Artificial Intelligence Anonymous part Deux Ex Machina

This is my attempt at providing a brief introduction to another subject I know nothing about. Much to my dismay, I never took AI. Ignorance hasn't stopped me from blogging on topics before (see my Lojban, income inequality, lottery and capitalist ideology pages) and it surely isn't going to stop me now.

1. Artificial intelligence anonymous, part one.


2. Artificial intelligence anonymous, part two.

How do you make artificial intelligence?

To make intelligence is easy. You look at what Homer Simpson does and do the exact opposite. To make a machine realise that being intelligent means being the opposite of stupid all by itself is a different story, however.


Homer Simpson. Artificial? Yes. Intelligent? Well..

There are three main approaches to creating artificial intelligence. These are symbolic, sub-symbolic and statistical.

Symbolic AI is sometimes called Good Old Fashioned AI or GOFAI. This approach is based on the premise that human thinking is largely based on manipulating symbols. All our thoughts require symbols and the relationships between them. The first wave of the rise of the machines was heavily based on lambda calculus. Lambda calculus involves a kind of bootstrapping thinking where a function can call itself. It is meant to simulate the human ability to think about thinking. Symbolic AI is still intimately tied with programming languages that can support this mode of thinking such as LISP.

Sub-symbolic AI is concerned with describing human thinking processes algorithmically in order to simulate these processes on a machine. Algorithmically means that the process is describe in a step-by-step manner like a cooking recipe. Sub-symbolic AI is thus based on simulation of specific thinking processes instead of on the underlying thinking process of symbolic processing. Neural networks fall under this category.

Statistical AI is an extension of sub-symbolic AI in the sense that it is heavily steeped in mathematics and algorithmic thinking. Certain tasks are solved mathematically and then implemented in a machine so the machine may exhibit the same intelligent behaviour. While GOFAI researchers are often contempt with having some fuzzy logic, statistical AI researchers require that their solutions are determinable and optimal. This means they require that the machines try to do something constructive by attempting problems that do have solutions and that they do so in the best way possible.

Computational intelligence is the new blanket term for AI. While it incorporates all the waves of AI so far, it relies heavily on mathematical and statistical techniques without much regard for replicating the fuzziness of human logic.

The three main approaches are still far from creating general intelligence, even though they've made progress in creating very smart artificial thinkers for specific domains.

The lunatic fringe of AI

By lunatic fringe, I don't mean emo hair. Of course you always get those people who aren't satisfied with the norm. I am one of those people so I sympathise with the lunatic fringe of AI. Two fields that I admire are artificial life and technological singularity.

Artificial life researchers are not satisfied with merely simulating one aspect of humanity. Nay, nay, they want machines that smoke, drink and fuck. Provided of course that they evolve to this amazing level of civilisation by themselves.

Singularity researchers reason that we need not be content with creating human-level AI. We can reach further and create superintelligent beings so we can worship them. This is much the same as any other religion except you can actually reach out and touch Far-fetched Artificial Intelligence Theology or F.A.I.T.H. No, not really, I just made up that acronym.

Artificial Intelligence Anonymous

This is my attempt at providing a brief introduction to another subject I know nothing about. Much to my dismay, I never took AI. Ignorance hasn't stopped me from blogging on topics before (see my Lojban, income inequality, lottery and capitalist ideology pages) and it surely isn't going to stop me now.

1. Artificial intelligence anonymous, part one.


2. Artificial intelligence anonymous, part two.

What is artificial intelligence?

Pope John McCarthy coined the term artificial intelligence for the Dartmouth Conference in 1956. The idea behind AI is that every learning process available to thinking, drinking, smoking and fucking humans can be described so accurately that a machine may also exhibit the same learning behaviour. It is thus artificial because it is a machine doing what humans tend to do (minus the drinking and fucking, although I do wonder where computer viruses come from). Or more precisely, it does what humans are supposed to do, namely learn.



John McCarthy. In the land of hobbits, he is a dwarf. The John McCarthy homepage is simple yet efficient and oh so wholesome.

There are as many definitions for artificial intelligence as there are artificial intelligence researchers, which is great because ultimately there can be no true AI until machines exhibit a general intelligence factor. Regardless, I find the quick and dirty definition of John McCarthy as valid, meaningful and descriptive so I'll go with that.

