Tag Archives: strategy

Google AI Versus the Human Race


It does indeed appear that a computer armed with Google’s experimental AI (artificial intelligence) software just beat a grandmaster of the strategy board game Go. The game was devised in ancient China — it’s been around for several millennia. Go is commonly held to be substantially more difficult than chess to master, to which I can personally attest.

So, does this mean that the human race is next in line for a defeat at the hands of an uber-intelligent AI? Well, not really, not yet anyway.

But, I’m with prominent scientists and entrepreneurs — including Stephen Hawking, Bill Gates and Elon Musk — who warn of the long-term existential peril to humanity from unfettered AI. In the meantime check out how AlphaGo from Google’s DeepMind unit set about thrashing a human.

From Wired:

An artificially intelligent Google machine just beat a human grandmaster at the game of Go, the 2,500-year-old contest of strategy and intellect that’s exponentially more complex than the game of chess. And Nick Bostrom isn’t exactly impressed.

Bostrom is the Swedish-born Oxford philosophy professor who rose to prominence on the back of his recent bestseller Superintelligence: Paths, Dangers, Strategies, a book that explores the benefits of AI, but also argues that a truly intelligent computer could hasten the extinction of humanity. It’s not that he discounts the power of Google’s Go-playing machine. He just argues that it isn’t necessarily a huge leap forward. The technologies behind Google’s system, Bostrom points out, have been steadily improving for years, including much-discussed AI techniques such as deep learning and reinforcement learning. Google beating a Go grandmaster is just part of a much bigger arc. It started long ago, and it will continue for years to come.

“There has been, and there is, a lot of progress in state-of-the-art artificial intelligence,” Bostrom says. “[Google’s] underlying technology is very much continuous with what has been under development for the last several years.”

But if you look at this another way, it’s exactly why Google’s triumph is so exciting—and perhaps a little frightening. Even Bostrom says it’s a good excuse to stop and take a look at how far this technology has come and where it’s going. Researchers once thought AI would struggle to crack Go for at least another decade. Now, it’s headed to places that once seemed unreachable. Or, at least, there are many people—with much power and money at their disposal—who are intent on reaching those places.

Building a Brain

Google’s AI system, known as AlphaGo, was developed at DeepMind, the AI research house that Google acquired for $400 million in early 2014. DeepMind specializes in both deep learning and reinforcement learning, technologies that allow machines to learn largely on their own.

Using what are called neural networks—networks of hardware and software that approximate the web of neurons in the human brain—deep learning is what drives the remarkably effective image search tool build into Google Photos—not to mention the face recognition service on Facebook and the language translation tool built into Microsoft’s Skype and the system that identifies porn on Twitter. If you feed millions of game moves into a deep neural net, you can teach it to play a video game.

Reinforcement learning takes things a step further. Once you’ve built a neural net that’s pretty good at playing a game, you can match it against itself. As two versions of this neural net play thousands of games against each other, the system tracks which moves yield the highest reward—that is, the highest score—and in this way, it learns to play the game at an even higher level.

AlphaGo uses all this. And then some. Hassabis [Demis Hassabis, AlphaGo founder] and his team added a second level of “deep reinforcement learning” that looks ahead to the longterm results of each move. And they lean on traditional AI techniques that have driven Go-playing AI in the past, including the Monte Carlo tree search method, which basically plays out a huge number of scenarios to their eventual conclusions. Drawing from techniques both new and old, they built a system capable of beating a top professional player. In October, AlphaGo played a close-door match against the reigning three-time European Go champion, which was only revealed to the public on Wednesday morning. The match spanned five games, and AlphaGo won all five.

Read the entire story here.

Image: Korean couple, in traditional dress, play Go; photograph dated between 1910 and 1920. Courtesy: Frank and Frances Carpenter Collection. Public Domain.

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Design Thinking Versus Product Development

Out with product managers; in with design thinkers. Time for some corporate creativity. Think user journeys and empathy roadmaps.

A different corporate mantra is beginning to take hold at some large companies like IBM. It’s called design thinking, and while it’s not necessarily new, it holds promise for companies seeking to meet the needs of their customers at a fundamental level. Where design is often thought of in terms of defining and constructing cool-looking products, design thinking is used to capture a business problem at a broader level, shape business strategy and deliver a more holistic, deeper solution to customers. And, importantly, to do so more quickly than through a typical product development life-cycle.

