Thinking man's language

On the horizon, programming languages face the daunting challenge of helping to turn the Internet into a more intelligent place. A year ago, Tim Berners-Lee, the inventor of the World Wide Web, published a manifesto for a semantic web. His vision is that computers should be able to recognise the meaning of information on the web by its context, and provide users with much more relevant information than web browsers now do.

There are many ways that this could happen. Certainly, some of the semantic information can lie in the data itself. XML helps to do this. And a standard known as RDF (resource description framework) defines how to encode some semantic meaning intoXML—for instance, whether one object (say, a person) has a relationship (eg, owns) with another (say, a car). Helpful as RDFand related standards will be in building a web endowed with more meaning, some kind of artificial intelligence programs will be needed to understand context as humans do.

Although such programs can no doubt be constructed in Java or C^#, these languages were not designed for such purposes. Herein lies an opportunity for languages designed with artificial intelligence specifically in mind. Such languages have existed for decades. The so-called functional language Lisp computes with symbolic expressions rather than numbers; the logical language Prolog works by making logical statements about objects.

Lisp and Prolog still have a loyal following in research circles, but their impact elsewhere has been modest. Languages such as Java have proved to be the fittest, in a Darwinian sense, because the Internet dictated that the big programming challenge was not one of artificial intelligence, but one of data manipulation, visualisation and communication between programs. As in Darwin's theory, the definition of what is fittest depends on the environment, which is constantly changing. Even though Lisp and Prolog may not be the shape of things to come, a programming language that incorporates concepts from artificial intelligence will no doubt appear when the time is ripe—and leave the likes of Java and C^# by the wayside.

How fast could all this happen? Although the. NET platform required a massive effort on the part of Microsoft, the language C^# was developed by a team of four researchers in a mere two years, with a similar-sized effort producing the compiler. It is thus within the realms of a small start-up's aspirations to develop the Java language for the next generation of the web, and to rely on open-source methods to generate the necessary environment. As the clash between C^# and Java shows, there is a huge amount at stake in setting the trend for programming languages. Expect a whole alphabet soup of new languages within the next decade.

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