Just yesterday, the Australian govt. passed two contentious laws - one that basically undoes hundreds of years of hard-won freedoms at a stroke in the name of "anti-terrorism" - you're not even allowed to makes jokes at the govt's expense now - in fact this posting breaks this new law. Free speech has gone.
I think that the people who annoy me most, when discussing such laws, are the ones who justify it, saying, "Well, that's only if someone abuses the law."
No, really? I guess we should legalize shooting into crowds, since certainly there is someone in the crowd who has broken a law.
Not a problem. I'm helping with an AI course here next semester that is intended to be an overview, but I haven't had time (finals) to talk to the professor regarding what the text is. If you go to my website (I'm updating the URL after I post this), I'll probably have a link to some bits out of it (when I update), which should include the textbook.
High school science classrooms are not a forum of scientific debate. What bothers me most about this entire discussion is the assertion that, for some reason, a board of education decides what is science... that introducing it in classrooms is somehow equivalent to having it published in Nature... and that, for some reason, this is a valid way to discuss what is and isn't science.
It just isn't. Classrooms are for teaching science. Science has its own forums for such debates.
Now, when you put it in that light, the question becomes "do we want material that is not accepted by the scientific community taught in classrooms.
For those of you digging at religion, remember that a good portion of the religious community, including the Catholic Church, do not accept ID.
I actually (and I feel guilty for this) HAVE done this in situations where I think that the person will be able to hit the brakes in time, but I'd rather live. Most of what is over your head in a Z-28 with t-tops is glass, and probably wouldn't fare well in an accident.
I drive a suped up Z-28. Back home in Va, I'll get kids in civics who want to think that they're fast who will tailgate and try to race. When one of those jerks comes to close (some of those putzes get pretty close to hitting you), I blast forward a bit to keep from getting my bumper tagged by some 16 year old who saw The Fast and the Furious too many times.
Should we honestly be concentrating on automotive fuels? Doesn't most of the air pollution and issue from fossil fuel consumption really come from energy production and industrial uses?
Machine learning is being used in the diagnosis of hospital patients.
Data mining is being done with machine learning techniques as well.
Space rovers use robotic motion planning algorithms, and soon will use algorithms to determine objectives (these aren't expert system type algorithms).
The cross-action toothbrush was developed using a neural network.
These are what I mean be entering our lives.
Expert systems had their hayday when big investment banks were using them, but interest in them has kind of burned out. There aren't any conferences on them or the like. Neural nets made a resurgence, as did decision trees in the past few years, so, who knows? I don't really think that expert systems will make that kind of comeback any time soon though.
No, you won't walk up to a robot and have a human-like conversation with it.
Yes, progress has been made.
Also, as I said to another poster, solvers and provers and constraint programs are nothing akin to human intelligence, nor do they try to be. That said, they are quite useful.
Check out Russel and Norvig. It's a very up-to-date text that gives an overview of the field. We use it for a 400 level class here, for undergrads.
I'm not sure what text is being used for the new AI classes here next semester, but I've heard murmurings of 2 (well, more than murmurs, but I've been so busy finishing up that I haven't really had time to look into it thoroughly).
Mitchell's book on machine learning is also a nice overview, but the material is a little dense (too detailed) if you're not specifically interested in machine learning. If you are interested, however, it's easy to follow and gives just the right amount of information. It's perhaps not perfect, but I don't really know of a better one in terms of giving you intuitions as to how things work.
CP is actually a vibrant, active area of artificial intelligence research with a large, strong community. If you go through the AAAI conference proceedings (available at http://www.aaai.org/), you'll see that, indeed, it had a number of papers this years. Additionally, they have their own conferences and researchers with strong interests in the area, including my research advisors and several of my colleagues.
Machine learning, also, has come a long way. Popular methods at the moment are support vector machines, and bayesian (graphical) models. You'll also see meta-learning taking hold, in the form of bagging, boosting, and ensemble techniques.
Building on this, you'll see systems that do a bit of both. Check out MaxSAT as a problem. You can easily see where researchers are driving toward systems that place probabilities in the weights of a MaxSAT solver, and then solve based on this. I attended a talk yesterday on this by Dan Roth. Very cool stuff.
Uhmm, that's just patently incorrect. You're thinking of expert systems, which represent a distinct sub-category of artificial intelligence.
However, if I go through this board correcting everyone, I'll never finish my final projects for the semester, so, I'll do it here.
Modern AI consists of a number of subdisciplines, each of which focuses on different things. I haven't RTFA, because I'll believe it when I see a paper on what they're doing.
