Beta
×

Welcome to the Slashdot Beta site -- learn more here. Use the link in the footer or click here to return to the Classic version of Slashdot.

Thank you!

Before you choose to head back to the Classic look of the site, we'd appreciate it if you share your thoughts on the Beta; your feedback is what drives our ongoing development.

Beta is different and we value you taking the time to try it out. Please take a look at the changes we've made in Beta and  learn more about it. Thanks for reading, and for making the site better!

AI Astronomer Aids Effort To Analyze Galaxies

timothy posted more than 4 years ago | from the kindly-disprove-loyalty-to-alien-invaders dept.

Software 40

kkleiner writes "Scientists are teaching an artificial intelligence how to classify galaxies imaged by telescopes like the Hubble. Manda Banerji at the University of Cambridge, along with researchers at University College London, Johns Hopkins, and elsewhere, has succeeded in getting the program to agree with human analysis at an impressive rate of more than 90%. Banerji used data from Galaxy Zoo, a massive online project that has used more than 250,000 volunteers to analyze more than 60 million galaxies. The new automated astronomer will help with even larger analytical projects on the horizon, taking care of trivial classifications and leaving the tough cases to humans."

Sorry! There are no comments related to the filter you selected.

Slight Bug. (-1, Troll)

jellomizer (103300) | more than 4 years ago | (#32515412)

It will not tell the Astronomers which of the billion galaxies it considerers questionable. Leaving the Astronomers to check each one, one at a time.

Source Please (1)

bazald (886779) | more than 4 years ago | (#32515484)

If it is making a "guess as to the most likely classification", it sounds like there is a measure of confidence. Perhaps the system is capable of presenting questionable cases to human experts.

Re:Source Please (1)

Locke2005 (849178) | more than 4 years ago | (#32515746)

I suspect that the same cases that make the software throw up its hands and say "I don't know" about also makes human "experts" throw up their own hands and say, "Gee, I don't know... what do you think?"

Re:Source Please (0, Offtopic)

Gilmoure (18428) | more than 4 years ago | (#32516122)

I see a turtle.

Not a troll - actually a very good point (3, Insightful)

Anonymous Coward | more than 4 years ago | (#32515542)

Let's say the system of scientific paradigms and their rise and fall is about finding outliers and surprising results that cannot easily be explained by current models.

If this is the case, then using a statistical system to classify observations has the danger that these "outliers" simply get classified in existing categories and whatever abnormality they represent thereby ignored.

An "AI researcher" must therefore have very explicit programming to set anything with even the slightest degree of abnormality aside for human evaluation. If it's set to classify anything and everything according to preset rules, it's actually mostly destructive to good science.

better than humans? (4, Interesting)

samwise098 (1463055) | more than 4 years ago | (#32515426)

I wonder how this program compares to a human doing the same job If given the same "training" I wonder how many humans would get a 90% agreement rate looking at the same data.

Re:better than humans? (0)

Anonymous Coward | more than 4 years ago | (#32515512)

I can't help feeling there's something wrong with your statement, but I can't quite put my finger on it...

Re:better than humans? (-1, Offtopic)

Anonymous Coward | more than 4 years ago | (#32515616)

(From completely different AC, promise!) ...totally deserves a +1 funny at least. :)

Re:better than humans? (0, Redundant)

Monkeedude1212 (1560403) | more than 4 years ago | (#32515674)

Well exactly. This isn't so much an "AI" as it is a script that has output depending on its input.

Essentially, any "errors" the computer makes would be an issue with setting up a debugger and seeing why it chose that selection. Then it falls into two categories: It spotted things humans missed when classifying or it has faulty programming that is creating false positives or missing data.

I'd hardly consider that "AI".

Re:better than humans? (2, Interesting)

Locke2005 (849178) | more than 4 years ago | (#32515764)

Sense the "training" consists of being shown hundreds of thousands of galaxies along with their classifications, I doubt that many humans would live long enough to be given the same "training"...

Name (4, Funny)

kellyb9 (954229) | more than 4 years ago | (#32515458)

I would think with a name like Al Astronmer your career choices would be limiting. I guess I was right.

Name (1)

MRe_nl (306212) | more than 4 years ago | (#32515572)

R. Daneel Olivaw

Re:Name (1)

AJ Mexico (732501) | more than 4 years ago | (#32524694)

I dunno, BHA (Butt Hole Astronomer) did okay.

