Slashdot Mirror
'Modern AI is Good at a Few Things But Bad at Everything Else' (wired.com)
Jason Pontin, writing for Wired: Sundar Pichai, the chief executive of Google, has said that AI "is more profound than ... electricity or fire." Andrew Ng, who founded Google Brain and now invests in AI startups, wrote that "If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future." Their enthusiasm is pardonable.
[...] But there are many things that people can do quickly that smart machines cannot. Natural language is beyond deep learning; new situations baffle artificial intelligences, like cows brought up short at a cattle grid. None of these shortcomings is likely to be solved soon. Once you've seen you've seen it, you can't un-see it: deep learning, now the dominant technique in artificial intelligence, will not lead to an AI that abstractly reasons and generalizes about the world. By itself, it is unlikely to automate ordinary human activities.
To see why modern AI is good at a few things but bad at everything else, it helps to understand how deep learning works. Deep learning is math: a statistical method where computers learn to classify patterns using neural networks. [...] Deep learning's advances are the product of pattern recognition: neural networks memorize classes of things and more-or-less reliably know when they encounter them again. But almost all the interesting problems in cognition aren't classification problems at all.
[...] But there are many things that people can do quickly that smart machines cannot. Natural language is beyond deep learning; new situations baffle artificial intelligences, like cows brought up short at a cattle grid. None of these shortcomings is likely to be solved soon. Once you've seen you've seen it, you can't un-see it: deep learning, now the dominant technique in artificial intelligence, will not lead to an AI that abstractly reasons and generalizes about the world. By itself, it is unlikely to automate ordinary human activities.
To see why modern AI is good at a few things but bad at everything else, it helps to understand how deep learning works. Deep learning is math: a statistical method where computers learn to classify patterns using neural networks. [...] Deep learning's advances are the product of pattern recognition: neural networks memorize classes of things and more-or-less reliably know when they encounter them again. But almost all the interesting problems in cognition aren't classification problems at all.
...before a bunch of angry old coots post telling us that none of this is AI.
AI getting into the trough (https://en.wikipedia.org/wiki/Hype_cycle) again (https://en.wikipedia.org/wiki/AI_winter)?
Prominent people seem to fear AI (http://time.com/3614349/artificial-intelligence-singularity-stephen-hawking-elon-musk/), but isn't this just Fear of the Unknown? I mean, Elon and Stephen are really smart people, but do they know that most NN:s come down to linear algegra and spiced with non-linearities in the end, just simulating neurons? I mean neurons are common-place on the planet already, equipped with malice and stuff...
We don't have AI, in any form, in the modern world. We have code which solves program similar to a neural network and we have code which can mutate within very strict limits with genetic algorithms. We have nothing even approaching "artificial intelligence," which at the very minimum of the bar would be the level of an "intelligent" Human. If it's not better than a Human with an IQ of no less than 135 at literally everything it's not AI. We have nothing remotely close to equal to an actually retarded Human with an IQ of 70.
"If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future."
Perhaps AI is already generating the majority of Slashdot posts these days.
This. It makes sense that google will tout its neural networks, they own them. And yes, the reality is that many tasks and displays of "intelligence" will be difficult of those specific algorithms to handle efficiently or correctly. But the field is in its infancy. Computers haven't been around for even a century. I think though that they have in very specific terms been intelligent all along. The fact that they can do math such as understand 2+2=4 is in and of itself AMAZING.
Why it doesn't impress us is because we know what's going on inside and can dispell the magic. We know how it works. If I showed you a machine and I said "it can treat you like a therapist and cure your depression with greater success rate than the worlds renound phychiatrists", or some other seemingly "beyond computers" task; you would say that's artificial intelligence. But once I show you the secret sauce, the algorithm, the data points, the learning attributes it takes in and the process it uses, it's no longer intelligent, it's just a dumb machine using someone it was given. That's because we don't know why we are intelligent. We can use natural language, and we can do facial recognition, and we can determine creatively how to fix something we haven't seen before. We don't understand the process we take as toddlers to gain those skills. If we did, we would replicate it simply.
True AI will never become a reality because we have to understand it to build it, and by understanding it, we remove the magic and dispell that which was created as "true AI". We just keep moving the goal posts in search of something that is seemingly human. We will get there though. There is nothing in our heads that the universe and all of physics has barred us from creating. There is no law like gravity that states lIntelligence shall not exist but for within the head of a human being". Computers are better than us at chess, go, poker, and so many other tasks. Surely that is intelligence already.
The argument that AI isn't even close, or isn't here, is just plain stupid. It won't take "perfect" or "true" AI to replace an imperfect prone-to-error human in a job. We're being blinded by the need for perfection when it will only take "good-enough" AI to start replacing human workers.
Even worrying about the problem of AI is rather stupid when the problem of automation is the more immediate issue staring the economy in the face. We're working quickly to replace cashiers, warehouse and assembly line workers, and soon we will be replacing drivers. Just targeting these jobs will make millions of people unemployable. And don't try and regurgitate that age-old mantra of go-get-an-education either. Not every human is capable of being re-trained for a more advanced skill, and we have a hell of a lot more humans on the planet to employ with this next evolution of job decimation. And when you start thinking about the types of jobs you held in order to get an education, you quickly realize that automation is looking to remove the bottom half of the ladder of success. Rather hard to climb that proverbial ladder when the first rung is 12 fucking feet in the air, and you're competing with a few million people.
