by John Markoff
It was a major step in bringing the Engelbart-Nelson hypertext vision to life. Overnight, anyone who was running a list server on a Unix computer could drop the program on their computer and their electronic conversations would be instantly available to the broader Internet. It was a powerful lesson for Gruber about how the Internet could be used to leverage a simple idea. EIT was purchased by VeriFone early in 1995, just at the outset of the dot-com era. Two years later VeriFone, known for its point-of-sale terminals, was itself purchased by HP during the run-up of the first Internet bubble, only to be cast out again after the bubble burst. Gruber had left Stanford to join EIT in 1994 but left before EIT was sold the first time to pursue his own ideas. Why stop with email, he wondered? He set out to build on a large chunk of Engelbart’s vision and sell it to corporate America.
In the early 1990s, Engelbart’s ideas enjoyed a renaissance at Stanford. The four years Gruber had spent at the university trying to create Feigenbaum’s engineering knowledge system from piles of statements of rules and assertions and ontologies hadn’t succeeded. In his Hypermail project, Gruber saw a way to build a valuable commercial knowledge system and, in the entrepreneurial heat of the dot-com explosion, set out to create his own company to do so. Berners-Lee had made the original breakthrough when he designed the World Wide Web. It was not just that he had created a working version of the Engelbart-Nelson hypertext system. He had established a system of permanent identifiers for bundles of information that the engineers described as “knowledge objects.” That changed everything. It allowed Web developers to create persistent knowledge structures that functioned as usable digital libraries, upon which it was possible to build both artificial intelligence and augmentation systems.
Gruber’s idea was to build a “corporate memory,” a system that would weave together all the documents that made a modern organization function, making them easy to structure and recall. It was reminiscent of Engelbart’s original oN-Line System, but was modernized to take advantage of the power of Berner-Lee’s invention. Lotus Notes had been an earlier effort by Ray Ozzie, then a young software designer working on a contract basis for Mitch Kapor at Lotus, but it was stuck in the proprietary world of corporate enterprise software. Now the Internet and new Web standards made it possible to build something with far greater scope.
With another AI researcher, Peter Friedland, and former DARPA program manager Craig Wier, Gruber founded Intraspect in 1996 in Los Altos and became the chief technology officer. In the beginning he worked with one programmer, who had a day job at Stanford. The programmer arrived in the evening after Gruber had worked on the prototype during the day and took over and continued development into the night. As Gruber was leaving at the end of the day, he discussed what he had done and what needed to be completed. They would iterate—it was an effective way to rapidly build a prototype.
The company eventually raised more than $60 million in venture funding and would have as many as 220 employees and a polished product. They were able to quickly build a base of blue-chip companies as well, including GTE, General Motors, KPMG, Boeing, and Siemens. The PC era had transformed the corporation and companies were being run with electronic mail rather than with printed interoffice memos. This shift made it possible to create an inexpensive system that simply “swallowed” every communication that was CC’ed to a special email address. No webmaster or heavy IT presence was necessary. The Intraspect system ingested corporate communications and documents and made them instantly accessible to anyone in a company with access to a personal computer. Desktop folder icons were still the common metaphor for organized documents, and so the Intraspect engineers built a Windows program based on a folder-oriented interface.
In Gruber’s mind this was what the future of AI should be. What had started as an effort to model a human brain would shift in focus and end up as an endeavor to model the interactions of a human group. In a sense, this distinction was at the heart of the cultural divide between the two research communities. The AI community began by trying to model isolated human intelligence while the emerging community of human-computer interaction designers followed in Engelbart’s augmentation tradition. He had begun by designing a computer system that enhanced the capabilities of small groups of people who collaborated. Now Gruber had firmly aligned himself with the IA community. At the Stanford Knowledge Systems Laboratory, he had interviewed avionics designers and took their insights to heart. There had been an entire era of industrial design during which designers assumed that people would adapt to the machine. Designers originally believed that the machine was the center of the universe and the people who used the machines were peripheral actors. Aircraft designers had learned the hard way that until they considered the human-machine interaction as a single system, they built control systems that led to aircraft crashes. It simply wasn’t possible to account for all accidents by blaming pilot error. Aircraft cockpit design changed, however, when designers realized that the pilot was part of the system. Variables like attention span and cognitive load, which had been pioneered and popularized by psychologists, became an integral part first in avionics and, more recently, computer system design.
Gruber thought hard about these issues while he designed the Intraspect query system. He imagined customers, often corporate salespeople, as aircraft pilots and tried to shape the program to avoid deluging them with information. Intraspect demonstrated the system to a J.P. Morgan executive. Gruber performed a simple search and the executive saw relevant recent communications between key employees at the firm with relevant documents attached. His jaw dropped. He could literally see what his company knew. The Intraspect system used a search engine that was engineered to prioritize both the most recent and most relevant documents, which was something that was not yet widely offered by the first generation of Internet search engines.
