When Will HAL Understand What We Are Saying? Computer Speech Recognition and Understanding, Section 13

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Moore's law states that computing speeds and densities double every eighteen months; it is the driving force behind a revolution so vast that the entire computer revolution to date represents only a minor ripple of its ultimate implications. It was first articulated in the mid-1960s by Dr. Gordon Moore. Moore's law actually is a corollary of a broader law I like to call Kurzweil's law, which concerns the exponentially quickening pace of technology back to the dawn of human history. A thousand years ago, not much happened in a century, technologically speaking. In the nineteenth century, quite a bit happened. Now major technological transformations occur in a few years time. Moore's law, a clear quantification of this exponential phenomenon, indicates that the pace will continue to accelerate.

Remarkably, this law has held true since the beginning of this century. It began with the mechanical card-based computing technology used in the 1890 census, moved to the relay-based computers of the 1940s, to the vacuum tube-based computers of the 1950s, to the transistor-based machines of the 1960s, and to all the generations of integrated circuits we've seen over the past three decades. If you chart the abilities of every calculator and computer developed in the past hundred years logarithmically, you get an essentially straight line. Computer memory, for example, is about sixteen thousand times more powerful today for the same unit cost than it was in about 1976 and is a hundred and fifty million times more powerful for the same unit cost than it was in 1948.

Moore's law will continue to operate unabated for many decades to come; we have not even begun to explore the third dimension in chip design. Today's chips are flat, whereas our brain is organized in three dimensions. We live in a three-dimensional world, why not use the third dimension? (Present-day chips are made up of a dozen or more layers of material that construct a single layer of transistors and other integrated components. A few chips do utilize more than one layer of components but make only limited use of the third dimension.) Improvements in semiconductor materials, including superconducting circuits that don't generate heat, will enable us to develop chips -- that is, cubes -- with thousands of layers of circuitry that, combined with far smaller component geometries, will improve computing power by a factor of many millions. There are more than enough new computing technologies under development to assure us of a continuation of Moore's law for a very long time. So, although some people argue that we are reaching the limits of Moore's law, I disagree. (See David Kuck's detailed analysis in chapter 3.)

Moore's law provides us with the infrastructure -- in terms of memory, computation, and communication technology -- to embody all our knowledge and methodologies and harness them on inexpensive platforms. It already enables us to live in a world where all our knowledge, all our creations, all our insights, all our ideas, and all our cultural expressions -- pictures, movies, art, sound, music, books and the secret of life itself -- are being digitized, captured, and understood in sequences of ones and zeroes. As we gather and codify more and more knowledge about the hierarchy of spoken language from speech sounds to subject matter, Moore's law will provide computing platforms able to embody that knowledge. At the front end, it will let us analyze a greater number of frequency bands, ultimately approaching the exquisite sensitivity of the human auditory sense to frequency. At the back end, it will allow us to take advantage of vast linguistic data bases.

Like many computer-science problems, recognizing human speech suffers from a number of potential combinatorial explosions. As we increase vocabulary size in a continuous-speech system, for example, the number and length of possible word combinations increases geometrically. So making linear progress in performance requires us to make exponential progress in our computing platforms. But that is exactly what we are doing.