Why Jupiter’s Great Red Spot Refuses to Die(nautil.us)
nautil.us
Why Jupiter’s Great Red Spot Refuses to Die
http://nautil.us/blog/why-jupiters-great-red-spot-refuses-to-die
22 comments
Too bad this data can't be opened for hobbyists to review, in the same manner that hobbyist astronomers assist in discovering new stars.
I had a 50-odd CD set of voyager data dumps from NASA once. Not sure what happened to them but the data was out there and obtainable.
Edit: turns out you can download at least some of them from archive.org! https://archive.org/details/VoyagerstotheOuterPlanetsVol5
Edit: turns out you can download at least some of them from archive.org! https://archive.org/details/VoyagerstotheOuterPlanetsVol5
for what it's worth, they were doing a much better job of getting data from their more recent missions (maybe 2000 on?) up on websites.
the data from these research instruments is not easily analyzed using public information, though. overviews of how the instruments are _supposed_ to work are published in a book on the entire mission (for instance, for SDO: https://link.springer.com/book/10.1007/978-1-4614-3673-7 ) but as far as i know the weirdness instruments develop over their life isn't written down anywhere public.
and the data processing code for these things is sufficiently complicated that even with all of the documentation and access to the PIs and hardware engineers, it takes at least a few engineer*years to get working.
the data from these research instruments is not easily analyzed using public information, though. overviews of how the instruments are _supposed_ to work are published in a book on the entire mission (for instance, for SDO: https://link.springer.com/book/10.1007/978-1-4614-3673-7 ) but as far as i know the weirdness instruments develop over their life isn't written down anywhere public.
and the data processing code for these things is sufficiently complicated that even with all of the documentation and access to the PIs and hardware engineers, it takes at least a few engineer*years to get working.
I sure hope someone has a plan to at least preserve all this data, if not to look at it. Does anyone know?
Can AI help solve this problem?
Not if you can't even tell the AI what you're looking for. We're a long way from "Computer, is there anything interesting about this data?"
Unsupervised learning is a thing. It could tell us "these data points are similar", we just still need a human to try and quantify why it thinks they are similar.
What if they open source the data sets to Google or Microsoft to figure it out?
Figure what out, exactly?
AI isn't just some magic that "figures out" anything and everything.
AI isn't just some magic that "figures out" anything and everything.
Machine learning does allow you to find patterns in data. Some of these models are getting very good with image recognition.
It seems you have a lot of faith in AI, but don't seem to really grasp what AI is/does/can do.
In your link, you neglected the part where NASA first had to learn what rocks made good samples before they could "teach" their AI to look for similarly interesting samples.
In this case, you have a lot of data strewn about many different mediums (some now obsolete). Yes there's images, but what would the AI look for? In the other data collected, what would it analyze... what would be the goal for it to achieve? This is why we still have human scientists... and yes, AI can help, but it cannot replace.
As another HN'er said, we're a long way away from "AI, discover new science!".
In your link, you neglected the part where NASA first had to learn what rocks made good samples before they could "teach" their AI to look for similarly interesting samples.
In this case, you have a lot of data strewn about many different mediums (some now obsolete). Yes there's images, but what would the AI look for? In the other data collected, what would it analyze... what would be the goal for it to achieve? This is why we still have human scientists... and yes, AI can help, but it cannot replace.
As another HN'er said, we're a long way away from "AI, discover new science!".
I am a Data Scientist with Master's in Neural Networks so I do understand the challenges in preparing data for modeling. I am merely suggesting the option of exploring the problem of finding patterns in data through ML techniques. This does not take away the work involved in preparing clean data sets for training. Here are some Astronomers who are doing this kind of work. https://www.wired.com/2017/03/astronomers-deploy-ai-unravel-... I agree I don't understand the nature of data NASA has but it does not hurt getting some help from companies that are searching for problems to solve.
