Taking our scientific and technological perspective a step farther, we can then ask: What else does this lack of appreciation of software imply, and how was it manifested in the film? Kubrick and Clarke -- and indeed all but a few computer visionaries in the 1960s -- failed to understand the important and unique nature of software: that it is general purpose, infinitely malleable, and can be divorced from hardware. This lack of understanding helps explain the excessive number of control buttons we see in the film, especially in the pods. Currently, jetliners and fighter jets are equipped with numerous computer screens that display different types of information and replace mechanical buttons. One good computer screen with windows and software buttons would have sufficed for Discovery. But 2001 was made before the Macintosh computer interface was developed, so we can't blame Kubrick and Clarke for overlooking this important trend, nor for the click of the (analog) shutter of a bulky camera where software (and smaller, digital cameras) would be used today. And, as Stephen Wolfram points out, the snippets of computer code visible on HAL's screens are reminiscent of BASIC or Fortran, popular computer languages at the time the film was made. Presumably, the software written for HAL's hardware is much less intuitive (i.e., easy for humans to understand) than languages developed since then.

In short, our technical analysis of the software issues suggested by the film draws together such details as HAL's birthday, the click of a camera, and the plethora of buttons, as well as snippets of code on the screens. It's hard to imagine how a traditional cinematic or literary analysis could shed such light or deepen our understanding of the film in this way.

In fact, 2001 is suffused -- explicitly and implicitly -- with the motif of birthdays: everything from the "dawn of humanity" and the explicit date when HAL "became operational," to the birthday of Heywood Floyd's daughter "Squirt" (played by Kubrick's daughter Vivian), to Frank's birthday (complete with his parents singing "Happy Birthday" via a radio transmission delayed by the immense distances of inter-planetary space), to the final scene -- the birth of a star child. All this, of course, occurs at the birth of the millennium.

As the chapters in this book illustrate, the film ranges widely over issues that are still salient in computer science (and in space travel), and presents a rich array of "predictions" -- though Clarke prefers to consider them "visions." It is a testament to the thoroughness of its makers that the film remains as vital and moving today as when it came out. It is appropriate that we analyze these points now, at yet another birthday, the time the novel says HAL "became operational": January 12, 1997.

The overarching technical issue associated with HAL -- and the one that captures the imagination, is his artificial intelligence (AI). 2001 is, in essence, a meditation on the evolution of intelligence, from the monolith-inspired development of tools, through HAL's artificial intelligence, up to the ultimate (and deliberately mysterious) stage of the star child.

How well does Kubrick and Clarke's vision stand up to the reality of 1997? Let's state the obvious: HAL doesn't exist, and there is no chance that some miraculous change in funding or insight will yield AI at the level portrayed in HAL by the year 2001. We have learned that artificial intelligence -- a notably hazy matter we don't even have a good definition for -- is one of the most profoundly difficult problems in science -- on a par with going to the moon, identifying the fundamental constituents of matter, and unlocking the puzzle of life. But we've gone to the moon, and we seem to be on the way to understanding these other mysteries. Why don't we have AI?

Marvin Minsky (who, incidentally, nearly lost his life consulting on 2001!) argues (in chapter 2) that the field made such good progress in its early days that researchers became overconfident and moved on prematurely to more immediate or practical problems -- for example, chess and speech recognition. They left undone the central work of understanding the general computational principles -- learning, reasoning and creativity -- that underlie intelligence. Without these, he believes, we will end up with a growing collection of dumb experts and will never achieve AI.

Stephen Wolfram (in chapter 15) agrees that we have overlooked deep principles but thinks the missing pieces lie in the domain of complex systems -- a field he helped launch -- where simple elements can interact to produce unexpectedly complex behavior. Just as the simple laws of physics applied to simple water molecules can give rise to the wonderfully complex vortex flow of a stream around a rock, so the relatively simple rules governing nerve cells (neurons) may lead to a complex cognitive system. His insight, though, is that we shouldn't be thinking so much in terms of mathematics (i.e., equations) as, instead, algorithms (i.e., computer programs).

Ray Kurzweil (chapter 7), on the other hand, says that we already know how to achieve AI -- just reverse engineer a brain! In a few decades, he suggests, we may be able to scan an entire human brain, down to the level of nerve cells and their interconnections. We need then merely (!) encode all that information into a computer to make a virtual brain every bit as intelligent as a human brain that is its model.

However, for Doug Lenat (chapter 9), there is no silver bullet for achieving AI. We first need to encode an enormous amount of common-sense knowledge into a computer through a laborious process of hand entering information gleaned from a wide range of sources -- such as encyclopedias. With such a "primed knowledge pump," a computer might be able to learn more by reading books and interacting with its environment, scientists and other experts, and, perhaps, other developing computers. That, at least, is the theory. Daniel Dennett (in chapter 16) stresses the need for a computer to explore the world, and learn from its interactions.