Final Jeopardy (3 page)

Physical strength has suffered a similar downgrade. Not so long ago, a man with superhuman strength played a valuable role in society. He was a formidable soldier. When villagers needed boulders moved or metal bent, he got the call. After the invention of steam engines and hydraulic pumps, however, archetypal strongmen were shunted to jobs outside the productive economy. They turned to bending metal in circuses or playing noseguard on Sunday afternoons. For many of us, physical strength, once so vital, has become little more than a fashion statement. Modern males now display muscles as mating attire, much the way peacocks fan their otherwise useless feathers.

It would be all too easy to dismiss human foes of the IBM machine as cognitive versions of circus strongmen: trivia wunderkinds. But from the very beginning, Ferrucci saw that the game required far more than the simple regurgitation of facts. It involved strategy, decision making, pattern recognition, and a knack for nuance in the language of the clues. As the computer grew from a whimsical idea into a
Jeopardy
behemoth, it underwent an entire education, triumphing in some areas, floundering in others. Its struggles, whether in untangling language or grappling with abstract ideas, highlighted the areas in which humans maintain an edge. It is in the story of Watson's development that we catch a glimpse of the future of human as well as machine intelligence.

The secret is wrapped up in the nature of knowledge itself. What is it? For humans, knowledge is an entire universe, a welter of sensations and memories, desires, facts, skills, songs and images, words, hopes, fears, and regrets, not to mention love. But for those hoping to build intelligent machines, it has to be simpler. Broadly speaking, it falls into three categories: sensory input, ideas, and symbols. Consider the color blue. Sensory perception is the raw material of knowledge. It's something that computers and people alike can perceive, each in their own fashion. Now think of the word “sky.” Those three letters are a symbol for the biggest piece of blue in our world. Computers can handle such symbols. They can find references to “sky” in documents and, when programmed, correlate it with others, such as “blue,” “clouds,” and “heaven.” A computer can master both sensory data and symbols. It can count, categorize, search, and store them. But how about this snippet from Lord Byron: “Friendship is love without his wings.” That sentence represents the third realm of knowledge: ideas. How can a machine make sense of them? In these early years of the twenty-first century, ideas remain the dominion of people—and the frontier for thinking machines.

David Ferrucci's mission was to explore that frontier. Like many in his profession, Ferrucci grew up watching
Star Trek
on television. The characters on the show, humans and pointy-eared Vulcans alike, spoke to their computer as if it were one of them. No formatting was necessary, no key words, no programming language. They spoke English. The computer understood the meaning and context of the questions. It consulted vast databases and came back with an immediate answer. True, it might not produce original ideas. But it was an extravagantly well-informed shipmate. That was the computer Ferrucci wanted to build.

As he served the last drops of his wine, Ferrucci was talking about the world he was busy creating, one in which people and their machines often appeared to switch roles. He didn't know, he said, whether engineers would ever be able to “create a sentient being.” But when he looked at his fellow humans through the eyes of a computer scientist, he saw patterns of behaviors that often appeared to be programmed. He mentioned the zombielike commutes, the retreat to the same chair, the hand reaching for the TV remote, and the near-identical routines, from toothbrushing to feeding the animals. “It's more interesting,” he said, “when humans delve inside themselves and say, ‘Why am I doing this? And why is it relevant and important to be human?'” His machine would nudge people toward that line of inquiry. Even with an avatar for a face and a robotic voice, the
Jeopardy
machine would invite comparisons to the other two contestants on the stage. This was inevitable. And whether it won or lost on a winter evening in 2011, the computer might lead millions of spectators to reflect on the nature, and probe the potential, of their own humanity.

