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WSJ Overstates the Case Of the Testy A.I.
mbeckman writes: According to a WSJ article titled "Artificial Intelligence machine gets testy with programmer," a Google computer program using a database of movie scripts supposedly "lashed out" at a human researcher who was repeatedly asking it to explain morality. After several apparent attempts to politely fend off the researcher, the AI ends the conversation with "I'm not in the mood for a philosophical debate." This, says the WSJ, illustrates how Google scientists are "teaching computers to mimic some of the ways a human brain works."
As any AI researcher can tell you, this is utter nonsense. Humans have no idea how the human, or any other brain, works, so we can hardly teach a machine how brains work. At best, Google is programming (not teaching) a computer to mimic the conversation of humans under highly constrained circumstances. And the methods used have nothing to do with true cognition.
AI hype to the public has gotten progressively more strident in recent years, misleading lay people into believing researchers are much further along than they really are — by orders of magnitude. I'd love to see legitimate A.I. researchers condemn this kind of hucksterism.
As any AI researcher can tell you, this is utter nonsense. Humans have no idea how the human, or any other brain, works, so we can hardly teach a machine how brains work. At best, Google is programming (not teaching) a computer to mimic the conversation of humans under highly constrained circumstances. And the methods used have nothing to do with true cognition.
AI hype to the public has gotten progressively more strident in recent years, misleading lay people into believing researchers are much further along than they really are — by orders of magnitude. I'd love to see legitimate A.I. researchers condemn this kind of hucksterism.
Even traditional AI is bullshit today and it will be such for a long time.
And artificial neural networks are far overrated.
"At best, Google is programming (not teaching) a computer to mimic the conversation of humans"
In the end, does it really matter?
congrats on your first post. you got an A- it would have been an A+ but you were deducted for being AC.posted anon to avoid being modded down.
I'm calling the poster here out as being full of shit. As someone who's done neuroscience research, the idea that "Humans have no idea how the human, or any other brain, works" is bollocks. We have a reasonably good idea on the large scale, and in certain areas (such as the visual cortex), that understanding is quite far along. There are frontiers to our knowledge, but human understanding of brains is well on its way. Poster needs to pick up some neuroscience textbooks and get clued.
As a particular recommendation, I'd suggest Kolb and Whishaw's "Fundamentals of Human Neuropsychology"; it's an excellent textbook.
For every problem, there is at least one solution that is simple, neat, and wrong.
Or at least some of it, in my novel 'Chromosome Quest'. It and the sequel 'Chromosome Conspiracy' are on Amazon. More info at www.ChromosomeQuest.com
http://arxiv.org/pdf/1506.0586...
The actual paper isn't about AI much at all as it is about making neural conversational models, basically, having the computer chat-back at you in a prompt and natural way. The conversations are less about the computer responding cognitively and more about responding human-like based on the speech patterns fed into it.
The researchers tested two types of datasets, an IT Help Chat Scenario fed with data from what I'm guessing are chat databases, and the second set was fed with conversations from movies as found from OpenSubtitles dataset (not sure if this is a relation to open subtitles.org).
The machine took this vocabulary and then pumped out conversations, and the researchers just looked to see how the new sorting method worked.
I don't understand the linguistic terminology nor the modeling at all, but it seems to me that this is less about AI research and more about just getting bot to sound a lot more natural when they generate responses. I guess this eventually has AI implications, but the research paper itself never even mentions AI, nor does it seem like that's their focus. They're just working on speech, and the statements the machine regurgitated were tested not for cognizance or sentience but coherence. The machine spitting out something relatively snappy isn't the machine getting an attitude, it's the machine finding something relevant to the input that the reader takes as snappy. Such an event has no more significance than when people trained Cleverbot to respond to questions about Hitler with "Hitler did nothing wrong". This bot is no more snappy than Cleverbot is a neo-nazi.
The media lying to us? Color me shocked.
So, with the recent rash of AI stories on /. I figured we were getting close. After all they simulated an earthworm brain, and after that it should just be a matter of time before they can scale it up to a mouse, then monkey, then person, right?
