Google invests fairly heavily into research and there is a fair amount of freedom among engineers and researchers to do projects with Google resources, even when there is no direct product application. For example, I ran an idle-cycle-harvesting service at Google called Exacycle that ran problems like protein folding, protein design, drug discovery, telescope discovery, and more. The only pushback I got was to run problems where the results could reasonably be considered "useful" (scientifically). One way to think about it is that many of the people with power at Google really like science and have the resources to support it. Once you've built things like TPUs, it would be a waste not to dedicate some about of their resources to problems that people wouldn't be able to address. Another way to think about it is these things have indirect effects- even if Google didn't want to make some sort of product with smell (like a phone with a builtin GC-MS?), publishing this work gets the attention of scientists, who will then read the paper, and consider Google Cloud as a place they'd like to do their work.
Pick-A-Hill2019 7y ago
From the second paragraph "Solving the odor prediction problem would aid in discovering new synthetic odorants,". Reading between the lines - a cheaper way to produce more realistic industrial aromatics cheaper.
Myrmornis 7y ago
If we're feeling positive about the world, since it's Friday: Google wants to help the world by reducing our reliance on farming animals for meat, and thought that research like this would help humanity's nascent artificial meat endeavours.

phonebucket 7y ago

The backbone of this work is graph convolutional neural networks. These have wide spread applicability in predicting molecular properties (useful to Google Health), building recommendation systems (useful in many obvious ways to Google), and modelling phenomena in social networks, to name a few off the top of my head. So while the scent identifying doesn’t seem directly relevant, nailing the underlying techniques is valuable.

Jabbles 7y ago

Google Cloud wants to be known as the best place for all kinds of machine learning. Google may not want to get into perfume manufacturing, but it wants Unilever (?) to run all their ML research on their cloud. This kind of research strengthens that part of their brand. (complete speculation, but seems plausible)

pharrington 7y ago

This is building a fundamental component for automated generalized molecule detectors.

dekhn 7y ago

Google invests fairly heavily into research and there is a fair amount of freedom among engineers and researchers to do projects with Google resources, even when there is no direct product application. For example, I ran an idle-cycle-harvesting service at Google called Exacycle that ran problems like protein folding, protein design, drug discovery, telescope discovery, and more. The only pushback I got was to run problems where the results could reasonably be considered "useful" (scientifically). One way to think about it is that many of the people with power at Google really like science and have the resources to support it. Once you've built things like TPUs, it would be a waste not to dedicate some about of their resources to problems that people wouldn't be able to address. Another way to think about it is these things have indirect effects- even if Google didn't want to make some sort of product with smell (like a phone with a builtin GC-MS?), publishing this work gets the attention of scientists, who will then read the paper, and consider Google Cloud as a place they'd like to do their work.

Pick-A-Hill2019 7y ago

From the second paragraph "Solving the odor prediction problem would aid in discovering new synthetic odorants,". Reading between the lines - a cheaper way to produce more realistic industrial aromatics cheaper.

Myrmornis 7y ago

If we're feeling positive about the world, since it's Friday: Google wants to help the world by reducing our reliance on farming animals for meat, and thought that research like this would help humanity's nascent artificial meat endeavours.