To be brief, however, there are Logical and Constraint programming, which focuses on solving problems through sets of contraints. Knowledge Representation, which focuses on how we represent the world to algorithms that work on that knowledge Natural Language processing, which deals with working with spoken language. It's considered that work in this field represents some of the hardest challenges in AI. Machine Learning, which has been described as statistics on steroids by one of it's popular researchers when addressing his class Human-Competitive/Human-Like AI, which generally works in bringing together these systems into a human-like intelligence Multi-Agent systems focuses on behaviors of more than one agent And others (I hope none of my collegues are offended that I didn't stick theirs in the list, but some of the descriptions get a bit intense, and, again, I need to get back to work)
Then you have all sorts of tasks: Autonomous navigation Word sense disambiguation Game playing Temporal and spatial reasoning Planning Scheduling Tabletop space problems (which most closely resemble your "true" AI, and do not merely mimic the actions of the teacher)
and man others, again, I hope I've offended no-one, these are the ones in my head due to PhD apps being around the corner.
The president of the AAAI this year, called for what are called "AI Decathalons," whereby researchers would construct systems that do multiple tasks. For example, a system might take a written or multiple choice exam, which requires forms of reasoning, it requires naturual language to read the questions, it requires knowledge representation to represent the questions and data.
At the same conference, Marvin Minsky had remarks more of the flavor of "AI needs to change directions (dramatically)," but he still wouldn't constrain the accomplishments of modern AI to expert systems. His book "The Society of Mind," is probably not a bad place to start if you want to learn about modern AI. It's very accessible to people who have only a passing interest in the field, while having enough solid content, ideas, and commentary (from Minsky of all people) to keep a fairly advanced researcher interested. Also, if it comes up in conversation, it's one of those "it's good to have read" books, even if you disagree with Minksky's ideas (one such controversial idea, consciousness does not exist).
Ahh, but see, that's where we don't agree. Even if Microsoft is evil, you have to allow the possibility for them being good.
They can't do the wrong thing if there is no right thing for them to do. Think of it game-theoretically, in terms of Nash equilibria.
THE MS IS EVIL PROBLEM
We assume that Microsoft only does the wrong thing when there is a benefit to doing so of, eh, +10.
We assume that being well thought of, however, for some reason, is a good thing... Eh, also +10.
The converse in either case is -10.
The column on the left is what the public will think of MS after they commit their actions.
Since you've preconditioned that MS is evil, we'll assume that MS starts out evil.
(Curse slashdot for having no way of doing tables in your posts).
I can't get the table to look right, but if you work out the Nash, MS has no motivation to do anything but evil, since it's the safest strategy in this scenario.
TABLE WAS HERE
We can see clearly, that if MS can make the public think that they are good, while doing evil things, that they stand to gain the most benefit. Also, if they're stuck with you thinking that they are evil, then their strategy does not change. In fact, there is no reason for them to do the right thing, since they will never benefit from having done so.
If I'm writing an application that lists x items from a data structure, then I'm putting that into the page through codebehind. I'll also stick my buttons onto the page and whatnot. I feel that codebehind is superior for this, over mixtures of JSP and servlets.
Get it?
I actually understand how to construct an app fairly well.
As far as libraries of well known primitives. If you had read my post, you'd realize that I was saying that the difference is negligible after working for a few weeks in either language.
In fact, my entire premise was that the difference is fairly negligible, not that C# was all that great.
Also, the JCP doesn't constitute a standard of any sort.
I like codebehind. I don't claim to be a crack web developer.
I actually know a good bit about java:-D
I'm not a refugee from ASP or PHP. I developed mostly unix platform software, including some radar and such, until my company decided to go web shop. Not wanting to be stuck for the rest of my life as some web developer, I bailed and returned to grad school to get a PhD.
Now, all of that aside, I'd rather never identify myself as a "Java" developer, or a "C++" developer, because I feel that that ties me to some lame vocational role. If anything, I'd rather be identified as a programmer, knowing a bit about a number of languages, and a lot about algorithms and such.
Interestingly, that's what I was. I can program in a good number of languages, and have a solid backing in theory and such.
Anyway, all of that aside, calling me stupid is about the lamest thing that you could possibly have done.
Slashdot Mirror
You're asking Slashdot for a way to acquire an UNBIASED opinion on GNOME vs KDE?
Have you ever asked us about vi vs emacs?
I'm sorry, I actually like Zonk... but only as a Slashdot editor.
He just gets picked on a lot, and this was a pretty heavy story, so I was like "whoa."
Zonk submitted a story worth reading.
Guess you snobs are all eating your words now, eh?
Just yesterday, the Australian govt. passed two contentious laws - one that basically undoes hundreds of years of hard-won freedoms at a stroke in the name of "anti-terrorism" - you're not even allowed to makes jokes at the govt's expense now - in fact this posting breaks this new law. Free speech has gone.
