I think the process would come about from running the power through a resistive load, which would generate heat and require cooling, potentially from a river.

Oh boy, a whole half an elective. I strongly suspect you didn't "acutally" write any real code or implement any kind of machine learning. I actually have implemented real machine learning solutions that used everything from neural nets to HMM to bayesian statistics. I can promise you that in all of those occasions, the program was working exactly as programmed and not exhibiting any signs of even your wikipedia definition of Intelligence.

I'm not trying to be, but there comes a point where I just can't sugar coat it anymore while still maintaining some semblance of rationality. You really either have no clue what you're talking about, or you're trying to get into an argument over semantics by making the term "intelligence" out to mean less than most people take it to mean.

Either way, 20 years ago it was people like you who set AI research back 20+ years by over promising on what AI actually was to the point no one would fund it when it became clear the false expectations weren't being met. Now your generation is posed to set it back again by going around spouting off clickbait headlines about how an animatronic puppet is an intelligent machine and switching it off is akin to murder.

What we see in chatterbots and neural nets isn't intelligence, or even the precursor to it. It's pure mimicry and nothing more.

way to give up. I'd have loved to give you some more specifics if you'd actually have defined some terms and quit trying to argue semantics.

It really just depends on the learner and the situation. When I was getting my scuba certification I remember having all sorts of trouble taking my mask off underwater in the pool (I have an almost involuntary reaction to water being on/around my eyes). I practiced it like crazy in the pool, but it was a real challenge to the point I wasn't sure I'd be able to pull it off at 40 feet in the ocean for the open water dives.

What finally did it for me was laying in bed visualizing myself removing my mask, and convincing myself that the imagined scenario was real to the point that my pulse and breathing rates started to go up with anxiety. Then I started replaying it over and over in my head until I could do it while keeping my heart rate and breathing under control. It ended up being significantly more effective than all those hours of pool time, though I suspect that I still would have had to have attempted it for real at least a few times in order to convincingly visualize it (and realize that there was actually going to be a problem).

It depends on how well either technology is used to create an immersive environment such that the learner is enticed into pretending like the real thing is happening. Simulations or narratives that suck you in and make you feel like you're actually in that situation will always add more than situations that don't. Whether that's playing a game on a monitor, playing a game on a VR headset, reading a book, doing an actual training exercise, or just sitting quietly and mentally walking through it. The more you can get the learner to suspend disbelief and envision themselves in the actual situation as if they're a little kid playing pretend, the more effective it will be.

Assuming you don't mean people with autoimmune disorders or legitimate allergies, I'm really curious to know what exactly falls into this category.

And again you show that you have no idea how machine learning actually works. By the way you choose to interpret the criteria, a piece of paper with some calculus written down on it is "intelligent".

And these people are idiots.

Two things here:
- I wasn't the one who asked that question, please pay attention to the usernames.
- All of your links demonstrated either reporters misreporting (e.g. the guardian article), or "smart" people trying to sensationalize something to get more funding (e.g. the turing test being passed, the vast majority of experts disagree that it actually passed). The other projects weren't even claimed to be intelligence (e.g. the animatronic chatterbot).

And that's exactly what the original asker of that question was getting at. There are no programs that can reliably pass the turing test without special rules in place, there are no actual "intelligent" networks, and most of the expert systems rely on a huge team of programmers and analysts to populate the database and create the search parameters. He asked the software equivalent of "where's my flying car" and then you did the software equivalent of calling him ignorant and linking the wikipedia article to a moller skycar and a sensationalist news report about flyboards, then claiming those are the beginnings of real jetpacks and flying cars.

It's not a matter of what I "thing" about neural nets, it's a fact. And by the same token, what you "belive" about them doesn't change anything. Please please please go find a tutorial and implement a neural net on your own if you still can't understand that. They aren't "learning" or "adapting" anymore than a summation equation that approaches a limit is learning or adapting. A neural net boils down to literally a set of 1-dimmensional linear algebra matrices in which the numbers in one matrix are tweaked up or down after each iteration.

That's a cop out. If you want to argue semantics, then by all means lay down some terms and we can have that discussion. Otherwise, by most accepted definitions of intelligence, there are no algorithms that exhibit signs of actually having it. The closest you might be able to get is swarm behavior, but even that is simply individual units responding in a very basic way to very basic stimulus. It appears complex and emergent because we have trouble following that many things at once.

