So I would think that if the dominant "form of life" in the universe were robots, it seems like a reasonable guess that they'd have learned to self-replicate. If they're really so smart and able to dominate the universe, one might suppose that they would accomplish this through master of nanoscale engineering, creating robots that are able to grow copies of itself. It'd seem likely that such a process would include having a machine made up of organic molecules, able to take in and absorb matter, both for the material and for energy.

Little by little, imagining the scenario based on what we know of science, it becomes increasingly likely that these "robots" would be life pretty much as we know it. Maybe not quite the chemical bonds that we're used to, and maybe not in the shape of things that we're used to, but something that eats "food", excretes waste, is made of chemicals comparable to proteins, DNA, and whatever else. Able to "get pregnant" and "have children". Perhaps as different from us as we are from exotic deep-sea fish, perhaps even more different, but still recognizably "life".

So I guess what I'm wondering is, what do we mean if we say that the dominant life form In the cosmos are "robots"? I we imagining something with microchips, circuit boards, and metallic gears? I could think that super-intelligent machines would be less crude.

No, it's not completely wrong. It's a model that approximates what happens within an acceptable degree of precision for many, many circumstances. We have another model that adds to it and modifies it, and that model is used for situations where that precision is not sufficient. It's not clear that science is capable of providing certainty of "right" or "wrong" beyond determining whether a model approximates what happens within an acceptable degree of precision.

Still, when talking about a "Liberal Arts education," you're talking about a generalized and broad education in a variety of topics, including subjects related to math and science. That's what the term means. No, that doesn't mean that you will study literally every subject, but it's not claiming to be about any particular subject. STEM, meanwhile, seems to be trying to claim to be a valid classification of a particular type of study, distinct from that kind of "broad, well rounded education."

If you say you want to get a Liberal Arts degree, you're telling me, "I'm not going to college for job training in a specific career. I'm going for a general education." If you say you want to get a BS in CompSci, you're basically telling me, "I'm going to college to get training for a career in software development," or something along those lines. Already that's kind of vague, because there are a number of different career paths that involve computer science, and computer science is already a fairly broad field. But if you tell me, "I want a STEM degree," you're telling me, "I have no idea why I'm going to school. I guess I want an education in sciencey stuff that will focus in on a particular field for career training, but I don't actually have any understanding of what field I want to study."

I'm struggling to come up with a good analogy, but it's like if you said, "I really want to travel!" and I asked, "Are you just interested in travelling generally and seeing the world? Or is there a particular place that you want to go?" and you respond, "No, there's a very specific place that I want to go."

So then I ask, "Where's that?" and you say, "Europe or Asia."

Now, I point out, "You're not narrowing it down very much there, you know."

And you respond, "Well you weren't narrowing it down much either, when you asked me if I wanted to see the world!"

And you're not wrong, but it's also a bit of a silly argument now, since the point of talking about "the world" was to be broad and cover everything. Liberal Arts covers everything. I guess that STEM is supposed to be "everything, minus that faggy art stuff, and stuff that makes you think about things."

That was one of my thoughts, as well. I think I understand the concept, and it seems like an interesting and possibly useful approach. However, it doesn't seem like it will necessarily give us causal links in a very certain way, since many real-life situations have many factors with complex relationships. Like: Z causes X and Y, but perhaps it always causes X and only makes Y more likely. Or: A, B, and C all independently increase the chances of E, but only when an unknown factor D is present.

So I'd guess that this isn't going to be anything like a magic bullet, but I don't know that the people who came up with it expected it to be. It might just be another useful tool for analysis.

Teaching jobs and various educational administrative jobs, marketing jobs, customer service jobs (not all of which include fries) and office worker jobs. Lawyers and associated jobs (paralegal). Sales jobs. Political positions.

I think the point here is there are loads and loads of jobs out there that don't require specific technical knowledge, or even many that make use a of broad education. The idea that there are no good jobs aside from technical/engineering jobs is pretty senseless and dumb.

But again, you miss the point entirely. If you were correct, it would be appropriate to use the line from The Big Lebowski, "You're not wrong. You're just an asshole." But you happen to be wrong too.

The larger issue here is that even if a certain education would lead you exclusively into the service industry, it would not excuse you being insufferably condescending about the prospects of having a job in the service industry. That's if a liberal arts degree were to make you unsuitable for any career other than food service, which I don't accept other than for the sake of argument.

Maybe if you had gotten a real education instead of merely vocational training, you'd be capable of understanding the distinctions being made. As it is, I encourage you to go back to being a code monkey and let the adults talk.