I think that the people who annoy me most, when discussing such laws, are the ones who justify it, saying, "Well, that's only if someone abuses the law."
No, really? I guess we should legalize shooting into crowds, since certainly there is someone in the crowd who has broken a law.
West Virginia is cold and has a small population too.
I wonder if these research teams need a CS grad student. I think that I could do an excellent job helping them to evaluate the effects of pornography.
What does it mean?
I Googled it and got nothing.
Not a problem. I'm helping with an AI course here next semester that is intended to be an overview, but I haven't had time (finals) to talk to the professor regarding what the text is. If you go to my website (I'm updating the URL after I post this), I'll probably have a link to some bits out of it (when I update), which should include the textbook.
How does that disagree with what I stated?
High school science classrooms are not a forum of scientific debate. What bothers me most about this entire discussion is the assertion that, for some reason, a board of education decides what is science... that introducing it in classrooms is somehow equivalent to having it published in Nature... and that, for some reason, this is a valid way to discuss what is and isn't science.
It just isn't. Classrooms are for teaching science. Science has its own forums for such debates.
Now, when you put it in that light, the question becomes "do we want material that is not accepted by the scientific community taught in classrooms.
For those of you digging at religion, remember that a good portion of the religious community, including the Catholic Church, do not accept ID.
I actually (and I feel guilty for this) HAVE done this in situations where I think that the person will be able to hit the brakes in time, but I'd rather live. Most of what is over your head in a Z-28 with t-tops is glass, and probably wouldn't fare well in an accident.
Bah.
I drive a suped up Z-28. Back home in Va, I'll get kids in civics who want to think that they're fast who will tailgate and try to race. When one of those jerks comes to close (some of those putzes get pretty close to hitting you), I blast forward a bit to keep from getting my bumper tagged by some 16 year old who saw The Fast and the Furious too many times.
Also, I'd rather the car behave as I expect.
Should we honestly be concentrating on automotive fuels? Doesn't most of the air pollution and issue from fossil fuel consumption really come from energy production and industrial uses?
Machine learning is being used in the diagnosis of hospital patients.
Data mining is being done with machine learning techniques as well.
Space rovers use robotic motion planning algorithms, and soon will use algorithms to determine objectives (these aren't expert system type algorithms).
The cross-action toothbrush was developed using a neural network.
These are what I mean be entering our lives.
Expert systems had their hayday when big investment banks were using them, but interest in them has kind of burned out. There aren't any conferences on them or the like. Neural nets made a resurgence, as did decision trees in the past few years, so, who knows? I don't really think that expert systems will make that kind of comeback any time soon though.
I have to be honest in my analysis though. I h
Also, to clarify, there was a post between yours and mine, which was the one that made the patently false statement.
Yours has subtle shades of grey to it.
There's really far more to it than that.
No, you won't walk up to a robot and have a human-like conversation with it.
Yes, progress has been made.
Also, as I said to another poster, solvers and provers and constraint programs are nothing akin to human intelligence, nor do they try to be. That said, they are quite useful.
AI is entering our daily lives. Just watch.
Check out Russel and Norvig. It's a very up-to-date text that gives an overview of the field. We use it for a 400 level class here, for undergrads.
I'm not sure what text is being used for the new AI classes here next semester, but I've heard murmurings of 2 (well, more than murmurs, but I've been so busy finishing up that I haven't really had time to look into it thoroughly).
Mitchell's book on machine learning is also a nice overview, but the material is a little dense (too detailed) if you're not specifically interested in machine learning. If you are interested, however, it's easy to follow and gives just the right amount of information. It's perhaps not perfect, but I don't really know of a better one in terms of giving you intuitions as to how things work.
Some have said this.
Still, AI isn't just about learning patterns. There's an inductive step and varieties that are also about problem solving.
Most CP style systems and solvers definately don't imitate people, to say the least!
CP is actually a vibrant, active area of artificial intelligence research with a large, strong community. If you go through the AAAI conference proceedings (available at http://www.aaai.org/), you'll see that, indeed, it had a number of papers this years. Additionally, they have their own conferences and researchers with strong interests in the area, including my research advisors and several of my colleagues.
Machine learning, also, has come a long way. Popular methods at the moment are support vector machines, and bayesian (graphical) models. You'll also see meta-learning taking hold, in the form of bagging, boosting, and ensemble techniques.
Building on this, you'll see systems that do a bit of both. Check out MaxSAT as a problem. You can easily see where researchers are driving toward systems that place probabilities in the weights of a MaxSAT solver, and then solve based on this. I attended a talk yesterday on this by Dan Roth. Very cool stuff.
Uhmm, that's just patently incorrect. You're thinking of expert systems, which represent a distinct sub-category of artificial intelligence.