Your Turing test example is terrible. iirc the slashdot commentors ripped the story to shreds when it appeared here. Other people agreed: http://www.theguardian.com/tec...

Another bad example. Self-learning algorithms aren't at all what you seem to imply here, and I'd love to see you continue to make the same claim after a few days of playing with a neural net implementation (there are tons of free libraries containing machine learning implementations, as well as tutorials).

I see you've linked:
- A hardware focused project appearing to emphasize simulating humanoid-like visuals more than implementing any kind of AI (the FAQ for the project even says it doesn't have memory and current research using the system doesn't require it: http://groups.csail.mit.edu/lb...)
- The MIT page for the department that made COG
- An system that uses image recognition to parse extremely simple handwritten commands and then write them out by hand. If this counts as machine intelligence, than so does a simple assembler.
- An "animatronic puppet" (the creators words, not mine), that uses speech recognition/TTS and a standard chatterbot interface to (poorly) mimic a humans responses. Did you notice how it kept talking over the people conversing with it? And that was a cherry picked clip of people talking to it who knew how to hold conversations with the thing. Show me an example of someone asking it a technical question (hell, they can type the question if that makes it easier to parse) and then getting a real answer out of it. e.g. "explain to me how a keyboard works".

There's nothing wrong with being excited about AI developments. It's just that historically, people like you who go around calling things AI that aren't really AI (and have no potential to actually be "AI") have done significant harm to the field by generating unrealistic hype and making promises that can't be delivered. Please take your own advice and google some tutorials and example projects for the neural nets that go into simple image recognition and the markov chains that go into making a chatterbot. Then get back to me about how your examples demonstrate some kind of true machine intelligence in the sensationalist sense of the word.

That's pretty much the main exception I had in mind. The only other one I can think of might be as a loan to establish credit and/or fix credit. In that case you'd have enough money in the bank to cover most/all of it and a plan to pay it off significantly (read: years) earlier than the default payment schedule does.

I was with you up to this point. There's almost never a good reason to finance a car (plus most exceptions involve having enough money banked that you could buy it outright if necessary), and a decent new car should still run you under 20k. If you can't save up enough for that in a few years, then learn some basic maintenance skills and buy a used one. A lot of cars depreciate several thousand dollars after just a year or two.

It's all a matter of optimizing your financial decisions. If you want to drive around in a $90k BMW X5 because it makes you feel important, you'll either have to be rich or make sacrifices elsewhere. If you don't want to make sacrifices elsewhere and aren't rich, then I'd highly recommend a few year old used Hundai Elantra, Ford Focus, or Mazda 3. If you want sporty, a super nice used miata can be had for under 10k (one with paint damage and the like can be had for 4k)

Whether or not it's an ultralight is defined by weight and capabilities, not visual features.

English to Spanish is very similar. I knew a guy who worked as a cook with all hispanic kitchen staff. He knew no spanish and they knew zero english, but they were able to understand each other well enough by him speaking english with a strong spanish accent and them speaking spanish with as much english accent as they could muster.

These things are still relatively rare, expensive, and nowhere near the level of completeness that most clickbait articles breathlessly written by a reporter with no technical knowledge would imply.

These are all things that people (especially reporters selling headlines) want very badly, but not necessarily things that will ever be able to become practical enough to make it out of R&D and into common use.

I haven't finished it yet, but so far it makes sense to me. They're basically the logical extrapolation if you take monks out of the middle ages and point their enthusiasm at knowledge instead of religion. Presumably it remained because of tradition and also wanting to only attract smart people who were serious about the pursuit of knowledge for knowledges sake without getting caught up in the specifics of implementation.

A system like that would also have a stabilizing influence on the planet. Remove the smart and curious from the general population (and genepool) and let them pursue knowledge in a way that won't take a destructive outlet (e.g. designing weapons for an unstable dictator). Leave the sheeple who are content to take soma and maintain the status quo as long as they're entertained.

I was as well, to the point I nearly shut it off and started looking for how to return it. I think it's a combination of the weird voice for the character talking, strange terms, and lack of context as to what's going on. Once I got a feel for what was actually happening it improved by several orders of magnitude. (I think the narrator toned down his voice acting a bit by then as well).