4 ms·

I assure you that the companies performing these screens expect a return on this investment. It is not for a journal paper.

godelski 2y ago
I used to believe this line. But then I worked for a big tech company where my manager constantly made those remarks ("the difference in industry and academia is that in industry it has to actually work"). I then improved the generalization performance (i.e. "actually work") by over 100% and they decided not to update the model they were selling. Then again, I had a small fast model and it was 90% as accurate as the new large transformer model. Though they also didn't take the lessons learned and apply them to the big model, which had similar issues but were just masked by the size. Plus, I mean, there are a lot of products that don't work. We all buy garbage and often can't buy not garbage. Though I guess you're technically correct that in either of these situations there can still be a return on investment, but maybe that shouldn't be good enough...
- shpongled 2y ago
  The post you are replying to is talking about high throughput assays for drug development. This is something actually run in a lab, not a model. As another person working at a biotech, I can assure you that screens are not just run as busy work.
  - rgmerk 2y ago
    No they’re not busywork, but not all such screens are directly in the drug discovery pipeline.
    - godelski 2y ago
      It also entirely misses the point of my comment which was that I don't believe this sentence to be true in an at least indirect sense. I conceded that it is technically valid in that lab experiments can also be used as advertisements and generate revenue even if such screens do not directly lead to novel or improved drug discoveries.
  - godelski 2y ago
    > The post you are replying to is talking about high throughput assays for drug development. While this is true, it is also true that the sentiment of this line is frequently used outside of the biotech (note that this entire website is primarily dominated by computer science posts). I think it is just worth mentioning that it is perfectly valid for discussions to not be pigeonholded and that you are perfectly allowed to talk about similarities in other fields (exact or inexact). It is also true that my reply is not invalidated by changing settings. If you pay close attention you'll notice the generality of the comment outside of the specific example. In fact, this is exactly what the OP did, considering the article is about a machine learning paper and the example they used to __illustrate__ their point was about their wife's work in biotech. But the sentiment/point/purpose of their comment would not have changed were their wife to work in physics/engineering/chemistry/underwater basket weaving/whatever. So if this is your issue, I think they are misdirected and I ask that you please take it up with the OP and ensure that they know no comments in this thread may be about anything but ML papers by DeepMind. Illustrative examples out of domain are not allowed. It is also true that this domain example was a product this company was selling. So I think you're being too quick to dismiss as not only did it run "in a lab" but the actual product runs in the real world. It has real customers who use the software. It's also true I never accused anyone of doing "just [running] busy work" and that such an interpretation is grossly inaccurate. My final sentence should make this abundantly clear and I would argue is far more important in a setting such as medicine where I've said conveyed that you can sell ineffective or subpar products while still generating a profit and suggested that this probably shouldn't be the metric we care about (it certainly isn't what the spirit of those metrics are about). But if you want to (implicitly) accuse me of derailing the conversation, I do not think you have the grounds to do so. But I will accuse you of doing so. If you disagree with my comment, you are more than welcome to reply in such a way. If you think my comment does not apply to dug discovery or think it only applies to ML[0], then you are welcome to state as much too and it is encouraged to state why. But the only derailing of the conversation has been the pigeonholing you have applied. If you think this is wrong, I still welcome a response to that as I am happy to learn how to communicate better but you did also catch me on a day where I'm not happy to be unreasonably and willfully misinterpreted. [0] I didn't tell you the application... a bit presumptuous are we?

godelski 2y ago

I used to believe this line. But then I worked for a big tech company where my manager constantly made those remarks ("the difference in industry and academia is that in industry it has to actually work"). I then improved the generalization performance (i.e. "actually work") by over 100% and they decided not to update the model they were selling. Then again, I had a small fast model and it was 90% as accurate as the new large transformer model. Though they also didn't take the lessons learned and apply them to the big model, which had similar issues but were just masked by the size. Plus, I mean, there are a lot of products that don't work. We all buy garbage and often can't buy not garbage. Though I guess you're technically correct that in either of these situations there can still be a return on investment, but maybe that shouldn't be good enough...

shpongled 2y ago
The post you are replying to is talking about high throughput assays for drug development. This is something actually run in a lab, not a model. As another person working at a biotech, I can assure you that screens are not just run as busy work.
- rgmerk 2y ago
  No they’re not busywork, but not all such screens are directly in the drug discovery pipeline.
  - godelski 2y ago
    It also entirely misses the point of my comment which was that I don't believe this sentence to be true in an at least indirect sense. I conceded that it is technically valid in that lab experiments can also be used as advertisements and generate revenue even if such screens do not directly lead to novel or improved drug discoveries.
- godelski 2y ago
  > The post you are replying to is talking about high throughput assays for drug development. While this is true, it is also true that the sentiment of this line is frequently used outside of the biotech (note that this entire website is primarily dominated by computer science posts). I think it is just worth mentioning that it is perfectly valid for discussions to not be pigeonholded and that you are perfectly allowed to talk about similarities in other fields (exact or inexact). It is also true that my reply is not invalidated by changing settings. If you pay close attention you'll notice the generality of the comment outside of the specific example. In fact, this is exactly what the OP did, considering the article is about a machine learning paper and the example they used to __illustrate__ their point was about their wife's work in biotech. But the sentiment/point/purpose of their comment would not have changed were their wife to work in physics/engineering/chemistry/underwater basket weaving/whatever. So if this is your issue, I think they are misdirected and I ask that you please take it up with the OP and ensure that they know no comments in this thread may be about anything but ML papers by DeepMind. Illustrative examples out of domain are not allowed. It is also true that this domain example was a product this company was selling. So I think you're being too quick to dismiss as not only did it run "in a lab" but the actual product runs in the real world. It has real customers who use the software. It's also true I never accused anyone of doing "just [running] busy work" and that such an interpretation is grossly inaccurate. My final sentence should make this abundantly clear and I would argue is far more important in a setting such as medicine where I've said conveyed that you can sell ineffective or subpar products while still generating a profit and suggested that this probably shouldn't be the metric we care about (it certainly isn't what the spirit of those metrics are about). But if you want to (implicitly) accuse me of derailing the conversation, I do not think you have the grounds to do so. But I will accuse you of doing so. If you disagree with my comment, you are more than welcome to reply in such a way. If you think my comment does not apply to dug discovery or think it only applies to ML[0], then you are welcome to state as much too and it is encouraged to state why. But the only derailing of the conversation has been the pigeonholing you have applied. If you think this is wrong, I still welcome a response to that as I am happy to learn how to communicate better but you did also catch me on a day where I'm not happy to be unreasonably and willfully misinterpreted. [0] I didn't tell you the application... a bit presumptuous are we?