Machines of Loving Grace (37 page)

Larry Page and Sergey Brin had given Hassan stock for programming PageRank, and Hassan also sold E-Groups, another of his information retrieval projects, to Yahoo!
for almost a half-billion dollars.
By then, he was a very wealthy Silicon Valley technologist looking for interesting projects.

In 2006 he backed both Ng and Salisbury and hired Salisbury’s students to join Willow Garage, a laboratory he’d
already created to facilitate the next generation of robotics technology—like designing driverless cars.
Hassan believed that building a home robot was a more marketable and achievable goal, so he set Willow Garage to work designing a PR2 robot to develop technology that he could ultimately introduce into more commercial projects.

S
ebastian Thrun had begun building a network of connections in Silicon Valley after he arrived on a sabbatical from CMU several years earlier.
One of those was Gary Bradski, an expert in machine vision at Intel Labs in Santa Clara.
The company was the world’s largest chipmaker and had developed a manufacturing strategy called “copy exact,” a way of developing next-generation manufacturing techniques to make ever-smaller chips.
Intel would develop a new technology at a prototype facility and then export that process to wherever it planned to produce the denser chips in volume.
It was a system that required discipline, and Bradski was a bit of a “Wild Duck”—a term that IBM originally used to describe employees who refused to fly in formation—compared to typical engineers in Intel’s regimented semiconductor manufacturing culture.

A refugee from the high-flying finance world of “quants” on the East Coast, Bradski arrived at Intel in 1996 and was forced to spend a year doing boring grunt work, like developing an image-processing software library for factory automation applications.
After paying his dues, he was moved to the chipmaker’s research laboratory and started researching interesting projects.
Bradski had grown up in Palo Alto before leaving to study physics and artificial intelligence at Berkeley and Boston University.
He returned because he had been bitten by the Silicon Valley entrepreneurial bug.

For a while he wrote academic research papers about machine vision, but he soon learned that there was no direct payoff.
The papers garnered respect at places like Berkeley,
Stanford, and MIT, but they didn’t resonate with the rest of Silicon Valley.
Besides, he realized that what was special about Intel was its deep pockets.
He decided he should be exploiting them.
“I should do something that has higher leverage,” he thought to himself.

In his first year at Intel he met some superstar Russian software designers who worked under contract for the chipmaker, and he realized that they could be an important resource for him.
At the time, the open-source software movement was incredibly popular.
His background was in computer vision, and so he put two and two together and decided to create a project to build a library of open-source machine vision software tools.
Taking the Linux operating system as a reference, it was obvious that when programmers worldwide have access to an extraordinary common set of tools, it makes everybody’s research a lot easier.
“I should give everyone that tool in vision research,” he decided.

While his boss was on sabbatical he launched OpenCV, or Open Source Computer Vision, a software library that made it easier for researchers to develop vision applications using Intel hardware.
Bradski was a believer in an iconoclastic operating style that was sometimes attributed to Admiral Grace Hopper and was shared by many who liked getting things done inside large organizations.
“Better to seek forgiveness than to ask permission” was his motto.
Eventually OpenCV contained a library of more than 2,500 algorithms including both computer vision and machine-learning software.
OpenCV also hosted programs that could recognize faces, identify objects, classify human motion, and so on.
From his initial team of just a handful of Intel researchers, a user community grew to more than 47,000 people, and more than ten million copies of the toolset have been downloaded to date.

Gary Bradski created a popular computer vision software library and helped design robots.
He would later leave robotics to work with a company seeking to build augmented reality glasses.
(
Photo © 2015 by Gary Bradski
)

Realizing that he would one day leave Intel and would need a powerful toolset for his next project, Bradski developed a second agenda.
OpenCV would be his calling card when he left his job at the chipmaker.
Open-source software efforts were in favor inside Intel because the company wanted leverage in its difficult relationship with Microsoft.
The two companies dominated the personal computing industry, but often clashed over issues of control, strategic direction, and ultimately revenue.
For a while Bradksi had tremendous support inside the laboratory: at one point, he had fifteen researchers on the OpenCV project.
That moment was one of the high points of his career at Intel.

Then, Intel gave him a division award and told him, “All right, now you have to move on.”
“What do you mean?”
he responded to his managers.
“This is a decadelong project.”
Grudgingly, he did some other things, but he covertly kept the OpenCV project going on the side.
That did not sit well inside the giant semiconductor firm.
One of his Russian programmers was given a performance review demerit—“improvement required”—by management because he was associated with the program.

Intel’s refusal to see the value of the project left Bradski feeling disaffected.
In 2001, Intel dropped its camera division, which pushed him to the edge.
“More shortsighted bean counter thinking,” he decided.
“Of course this is low-margin silicon, but this is a loss leader, so you can eventually profit from the whole thing!”
He had no idea that the mobile computing and smartphone wave was just a half decade away, but at that moment, he was right.
Intel, in retrospect, had had a history of trying new ideas and then canceling them before they
could bear fruit.
His frustration made him an easy recruit for Sebastian Thrun, who was then building his team at Stanford to create the Stanley autonomous vehicle for the 2005 DARPA competition.