I think I understand... vaguely. To simplify, you're saying it's been trained on a specific dataset, and it chooses whichever image in the dataset the input is most like. It doesn't really have the ability to choose "unknown" and must choose an image from the dataset that it's most like. Its "confidence" in the choice is not really based on similarity to the image it has chosen, but instead based on dissimilarity to any of the other images. Therefore, when you give it garbage, it chooses the image that it's most similar to, and it gives a high confidence rating because it doesn't resemble anything else.

Is that about the gist? I'm probably not going to understand things about higher dimensions without a lot of additional information.

But if I'm on the right track on that, do you foresee a possible solution being reached by feeding it a very large dataset? Or is there basically no possibility of it handling a dataset big enough? Like if you gave it enough computing power and fed it all of Google images, would that help to solve the issue?

I ask because, though I understand computers, I'm not remotely an expert in current AI approaches and theory, but I do know a fair bit about philosophy and psychology, and I suspect that the idea of optical illusions and biases are going to be really import AI image recognition, and not just as "an obstacle to be overcome". I think people misunderstand and think that the optical illusions are examples of our vision and perception "being dumb" because we're seeing things incorrectly, but on the contrary, it's often caused by our perception being very smart/efficient at seeing particular things. Our image processing is (loosely speaking) built to see the things that were important to our survival and to disregard things that don't matter. That's how it works. So I would suspect that in "training" an image recognition system, it would be important to think about what the AI is looking for.

Because, you know, when we see a school bus, we don't simply associate the image with the words "school bus". We also recognize it as a method of transportation, as a possible source of danger (if you're standing in front of it when it's moving), and we might associate it with various memories and feelings that we had regarding school during our formative years. When we see a painting of a school bus, we understand it not only as an image of a school bus, but a painting, a work of expression which might have meaning beyond its literal content.

Maybe it seems like I'm going off on a complete tangent here, but I think it's worth understanding that seeing and understanding images, and linking them to meaning, might be more complicated than being able to accurately compare it to other images and find correlation of shape and color.

Do we have reason to believe that this group is actually capable of or prepared to carry out the attacks that they're threatening? If theaters around the country showed the movie, can these terrorists bomb them all?

Or did all these companies simply buckle to a random threat without anything behind it? Because, yeah, I guess if someone calls in a bomb threat to the local high school, you might have to go evacuate the school while the police check it out, but you should have some plan for keeping the kids from calling in new threats every day and shutting the school down permanently.

When people talk about getting a "Liberal Arts education", they're usually talking about getting an education that is supposed to be 'well rounded', giving exposure to subjects like philosophy, literature, art, and even various branches of math and science.

So you ask, "Do you mean sculpture, writing, philosophy, music, or whatever?"

And I answer, "Yes."

I think you're missing the point that grcumb was making, which I think was a good one. I don't believe he was arguing anything like, "If you want to optimize your chances of success, drop out of school and don't get a diploma." He was responding directly to the quote, "most of the jobs with a liberal arts degree involve asking 'Do you want fries with that?'"

I think what he was saying is something more like, "You have no ground to be so glib about other people's lives."

People who work in service industry jobs deserve some measure of dignity. People who never got a degree can still go on to do amazing things. There are people who have no connection to "STEM" fields who have made huge contributions to your life without developing software. And finally, liberal arts degrees do actually have a use.

There are no guarantees that you will be successful in any case, and there's always a vanishingly small slice of the human population that makes it to the top of their field. But who said that was the point?

If you want to make movies for example, you could pursue that. Maybe you'll be a complete failure. Maybe you'll make something great that's a commercial failure. Maybe you'll make an absolute piece of crap movie that's a commercial success. There's a very small chance that you'll ever be rich and famous as a result.

If you want to make software, you could pursue that. Maybe you'll be a complete failure. Maybe you'll make something great that's a commercial failure. Maybe you'll make an absolute piece of crap application that's a commercial success. There's a very small chance that you'll ever be rich and famous as a result. And so what? Pursue what you want to pursue. If you just want to make money and live a comfortable life, then do some research and figure out whatever career provides that, and be prepared if demand for that job dries up, because that can happen to any job.

But in any case, there's really no reason to be a glib, condescending asshole about other people's lives. There are a lot of good, hard working people out there who are making good use of their liberal arts educations. Some may even have a job that involves asking the question, "Do you want fries with that?" If you're ready to condemn them all as 'losers' because they don't write software for a living, then you're an asshole.

Yes, I think it's very interesting when you look at Figure 4 here. They almost look like they could be an artist's interpretation of the things they're supposed to be, or a similarity that a person might pick up on subconsciously. The ones that look like static may just be the AI "being stupid", but I think the comparison to human optical illusions is an interesting one. We see faces because we have a bias to see them. Faces are very important to participating in social activities, since they give many cues to another person's emotions and intentions. It's a whole form of communication. A lot of other sensory biases and reactions are related to things like finding food, avoiding predators, and understanding potentially dangerous obstacles (e.g. if I step here, am I going to fall down?).