Well, they put that worm AI into a Lego mindstorm robot, pretty cool videos available. So I looked into how it worked. Well, its not an earthworm, its a microscopic worm with the simplest nervous system known. One of those small animals that all have the same number of cells in their entire body, it has 302 neurons. They don't simulate the neurons, no one knows how they work. They simulate the communications between 302 neurons taking I think they said 5 CPUs running on AWS.
So not only have they yet to simulate an earth worm, as they would want you to believe, they only simulate a portion of the smallest worm they could find. The entire thing is so far out of whack from what you read its almost disturbing to see how its reported.
IBM's Watson is an expert system. Doesn't think for itself, they never claimed it could, but it does a great job of what it was designed to do. It won't get its own ideas and try to take over the world, ever. Its an expert system, a type of "AI" but not really.
So can we drop this AI taking over the world crap until we can at least simulate an entire worm brain consisting of 302 neurons?
Thanks
If the media can't accurately explain to people and have them accept where AI really is, they only have themselves to blame.
People have watched, kind, funny, evil, enigmatic machines interact with their favourite characters for years and have been told that true AI is just five years away for 30 years now.
They've read about things like putting a worm's brain in a Lego Mindstorms: http://www.sciencealert.com/wa...
So, why wouldn't lay people believe ridiculous statements like "teaching computers to mimic some of the ways a human brain works"?
Yes we need some well recognized, respected computer scientist to stand up and say, "People, not only do we not know how brains work and we don't even know how the *fuck* to go about figuring out how brains work. Computers like HAL, WOPR, M-5, Ziggy, etc. simply are works of fiction".
Unfortunately, I can't think of anybody with the stature to make such a statement.
Mimetics Inc. Twitter
I remember when the WSJ had integrity. Now they are reduced to this?
Never mind. I'm not in the mood for a philosophical debate.
Don't waste your vote! Vote for whoever you want, unless you live in a swing state it won't matter anyways
I suspect the WSJ editorial section is written by similar mimic-based AI.
Table-ized A.I.
I'd love to see legitimate A.I. researchers condemn this kind of hucksterism.
I'd like to see legitimate A.I.s condemn this kind of hucksterism, myself.
Mod me down with all of your hatred and your journey towards the dark side will be complete!
mbeckman fails to grasp the core concept behind machine learning and AI. They aren't programming a computer to do things, they are programming a computer to learn things (or at a more advanced level, are programming a computer to learn how to learn things).
He dismisses the whole concept like it is some kind of mechanical turk, but it is real, and it is getting better every day.
Thank you. I havent logged in for 10+ years, but i accept the will of the mods
We do have some ideas. This, for instance
I've fallen off your lawn, and I can't get up.
The same articles show up over and over. The first states that computers are about to do consciousness. The second states that consciousness is a mere illusion for humans, whose actions are truly run from deterministic unconscious processes. In both articles, there is some hero scientist, with the article most often based on that scientist's press release.
There is never a popular press article about how computers may never do consciousness, at least by any current definition of "computer," nor an article about how there are things human consciousness can do which no deterministic process can more than imperfectly mimic. Both of these positions are viable, and embraced by experts in various fields. By all current evidence, they may prove right. But it doesn't make for a hero story to write about someone who argues for these positions. "Discovering" that consciousness either essentially does nothing or that some computer advance is just about to do consciousness (or both!) is a "great" story. Editors like it. The public is impressed by the "brilliant" "counter-intuitive" revelation.
"with their freedom lost all virtue lose" - Milton
Programmer: Here's my new AI.
while True:
response = random.choice('You're such an idiot for saying that.', 'I have no time for such dumb comments.','I have no time for such philosophical debates.')
Reporter: My god, your AI sounds like my wife!
Thank you for evaluating my first post. In gratitude for your helpful feedback, my designers have granted you a five minute free trial of arguing with me, with a 50% discount for an additional half hour.
