Comparing Clarke/Kubrick's 2001 To Now

angkor wrote us about a recent Economist article that explores and compares the differences between Clarke/Kubrick's vision of 2001, and what we've got. Of course, I'd point out that the literary one wasn't meant to be a literal 2001; but this an interesting comparasion nonetheless.

Comments

not literal?

[ceswiedler]

What do you mean, it wasn't literal? Clarke and Kubrick obviously thought about things they thought would be happening in the near future. I seem to recall Clarke being pessimistic about an AI as smart as HAL, but that's not quite enough to label the date of 2001 as "not literal." In the book, the events clearly happen in the year 2001 AD (or most of them, anyway). 2001 is much more specific and literal than a dystopian book like 1984 (where I would agree the date is more symbolic).

Science fiction is never completely accurate, obviously. But Clarke was one of the most accurate and scientifically rational writers of the century. We haven't gotten to convenient interplanetary travel quite yet, but you can be sure that it will happen much like he describes: a large space station using 'centrifigal force' to simulate gravity, and rockets using the station as a waypoint so the same spacecraft doesn't have to be capable of lifting off from Earth as well as travelling to and landing on another planet or moon.

Now, being able to phone from the station to America for only a few dollars, that's probably a little over-optimistic...

Re:not literal?

[jimharris]

The progression of computer science evolution has far outstripped Clarke and Kubrick's imaginations. They only imagined an intelligent machine without going into the details. The details of computers have been developing at a wild pace since the sixties, which science fiction failed to predict.

Clarke's and Kubrick's real failure was not seeing how quickly space exploration would die. In 1968 it would be natural to predict that mankind would be traveling to Jupiter by 2001. What was unnatural to imagine was mankind would visit the moon, and then never leave low earth orbit for three decades. And there is no real reason to assume we'll leave low earth orbit for three more decades.

If they had predicted that in 1968 I would have been blown away by their power of their wisdom.
At the time I was positive that mankind would reach Mars in the 80's. Humanity's lack of real interest in space exploration has been my lifelong disappointment.

And, even though I love science fiction, the older I get the more I realize that science fiction is no more than fantasy. The gravity of the mundane keep us tied to this planet.

2001, the story just plain missed the mark.

Re:not literal?

[awol]

1984 was a completely symbolic date. The book was written in 1948 as a critique of the british society of the day by reversing the digits of the time Orwell cast a dystopian future metaphor for the subject of his ire.

Chris Black

[jorbettis]

Chris Black was doing his "Year in review" on the daily show when he said:

"So my review for 2001 the year is the same as for 2001 the space odyssey, It went on too long, it was hard to follow, and you could only enjoy it if you were really, really stoned.

I think that is a pretty apt analysis of the similarities between the two ;-)

1960s stable, ordered corporate climate gone

[Anonymous Coward]

Pan Am, Bell Telephone, Howard Johnsons - and their logos which graced 2001 - pretty much all gone. We now live in a world dominated by quickie, cheap, here today, gone tomorrow corporate culture.

Leveraged buy-outs, insider trading, junk bonds, corporate mergers, golden parachutes - all this has destroyed what was once the paradigm for how to do things right. When 2001 was made, a 10 or 20 year corporate game plan was not unusual. Now you'd be luck to find any corporate plans looking ahead more than 10 or 20 months. Oh, and need I mention the "dot-com" crash as a perfect example of what this new culture breeds?

Stranger Than We Can Imagine...

[cybrpnk]

The Economist article outlines three distinct eras of AI research and concludes that none of them had any real hope of success because none mimiced the true nature of the human brain - billions of neurons, each making connections with 10,000 others, for a wiring complexity that is far beyond mere bulk transistors on a 2D spread like current microprocessors. But I wonder - with all the current research about qbits and quantum computing, where a handful of qbits could factor prime numbers of amazing complexity - perhaps the REAL source of artificial consciousness in the future won't be achieved by physical hardwiring of any complexity, but with some sort of "quantum ghost in the machine". Or maybe something even weirder - remember what Clarke said, the future is not only stranger than we imagine, it's stranger than we CAN imagine....