Original paper (4, Informative)

JoshuaZ (1134087) | more than 4 years ago | (#32515536)

The paper discussing this work is http://arxiv.org/abs/0908.2033 [arxiv.org] . They appear to be using a pretty standard neural network approach (disclaimer: I don't have much background in neural nets at all. I'm just going off of how they were described in the last class I took that discussed them.) This is part of a very general pattern where programs have done a lot of work that we would think could only be done by people. Other examples include the computerized proof of the Robbins conjecturehttp://en.wikipedia.org/wiki/Robbins_conjecture [wikipedia.org] . TFA lists a few examples as well which are in more applied areas.

Ohh! A Galaxy Zoo! (1)

Izabael_DaJinn (1231856) | more than 4 years ago | (#32515552)

I wonder if it has any Tauntauns!

I have seen the future (3, Insightful)

Locke2005 (849178) | more than 4 years ago | (#32515660)

If this technologies works for classifying galaxies, perhaps next we could put it to work classifying porn on the web!

Re:I have seen the future (-1, Troll)

Anonymous Coward | more than 4 years ago | (#32515790)

The quick brown nigger jumped over the lazy dog.

Re:I have seen the future (1, Funny)

Anonymous Coward | more than 4 years ago | (#32516146)

For the love of God, delete this post! This comment is the reason Skynet starts down the logic path of removing humans!

- John Connor

Re:I have seen the future (1)

Adambomb (118938) | more than 4 years ago | (#32516572)

I propose that this is a task is best left suited to actual humans... ...and that I should be hired to assist.

Re:I have seen the future (1)

Locke2005 (849178) | more than 4 years ago | (#32516858)

They're so cute when they're young and naive! Your first task is classifying the classic goatse, tubgirl, and lemon party pics, as well as the classic "2 girls 1 cup" video. The eye bleach is on the counter. Good luck!

Re:I have seen the future (1)

Adambomb (118938) | more than 4 years ago | (#32516996)

Proposition: The proportion of porn on the internet requiring eye bleach is but a tiny fraction of porn on the internet. A few instances of mind-rending pain would probably be worth that being ones occupation for the entire rest of the time!

My Life is Now Pointless (1)

braindrainbahrain (874202) | more than 4 years ago | (#32515804)

So Galaxy Zoo doesn't need me anymore? That is the one activity where I was contributing to science to benefit all mankind.

Oh well, I guess I'll go back to trying to beat Mario 64 or something equally pointless....

Re:My Life is Now Pointless (2, Interesting)

$RANDOMLUSER (804576) | more than 4 years ago | (#32516126)

I'm a Galaxy Zoomate, too, but I sure wouldn't mind an AI that would weed out even 75% of the boring eliptical galaxies, and let us concentrate on the pretty spirals and irregulars.

pros and cons of this approach (5, Informative)

Anonymous Coward | more than 4 years ago | (#32515826)

PRO:

Using neural networks allows for graceful degradation when classifying galaxies by indicating to what degree it believes this galaxy is similar to other galaxies of this type (that it has been trained on). A threshold can be set so that if confidence falls below this threshold, the image is flagged for human intervention.

CONS:

Neural nets are largely black boxes. They use learned statistical relationships to classify images, but they're unable to provide an explanation as to why they made the decision that they did.

Re:pros and cons of this approach (1)

chichilalescu (1647065) | more than 4 years ago | (#32520796)

that is not a "CON". there is an explanation: statistically, that is the class that the image belongs to.
consider this: infants have a lot of inborn reflexes. and trust me, they don't understand why they do the things they do anymore than you would understand why your foot jumps when the doctor pokes your knee (I don't know the name of that reflex).
there is absolutely no difference between using a trained human brain and using a trained simulated neural net.

Re:pros and cons of this approach (1)

sourcerror (1718066) | more than 4 years ago | (#32522260)

Your analogy is bogus. We're talking about learning. Reflexes are prewired, not learned.
Decision trees and KBANN can provide explanation.

(I don't say that those explanation are always that useful. Giving useful explanations isn't an easy task even for humans, and it's ambigous as well. )

What's the point? (0, Redundant)

Grishnakh (216268) | more than 4 years ago | (#32515906)

Maybe I'm missing something, but what exactly is the point of going to all this effort to classify far-away galaxies? I can understand astronomers wanting to examine closer galaxies and see how they work and interact and all, but surely all the galaxies that are close enough for us to be able to see that much detail have already been known for some time, and are classified, and studied in far more detail than just classifying what kind of galaxy they are (spiral, barred spiral, elliptical, etc.). What good does it do to classify millions of galaxies that you can barely see?

