Random Things

With its 4.5-billion-year head start on mankind, the natural world has developed some clever mechanisms for solving big problems, and that natural cleverness isn’t just informing new ways to generate energy. It’s slowly but surely informing everything from the the way emergency rooms are designed to how data networks communicate. It asks that electricity grids act like bees and businesses manage resources like coral reefs manage calories. Seriously.

“Biomimicry is a beautiful way of framing the design process to be cognizant of how nature does things,” says Dr. John Warner of the Warner Babcock Institute for Green Chemistry. “I think that over the centuries humans have become a little egotistical in trying to bend materials and things to our will.”

Warner and his colleagues are on the science side of biomimicry’s collaboration between biology and design. As a green chemist, he and his lab develop new environmentally benign materials often borrowing from natural processes along the way. In Warner’s world, gone are the heat, high pressures, and toxic additives native to much man-made chemistry, replaced with processes that hew more closely to the way nature creates materials.

On the other side of that equation are the engineers looking for new and better materials with which to design. And increasingly there’s a stronger dialogue between the two, driven partially by an increased environmental consciousness but moreso by a pressing imperative to solve big, overarching problems at the macro scale.

Take Nocera’s leaf for instance: in light of an always-looming global energy (and environmental) crisis, a means to generate electricity from plentiful (and renewable) water and sunlight could solve a number of huge problems, both natural and man made. The answer is right there in the leaf, and has been for millennia--unlock that natural mechanism in a feasible, economically viable manner and you’ve got a beautiful solution to problems ranging from the environmental to the humanitarian to the geopolitical.

“When you think about the natural world, nature outperforms us in its diversity, in its complexity, but does so at ambient temperature, at low pressures, using water for the most part as a solvent.” Warner says. By helping humans to think more like a leaf (or an ant hill, or a 1,200-year-old oak, or a bacterial colony), biomimicry is tapping that multi-billion-year head start to bring the same kind of complexity and diversity to human invention.

Six examples of how bio-inspired solutions are reshaping the world can be found in this gallery

Money is always welcome and notoriety can be nice. Most research academics will cheerfully accept funding and fame. However, the surest way to gain access to the world's brightest students and most brilliant professors is to bring problems that simultaneously goad their curiosity and tap their expertise from unexpected angles. World-class researchers always have their own agendas. They don't need another one from you. But they almost always will make time for smart, passionate people with problems that can make their work more valuable and accessible.

That's why you see cutting-edge molecular gastronomy innovators like Heston Blumenthal and Ferran Adria enjoy fruitful and meaty collaborations with top-tier research institutions. They're not just technically brilliant and successful in their own right; they bring novel challenges and unusual constraints that invite creative academic participation. Money isn't irrelevant but it's neither the real or most compelling reason for partnership. You've picked the wrong problem if it's your budget that gets your erstwhile collaborators hot-to-trot. You know you've picked a winner when the academics ask if it would be OK if someone could do a doctoral dissertation based on some slice of the problem you've posed.

This kind of innovation collaboration is fundamentally different from the contract research and development so many Fortune 1000 firms seem to desire from research universities. Crudely put, there's no shortage of cash-strapped companies hoping to "outsource" some of their harder science and engineering problems to a chemistry or metallurgy or biology department because they hope it would be cheaper than doing them in-house. That's a recipe for mutual frustration, not productive partnership.

The provocative problem sets we're talking about aren't investigator-driven but investigator-seductive. That is, researchers go into them confident that they can be solved but not quite sure how. They're betting, and it's a good bet, that they'll learn something interesting and important along the way. Just as important, their students will learn something interesting and important. In the meantime, your problem gets solved and you likely gain insight into a suite of analytic techniques and technologies that can empower your next generation innovations.

via blogs.hbr.org

In 1985 Garry Kasparvo played simultaneous games against 32 dedicated chess computers, and won all them (there were no draws, mind you; his record was 32-0). In 1996 he beat Deep Blue 4-2 (with wins counting for one point, and draws for 1/2 point). In 1997 an improved version of the same machine beat him 3 1/2 to 2 1/2.

Deep Blue was a $10 million highly specialized supercomputer programmed by a full-time team, but within a few years, such dedicated horsepower was no longer necessary. In 2003 Kasparov played non-simultaneous matches against two commercially available chess programs running on standard servers. Both matches ended in similar ties, consisting of one win for each contestant and several draws.

As these examples show, computers improve so quickly that their capabilities pass from the realm of science fiction to the realm of the mundane not over the course of a human lifetime, but rather well within the span of one professional's career. As Kasparov describes, "It was my luck (perhaps my bad luck) to be the world chess champion during the critical years in which computers challenged, then surpassed, human chess players. Before 1994 and after 2004 these duels held little interest. The computers quickly went from too weak to too strong."

Even more remarkable than this rapid improvement, though, is the fact that humans have not been relegated to the sidelines of high-level chess. Instead, more recent competitions have shown how fruitful it can be to mix human strengths with machine ones, and how the best such combinations can be difficult to predict, even for experts.

Kasparov notes that computers play chess not by simulating human reasoning, but instead by comparing all possible moves and their consequences — the resulting board positions, subsequently available countermoves, possible counter-countermoves, etc. — until time runs out and a decision is necessary. And time will always run out; there are 10^40 possible legal board positions and 10^120 possible games, so even today's fastest computers can't be exhaustive. But they can be thorough, precise, and consistent. They evaluate lots of options, compare them rigorously, and never ever overlook or forget anything that they've been programmed to take into account.