They had struck up a relationship when Thrun had been at Stanford on sabbatical in 2001.
When he returned in 2003 as a faculty member, Bradski, who was disaffected with Intel, was preparing to take his own sabbatical at EPFL, a Swiss research university in Lausanne.
Thrun said, “Why don’t you come to Stanford instead?”
Bradski was faced with a difficult decision.
Switzerland would have offered him an academic feast, a chance to work on neural nets and evolutionary learning algorithms, and a great party.
At the end of the day, he realized that a sabbatical at EPFL was a diversion for someone who had entrepreneurial aspirations, and the nightmare Swiss bureaucracy overwhelmed him: he should have started a year earlier getting his kids into private school, and renting a house in Lausanne was a challenge—one potential landlord told him there would be no showering after ten
P
.
M
.
and he wouldn’t permit noisy children!

So Bradski switched gears and took his sabbatical at relatively laid-back Stanford.
He taught courses and flirted with ideas for a new start-up.
His first project involved building an advanced security camera.
However, he ended up with a partner who was a poor match for the project, and it quickly turned into a bad marriage.
Bradski backed out.
By that time, his sabbatical was over, so he went back to work at Intel and managed a large research group.
He quickly realized that management involved a lot of headaches and little interesting work, so he tried to pare down his group to a core team.

Before, Bradski had been oblivious to the frustrations of other researchers, but now he noticed that engineers everywhere inside the company had similar frustrations.
He joined an underground laboratory for the disaffected.
Then, on a visit to Stanford, Thrun said, “Come out back to the parking lot.”
Thrun
showed Bradski Stanley, the secret project preparing to enter the second DARPA Grand Challenge.
This was obviously the coolest thing around, and Bradski immediately fell in love with the idea.
Back at Intel, he quickly pulled together a secret skunkworks group to help with the computer vision system for the car.
He didn’t bother to ask permission.
He hosted his design meetings during lunchtime and met with the Stanford team on Tuesdays.

There were immediately two problems.
After Intel promised that it would not involve itself directly in the DARPA Grand Challenge, the company started sponsoring Red Whittaker’s CMU team.
Bradski’s boss started getting complaints that Bradski was distracting people from their assigned work.
“This could build up to be a firing offense,” his boss told him.
“We’re not sponsoring the Stanford team and we’re not getting into robotics.”
As a concession, Bradski’s boss told him he could continue to work on the project personally, but could not involve other Intel Labs researchers.
By then, however, Bradski no longer cared about being fired.
That made everything a lot easier, and the lunchtime meetings intensified.

The tensions at Intel came to a head two days before the race.
The cars and teams had arrived in Primm, Nevada, a three-casino watering hole on the California-Nevada border.
Bradski called a contact in Intel’s marketing department and said he needed an immediate decision about whether Intel was going to officially sponsor the Stanford car.
A decal on the car would usually cost $100,000, but Thrun told him that Bradski’s team had donated so much volunteer labor that they could have the sponsorship for just $20,000.
The Intel marketing guy loved the idea: sponsoring two cars would double Intel’s chance of backing a winner, but he balked at making an instant decision.
“The money’s there, but I can’t just give it to you unilaterally,” the executive told him.

“Look, the cars are about to be sequestered, we have half an hour left,” Bradski responded.

It worked.
“Okay, do it,” the executive said.

Because it was so late, there was no room left on the car except a passenger window—a brilliantly visible location.
Stanley won the race and Intel had backed a winner, so that was a coup.
Bradski had pulled himself back from the edge of unemployment.

The vision system contributed to Stanley’s success.
The car relied on lasers that could sense a dynamic point cloud around the car and digital cameras that fed machine vision algorithms.
In the end, the cameras saw far enough ahead that Stanley could maintain speed without slowing down.
And going fast, needless to say, was necessary to win.

The glory didn’t last long, however.
Bradski had secured a small DARPA contract to research “cognitive architectures” with Thrun and Daphne Koller, another Stanford machine-learning expert.
However, the DARPA program manager had announced his departure, which meant the grant was likely not be renewed, which in turn meant Bradski would have to look for funding elsewhere.
Sure enough, Phase II was canceled as “too ambitious.”

Bradski was very intrigued by robotics, so he used some of his grant money to purchase a robot arm.
The $20,000 purchase set off a small explosion inside Intel’s legal department.
The grant money, they insisted, was restricted for hiring interns, not buying hardware, and he had to transfer the ownership of the robot arm away from Intel.
Bradski gave the arm to the Stanford STAIR project, which was run by Andrew Ng.
Ng was starting to explore the world of robotics with machine-learning ideas.
Could they design a robot to load and unload a dishwasher?
It became part of the mix leading to the PR1 robot that was brewing between Salisbury’s laboratory and Ng’s project.