Good News Bad News How to Win Big
How to Win Big
How to Win Big
Richard P. Gabriel
The Lisp world is in great shape: Ten years ago there was no standard Lisp; the most standard Lisp was InterLisp, which ran on PDP-10's and Xerox Lisp machines (some said it ran on Vaxes, but I think they exaggerated); the second most standard Lisp was MacLisp, which ran only on PDP-10's, but under the three most popular operating systems for that machine; the third most standard Lisp was Portable Standard Lisp, which ran on many machines, but very few people wanted to use it; the fourth most standard Lisp was Zetalisp, which ran on two varieties of Lisp machine; and the fifth most standard Lisp was Scheme, which ran on a few different kinds of machine, but very few people wanted to use it. By today's standards, each of these had poor or just barely acceptable performance, nonexistent or just barely satisfactory environments, nonexistent or poor integration with other languages and software, poor portability, poor acceptance, and poor commercial prospects.
Today there is Common Lisp (CL), which runs on all major machines, all major operating systems, and virtually in every country. Common Lisp is about to be standardized by ANSI, has good performance, is surrounded with good environments, and has good integration with other languages and software.
But, as a business, Lisp is considered to be in ill health. There are persistent-and sometimes true-rumors about the abandonment of Lisp as a vehicle for delivery of practical applications.
To some extent the problem is one of perception-there are simply better Lisp delivery solutions than are generally believed to exist-and to a disturbing extent the problem is one of unplaced or misplaced resources, of projects not undertaken, and of implementation strategies not activated.
Part of the problem stems from our very dear friends in the artificial intelligence (AI) business. AI has a number of good approaches to formalizing human knowledge and problem solving behavior. However, AI does not provide a panacea in any area of its applicability. Some early promoters of AI to the commercial world raised expectation levels too high. These expectations had to do with the effectiveness and deliverability of expert-system-based applications.
When these expectations were not met, some looked for scapegoats, which frequently were the Lisp companies, particularly when it came to deliverability. Of course, if the AI companies had any notion about what the market would eventually expect from delivered AI software, they never shared it with any Lisp companies I know about. I believe the attitude of the AI companies was that the Lisp companies will do what they need to survive, so why share customer lists and information with them?
Another part of the problem is the relatively bad press Lisp got, sometimes from very respectable publications. I saw an article in Forbes (October 16, 1989) entitled ``Where Lisp Slipped'' by Julie Pitta. However, the article was about Symbolics and its fortunes. The largest criticisms of Symbolics in the article are that Symbolics believed AI would take off and that Symbolics mistakenly pushed its view that proprietary hardware was the way to go for AI. There was nothing about Lisp in the article except the statement that it is a ``somewhat obscure programming language used extensively in artificial intelligence.''
It seems a pity for the Lisp business to take a bump partly because Julie thought she could make a cute title for her article out of the name ``Lisp''.
But, there are some real successes for Lisp, some problems, and some ways out of those problems.