THE
JEOPARDY
MACHINE'S
birthplace—if a computer can stake such a claim—was the sprawling headquarters of the global research division named after its flesh-and-blood ancestor, IBM's founder, Thomas J. Watson. In 1957, when IBM presided over the rest of the infant computer industry, the company cleared woods on a hill in Yorktown Heights, New York, about forty miles north of midtown Manhattan, and hired the Finnish-American architect Eero Saarinen to design a lab. If computing was the future, as seemed inevitable, it was on this hill that a good part of it would be dreamed up, modeled mathematically, and prototyped. Saarinen was a natural choice to express this sparkling future in glass and rock. A year earlier, he had designed the winged TWA Terminal for the new Idlewild Airport (later called JFK). Before that, he'd drawn up the majestic Gateway Arch that would loom over St. Louis. In Yorktown, it was as if he had laid the Gateway Arch on its side. The building, with three stories of glass walls, curved along the top of the hill. For visitors strolling the wide corridors decades later, the combination of the structure's rough stone and the broad vistas of rolling hills still delivered just the right message of wealth, vision, and permanence.

The idea for a
Jeopardy
machine, at least according to one version of the story, dates back to an autumn day in 2004. For several years, top executives at the company had been pushing researchers to come up with the next Grand Challenge. In the '90s, the challenge had been to build a computer that would beat a grand champion in chess. This produced Deep Blue. Its 1997 victory over Garry Kasparov turned into a global event and fortified IBM's reputation as a giant in cutting-edge computing. (This grew more important as consumer and Web companies, from Microsoft to Yahoo!, threatened to steal the spotlight—and the young brainpower. Google was still just a couple of grad students at Stanford.) Later, in another Grand Challenge in the first years of the new century, IBM produced Blue Gene, the world's fastest supercomputer.

What would the next challenge be? On that fall day, a senior manager at IBM Research named Charles Lickel drove north from his lab, up the Hudson, to the town of Poughkeepsie, and spent the day with a small team he managed. That evening, the group went to the Sapore Steakhouse in nearby Fishkill, where they could order venison, elk, or buffalo, or split a whopping fifty-two-ounce porterhouse steak for two. There, something strange happened. At seven o'clock, many of the diners stood up from their tables, their food untouched, and filed into the bar, which had a television set. “The dining room emptied,” Lickel said. People were packed in there, three rows deep, to see whether Ken Jennings, who had won more than fifty straight matches on
Jeopardy,
would win again. He did. A half hour later, the crowd returned to their food, raving about the question-answering phenom. As Lickel noted, their steaks had to have been stone cold.

Though he hadn't watched much
Jeopardy
since he was a kid, that scene in the bar gave him an idea for the next Grand Challenge. What if an IBM computer could beat Ken Jennings? (Other accounts have it that the vision for a
Jeopardy
computer was already circulating along the corridors of the Yorktown lab. The original idea, it turns out, is tough to trace.)

In any event, Lickel pushed the idea. In the first meeting, it provoked plenty of dissent. Chess was nearly as clean and timeless as mathematics itself, a cerebral treasure handed down through the ages.
Jeopardy
, by contrast, looked questionable from the get-go. Produced by a publicly traded company, Sony, and subject to ratings and advertisers, it was in the business of making money and pleasing investors. It was Hollywood, for crying out loud. “There was a lot of doubt in the room,” Lickel said. “People wanted something more obviously scientific.” A second argument was perhaps more compelling: people playing
Jeopardy
would in all likelihood annihilate an IBM machine. “They all grabbed me after the meeting,” Lickel recalled, “and said, ‘Charles, you're going to regret this.'”

In the end, it was up to Paul Horn. A former professor of physics at the University of Chicago, Horn had headed IBM's three-thousand-person research arm since 1996. “If you think about smart machines,” he later said, “Blue Gene by some measures had the raw computing power of the human brain, at least within an order of magnitude or two.” Horn discussed those early days in his sun-splashed office at New York University, where he took up residence after his 2008 retirement from IBM. He had a black beard, and a tiny ponytail poked out from the back of his head.

“So here we have a machine that's as fast as your brain, or close,” he said. “But it doesn't think the way we think. So what would be an appropriate grand challenge that would have high visibility and excite people?” He didn't remember the idea coming from Lickel or hearing about the Fishkill dinner. In fact, Horn thought the idea might have come from him. In any case, he liked it—and promptly ran into resistance. “The general response was negative,” he recalled. “People said, ‘It can't be done. It's too much of a publicity stunt. The only reason that you're interested in it is because it's a show on TV.'” But Horn thought that building a savvy answering machine was the ideal challenge for IBM. While he maintained that he viewed the grand challenge as pure research, it also made plenty of sense.