From NYT:

Phil Gilbert is a tall man with a shaved head and wire-rimmed glasses. He typically wears cowboy boots and bluejeans to work — hardly unusual these days, except he’s an executive at IBM, a company that still has a button-down suit-and-tie reputation. And in case you don’t get the message from his wardrobe, there’s a huge black-and-white photograph hanging in his office of a young Bob Dylan, hunched over sheet music, making changes to songs in the “Highway 61 Revisited” album. It’s an image, Mr. Gilbert will tell you, that conveys both a rebel spirit and hard work.

Let’s not get carried away. Mr. Gilbert, who is 59 years old, is not trying to redefine an entire generation. On the other hand, he wants to change the habits of a huge company as it tries to adjust to a new era, and that is no small task.

IBM, like many established companies, is confronting the relentless advance of digital technology. For these companies, the question is: Can you grow in the new businesses faster than your older, lucrative businesses decline?

Mr. Gilbert answers that question with something called design thinking. (His title is general manager of design.) Among other things, design thinking flips traditional technology product development on its head. The old way is that you come up with a new product idea and then try to sell it to customers. In the design thinking way, the idea is to identify users’ needs as a starting point.

Mr. Gilbert and his team talk a lot about “iteration cycles,” “lateral thinking,” “user journeys” and “empathy maps.” To the uninitiated, the canons of design thinking can sound mushy and self-evident. But across corporate America, there is a rising enthusiasm for design thinking not only to develop products but also to guide strategy and shape decisions of all kinds. The September cover article of the Harvard Business Review was “The Evolution of Design Thinking.” Venture capital firms are hiring design experts, and so are companies in many industries.

Still, the IBM initiative stands out. The company is well on its way to hiring more than 1,000 professional designers, and much of its management work force is being trained in design thinking. “I’ve never seen any company implement it on the scale of IBM,” said William Burnett, executive director of the design program at Stanford University. “To try to change a culture in a company that size is a daunting task.”

Daunting seems an understatement. IBM has more than 370,000 employees. While its revenues are huge, the company’s quarterly reports have shown them steadily declining in the last two years. The falloff in revenue is partly intentional, as the company sold off less profitable operations, but the sometimes disappointing profits are not, and they reflect IBM’s struggle with its transition. Last month, the company shaved its profit target for 2015.

In recent years, the company has invested heavily in new fields, including data analytics, cloud computing, mobile technology, security, social media software for business and its Watson artificial intelligence technology. Those businesses are growing rapidly, generating revenue of $25 billion last year, and IBM forecasts that they will contribute $40 billion by 2018, through internal growth and acquisitions. Just recently, for example, IBM agreed to pay $2 billion for the Weather Company (not including its television channel), gaining its real-time and historical weather data to feed into Watson and analytics software.

But IBM’s biggest businesses are still the traditional ones — conventional hardware, software and services — which contribute 60 percent of its revenue and most of its profit. And these IBM mainstays are vulnerable, as customers increasingly prefer to buy software as a service, delivered over the Internet from remote data centers.

Recognizing the importance of design is not new, certainly not at IBM. In the 1950s, Thomas J. Watson Jr., then the company’s chief executive, brought on Eliot Noyes, a distinguished architect and industrial designer, to guide a design program at IBM. And Noyes, in turn, tapped others including Paul Rand, Charles Eames and Eero Saarinen in helping design everything from corporate buildings to the eight-bar corporate logo to the IBM Selectric typewriter with its golf-ball-shaped head.

At that time, and for many years, design meant creating eye-pleasing, functional products. Now design thinking has broader aims, as a faster, more productive way of organizing work: Look at problems first through the prism of users’ needs, research those needs with real people and then build prototype products quickly.

Defining problems more expansively is part of the design-thinking ethos. At a course in New York recently, a group of IBM managers were given pads and felt-tip pens and told to sketch designs for “the thing that holds flowers on a table” in two minutes. The results, predictably, were vases of different sizes and shapes.

Next, they were given two minutes to design “a better way for people to enjoy flowers in their home.” In Round 2, the ideas included wall placements, a rotating flower pot run by solar power and a software app for displaying images of flowers on a home TV screen.

Read the entire story here.

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