Wouldn't it be more useful to expend this effort on observing objects that are closer to us, and which we can see in much better detail, such as various stars and nebulae within our own galaxy? Or in trying to find more evidence of exoplanets and determine if there's life on them?

After all, it might be possible for us to send ships to nearby stars (like Alpha Centauri) eventually, and examine exoplanets there first-hand. Such a voyage may take a few decades, but it's doable. But unless we come up with a way of creating wormholes or something else that allows us to teleport vast distances instantly, there's no way we'll be able to visit far-off galaxies, ever. They're simply too far away. Even in uber-optimistic Star Trek, with warp speed travel, humans still never left the Milky Way galaxy (except for one episode of TNG with the Traveler, and even that was a nearby galaxy), and stayed mostly within one sector. The whole underlying plot of Voyager was that they were on the other side of the Milky Way, and it'd take hundreds of years to get back at top warp speed.

Pictures showing galaxies that are billions of light-years away make nice posters, but it seems totally pointless to put too much effort into these things, when there's so much we don't know about the stuff inside our own galaxy.

Re:What's the point? (3, Insightful)

Daniel Dvorkin (106857) | more than 4 years ago | (#32516256)

There are a couple of answers to your question. The first is the answer to the more general question, "Why study the universe at all?" and the answer is "Because it's there." We want to understand the processes by which the universe we see around us was formed, what it's like now (to the degree that "now" has any meaning on cosmological scales) and where it's going. It is an awe-inspiring place, and becomes more so the more we learn about it.

The second, with respect to the study of the Milky Way, is that we learn a lot about our galaxy by studying other galaxies. We don't have a good vantage point for studying the Milky Way, for obvious reasons. Hell, it wasn't until quite recently that we even knew what shape it was (barred spiral vs. plain spiral.) With the enormous number of galaxies out there, many of them similar to our own, at a variety of viewing angles from Earth, we can get a much better idea of what's going on in our own neighborhood than we could by restricting our observations to the Milky Way alone.

Re:What's the point? (0)

Grishnakh (216268) | more than 4 years ago | (#32516408)

The first is the answer to the more general question, "Why study the universe at all?" and the answer is "Because it's there."

I'm not disputing that, only pointing out that observation resources are limited and should be put to best use.

With the enormous number of galaxies out there, many of them similar to our own, at a variety of viewing angles from Earth, we can get a much better idea of what's going on in our own neighborhood than we could by restricting our observations to the Milky Way alone.

I understand this too, but (remember, IANAA) don't we learn more by examining galaxies that are relatively close to us (such as the one that's actually colliding with the MW)? The ones that are close to us have been known about for ages, and already observed and classified, and can be examined in much more detail than the far-away galaxies that seem to be the object of this study, which can barely be seen even with our best telescopes.

Re:What's the point? (1)

flowwolf (1824892) | more than 4 years ago | (#32520014)

How do we know what the best use for observation resources is? why are ones that are closer to us any better than the ones far away? How do you determine where the good discoveries will be ? This seems like a politician's approach to science.

Re:What's the point? (2, Insightful)

Grishnakh (216268) | more than 4 years ago | (#32520182)

That's what I was asking, because on the surface it seemed to me to make more sense studying nearby galaxies only. However, some other helpful responders pointed out that far-away galaxies allow us to see farther back in time (essentially, what we see of the far-away galaxies is how they appeared billions of years now, not how they appear now), and see how galaxies form and collide, and this might lead to insight into how our galaxy came into being.

The difference between my questioning and the politicians is that the politicians, being lawyers, aren't honestly looking for answers to their questions. They already have their minds made up and are trying to twist things around to benefit themselves. Normal questions from laymen like myself, when given appropriate answers, yield more understanding for all laymen.

Re:What's the point? (4, Insightful)

$RANDOMLUSER (804576) | more than 4 years ago | (#32516346)

Because the farther away they are, the farther back in time we're looking. By collecting images of galaxies at different stages of evolution (and different types of collisions) cosmologists are able to form a much better picture of how galaxies (and the universe in general) form and evolve.

Re:What's the point? (1)

Grishnakh (216268) | more than 4 years ago | (#32516432)

Ah, ok. This makes sense. Thanks!