> I agree I don't understand the nature of data NASA
It's not the nature of the data that poses an issue... it's the lack of direction. AI/ML/NN (whatever buzz word of choice) simply cannot do the things you seem to believe it capable of.
> it does not hurt getting some help from companies that are searching for problems to solve.
What makes you think Google or Microsoft have any interest in working on NASA's research? These are very, very different domains.
Even if they were interested, what problems would they be solving exactly? This is the lack of direction that is the core problem with you assertion AI/ML/NN would be of any help here on it's own.
It's not the nature of the data that poses an issue... it's the lack of direction. AI/ML/NN (whatever buzz word of choice) simply cannot do the things you seem to believe it capable of.
> it does not hurt getting some help from companies that are searching for problems to solve.
What makes you think Google or Microsoft have any interest in working on NASA's research? These are very, very different domains.
Even if they were interested, what problems would they be solving exactly? This is the lack of direction that is the core problem with you assertion AI/ML/NN would be of any help here on it's own.
To add to the above, it's the difference between telling a model:
"Model, show me spectral signatures which are similar."
And "Model, is there anything interesting about the spectral signatures collected?"
In the former, you are potentially able to (or your NN layers can) identify representative features for your intended result.
In the latter, you're asking machine learning to synthesize the sum of human scientific knowledge, then extract interesting facts from the data using it. E.g. "Hmm, the vortex patterns on this Jupiter storm are incongruous with our fluid dynamics models" or "The reflectivity of the surface seems to indicate a different composition than we expected."
AI isn't currently capable of formulating questions, asking them, answering them, and ranking the results on significance.
And in lieu of that, the only use is "Help a scientist answer a question they posed." Which seems to be the initial problem that started this thread! Not enough scientists can get grants to pose all the questions that should be asked of old data.
"Model, show me spectral signatures which are similar."
And "Model, is there anything interesting about the spectral signatures collected?"
In the former, you are potentially able to (or your NN layers can) identify representative features for your intended result.
In the latter, you're asking machine learning to synthesize the sum of human scientific knowledge, then extract interesting facts from the data using it. E.g. "Hmm, the vortex patterns on this Jupiter storm are incongruous with our fluid dynamics models" or "The reflectivity of the surface seems to indicate a different composition than we expected."
AI isn't currently capable of formulating questions, asking them, answering them, and ranking the results on significance.
And in lieu of that, the only use is "Help a scientist answer a question they posed." Which seems to be the initial problem that started this thread! Not enough scientists can get grants to pose all the questions that should be asked of old data.
It explicitly says "trained".
I'm glad it is still there. It's such an interesting feature.
Here's one thing that has bugged me for a while. Why is it said that the great red spot is around 500 years old? How do we know that it hasn't been around for much longer?
Do we have before/after evidence that at one point it didn't exist, and then around 500 years ago it existed?
Do we have before/after evidence that at one point it didn't exist, and then around 500 years ago it existed?
In fact we don't even know that it's been there for 500 years. It's only been continuously observed for 187 years.
While there were earlier observations of large spots on Jupiter, it's not 100% certain they were actually the same storm.
https://en.wikipedia.org/wiki/Great_Red_Spot
To extend, a series of disjoint astronomical observations of the Earth would likely show a hurricane/cyclone/typhoon somewhere, but it wouldn't necessarily follow that they were all the same one.
While there were earlier observations of large spots on Jupiter, it's not 100% certain they were actually the same storm.
https://en.wikipedia.org/wiki/Great_Red_Spot
To extend, a series of disjoint astronomical observations of the Earth would likely show a hurricane/cyclone/typhoon somewhere, but it wouldn't necessarily follow that they were all the same one.
I've always heard the "at least 500 years old" sentiment, because Galileo describes it in his observations.
Where is that said?
the PIs i dealt with on space missions were usually on to the next piece of hardware they were going to fling into space before they had the data from the last one.
and i think the lab i was at had some voyager (or pioneer?) data laying around that one of the emeritus scientists was talking about getting transferred off of tape so he could finally look at it.