So if these are optical illusions for computers, what are the computer's biases based on? The computer isn't trying to find food or avoid predators, so what is it "trying to do" when it "sees"?

Even if national borders were to become meaningless, I'm not sure that jurisdiction stops being relevant. Which law enforcement agency will pursue the crime, and which court will it be tried in?

Jon Postel was murder/assassinated.

This sounds suspiciously like, "If you have nothing to hide, then you have nothing to fear." I'm not on board with that idea.

Just so I've said it, my comment wasn't intended to be in favor of law enforcement being able to search anything without a warrant, or without proper procedure. I'm just pointing out that the issue, as it's stated in the summary, is a legal argument about whether data lies in a particular jurisdiction. I meant to point out that, with the ephemeral quality of data and the ease with which it can move through countries-- even unintentionally, it might not be the best policy to make it as simple as "data is under the jurisdiction of wherever the physical hardware is that happens to hold it at the moment."

However, it might need to be that rule, because I'm not sure there's a workable alternative. All data is automatically under the jurisdiction of the location where it was created? Under the jurisdiction of the creator's primary place of residence? Under the jurisdiction of the primary location where it is most often accessed? I'm not sure I see how any of those policies would be enforceable.

Whichever jurisdiction it is decided to be under, law enforcement should be required to follow the laws of that jurisdiction.

I'm with you on this. STEM is a term that's being pushed on us by political/media types for who-knows-what reasons. It reminds me of people talking about "ya". I saw that thrown around a lot as a genre of books, apparently meaning "Young Adult (literature)", and it took me a while to figure out what the hell people were talking about. It's not really even a genre, but a classification of the target audience. It's pretty dumb use of jargon.

Back to STEM. Science, technology, engineering, and math. As though those are the same things. As though astrophysicists and programmers and marine biologists are all doing the same thing, and their expertise is interchangeable. Whoever lumped all that stuff together either has an agenda, or has no idea what they're talking about. In the contexts I see it being used, I assume that the intention is either:

(a) Companies that rely on software developers complaining about the lack of people with "STEM degrees", in an attempt to justify more H-1B visas; or
(b) Dimwitted programmers who want to lump all kinds of people into a subculture of "science people" to make themselves feel important. Like, "I'm a STEM person, just like Einstein, Neil deGrasse Tyson, and Carl Sagan. I'm just like those guys, because we're all STEM, unlike the filthy common people who like reading fiction and looking at art."

I mean, I'm not sure what else I'm supposed to take away from the whole STEM thing. Nobody talked about it 10 years ago. Having a lot of biologists does not help with developing software. Having lots of people capable of making iPhone apps does not push particle physics forward. I really think we need to drop the whole classification of "STEM" as a thing.

And the whole "preferably within the space industry"... what space industry does this guy mean? Does he want to work for NASA designing probes, or Boeing trying to design a space plane? Or is there some other "space industry". It'd be great to know, because it would really help narrow down what he'd need to do to accomplish that goal. But doing something related to space would probably mean, yes, you need to go back to school and get a undergrad in that particular field. Go find out what schools have the best Aerospace Engineering departments, and work your ass off, because that's going to get competitive.

I would say that it's not just the implementation, but choosing which thing to implement in the first place. A lot of these fads, whether it's "big data" or "cloud computing" or "agile development", have become popular because they're extremely useful in some cases. The mistake, sometimes, is in thinking that you've found a single solution to solve all problems, and applying it everywhere will fix everything.

Someone else here used the example of the language "Ruby" as a fad that was useless because Ruby is "awful". That doesn't seem right to me. In my experience, which is admittedly a bit limited (I'm not actually a programmer), it seems like different programming languages have their own strengths and weaknesses, so you may want to choose a specific language for a specific goal. However, realistically, in the projects that I've managed, it always made the more sense to take into account (a) the language any current code is written in; and (b) the languages my team is most comfortable working with. If you have a bunch of PHP programmers who only know PHP well, working to revise a web application written in PHP, then Ruby is probably a terrible choice. But then, Perl and C++ would also be terrible choices. Those aren't bad languages. They're just not the best choice for that particular project.

I don't want to start a shit-storm by talking about languages, since as I said, I'm not a programmer, but I think that example is simple enough. Similarly, "cloud storage" like Dropbox can be great for small teams working from different locations on small office documents. On the other hand, if you're a big company with tons of people working in a central office, editing video files that are multiple gigabytes each, then you're going to want some kind of internal storage. The issue isn't about implementing your Dropbox well, but making an appropriate choice for your needs.