Then again, what's stranger than three pounds of meat reciting "twinkle, twinke little star..."?

Re:Stranger Than We Can Imagine...

[ToLu the Happy Furby]

Our problem is that we think like the humans we are.. That includes a pretty large amount of overestimation of our own abilities. The human kind of intelligence is probably *not* the only one that can exist....Let's not be too arrogant and conclude that because our first attempts of creating intelligence failed we'll never achieve it.. Maybe just rethink what intelligence actually is.

But that's precisely the problem with trying to "achieve AI"--defining what the hell "intelligence" is. For better or worse, people have traditionally defined "intelligence" roughly as "the things people can do but animals can't," or, "the things people can do but it makes our noggins hurt after a while." When put this way, the deficiencies in this definition become pretty apparent, but no one has come up with an obviously better version. Instead we usually approach the question of whether a thing is "intelligent" using the standards of the old Supreme Court decision defining obscenity--we think we know it when we see it.

Or more often, we think we know what it isn't when we see that. The history of "the quest for AI" (I put that in quotes very advisedly) is full of problems that, if solved, would surely be proof of AI...until they are solved, in which case it's still a dumb computer. Computers are now the world champions or competitive with world champions in chess, checkers, backgammon, othello, poker, bridge, and almost any game of mental skill with the significant exception of go. Computers have both proven several important and previously unproved mathematical theorems (e.g. the 4 color map coloring conjecture) and have come up with elegant and/or novel proofs for existing theorems (e.g. a computer proof of Godel's Incompleteness Theorem which "invented" Cantor's diagonalization technique on its own).

On the other hand, we have yet to make a computer which can navigate and react to its environment as well as, say, a pet dog can (sorry AIBO), nor one which can understand human language in any but the most limited domains. (Of course "understand" is a similarly difficult to define term. As an example of what I mean, look at CYC, a company which gets its name from its initial mission when it was founded IIRC back in 1984--to program a computer which understood enough concepts to understand language well enough that it could read an enCYClopedia (or any other descriptions in natural language) and learn what it didn't already know. While CYC has developed a useful system, it's still a ways from passing the encyclopedia test.)

Even though we're used to thinking of playing championship-level chess or doing advanced mathematics as hallmarks of particularly intelligent humans, while navigating an environment or understanding language is something that even the dumbest people can do, we find that computers are good at different things. (Or rather, we know how to program computers to be good at some things but not other things.)

The "problem" has been that in the early days of computers and on into the "golden age" of AI, we didn't know squat about how the human brain worked, nor even about what sorts of steps were needed in order to e.g. understand natural language. Back then, most AI researchers--brilliant people, mind you--figured all that would be necessary for a computer to understand language would be a link to a dictionary and maybe some rudimentary ability to parse grammar. Indeed, in many ways the field of linguistics arose as a result of the attempts and failures of computer scientists to get computers to understand language. Similarly, the successes and failures of AI have been instrumental in guiding or even creating the field of computational neuroscience.

What we are coming to understand is that the things that only "more intelligent" people can do are not really the hallmarks of "intelligence" but rather are examples of people fitting their brains to tasks they were not really designed for. For AI to truly "be achieved", we will have to get much better at making computers succeed at the tasks which a monkey can do just as well as a human, rather than those which humans can do but monkeys can't.

Also, we're learning that our instinctive idea of "intelligence" demands that techniques be general rather than specific. In other words, we don't consider exhaustive depth-limited minimax search with static evaluation to be a truly intelligent game playing technique--even though it can allow a computer to become the world chess champion--because it really sucks at go. The fact that go has a branching factor (i.e. avg. # of legal moves) of over 300 while chess has one of around 30 doesn't mean that similar thinking techniques (so far as we can tell) can't be used for a human to play both, but it does mean that exhaustive search is a feasible technique for a chess-playing computer but not a go-playing computer; we tend to interpret this (rightly or wrongly) as saying that exhaustive search is not an "intelligent" technique.