IBM's business had undergone a radical transformation over the course of Horn's thirty-year career at the company. As late as the 1970s, IBM ruled the computer industry. It launched its first computers for business in 1952. But it was its breakthrough mainframe in 1964, Series 360, that established a single standard of computing in business, industry, and science. IBM pitched itself as a safe, if expensive, bet for companies looking to computerize. Its buttoned-down sales and consulting teams spread a compelling message around the world: “Nobody ever got fired for buying IBM.” Big Blue, a name derived from the massive blue mainframes it sold, grew so big that its rivals, including Sperry, Burroughs, Honeywell, and four other companies, came to be known as the Seven Dwarfs. During this time, IBM researchers at Saarinen's edifice and at other labs around the world churned out an array of new technologies. They came up with magnetic strips for credit cards and floppy disks for computer data storage. Yet it was computers that drove the business. When Horn arrived at IBM Research in 1979, the greatest threat to IBM appeared to be a decade-long antitrust complaint brought by the U.S. Justice Department. It alleged that IBM had violated the Sherman Act by attempting to monopolize the fast-growing industry for business computers. Whether or not Big Blue had broken the law, its dominance was beyond question.

By 1982, when the Justice Department dropped the suit for lack of evidence, the computer world was shifting under Big Blue's feet. The previous year, IBM had unveiled its first personal computer, or PC. Priced at $1,500, it provided both legitimacy and a standard for the young industry. Early on, as corporate customers gobbled up PCs, it seemed as though IBM would go on to dominate this next stage of computing. But there was a crucial difference between these desktop machines and the mainframes. Nearly every component of the mainframes, including their processors and software, was made by IBM. In the lingo of the industry, the computers were vertically integrated. This was not the case with PCs. In order to get to market quickly at a low price, IBM built them from off-the-shelf technology—microprocessors from Intel and a rudimentary operating system, MS-DOS, from a Seattle startup called Microsoft. Since the PC had commodity innards, it took no time at all for newcomers, including Compaq and Taiwan's Acer, to plug them into cheaper “IBM-compatible” computers, or clones. IBM found itself slugging it out with a slew of upstarts while Intel and Microsoft ran away with the profits and grew into titans. Big Blue was in decline, falling faster than most people imagined. And in 1992, the vast industrial behemoth stunned the business world by registering a $4.97 billion loss, the largest in U.S. history at the time. In the space of a decade, a company that had been synonymous with cutting-edge technology now looked tired and wasteful, a manufacturing titan ill-suited to the Information Age. It almost went under.

A new chief executive, Louis V. Gerstner, arrived in 1993 and transformed IBM. He sold off or shuttered old manufacturing divisions and steered the company toward businesses based on information. IBM did not have to sell machinery to be a leader in technology, he said. It could focus on the intelligence to run the technology—the software—along with the know-how to put the systems to good use. That was services, including consulting, and it led IBM back to growth.

Technology, in the early '90s, was convulsing entire industries and the new World Wide Web promised even more dramatic change. IBM's customers, which included virtually every blue-chip company on the planet, were confused about how these new networks and services fit into their businesses. Did it make sense to shift design work to China or India and have teams work virtually? Should they remake customer service around the Web? They had loads of questions, and IBM decided it could sell the answers. It could even take over tech operations for some of its customers and charge for the service.

This push toward services and software continued under Gerstner's successor, Samuel J. Palmisano. Two months after Charles Lickel came back from Poughkeepsie with the idea for a
Jeopardy
computer that could play
Jeopardy
, IBM sold its PC division to Lenovo Group of China. That year IBM Global Services registered $40 billion in sales, more than the $31 billion in hardware sales and a much larger share of profits. (By 2009, services would grow to $55 billion, nearly 60 percent of the company's revenue. And the consultants working in the division sold lots of IBM software, which registered $21 billion in sales.) Naturally, a
Jeopardy
computer would run on IBM hardware. But the heart of the system, like IBM itself, would be the software created to answer difficult questions.