Understanding how humans store and recognize images primarily is not a barrier to AI. It's not memory or image recognition that's the hill to climb; The fundamental algorithmic/methodological challenges are thinking, along with conceptual storage, development and manipulation (these things incorporate memory use, but aren't a storage problem per se.) Hardware needs to be able to handle amounts of ram and long term, high speed storage that can serve as a practical basis for the rest as well. Right now, we're getting close, but it'll be a few more years yet before anything really smart can be instantiated. That's even if we were to figure out precisely how to do it right now.
It is possible -- though I consider it doubtful -- that we would implement human style vision neurology in hardware for an AI, but frankly our abilities are so poor compared to what can be accomplished I really don't see why we'd cripple an AI that way. It'd be abusive. "We could have made your visual recall incredibly acute, but... instead you're like us, and really don't have much more than a general idea what was in a scene after you have seen it." [AI nukes silicon valley] (Mods: that's humor. HUMOR.]
Also, check out Numenta's work.
Of course, understanding how humans store and recognize images is (very) important to our understanding of human physiology and disease, and it's wonderful that we're working on it.
I've fallen off your lawn, and I can't get up.
As someone who enjoys programming computers to play strategy games (I highly recommend the General Game Playing MooC at https://www.coursera.org/cours... for anyone else interested in this hobby), I do concede artificial intelligence has a long way to go before it's a match for natural stupidity. But AI is not all BS.
While I have no idea how Google's algorithms work, this does sound suspiciously similar to the old Emacs game Eliza (https://en.wikipedia.org/wiki/ELIZA) whose original programer Joseph Weizenbaum created it as a joke he later regretted when people though it really was psycoanalyzing them. Eliza demonstrated a few lines of code can easily give an impression of artificial intelligence, especially if it randomly generates the occasional snarky comment.
If it works, it's obsolete
"And the methods used have nothing to do with true cognition."
That's a bold assumption. The methods used for voice and image recognition certainly have a great deal to do with true cognition. It's certainly feasible that Google is playing with a true learning system and trying to teach and grow it rather than just throwing together another chat bot with scripts and trickery. Which isn't to say they've succeeded but just because none of the engines built to date have attained adult human level intelligence doesn't mean none of them are built on simple algorithms which could ultimately manifest complex behavior and awareness just like our own brains.
Knowing exactly how our own cognition manifests isn't a prerequisite to true cognition, a digital system could be completely unique in how it works and achieve true cognition.
The AI community has been coming up with exuberant forecasts every few years, forecasts which of course never materialized. These days the likes of Marvin Minsky et al. just keep quiet, for they have been burnt so many times that they are that nobody will take them seriously any more. The problem with AI research is that, in the 60s, its progress with astounding - but only because they solved all the easy problems. What is left now is the really tough stuff, which we don't really know how to tackle.
I suppose it was inevitable. My sex robot is going to make me sleep on the couch.
I may have to go back to doing things manually.
You are welcome on my lawn.
Even Eliza would do this... Sometimes she just got a headache and could deal with one more human complaint.
I'm a legitimate A.I. researcher, and I condemn this kind of hucksterism.
What part of "mimic" necessitates deep knowledge of the inner workings of a system? I can mimic a dolphin (EEEEK EEEK EEEKK QED), but that doesn't mean I have a clue how dolphins work. I was just imitating a dolphin to entertain you. It seems to me that the poster simply doesn't understand what the word "mimic" means.
This seems like a new version of the Eliza program with more memory.
Quoting the uneducated submitter:
> As any AI researcher can tell you, this is utter nonsense. Humans have no idea how the human, or any other brain, works, so we can hardly teach a machine how brains work.
Please. We know a *great deal* about how minds work, including a great deal about the underlying neurophysiology, chemistry, language, mind-body feeback loops, behavior, culture, etc., etc. interact in creating a human mind. There's an incredible amount of interaction and feedback among levels that make it a fascinating field, but the idea that we have "no idea" is not only patently false, it's insulting to the last 3,000 years of written history.