Next, it's time to stop tossing around that crap about how computers are so much faster or more powerful than human brains. That's complete hogwash. A modern CPU has roughly 10^6 gates, compared to ~10^11 neurons in a human brain. A computer might have 10^9 bits of memory (or even 10^10 if we go really high-end), and 10^11 bits of storage space, but a human brain has ~10^14 synapses, which can be viewed as encoding part of what the brain knows. A human brain has a remarkable 10^14 bits/sec of data bandwidth, compared to ~10^10 bps for a PC and 10^11 bps for e.g. the upcoming Alpha EV7. The only category computers lead in is cycle time, roughly 10^-9 for computers compared to ~10^-3 for the human brain. The upshot of all this is that, when it comes to computers programed as neural networks, a computer can only perform about 10^6 neuron updates/sec compared with 10^14 for a human brain, and the largest computer networks (limited by feasibility not by space) are maybe 10^5 neurons compared to 10^11 in the brain. So, roughly 100,000,000 times slower and 1,000,000,000 times smaller than a brain. (Figures based upon those in _Artificial Intelligence: A Modern Approach_, updated for the 7 years since the book was published.) No wonder computers aren't as intelligent as a human brain! And yet despite the huge disadvantage, neural nets are still the best technique for many AI problems, especially if we are worried about coming up with a technique which seems to be generally intelligent.

And finally, while it's interesting to talk about why we haven't created HAL yet, it's important not to confuse this with the idea that "the field of AI is a failure". AI is *not* a failure. While some problems have proven much harder than we initially expected, this is almost entirely because our initial expectations were completely ignorant, rather than because progress has not been made. Most importantly, we need to realize that people who are working in the field of AI are not sitting there day after day trying to create Lt. Commander Data or pass the Turing Test. Rather they're working on solutions to limited domain problems where computers can augment or replace the efforts of humans--and they're succeeding in many, many instances. The only real "problem" with the field of AI is defining what exactly it is.

Re:Software difference

[Black Parrot]

> It took a lot to take down HAL. Of course we have nothing near the AI as that, but if we did, a script kiddie could probably bring it down

Daisy, Daisy,
Click the attachment, do.
I have sent it,
For the opinion of you!

The human race. . .

[Wire Tap]

. . . is so full of diversity, and what we have come up with in the past several years has been amazing, to say the least. Science Fiction writers are generally accurate with regards to the underlying technologies that come about, but often miss the mark with the specifics, and therefore the spinoffs. I'm not saying that's bad, on the contrary, Sci Fi writers are often great inspirers of the scientists of the futute - and that's good!

Every time I read a good Sci Fi book, I am amazed by what I read, but, then, I look around, and I see things that are not even remotely considered by the writers:

Composite Materials
Polymers
VIDEO GAMES
MP3s!
Post-It-Notes

Of course, some of those things are quite frivolous (or are they?), but, that's what makes the human race so beautiful: we come up with things that are truly amazing, in their diversity and simplicity. We are an unruly and unpreditable crew of warriors, writers, diplomats, scientists, researchers, dreamers, and a myriad of other vocations - we are beautiful.

I hope we continue to pave the path of peace and progress for ever and ever.

Re:It's 2001 and AI is here but not HAL.

[Zalgon 26 McGee]

Once the VB mind becomes truly self-aware, it'll probably want to kill itself.

"I was written with WHAT????"

(+1, MS-bashing)

Missing the meaning of the book...

[mindslip]

It would seem the posts (other than the typical troll/spam) completely miss the meaning of the book. Much like one of his previous masterpieces (I think *very* highly of the philosophical teachings of Clarke), "Childhood's End", "2001: A Space Odyssey" used technology only as a subtext.

The fact that the environment of 2001 includes a world where computers are "intelligent" is only presented to illustrate the evolution not only of Humans, but as Humans-As-Gods.