Our economy is going to feel this pain well before we start having to worry about any shitty form of AI.
We saw roughly how heavier-than-air flight would work, but we didn't have the pieces to put it together. We understood the airborne part enough to carry humans dating back at *least* to the sixth century (earliest recorded 'paragliding'). We couldn't make a practical aircraft, but we could see how the pieces would play a role in such a marvel if we solved other pieces.
Here, the current 'AI' craze doesn't even in theory extrapolate to higher-order displays of intelligence. It is a highly practical field to advance and is certainly useful, but *if* we want to go to more 'intelligent' systems, it's going to be based on a different methodology, or at least no one who understands the field can see a hypothetical extrapolation of this approach that leads to those results.
The problem people have is that a useful, albeit narrow discipline is conflated with the entirety of human intelligence. I have seen many in the field understandably trying to discourage the phrase 'AI' to head off very annoying irrelevant conversations and concerns.
XML is like violence. If it doesn't solve the problem, use more.
This "news" is "dog bites man" please come back when it is "man bites dog".
Well, OK then.
+1. This is algorithms and infant ML.
I can take my kid and train him to swim and then train him to drive a car and get rudimentary skill in a week in both.
You can only do this after about six years of full-time learning in how to navigate in the real world and how to operate his body. This is the hard part, the part that humans learn in their first six years and AIs don't: dealing with the external world.
Learning to swim and learning to drive a car are easy; machines can do that. Learning to make a peanut-butter-and-jelly sandwich out of what is in the refrigerator: now that's hard.
Low skill labor is still going to be at risk of being automated away, especially as sensors and robotics continue to improve as well.
Probably not to the degree you imply. The reason is simple economics. Automation is in most cases expensive and if you actually do the financial analysis (which I do for a living FYI) you'll find that it's nearly impossible to automate most jobs to such a degree that low skill labor becomes unnecessary. Automation is used in high volume or high content value or high risk jobs. While automation has gotten and will continue to get cheaper, it's unlikely to reach such a low price point that it pushes people out of the work force entirely within the lifetime of anyone reading this. To do that you would have to have near human level intelligence AI that you can sell for less money per unit than a human costs. That is a FAR more difficult goal to reach than most people realize. People are flexible and for low production volumes or ill defined tasks rather inexpensive.
...before a bunch of angry old coots post telling us that none of this is AI.
Let's put some of that into context.
A 5-year old can recognize a dog in an image in about 1/2 a second. A neuron takes about 0.05 seconds to activate and fire, so on average the entire recognition process takes about 10 steps.
Those steps include reading the image (sensing and converting the image data to internal form), and activating the physical response: saying "dog" or clicking the right button or whatever.
So let me ask this: what AI algorithm takes ten *steps* to recognize something as complicated as a dog?
Note that this works with dogs partially obscured (half masked by a tree, for instance), any size, rotated, from any angle (top down, face on, from the side), any breed (dalmations and chihuahuas), toys made to look like dogs, and cartoon dogs.
The algorithm does this at a very high level of accuracy, and can tell dogs apart from other animals with similar features: cats, opossums, and so on.
And the algorithm does this without a zillion training examples. A typical 5-year old has seen far fewer dogs than the Tensor Flow algorithm training set.
So tell me again: in what measure is our current level of AI anywhere close to being "real" AI?
30 years ago when I was taking AI in college my professor summed this up perfectly. He said "AI is like artificial milk. Artificial milk doesn't have to be as good as real milk, it's just quite handy if you haven't got any real milk."
Computers don't understand 2+2. They perform the operation by moving electrons from one place to another, ending in a pattern that humans interpret as 4.
Use any definition other than "pattern recognition" and we don't have it.
So me any form of intelligence that isn't some form of pattern recognition. Hell the entire field of physics and every other science is simply the act of observing patterns and building a model to describe them that has predictive value. At it's most basic form that is just sophisticated pattern recognition.
Oh for crying out loud, stop using the true scotsman fallacy in this case. The fallacy requires a person to make a subjective statement that nothing applies to. If you don't like the definition of 'intelligence' being used then say so, but this isn't no true scotsman. As far as I know, intelligence means ability to gather knowledge through external experience, which is a hard and fast definition that can either apply to 'AI' or not. For an 'AI' to truly be intelligent at playing Go, it needs to start with a seed and be shown instructions to Go and learn how to play from that. If someone programmed the rules for Go into it, then it has not learned to play through intelligence. The same 'seed' should also similarly be able to learn to play chess, do s crossword, or identify animals. Intelligence implies a certain amount of general purpose ability, since there are no bounds in the definition for the number of things you use knowledge for in order to be intelligent. This is why a human savant that can't talk or understand anything about life but playing Go or Chess is not called 'intelligent'.
Laws are rules for the court, but merely a bottom bar to hit for life. Think beyond laws in your actions always.