Machines of Loving Grace (20 page)

Kaplan rapidly became a “biz-dev” guy.
It was in the air.
He had an evening consulting gig developing the software for what would become Synergy, the first all-digital music keyboard synthesizer.
It was chock-full of features that have become standard on modern synthesizers, and was used to produce the soundtrack for the movie
Tron
.
Like everyone at Stanford, he was making money on the side.
They were all starting companies.
There was a guy in the basement, Leonard Bosack, who was trying to figure out how to interconnect computers and would eventually found Cisco Systems with his wife, Sandy Lerner, to make the first network routers.

Kaplan had a research associate job at Stanford, which was great.
It was equivalent to a non–tenure track teaching position, but without the pain of having to teach.
There was, however, a downside.
Research staff were second-class citizens to academic faculty.
He was treated like the hired help, even though he could write code and do serious technical work.
His role was like Scotty, the reliable engineer on the starship
Enterprise
in
Star Trek
.
He was the person who made things work.
Fueled in part by the Reagan-era Strategic Defense Initiative, vast new investments were being made in artificial intelligence.
It was military-led spending, but it wasn’t entirely about military applications.
Corporate America was toying with the idea of expert systems.
Ultimately the boom would lead to forty start-up companies and U.S.
sales of AI-related hardware and software of $425 million in 1986.
As an academic, Kaplan lasted just two years at Stanford.
He received two offers to join start-ups at the same time, both in the AI world.
Ed Feigenbaum, who had decided that the Stanford computer scientists
should get paid for what they were already doing academically, was assembling one of the start-ups, Teknowledge.
The new company would rapidly become the Cadillac of expert system consulting, also developing custom products.
The other start-up was called Symantec.
Decades later it would become a giant computer security firm, but at the outset Symantec began with an AI database program that overlapped with Kaplan’s technical expertise.

It was a time when Kaplan seemed to have an unlimited capacity to work.
He wasn’t a big partier, he didn’t like being interrupted, and he viewed holidays as a time to get even more accomplished.
Gary Hendrix, a respected natural language researcher at SRI, approached him to help with the programming of an early demo version of a program called Q&A, the first natural language database.
The idea was that unskilled users would be able to retrieve information by posing queries in normal sentences.
There was no money, only a promise of stock if the project took off.

Kaplan’s expertise was on natural language front ends that would allow typed questions to an expert system.
What Hendrix needed, however, was a simple database back end for his demonstration.
And so over a Christmas holiday at the end of 1980, Kaplan sat down and programmed one.
The entire thing initially ran on an Apple II.
He did it on a contingent basis and in fact he didn’t get rich.
The first Symantec never went anywhere commercially and the venture capitalists did a “cram down,” a financial maneuver in which company founders often see their equity lose value in exchange for new investments.
As a result, what little stock Kaplan owned was now worthless.

In the end he left Stanford and joined Teknowledge because he admired Lee Hecht, the University of Chicago physicist and business school professor who had been brought in to be CEO and provide adult supervision for the twenty Stanford AI refugees who were the Teknowledge shock troops.
“Our founders have build [
sic
] more expert systems than anyone else,” Hecht
told
Popular Science
in 1982.
⁴⁰
Teknowledge set up shop at the foot of University Ave., just off the Stanford campus, but soon moved to flashier quarters farther down the street in the one high-rise in downtown Palo Alto.
In the early 1980s the office had a sleek modernist style that leaned heavily toward black.

The state-of-the-art office offered a clear indication that the new AI programs wouldn’t be cheap.
Just one rule for one of the expert systems would require an interviewer to spend an hour with a human expert, and a working expert system would consist of five hundred rules or more.
A complete system might cost as much as $4 million to build, but Hecht, like Breiner, believed that by bottling human expertise, corporations could reap vast savings over time.
A complete system might save a manufacturer as much as $100 million annually, he told the magazine.
An oil company expert system that they were prototyping might save as much as $1,000 per well per day, Hecht claimed.
In the article Feigenbaum also asserted that the bottleneck would be broken when computers themselves began automatically interviewing experts.
⁴¹
Hecht saw more than a hacker in Kaplan and made him a promise—if he came to Teknowledge he would teach him how to run a business.
He jumped at the chance.
His office was adjacent to Hecht’s and he set out to build a next-generation consulting firm whose mission was to replace the labor of human experts with software.

However, in the beginning Kaplan knew nothing about the art of selling high-technology services.
He was put in charge of marketing and the first thing he did was prepare a brochure describing the firm’s services.
From an entirely academic background he put together a trifold marketing flyer that was intended to attract corporate customers to a series of seminars on how to build an expert system featuring Feigenbaum as the star speaker.
He sent out five thousand brochures.
You were supposed to get a 2 percent response rate.
Instead of a hundred responses, they got just three, and one was from a
guy who thought they were teaching about artificial insemination.
It was a rude shock for a group of AI researchers, confident that they were about to change the world overnight, that outside of the university nobody had heard of artificial intelligence.
Eventually, they were able to pull together a small group of mostly large and defense-oriented corporations, making it possible for Hecht to say that there had “been inquiries from more than 50 major companies from all over the world,” and Teknowledge was able to do $1 million in business in two months at the beginning of 1982.
⁴²