Why artificial intelligence?

Because whenever humans get a mathematical problem with decimal points, we tend to look like cowboys. Not the Brokeback Mountain kind of cowboys, but the gunslinger cowboys who reach for the hip and try to be the quickest on the calculator draw.



Qbo, an open source hardware project with AI listed at Harkopen. Notice the uncanny resemblance to John McCarthy.

Since the abolition of slavery humans have been looking for new slaves. Computers solve this intricate masochist/sado-masochist equation in an ethical manner. The idea behind artificial intelligence is to relieve humans of mundane, repetitive thinking tasks so we can focus on more important aspects of humanity. Like drinking, smoking and fucking.

Human by Death review

Last year, I had a Month of Megadeth during May. May is my birthday month so I like to do something special. Something so special that I won't forget it during the inevitable bouts of drinking and debauchery. This year, I'm having a Death Month.

• Human


• Symbolic


• The Sound of Perseverance

Conclusion

Chuck Schuldiner basically hires Cynic as his backing band and together they craft one of the most skin tearing albums of all time.

Review

The album opens with Sean Reinert's incredible drumming fading in. From there, the riffs exchanged between Chuck and Paul Masvidal are tighter than the fix Government Motors (er, General Motors) finds itself in. Widely regarded as Death's finest moment, I prefer Symbolic but Human is certainly just as flawless.

The lyrics are introspective to the point of becoming existential. They deal with euthanasia, masks people wear to project a desired, distorted image to the world and simply with being human. This prompts some questions about what it means to be human. Are we human because we do human things, or are we human because we are born this way? Alan Turing and John Searle are two bright minds who have answered this question in different ways.

The Turing Test

Alan Turing described his Turing test in his paper Computing Machinery and Intelligence.

The Turing test involved three participants: two humans and one computer. One human and one computer are locked in separate rooms. The remaining human poses questions to the inhabitants of each room by typing them into a terminal. The purpose of these questions is to find out which room hosts the human and which the machine. Turing suggests that when the computer can fool the player to think that its room hosts a human, the computer would have passed the Turing test.



Turing seems to suggest that we are human because we do human things. Thus, if a computer were to do the same human things and can fool us into believing it is human, it would be as good as human. Basically, computers would be human when we say they are human and we can decide when and how they are to become human. Thus, computers would become human because Stone Cold says so.



Stone Cold Steve Austin. According to Turing, computers become human when Stone Cold says so.

This avoids the issue a little - something that Turing no doubt knew, but he probably avoided the issue in this way for the practical purposes of building imitation humans. Philosopher John Searle is not happy with this arrangement.

Searle's Chinese Room

John Searle presents his Chinese Room argument in his paper Minds, Brains, and Programs. Searle proposes a scenario whereby artificial intelligence has evolved to the point where one such system can be taught fluent Chinese. The system is hosted inside a room and comfortably passes the Turing test by conversing with a human Chinese speaker outside the room.

According to Searle, the machine merely did symbol manipulating according to algorithms. Some proponents of strong AI would reason that the computer passed the Turing test as it understands Chinese. However, Searle turns the experiment around by suggesting that he himself is in a room with all the tools he would need to translate Chinese - dictionaries, pencils, paper, etc. He would be able to translate any Chinese characters which came through the door without understanding a world of Chinese. Searle argues that since he clearly does not understand a word of Chinese, yet can translate Chinese into English with the appropriate algorithms and tools, we have to conclude that the Chinese computer does not necessarily understand Chinese either.

Yet failing the Turing test does not make us less human and more machine. Searle seems to suggest that we aren't human merely because we do human things and no amount of nurture can give machines human nature. Not even when Stone Cold says so.

Track listing

1. Flattening of Emotions


2. Suicide Machine


3. Together as One


4. Secret Face


5. Lack of Comprehension


6. See Through Dreams


7. Cosmic Sea (Instrumental)


8. Vacant Planets

Personnel

• Steve DiGiorgio: fretless bass.


• Paul Masvidal: guitar


• Sean Reinert: drums.


• Chuck Schuldiner: guitar, vocals, production.

Rating