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Having a cursory knowledge of science is not enough, you are competing against people who read hundreds of papers on extremely specialized topics and spend 1000

Having a cursory knowledge of science is not enough, you are competing against people who read hundreds of papers on extremely specialized topics and spend 1000s of hours every year thinking and researching these topics. The first part of research is reading the literature, if you are new to a field you usually realize all your ideas have been explored thoroughly 10s or 100s of years prior. Research is not a spectator sport, it's highly specialized and competitive. That's not to say you can't contribute, if you want to participate the prerequisite is being willing to put a significant amount of time and effort into learning the skills of research, and learning about the specific domain you are interested in. You'll need to go from the basic theory to more specialized topics, read review papers, understand where the state of the art is, etc... As you read more and more you'll get insights on what's been done and what hasn't, you might find a niche that you can contribute to. In some fields the obstacle is gathering data and doing field work, you could make a contribution there as well. You could also contribute to open-source scientific software, I'd imagine it's be less competitive than doing research, you'd still need domain knowledge though.

dontbenebby 4y ago
>Having a cursory knowledge of science is not enough, you are competing against people who read hundreds of papers I've read hundreds of papers on security and privacy. People make flippant comments like "You can't work on my team unless you have a PhD" followed shortly out of band by comments like "I'm the head of the Montreal office". I currently find it difficult to study those topics anymore, since there seems to be some fundemental disconnect between my actions and results. (And then, in parallel, thanks to deleting Facebook, I know a lot more about celebrity gossip and geopolitcs than I used to, so sometimes the old self soothing method of watching a movie isn't as fun, depending on who was involved.) If you have suggestions taking into account the above, feel free to reply here or 1:1 to the email listed on my profile.
cgriswald 4y ago
The domain knowledge needed for this particular paper is literally just math, first semester undergrad physics, a chapter or two of an introductory astrophysics text, and some image processing—which, if you understand the underlying math, is easy to pick up. The novelty here is the algorithm, which I imagine, given the prerequisite knowledge, most people here could conceivably develop. Astronomy is currently a highly accessible field. Amateurs are still making meaningful research contributions. There is also a lot of grunt work available using other people's methods. Edit to add: You don't even need to gather your own data. There are many, many datasets lying around waiting to be processed by new techniques.
- ad404b8a372f2b9 4y ago
  That's unrealistic, the final result being understandable with an undergrad level of math does not mean it takes an undergrad level of math to reach that result. No one here could have divinated that algorithm without doing the legwork. The basic theory alone, which you list, represents a significant time investment and that's only to reproduce the work, knowing exactly which concepts you need to learn. A lot of the papers I read are implemented by adding a single line of code to a model that someone with an undergrad knowledge of probabilities could have written. Except they couldn't because to get that line of code you need a deep knowledge of the prior work, good fundamental knowledge of the discipline to even come up with such an idea, knowledge of the datasets that are in use, the problems that are interesting to work on and those that aren't, etc ...
  - cgriswald 4y ago
    No, this guy just wants to get involved in stuff like this and you're telling him its impossible; in a field where amateurs are making meaningful contributions; in response to a paper that is more data science than astrophysics. > No one here could have divinated that algorithm without doing the legwork. No one here could understand how to combine rudimentary image processing in such a way as to track a moving object over time? It's impressive, certainly, but there's more data processing here than astrophysics. Most people with a BA in science or math would have enough requisite knowledge to pick up what they would need for this paper over the course of a weekend. The part they couldn't do that with would be the image processing and data science. If they already have that? Yes, this is absolutely achievable. Just copying this work on a different data set? Also very achievable. The knowledge of which datasets are in use? In this field those are both mostly public and easy to find. Yes, those who don't have some of this knowledge will have to put in more time than others, but the implication you make about the sheer amount of time needed and what would actually be required just to get involved just doesn't apply here. There was a time half a decade ago where someone like the original poster could literally get a job doing this stuff. That may still even be the case.
    - ad404b8a372f2b9 4y ago

dontbenebby 4y ago

>Having a cursory knowledge of science is not enough, you are competing against people who read hundreds of papers I've read hundreds of papers on security and privacy. People make flippant comments like "You can't work on my team unless you have a PhD" followed shortly out of band by comments like "I'm the head of the Montreal office". I currently find it difficult to study those topics anymore, since there seems to be some fundemental disconnect between my actions and results. (And then, in parallel, thanks to deleting Facebook, I know a lot more about celebrity gossip and geopolitcs than I used to, so sometimes the old self soothing method of watching a movie isn't as fun, depending on who was involved.) If you have suggestions taking into account the above, feel free to reply here or 1:1 to the email listed on my profile.

cgriswald 4y ago

The domain knowledge needed for this particular paper is literally just math, first semester undergrad physics, a chapter or two of an introductory astrophysics text, and some image processing—which, if you understand the underlying math, is easy to pick up. The novelty here is the algorithm, which I imagine, given the prerequisite knowledge, most people here could conceivably develop. Astronomy is currently a highly accessible field. Amateurs are still making meaningful research contributions. There is also a lot of grunt work available using other people's methods. Edit to add: You don't even need to gather your own data. There are many, many datasets lying around waiting to be processed by new techniques.

ad404b8a372f2b9 4y ago
That's unrealistic, the final result being understandable with an undergrad level of math does not mean it takes an undergrad level of math to reach that result. No one here could have divinated that algorithm without doing the legwork. The basic theory alone, which you list, represents a significant time investment and that's only to reproduce the work, knowing exactly which concepts you need to learn. A lot of the papers I read are implemented by adding a single line of code to a model that someone with an undergrad knowledge of probabilities could have written. Except they couldn't because to get that line of code you need a deep knowledge of the prior work, good fundamental knowledge of the discipline to even come up with such an idea, knowledge of the datasets that are in use, the problems that are interesting to work on and those that aren't, etc ...
- cgriswald 4y ago
  No, this guy just wants to get involved in stuff like this and you're telling him its impossible; in a field where amateurs are making meaningful contributions; in response to a paper that is more data science than astrophysics. > No one here could have divinated that algorithm without doing the legwork. No one here could understand how to combine rudimentary image processing in such a way as to track a moving object over time? It's impressive, certainly, but there's more data processing here than astrophysics. Most people with a BA in science or math would have enough requisite knowledge to pick up what they would need for this paper over the course of a weekend. The part they couldn't do that with would be the image processing and data science. If they already have that? Yes, this is absolutely achievable. Just copying this work on a different data set? Also very achievable. The knowledge of which datasets are in use? In this field those are both mostly public and easy to find. Yes, those who don't have some of this knowledge will have to put in more time than others, but the implication you make about the sheer amount of time needed and what would actually be required just to get involved just doesn't apply here. There was a time half a decade ago where someone like the original poster could literally get a job doing this stuff. That may still even be the case.
  - ad404b8a372f2b9 4y ago