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The results suggest that outsiders to a specific scientific field are reluctant to challenge a research star who is viewed as a leader within that field. I don

by Mz 10y ago

The results suggest that outsiders to a specific scientific field are reluctant to challenge a research star who is viewed as a leader within that field. I don't think this is how it works at all. I think people are unable to challenge stars in their field. When everyone is celebrating some star, good luck getting heard if you disagree with them. It is worse if, like so many people, this star will defend their territory by following the maxim "A good offense is the best defense." My observation of behavior in online forums is that a typical pattern of behavior is that everyone seeks to either align themselves with one of the "stars" of the forum or position themselves as being "against" anything that person says. It is very much about pecking order, not truth, and if you have two or three really popular people, then you get camps that revolve around each person. All conversation tends to default into a polarizing back and forth of "I am for STAR!" and "I am against STAR!" Since all conversation is framed as either for or against STAR, no conversation can occur that genuinely diverges from the framing given. Even if you genuinely try to diverge from this framing of for or against the idea set that this star individual represents, people will actively paint you into a corner as being in either the for or against camp. Good luck with saying "Yeah, no. That isn't what I am saying At All." This only stops when that person exits the picture. Dying is the most final and absolute means to exit the picture.

emcq 10y ago
This is so true. We can see it very recently too. As a specific example look at evolutionary optimization. It's existed for decades, has a bit of a non mainstream cult following, but now the leaders of the field are finding they can beat the fanciest deep reinforcement learning approaches with it. https://blog.openai.com/evolution-strategies/ https://blog.openai.com/evolution-strategies/
- letitgo12345 10y ago
  That paper, while interesting, is not really "evolutionary" optimization
- leereeves 10y ago
  How does that fit in this discussion? The stars of deep reinforcement learning haven't exited the picture. Have there been polarized discussions here between the two camps?
  - emcq 10y ago
    Up until the last sentence of the grandparents post, the point was "I think people are unable to challenge stars in their field." The fact that an alternative perspective that proves simple, effective, and popular in alternative communities is now popularized from stars in the field of deep learning rather than the alternative communities is exactly this. In fact, the resources available to the stars is much different than what these other communities may have access to such that they may never be able to demonstrate value themselves. It's not very often you have a 720 core machine to run these tests. Resource constrained science exists all over from chemistry, physics, and biotech to computer science. The rich get richer as they say. However it's also a great instance of solid science to test alternative approaches and I don't mean to take anything away from anyone, but simply to point to a case where that it is extremely difficult for people to challenge stars in the field.
    - leereeves 10y ago
      That OpenAI article is based on the paper: Evolution Strategies as a Scalable Alternative to Reinforcement Learning by Tim Salimans, Jonathan Ho, Xi Chen, Ilya Sutskever This seems like counter-evidence to the idea that people are unable to challenge the stars of the dominant paradigm.
deleted 10y ago
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by Mz 10y ago

emcq 10y ago

This is so true. We can see it very recently too. As a specific example look at evolutionary optimization. It's existed for decades, has a bit of a non mainstream cult following, but now the leaders of the field are finding they can beat the fanciest deep reinforcement learning approaches with it. https://blog.openai.com/evolution-strategies/ https://blog.openai.com/evolution-strategies/

letitgo12345 10y ago
That paper, while interesting, is not really "evolutionary" optimization
leereeves 10y ago
How does that fit in this discussion? The stars of deep reinforcement learning haven't exited the picture. Have there been polarized discussions here between the two camps?
- emcq 10y ago
  Up until the last sentence of the grandparents post, the point was "I think people are unable to challenge stars in their field." The fact that an alternative perspective that proves simple, effective, and popular in alternative communities is now popularized from stars in the field of deep learning rather than the alternative communities is exactly this. In fact, the resources available to the stars is much different than what these other communities may have access to such that they may never be able to demonstrate value themselves. It's not very often you have a 720 core machine to run these tests. Resource constrained science exists all over from chemistry, physics, and biotech to computer science. The rich get richer as they say. However it's also a great instance of solid science to test alternative approaches and I don't mean to take anything away from anyone, but simply to point to a case where that it is extremely difficult for people to challenge stars in the field.
  - leereeves 10y ago
    That OpenAI article is based on the paper: Evolution Strategies as a Scalable Alternative to Reinforcement Learning by Tim Salimans, Jonathan Ho, Xi Chen, Ilya Sutskever This seems like counter-evidence to the idea that people are unable to challenge the stars of the dominant paradigm.

deleted 10y ago

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