It was indeed a Cadillac operation.
They wrote the programs in Lisp on fancy $20,000 Xerox Star workstations.
Worse, the whole operation was buttressed by just a handful of marketers led by Kaplan.
The Teknowledge worldview was, “We’re smart, we’re great, people should just give us money.”
It was completely backward, and besides, the technology didn’t really work.
Despite the early stumbles, however, they eventually attracted attention.
One day the king of Sweden even came to visit.
True to protocol his arrival had all the trappings of a regal entourage.
The Secret Service showed up first to inspect the office, including the bathroom.
The assembled advance team appeared to be tracking the king in real time as they waited.
Kaplan was standing breathlessly at the door when a small, nondescript gentleman in standard Silicon Valley attire—business casual—walked in unaccompanied and innocently said to the young Teknowledge executive, “Where should I sit?”
Flustered, Kaplan responded, “Well, this is a really bad time because we’re waiting for the king of Sweden at the moment.”
The king interrupted him.
“I am the king of Sweden.”
The king turned out to be perfectly tech savvy: he had a deep understanding of what they were trying to do, more so than most of their prospective customers—which, of course, was at the heart of the challenge that they faced.

There was, however, one distinct upside for Kaplan.
He was invited to an evening reception for the king held at the Bohemian
Club in San Francisco.
He arrived and fell into conversation with a beautiful Swedish woman.
They spoke for almost an hour and Kaplan thought that maybe she was the queen.
As it turned out, she was a stewardess who worked for the Swedish airline that flew the royal entourage to the United States.
The joke cut both ways, because she thought he was Steve Jobs.
There was a happy ending.
They would date for the next eight years.

Teknowledge wasn’t so lucky.
The company had a good dose of “The Smartest Guys in the Room” syndrome.
With a who’s who of some of the best engineers in AI, they had captured the magic of the new field and for what might otherwise pass for exorbitant consulting fees they would impart their alchemy.
However, artificial intelligence systems at the time were little more than accretions of if-then-else statements packaged in overpriced workstations and presented with what were then unusually large computer displays with alluring graphical interfaces.
In truth, they were more smoke and mirrors than canned expertise.

It was Kaplan himself who would become something of a Trojan horse within the company.
In 1981 the IBM PC had legitimized personal computers and dramatically reduced their cost while expanding the popular reach of computing.
Doug Engelbart and Alan Kay’s intelligence augmentation—IA—meme was showing up everywhere.
Computing could be used to extend or replace people, and the falling cost made it possible for software designers to take either path.
Computing was now sneaking out from behind the carefully maintained glass wall of the corporate data center and showing up in the corporate office supplies budget.

Kaplan was quick to grasp the implications of the changes.
Larry Tesler, a former SAIL researcher who would work for Steve Jobs in designing the Lisa and the Macintosh and help engineer the Newton for John Sculley, had the same early epiphany.
He had tried to warn his coworkers at Xerox PARC
that cheap PCs were going to change the world, but at the time—1975—no one was listening.
Six years later, many people still didn’t comprehend the impact of the falling cost of the microprocessor.
Teknowledge’s expert system software was then designed and deployed on an overpriced workstation, which cost about $17,000, and a complete installation might run between $50,000 and $100,000.
But Kaplan realized that PCs were already powerful enough to run the high-priced Teknowledge software handily.
Of course, the business implication was that without their flashy workstation trappings, they would be seen for what they really were—software packages that should sell for PC software prices.

Nobody at Teknowledge wanted to hear this particular heresy.
So Kaplan did what he had done a few years earlier when he had briefly helped found Symantec in his spare time at Stanford.
It was Christmas, and everyone else was on vacation, so he holed up in his cottage in the hills behind Stanford and went to work rewriting the Teknowledge software to run on a PC.
Kaplan used a copy of Turbo Pascal, a lightning-fast programming language that made his version of the expert system interpreter run faster than the original workstation product.
He finished the program over the holidays and came in and demoed the Wine Advisor, the Teknowledge demonstration program, on his “toy” personal computer.
It just killed the official software running on the Xerox Star workstation.

All hell broke loose.
Not only did it break the Teknowledge business model because software for personal computers was comparatively dirt cheap, but it violated their very sense of their place in the universe!
Everyone hated him.
Nonetheless, Kaplan managed to persuade Lee Hecht to commit to putting out a product based on the PC technology.
But it was crazy.
It meant selling a product for $80 rather than $80,000.
Kaplan had become the apostate and he knew he was heading for the door.
Ann Winblad, who was then working as a Wall Street technology analyst and would later become a well-known Silicon
Valley venture capitalist, came by and Kaplan pitched her on the changing state of the computing world.

“I know someone you need to meet,” she told him.

That someone turned out to be Mitch Kapor, the founder and chief executive of Lotus Development Corporation, the publisher of the 1-2-3 spreadsheet program.
Kapor came by and Kaplan pitched him on his AI-for-the masses vision.
The Lotus founder was enthusiastic about the idea: “I’ve got money, why don’t you propose a product you want to build for me,” he said.

Kaplan’s first idea was to invent an inexpensive version of the Teknowledge expert system to be called ABC, as a play on 1-2-3.
The idea attracted little enthusiasm.
Not long afterward, however, he was flying on Kapor’s private jet.
The Lotus founder sat down with paper notes and a bulky Compaq computer the size of a sewing machine and began typing.
That gave Kaplan a new idea.
He proposed a free-form note-taking program that would act as a calendar and a repository for all the odds and ends of daily life.
Kapor loved the idea and with Ed Belove, another Lotus software designer, the three men outlined a set of ideas for the program.