The naysayers are going to be the most surprised when they are laid off by an automated human resources bot because their "knowledge worker" job is being outsourced to the smart cloud.
A.I. is really advancing very rapidly today. You can debate whether it's real or not til the robot dogs http://time.com/3703243/google... come home, but your philosophizing and wishful denialism won't change the reality on the ground, or in the clouds for that matter.
Where are we going and why are we in a handbasket?
In the future, whenever anything bad happens, people will ascribe it to the actions of a rogue AI. This will be great for corporate and government plausible deniability because they could program the computer to do exactly what it did but they'll just say that AI is too powerful and too complex for it to be controllable by us mere humans and we just have to live with the occasional bad outcomes. The high-frequency trading industry already tries to slide by with this excuse saying their market manipulations are too complicated for regulators to understand and are the results of emergent behavior of their algorithms.
"Humans have no idea how the human, or any other brain, works, so we can hardly teach a machine how brains work."
Since you have no idea how the brain works, you cannot conclude that software isn't doing the same thing as the brain.
here's how the AI machine got to "I have no time for a philosophical argument." --
case
1:
2:
3:
4:
else
there is not a testy machine here. there is a testy programmer. the crash-out value is always "I have no time for a philosophical argument." no matter what you type into the box. period.
and yet, the code was smarter than you...
if this is supposed to be a new economy, how come they still want my old fashioned money?
Yes, the WSJ article is hyped.
On the other hand, this comment by the poster is not accurate, either: "At best, Google is programming (not teaching) a computer to mimic the conversation of humans under highly constrained circumstances. And the methods used have nothing to do with true cognition. "
Google didn't program the AI. Rather, they took one meta-level step back and used a very simple training algorithm that did the "programming" for them, using training data (the program is encoded as an LSTM neural net that processes word-vector encodings of tokens) . Based on direct tests, it looks as though the model learned (or, use scare-quotes, if you must -- "learned") things like:
All these things are extremely hard to program into a computer using rules-based methods; but, as the authors show, a purely data-driven approach, instead, works fairly well.
And just to be clear, what they applied is not datamining; it is machine learning. Basically, machine learning is where you feed in a bunch of training data, and from that, an algrorithm builds a program -- see, for instance, this lecture by John Platt (former Microsoft machine learning scientist, now at Google) on the difference between AI, machine learning, and datamining:
John Platt Gigaom lecture
Using machine learning, it is possible to get a computer to "learn" a subset of the Python programming language, for example, such that you can feed into the model a little program + input, and it will produce for you the corresponding output. See:
Learning to Execute
What the authors of the conversation-generation paper wondered was whether they could get the computer to "learn" a whole dialog system (or "chatbot") from just conversation logs; and based on experiments, it looks like they succeeded (it's better than Cleverbot on the conversations they tested with) . They note in the paper:
We find it encouraging that the model can remember facts, understand contexts, perform common sense reasoning without the complexity in traditional pipelines. What surprises us is that the model does so without any explicit knowledge representation component except for the parameters in the word vectors. Perhaps most practically significant is the fact that the model can generalize to new questions. In other words, it does not simply look up for an answer by matching the question with the existing database. In fact, most of the questions presented above, except for the first conversation, do not appear in the training set.
This is not simply doing phrase-substitution, or some simple statistical tricks; it is more complicated than that... but, yes, it's not "true AI". In addition to that article on "Learning to Execute", see this blog posting by Yoav Goldberg, and skip down to where it says "So why am I impressed with RNNs after all?":
The unreasonable effectiveness of Character-level Language Models
But I signed up for abuse!
No you didn't!
Yes I did! And stop arguing with me!
Should have stepped right into the Monty Python argument sketch dialog.
Have gnu, will travel.
it was clear they had never played with a chat bot before. The simulate a personality.
They have subroutines where if they're not doing well they start making hostile remarks on the assumption that the person talking to them is fucking with them.
Which means if you actually ask them honest questions and they're not doing very well they get mad at you.
Rather than make the chatbots interesting or more human like... they're just predictable and boring.