The two most important scenes in the movie (which by the way are *far* more insightful in the book, as almost all book-to-movie translations are) are the following:

In the opening chapter, "The Dawn Of Man", an ape looks upon a pile of armadillo bones. This is nothing new, but the ape has something happen to him that has never happened before in the history of the Earth: The ape has an insight.
Picking up a bone, it flops in his wrist and hits some others. The ape picks it up again, and instead of it flopping by accident, he *lets* it flop in his wrist, seeing it hit the other bones and making them jump. This was a beautiful literary demonstration of the spark of intelligence happening in an otherwise "merely-sentient" being.
A few scenes later, in a triumph of the knowledge and abilities gained by discovering this new tool, and indeed, the ability to use tools at all, an ape after winning a fight for terratory hurls the weapon used (the bone) into the air. The camera pans up slowly with the rising bone, and pans back down with the falling spacecraft as it floats in space.

The beautiful imagination of Clarke and the wonderful cinematography of Kubrick, without even so much as dialogue, make a startling presentation of how from a tiny spark of insight, and a *lot* of time, Human Beings have evolved to the point where they are able to move even beyond their own world.

The final scene ("Jupiter, and Beyond the Infinite"), that of Cmdr. Dave Bowman in a white room, completes the progression of evolution as Clarke intended to explain it in his book:
Bowman, an evolved ape, a Human Being capable of venturing out beyond his own world, finds himself in the realm of his own mind, and his own existance. He observes himself, as if "out-of-body", locked in a space pod. Turning to look elsewhere, he finds himself an older man sitting eating dinner. Becoming that older man, and turning to look elsewhere, he finds himself a very old man laying in a bed. Becoming that old man and looking up from his bed, he finds the Monolith, representative of a God, or "creator-being", seeming to watch over him.

Then, from the Monoliths point of view, or perhaps it could be explained as becoming the Monolith, becoming that God-Creator-Being which Clarke seems to imply is the final destiny of Human evolution, he sees himself as an embryo, but not the embryo of a Human Being, rather, a "Starchild" as the book (and sequel movie, "2010: The Year We Make Contact") calls it.

This Starchild is the evolution of Humanity. *THIS* is what the book (much like "Childhood's End") is about: The evolution of Humanity from merely physically aware ape, to intelligent Human Being, able to take control of the world around him, to God-like Creator-Being, existing in a metaphysical sense, and evolved beyond the physical. Indeed, "Beyond the Infinite", as the chapter is called.

Clarke's startlingly insightful book, indeed his whole philosophy and dream of Humanity's potential, is not at all about technology. It's not at all about Artificial Intelligence, nor about computers becoming sentient. It's about *HUMANS* becoming sentient. It's about Human Beings evolving beyond the physical limitations of merely "in the image of Him" to a being not of body but of energy and an ability beyond our comprehension.

Much like the statement "Created in the image of God" would imply "Created with the abilities and the potential of God", much like the irrefutable knowledge that Humans pass their abilities, their weaknesses, and their potential on genetically from generation to generation, each generation becoming stronger and more knowledgeable by the rules of self-preservation (in a Darwinian and genetic sense), Clarke's stories and philosophies are about evolving further towards that which created Us, to the destiny of becoming that which can Create.

Technology (those of AI, space travel, genetic research, cloning, destruction, and healing) is merely one of the tools we have been given the insight and intelligence to develop along our evolutionary path.

mindslip.

The uses of science fiction.

[Lemmy Caution]

While an element of prophesy is part-and-parcel of science fiction, ultimately any work of literature is more about the times that it was written in rather than the times they are writing about.

A great book about the role of science fiction is Thomas Disch's "The Dreams Our Stuff is Made Of." The science fiction of the past often shapes our present by informing the imaginations of the people who created it. How many AI researchers cite HAL as an inspiration, goal, or benchmark?

With all due respect to Arthur C Clarke

[MisterBlister]

(Who was one of the more famous Amiga users, back in the day...) While Clarke has forecasted some amazing bits of technology, like the satellite, etc, I'm still more constantly amazed at the predictions made in Huxley's "Brave New World", including those of genetic engineering and cloning...