However, if I go through this board correcting everyone, I'll never finish my final projects for the semester, so, I'll do it here.
Modern AI consists of a number of subdisciplines, each of which focuses on different things. I haven't RTFA, because I'll believe it when I see a paper on what they're doing.
To be brief, however, there are
Logical and Constraint programming, which focuses on solving problems through sets of contraints.
Knowledge Representation, which focuses on how we represent the world to algorithms that work on that knowledge
Natural Language processing, which deals with working with spoken language. It's considered that work in this field represents some of the hardest challenges in AI.
Machine Learning, which has been described as statistics on steroids by one of it's popular researchers when addressing his class
Human-Competitive/Human-Like AI, which generally works in bringing together these systems into a human-like intelligence
Multi-Agent systems focuses on behaviors of more than one agent
And others (I hope none of my collegues are offended that I didn't stick theirs in the list, but some of the descriptions get a bit intense, and, again, I need to get back to work)
Then you have all sorts of tasks:
Autonomous navigation
Word sense disambiguation
Game playing
Temporal and spatial reasoning
Planning
Scheduling
Tabletop space problems (which most closely resemble your "true" AI, and do not merely mimic the actions of the teacher)
and man others, again, I hope I've offended no-one, these are the ones in my head due to PhD apps being around the corner.
The president of the AAAI this year, called for what are called "AI Decathalons," whereby researchers would construct systems that do multiple tasks. For example, a system might take a written or multiple choice exam, which requires forms of reasoning, it requires naturual language to read the questions, it requires knowledge representation to represent the questions and data.
At the same conference, Marvin Minsky had remarks more of the flavor of "AI needs to change directions (dramatically)," but he still wouldn't constrain the accomplishments of modern AI to expert systems. His book "The Society of Mind," is probably not a bad place to start if you want to learn about modern AI. It's very accessible to people who have only a passing interest in the field, while having enough solid content, ideas, and commentary (from Minsky of all people) to keep a fairly advanced researcher interested. Also, if it comes up in conversation, it's one of those "it's good to have read" books, even if you disagree with Minksky's ideas (one such controversial idea, consciousness does not exist).
We've already got those in the pipes. Read up on what the DARPA Grand Challenge is all about.
Ahh, but see, that's where we don't agree. Even if Microsoft is evil, you have to allow the possibility for them being good.
They can't do the wrong thing if there is no right thing for them to do. Think of it game-theoretically, in terms of Nash equilibria.
THE MS IS EVIL PROBLEM
We assume that Microsoft only does the wrong thing when there is a benefit to doing so of, eh, +10.
We assume that being well thought of, however, for some reason, is a good thing... Eh, also +10.
The converse in either case is -10.
The column on the left is what the public will think of MS after they commit their actions.
Since you've preconditioned that MS is evil, we'll assume that MS starts out evil.
(Curse slashdot for having no way of doing tables in your posts). I can't get the table to look right, but if you work out the Nash, MS has no motivation to do anything but evil, since it's the safest strategy in this scenario.
TABLE WAS HERE
We can see clearly, that if MS can make the public think that they are good, while doing evil things, that they stand to gain the most benefit. Also, if they're stuck with you thinking that they are evil, then their strategy does not change. In fact, there is no reason for them to do the right thing, since they will never benefit from having done so.
Oh, ok, one more.
If I'm writing an application that lists x items from a data structure, then I'm putting that into the page through codebehind. I'll also stick my buttons onto the page and whatnot. I feel that codebehind is superior for this, over mixtures of JSP and servlets.
Get it?
I actually understand how to construct an app fairly well.
As far as libraries of well known primitives. If you had read my post, you'd realize that I was saying that the difference is negligible after working for a few weeks in either language.
In fact, my entire premise was that the difference is fairly negligible, not that C# was all that great.
Also, the JCP doesn't constitute a standard of any sort.
Oh well, lets continue with this.
:-D
I like codebehind. I don't claim to be a crack web developer.
I actually know a good bit about java
I'm not a refugee from ASP or PHP. I developed mostly unix platform software, including some radar and such, until my company decided to go web shop. Not wanting to be stuck for the rest of my life as some web developer, I bailed and returned to grad school to get a PhD.
Now, all of that aside, I'd rather never identify myself as a "Java" developer, or a "C++" developer, because I feel that that ties me to some lame vocational role. If anything, I'd rather be identified as a programmer, knowing a bit about a number of languages, and a lot about algorithms and such.
Interestingly, that's what I was. I can program in a good number of languages, and have a solid backing in theory and such.
Anyway, all of that aside, calling me stupid is about the lamest thing that you could possibly have done.
I've developed large applications in both.
Thanks for making it personal.
I'll avoid the obvious digs on you.