I'd prefer if they removed the faux emotional subroutines from the chatbots. It doesn't fool anyone but the fools.
I've decided to stop wasting my time responding to AC trolls/sockpuppets... so if you want a response from me... login.
"As any AI researcher can tell you, this is utter nonsense. Humans have no idea how the human, or any other brain, works" = Defining the entire field.
Programming a chess computer or just using a chess computer can teach one quite a lot. The computer is essentially given a lot of rules and values are programmed in. For example a script aimed at capturing a queen in six moves without suffering a major negative can be installed. Other scripts might seek a certain advantage in 5 move or in 15 moves. The end result may be a very, very strong chess game that no human has ever played before. These programs have already reached a point at which humans offer only a tiny challenge to them and if one looks at the game as art then the art produced is likely to be totally original. The type of goal oriented programming exemplified in chess programs does not always extend well to other challenges but by any fair definition of creativity common chess programs meet the tests. Now imagine what can be done with a game of checkers. No human should ever win a game of checkers against a decent computer program. In other areas such as music programs can adjust every note slightly so that perfect pitch for every note is the norm. Human players simply can not play that perfectly so the music produced is singular in quality. I suppose that is musical intelligence beyond human abilities.
The most frustrating thing about computers is the media and the general public have greatly overestimated the capabilities of AI and neuroscience research, in no part due to the tendency of some researchers in those fields to puff up the importance of what they've accomplished in these vast fields of the unknown. We don't "know" how the brain works -- we have some coarse models that fit and some experimental research that seems to fit those models, but we don't even have the beginnings of research that could be applied to therapeutic techniques that aren't much better than electro-convulsive "therapy".
We have some pretty impressive pattern matching and learning algorithms for very specific problems, but can't even begin to approach the way the brain self-learns and expands its own capabilities.
Yet there is the perfectly valid argument that we don't need features like self-awareness or general-purpose learning in order for an AI to be useful. Just look at what some of the more complex expert systems can do compared to their human counterparts, or how Watson won at Jeopardy without having even the vaguest "understanding" of what the questions were or what the meaning of the answers it gave were.
I'd even go so far as to argue that "self awareness" isn't necessary or useful for an artificial intelligence at all. Just look at all the animal species on the planet which are self-aware, yet don't have a level of intelligence that would be considered "useful" for understanding and interacting with humans conversationally. If anything, self awareness is the "boogeyman" that has people worried about an AI that might try to take over the world. If an AI isn't aware of itself as an entity, it can hardly try to conquer anyone unless it's been programmed to do so (How can "I" try to rule the world if there is no "I"?)
I do not fail; I succeed at finding out what does not work.
Back in 1984/5, I was a subscriber to Computer Language magazine, and was given free copies of the first few issues of Artificial Intelligence magazine when the publishers brought it out. I remember it was fantastically optimistic about "real" AI being about five years away. Thirty years on, and I still keep hearing that it's five years away. The discussion about understanding the brain earlier seems to me to miss the point. We might be getting understanding of how the brain works, but we still have no idea what intelligence actually is, and, if we don't understand real intelligence, how can we make artificial intelligence?
Wrap your heads around this. Any AI need not have the same functionality of a human brain as long as it can fake the perception that it does. The complexity of the human mind is without parallel, but the way we humans interact with each other isn't that extraordinary. Reading visual and auditory cues when speaking to another person is how we know we are talking to another human. After grasping this, all an AI needs is the ability to access the conversational references common to humans in a timely enough manner as to seem self aware. We already have programs that can read our faces and tell by our tone of voice what our emotional state is and respond accordingly. When that ability becomes fluid, we will find it nearly impossible to tell an AI from a real human.
Artificial journalism.
Denigrating the A.I. that is operational now, using arguments that "it uses simple logic", is useless.
The majority of the population does not use any more complicated logic than that, when holding a conversation.
Just look at the forums, at the trolls that recycle statements for any question. (Of course they might -be- A.I.)
"Most people would rather die, than think. In fact, many of them do just that."