Considering Huxley wrote that novel in 1932 (the structure of DNA wasn't even found until the 1950s!), its rather amazing how accurate both the technology (in general, not the details, since when he was writing it a lot of this was far off fantasy) and the social aspects of it are compared to the current day.

Simple amazing...

Re:no HAL, no AI?

[roman_mir]

I am an atheist but I do not want my answer to be based on purely that assumption, I've being drawn into some religious battles but normally I try to stay away, it really is none of my business if someone believes in something. Atheism is in itself a system of believes, no doubts about that, of course atheists have rejected faith de facto and are trying to regain understanding of the world based on a different system of believes - so called scientific approach.

Are people just complex machines? Well, we know that no matter what else we are, we are also complex machines in some sence. We also benefit from symbiosis with other creatures (microorganisms that live inside our bodies) and we consume products that came from other organisms of this planet (I am a vegetarian, to me tomato is one of such products)
Now, let us assume that we do not know whether we just complex machines or we are some special creatures breeded by super-powerful God (or Gods, depending on your religion) So we have two cases to look at: first - we are very complex machines. If this is assumed, then it is not inconcievable that at some point in time we should be able to produce non-organic organisms that somehow imitate our own behaviour and even the train of thoughts. To duplicate our thought patterns, the creature will have to posses qualities that are shared by all living organisms on this planet (ability to see, hear, feel a touch, necessities for food or fuel) and qualities specific to human race - sex drive and necessity to socialize and some others. If we are just very complex machines, duplicating the environment for robots capable of all the above mentioned will probably drive these robots to become more like humans, will teach them to think in abstract ways, will force these robots to evolve (the merits of this evolution are questionable)

Now let's assume we are not simply complex machines, that for us in order to think in an abstract manner we need some divine intervention. In this case we still should be able to produce robots with above mentioned traits, but these robots will not amount to anything beyond social structures found in bee or ant colonies. At best in this case we could hope to produce intelligence comparable to that of a primate ape, a gorilla maybe, but even that would be a major break through. However, if it is completely and totally impossible to create intelligence comparable to human in a manner that humans can comprehend, we can still simulate it. You see, Alan Turin left specifications that allowed many to devise tests that can be used to find out whether you are communicating with a real human or with a machine. In fact, there are already today some AI programs that are capable of fooling some people and make us think that we are talking to a human rather than a machine. But the catch is that it does not really matter what or who you are talking to if you cannot tell the difference between it and an identifiable human. So, we could in principle have machines that would run simulated versions of ourself convincinly.

About us being unique - we are unique on this planet, we are the only creatures capable of handling tools and more importantly of producing a large number of different sounds that can be combined into complex speech. This is our main advantage and not something unidentifiable (if it were identifiable, we would have identified it already, otherwise it does not make any difference if it is there or not.)

Article explains success of AOL...

[alienmole]

The article quotes sociobiologist Richard Dawkins contemplating willow seeds floating through the air:

It is raining instructions out there; it's raining programs; it's raining tree-growing, fluff-spreading, algorithms. That is not a metaphor, it is the plain truth. It couldn't be any plainer if it were raining floppy discs.

Or raining, say, AOL CDs...?

The state of A.I.

[Animats]

It's a very depressing field right now. All the main ideas (mathematical logic, expert systems, neural nets, genetic algorithms, subsumption) have hit a wall. Each one will take you so far, but no farther.

Most progress has been made by hammering on specific areas as engineering problems. Symbolic integration, chess, fingerprint recognition, and speech recognition each yielded, after heavy effort. But no broadly useful approach has emerged.

Compute power isn't the problem. We don't have good algorithms that just run too slow. We really have no idea what to do next to get to strong AI.

I went through Stanford CS during the "strong AI is right around the corner" enthusiasm of the mid-1980s. Today, you can go up to the second floor of the Gates Building and see the empty cubicles, and obsolete computers below the gold letters "Knowledge Systems Lab".