Re:What's the point? (1)

chichilalescu (1647065) | more than 4 years ago | (#32520876)

further on, once we have a good idea about what happened in the universe, we can start checking that against the various sets of "laws of the universe" that we can generate, and decide which are valid (i.e. "is string theory ok, or do we need something else?").
Afterwards, we can try to use the "correct" model of the universe to generate cool stuff (like quantum physics was used to properly describe semiconductors, and we got miniaturized electronics).

I wasn't trying to exagerate. Usually in science, each geek gets excited about a different thing; some years later, a less geeky person tries to do something practical, but is geeky enough to understand what the other geeks were doing, and succeeds in putting together all the information to come up with something useful. Generally, we have to try to finance all the excited geeks, because we can't properly decide which of them will come up with something useful.

Re:What's the point? (1, Insightful)

dissy (172727) | more than 4 years ago | (#32518726)

Pictures showing galaxies that are billions of light-years away make nice posters, but it seems totally pointless to put too much effort into these things, when there's so much we don't know about the stuff inside our own galaxy.

But to learn about the stuff inside our galaxy, and how it came to be, we need to see how it looked in the past.
Since you haven't gotten around to making that time machine yet, we can't do it that way ;}

Instead we look at light from galaxies that have been traveling in space for an amount of time equal to how far back in time we want to see, and we discover such things as galaxy formation.

This is ONLY possible to do by looking at distant and thus older galaxies. And it does teach us more about our own.

finally? (2, Interesting)

Black Parrot (19622) | more than 4 years ago | (#32515952)

I'm surprised they're just now getting around to this. It's a straightforward pattern classification problem, and there is a huge set of training examples to be used for training a neural network or other Learning Classifier System technologies.

so close to a completely alliterative subject line (1)

sweatyboatman (457800) | more than 4 years ago | (#32516018)

Artificial Agent Aids Astral Analysis

Great progress but less scope for amateurs (1)

syousef (465911) | more than 4 years ago | (#32516722)

This makes me very happy on one level and very sad on another.

At the amateur end, the advances in technology have meant that what use to be done by a professional with mind blowingly expensive equipment or what was not at all possible because it hadn't been invented can now be done by a dedicated amateur with a reasonable but largish hobby budget. For the amount of money some spend on recreational vehicles and holiday homes an amateur can now do spectroscopy, deep imaging, even adaptive optics. It's not open to everyone - you need to have good circumstances - a job that both pays well and puts somewhere within driving distance from less light polluted skies. But it can be done..

On the other hand the technology has meant at the professional end what was cutting edge a few decades ago is now obsolete and not an area of interest. What use to be done on an individual basis is being taken over by surveys etc.

What this means is that there are only a handful of ways in which an amateur can contribute real science. Mostly this revolves around tasks that are either considered not important enough to dedicate professional resources to, or areas that aren't easily automated or taken over by sky surveys. Stuff like variable star observing and galaxy zoo. Now those areas are dwindling too as the automation gets better. The amateurs have done a wonderful job especially with variable star observing - with records extending back hundreds of years - this is data that professionals did not have the time to gather themselves nor the technology to gather in bulk....until now. With projects like Pan-STARRS [wikipedia.org] coming online, how long will this be a useful way to contribute? The records will improve but the opportunity to contribute will dwindle.

Also there's the nagging feeling that automation, while good for most things, can't completely replace human curiosity. For the Galaxy Zoo project, I wonder if this method would detect anomalous objects like Hanny's Voorwerp [wikipedia.org] . That was only discovered because a schoolteacher bothered to ask "what the heck is that smudge" instead of simply dismissing it as a photographic error. This led to Galaxy Zoo 2 including a button to report such objects.

So overall I think we'll make great progress - much greater than human only efforts - but I do wonder what discoveries we'll miss.

Ok.. Riddle me this (0, Troll)

gringofrijolero (1489395) | more than 4 years ago | (#32519322)

How many galaxies are there in the Milky Way?

1995: SKICAT System classified galaxies (1)

cyberfringe (641163) | more than 4 years ago | (#32524588)

Sorry to burst the bubble, but automatic classification of galaxies from sky survey data using machine learning techniques was accomplished in the early '90s by the SKICAT system developed at JPL and Caltech. http://adsabs.harvard.edu//abs/1995PASP..107.1243W [harvard.edu] is a good overview of the system and its accomplishments as of 1995.
Check for New Comments
Slashdot Login

Need an Account?

Forgot your password?