These attributes, when coupled with enough computational muscle, make chess computers unbeatable by people. So much for the intangible yet profound value of human creativity, intuition, and spark, right? Doesn't the example of chess illustrate that these things, lovely though they may be, are rendered insignificant by fast chips and cold logic?

Thankfully, no (whew!). Kasparov writes that in competitions allowing any combination of people and computers, "The teams of human plus machine dominated even the strongest computers. The chess machine Hydra, which is a chess-specific supercomputer like Deep Blue, was no match for a strong human player using a relatively weak laptop. Human strategic guidance combined with the tactical acuity of a computer was overwhelming."

This is incredibly good news, isn't it? It suggests when we talk about the inimitable spark of human creativity and intuition we're not just patting ourselves on the back, even in rational domains like chess. In this arena, a thoughtful human expert and a well-designed technology has proved to be a powerful combination. Kasparov says it well: when playing with the assistance of computers, "we [people] could concentrate on strategic planning instead of spending so much time on calculations. Human creativity was even more paramount under these conditions." (yeah!)

My favorite aspect of these 'freestyle' competitions was the specific type of human creativity that led to victory. Instead of pure chess genius, it was something much closer to business process design brilliance. The overall winner was a team that contained neither the best human players nor the biggest and fastest computers. Instead, it consisted of "a pair of amateur American chess players using three computers at the same time. Their skill at manipulating and "coaching" their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants."

Kasparov was surprised at this outcome and I have to confess that I was as well, despite my deep conviction that a well-designed process is a potent weapon. I didn't think that smart process design — in this case, a process for determining the "best" chess move — could overcome both cognitive and computational deficits. But it did, even in this domain where brains and calculations would appear to be the only things that matter. As Kasparov writes of this amazing result, "Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process." I think that's my new motto.

You don't have to have the pattern-recognition capabilities of a grandmaster to see that a dominant approach to achieving good results is becoming visible. This approach consists of teamwork among humans and computers, with each playing to its comparative strength. The good news for this team is that each partner is strong precisely where the other is weak, a happy situation known as Moravec's paradox .

It's fiendishly hard to give computers intuition, or to make people consistent and error-free. Luckily, we don't have do. Environments as different as chess and medicine are showing us that the right approach is to let people exercise their intuition and creativity, supported and double-checked by their computer assistants as part of a well-designed process. This approach yields better outcomes than a purely automated one (which, in turn, does better than a purely human one, in chess and many other domains).

She told a story with some important innovation implications.

The story dates back to the 1990s, when Healey was a brand manager in Brazil. She was responsible for growing P&G's Hipoglos brand of diaper rash ointments. The problem? The product already had 99 percent household penetration.

A tough challenge, right?

Healey did what good P&G people do — she went out to talk to consumers to find out what they thought about the product, the problem it addressed, and so on.

People claimed they used the product regularly to prevent diaper rash. If that were true, however, Healey knew consumers would buy much more Hipoglos than they did today.

So, she dug deeper. By probing when consumers used the product, she found that parents applied it when early signs of rash began to appear. Of course, that's too late if you truly want to use a product for preventive purposes.

Healey had a critical insight. Consumers weren't actually realizing all of the benefits of the product, resulting in cranky babies and sleepless nights. P&G began running advertisements showing how applying the cream to an already emerging rash was too late to prevent the rash from occurring. Not surprisingly, sales soared.

Innovation doesn't always involve new features, functions, services, or business models. Sometimes it can be as seemingly simple as a new marketing message.

I suggested that my colleague try a new sort of ice cream from Häagen-Dazs. It's called Häagen-Dazs Five, and each flavor has only five ingredients. For instance, the brown sugar flavor (which I've had and is quite good) contains only skim milk, cream, brown sugar, sugar and egg yolks. Far from healthful, but definitely simplistic.

My colleague then very smartly asked, How many ingredients does Häagen-Dazs normally have? A quick visit to Haagen-Dazs.com yields the answer: five.

Here are the ingredients in Häagen-Dazs Five coffee ice cream:

Skim Milk, Cream, Sugar, Egg Yolks, Coffee.

And now here are the ingredients in the regular version of Häagen-Dazs coffee ice cream:

Cream, Skim Milk, Sugar, Egg Yolks, Coffee.

Engineering new products is so complicated. Who has the time or the money? Why not simply repackage an existing product as having some sort of new, beneficial feature—when, in fact, it had that feature all along? As my colleague said: "I hope someone got a bonus for that."

Now, to be fair, Häagen-Dazs Five is slightly lower in calories and fat (notice how skim milk comes first on the ingredients list instead of cream). And while plenty of regular Häagen-Dazs flavors only have five ingredients (chocolate, vanilla, strawberry), others do have many more. The banana split flavor has 13, including corn syrup and pectin. My colleague is having none of that, thank you very much.

Still, a great little lesson in marketing, no? And, really, we shouldn't be surprised. Those Häagen-Dazs people (who are now technically Nestlé people) have a history of smart ideas. For instance, which country do you think Häagen-Dazs comes from? Sweden? Norway? Finland?

Actually, Häagen-Dazs was invented in New York City in the 1960s. The name is nonsense, designed to make you think you're getting some sort special Old World recipe. Though really, it's just five ingredients.