At the peak of the dot-com era, Intraspect was doing spectacularly well. They had blue-chip customers and footholds in major industries like financial services and a run rate of $30 to $40 million in revenue. They had even written an S-1 in preparation for going public and had moved into a large new building and a prominent logo that was visible from the 101 freeway. Then everything collapsed. Although Intraspect survived the dot-com crash, the meltdown crippled some of its best customers.
September 11, 2001, followed. Overnight, everything changed. By the following March, CFOs at major companies were simply prohibiting the purchase of any product or service that wasn’t from a public company. The wave of fear nailed Intraspect. Gruber had spent six years building the company and at first he refused to believe that it was over. They had such strong customers and such a versatile product that they were convinced there must be a way to survive. But the company had been riding on its ability to leverage professional service firms like the Big Five accounting companies to sell its product, and those sales channels dried up during the crash.
Gruber was forced to lay off 60 percent of his company to stay afloat. In the end, Intraspect died with a whimper. Although it had advantages over its competitors, the entire market for collaborative corporate software collapsed. Portal companies, document management companies, search companies, and knowledge management companies all merged into one another. In 2003 Intraspect was sold for a fire sale price to Vignette and that was the end.
Gruber stayed at Vignette for a couple of months and then took a year off to recharge and think about what he would do next. He traveled to Thailand, where he went scuba diving and took pictures. He discovered Burning Man, the annual weeklong gathering in the Nevada desert that attracted tens of thousands of the Valley’s digerati. When Gruber’s sabbatical year ended he was ready to build a new company.
He knew Reid Hoffman, who had by then started LinkedIn, the business networking company. Because of his experience at Intraspect, Gruber had good insights into “social software.” The two men had a long series of conversations about Gruber joining the start-up, which was on track to become one of Silicon Valley’s early
social networking success stories. Gruber wanted to focus on design issues and Hoffman was looking for a new CTO, but in the end the LinkedIn board vetoed the idea because the company was on the verge of a large investment round.
Gruber’s year of traveling had left him thinking about the intersection of travel and “collective intelligence” that was coming to life with emergence of “Web 2.0.” The Internet had not only made it possible to create corporate memories, but now crowdsourcing had become trivial for any human endeavor. Google, of course, was the most spectacular example. The company’s PageRank search algorithm exploited human preferences to rank Internet search query results. Through Reid Hoffman, Gruber found a start-up that was planning to compete with TripAdvisor, which at that point was only offering travelers’ reviews of hotels. He convinced them that he could bring them a big audience—they just needed to handle the business development side of the project. And so Gruber started over as the vice president of design at this new start-up, although this time he had a team of three engineers instead of sixty. Having a small army of programmers, however, was no longer critical to the success of a company—the Internet had changed everything. Even the smallest start-ups could leverage vastly more powerful development toolkits.
The start-up planned to collect the best trip descriptions that global travelers had to offer. It took them a year to build the service and they unveiled realtravel.com at the 2006 O’Reilly Web 2.0 Conference—an Internet event that had rapidly become the conference of choice for the next wave of so-called social start-ups. Realtravel.com grew fast—it even boasted a couple million unique visitors at one point—but it didn’t grow quickly enough, and the company was sold in 2008, just two years after receiving its seed funding. Gruber had left the company before it was sold, having feuded with the CEO—who was color-blind—over issues like what were the best colors on the site’s Web pages.
He took another year off. He had worked in various positions at realtravel.com—from writing code to overseeing design—and he needed the time away. When he returned, he used his Silicon Valley network of contacts to look for interesting projects. He was a member of an informal group called the CTO Club, which met regularly, and someone there mentioned a new project at SRI.
The research center had been showered with funding by DARPA under Tony Tether, who had taken a deep interest in building a software personal assistant. For five years, between 2003 and 2008, the Pentagon agency invested heavily in the idea of a “cognitive assistant.” The project would ultimately bring together more than three hundred researchers at twenty-five universities and corporate research laboratories, with SRI playing the role of the integrator for the project. The cognitive assistant, CALO, was in DARPA’s tradition of funding blue-sky research that had already created entire industries in Silicon Valley. Workstations, networking, and personal computing had all started as DARPA research projects.
The term “CALO” was inspired by calonis, a Latin word meaning “soldier’s low servant,” or clumsy drudge, but the project also had a significant overlap with Engelbart’s original work that was funded by DARPA in the sixties and seventies. CALO was intended to help an office worker with project management: it would organize workers’ email, calendars, documents, communication, schedules, and task management. Eventually, there were a number of commercial spin-offs from the CALO project—a smart calendar, a personalized travel guide, and a game development and education company—but they all paled compared to the success of Siri.
Long before the Maker Movement—the Silicon Valley subculture extolling an inclusive do-it-yourself approach to technology—gained steam, Gruber’s Siri cofounder Adam Cheyer was drafted into that world by his mother. As a child in a Boston suburb, he was restricted to just an hour of television each week, which offered him a brief glimpse of technology that whet his appetite for the latest toys. When he asked his mother to buy toys for him, however, she responded by giving him a stack of cardboard inserts that cleaners used to stiffen shirts. He resorted to tape, glue, and scissors to re-create the toys that he had seen on television, like robots and Rube Goldberg contraptions. It taught Cheyer that with a small dose of imagination, he could make anything he wanted.2
As a child he dreamed of becoming a magician. He had read books about the great magicians and thought of them as inventors and tinkerers who tricked others by using technology. Before he was ten he was saving his money to buy books and tricks from the local magic store. Later, he realized that his interest in artificial intelligence was rooted in his love of magic. His favorite eighteenth-century magicians and clockmakers led by Jacques de Vaucanson had built early automata: chess-playing and speaking machines and other mechanical humanoid robots that attempted to illuminate the inner workings of what he, like Gruber, would come to see as the most magical device of all—the human brain.3
Although Cheyer knew nothing of Engelbart’s legendary NLS, in 1987 he built his own system called HyperDoc while working as an artificial intelligence researcher with Bull, the aerospace firm, in France. He integrated a documentation system into the editor the programmers were using to design their expert systems. That update made it possible to simply click on any function or command to view a related online manual. Having easy access to the software documentation made it simpler for developers to program the computers and reduce the number of bugs. At the time, however, he was unfamiliar with the history of Doug Engelbart’s Augmentation Research Center in Menlo Park during the 1960s and 1970s. He had moved to California to get a master’s degree in computer science, with a plan to move back to France after graduation. It had been a fun sojourn in California, but the French computer firm would pay for his schooling only if he returned to Europe.
Not long before he was scheduled to return, however, he stumbled across a small blurb advertising a job in an artificial intelligence research laboratory at SRI. The job sounded intriguing and he decided to apply. Before flying to the Bay Area for the interview, he read extensively on the work of all of the researchers in the group. Between interviews he went into the bathroom to scan his notes in preparation for each appointment. When he arrived, he knew everything that everyone had worked on, who they worked with, and what their views were on different issues. His research paid off. He was hired in the SRI Artificial Intelligence Center.
In the early 1990s, despite the AI Winter, SRI remained a thriving hub for commercial, military, and academic artificial intelligence research, and decades after Shakey, robots were still roaming the halls. When Cheyer arrived at the laboratory, he received a small research grant from a Korean telecom lab run by the South Korean government. The project funding was for a pen and voice control system for the office environment. “Build us one of those,” they instructed him.
He decided to build a system that would make it easy to plug in additional capabilities in the future. The system was named Open Agent Architecture, or OAA. It was designed to facilitate what Cheyer thought of as “delegated computing.” For example, if a computer needed to answer a question like, “What’s Bob’s email address?” there was a range of ways that it could hunt for the answer. Cheyer created a language that would make it possible for a virtual software assistant to interpret the task and hunt for the answer efficiently.
In designing his framework, he found that he was at the heart of a debate that was raging between artificial intelligence researchers and the rival human-computer interaction community. One group believed the user needed to be in complete control of the computer and the other group envisioned software agents that could “live” in computer networks and operate on behalf of human users. From the beginning Cheyer had a nuanced view of the ideal human-machine relationship. He thought that humans sometimes like to control systems directly, but often they just want the system to do something on their behalf without bothering them with the details. To that end, his language made it possible to separate what the user wanted the system to do or find from how the task would be accomplished.
Within a
year of arriving at SRI, Cheyer was focused on the challenge of actually building a working version of the Knowledge Navigator software avatar that John Sculley had extolled in a futuristic video in 1987. Like Alan Kay, who started out by building “interim” Dynabooks, during the next two decades Cheyer repeatedly developed prototypes, each of which more closely approximated the capabilities of the Knowledge Navigator. He was building software virtual robots, software assistants that were intended to act as much as partners as slaves.
By the end of 1993 he had designed a tablet PC resembling an iPad. No one had developed a touch interface yet and so Cheyer had integrated pen input into his tablet, which allowed it to recognize both handwriting and user gestures, like drawing circles around certain objects to select them. It also had the ability to recognize speech, largely because Cheyer had become adept at the technology equivalent of borrowing a cup of sugar from his neighbors down the hall. He had persuaded the researchers at SRI’s Speech Technology and Research Laboratory to install a software connector—known as an API—for his tablet. That allowed him to plug the mainframe-based speech recognition system into his system. SRI’s speech technology—which was a research activity that had started with Shakey—would be spun out the next year as a separate start-up, Nuance Communications, which initially pioneered voice applications for call centers. He did the same with SRI handwriting recognition technologies. He built a demonstration system that used voice and pen input to approximate a software secretary. It automated calendar tasks and handled email, contact lists, and databases, and he started experimenting with virtual assistance tasks, like using maps to find restaurants and movie theaters.