On April 3rd, 1921, a handful of journalists went to interview a relatively unknown scientist named Albert Einstein. When they arrived to meet his ship they found a crowd of thousands waiting for him, screaming with adulation. Surprised at his popularity, and charmed by his genial personality, the story of Einstein’s arrival made the front page in major newspapers.
It was all a bit of a mistake. The people in the crowd weren’t there to see Einstein, but Chaim Weizmann, the popular Zionist leader that Einstein was traveling with. Nevertheless, that’s how Einstein gained his iconic status. In a way, Einstein didn’t get famous because of relativity, relativity got famous because of Einstein.
This, of course, in no way lessens Einstein’s accomplishments, which were considerable. Yet as Albert-László Barabási, another highly accomplished scientist, explains in The Formula, there is a big difference between success and accomplishment. The truth is that success isn’t what you think it is but, with talent, persistence and some luck, anyone can achieve it.
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In 1965, Intel co-founder Gordon Moore published a remarkably prescient paper, which predicted that the number of transistors on a computer chip would double about every two years. For a half century, this process of doubling has proved to be so remarkably consistent that today it is commonly known as Moore’s Law and has driven the digital revolution.
For most of the past 50 years, Intel has led the industry by doubling transistors faster than its rivals, investing billions into massive fabs to produce the next generation of chips before anyone else. More recently, however, the giant has stumbled, losing ground to firms such as AMD, Qualcomm and Nvidia.
Yet the company recently announced a breakthrough with its Foveros technology that has the potential to put it back on top. No longer just cramming more transistors onto a silicon wafer, it has solved a decades old physics problem to stack chips on top of each other. This has the potential to not only change Intel’s fortunes, but to reshape the industry for years to come.
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When H.G. Wells was born in 1866, there was no electricity or cars or even indoor plumbing. Still, his active imagination conjured up a world of time machines, space travel and genetic engineering. This was all completely fantasy, but his books foresaw many modern inventions, such as email, lasers and nuclear energy.
It’s no accident that people who invent the future are often fans of science fiction. In fact, in Leading Transformation, the former head of Lowe’s innovation lab explains how he hired science fiction writers to help inspire the company to leverage virtual reality and build a new future for the company.
To create anything truly new and different, you often need to discard the constraints of the present. Yet that comes with a problem. How do you transform fantasy into something real and useful? What makes great innovators truly different is how they combine imagination with practical problem solving in order to bring even the wildest pipe dreams into reality.
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Ever since IBM’s Watson system defeated the best human champions at the game show Jeopardy!, artificial intelligence (AI) has been the buzzword of choice. More than just hype, intelligent systems are revolutionizing fields from medicine and manufacturing to changing fundamental assumptions about how science is done.
Yet for all the progress, it appears that we are closer to the beginning of the AI revolution than the end. Intelligent systems are still limited in many ways. They depend on massive amounts of data to learn accurately, have trouble understanding context and their susceptibility to bias makes them ripe targets for sabotage.
IBM, which has been working on AI since the 1950s, is not only keenly aware of these shortcomings, it is working hard to improve the basic technology. As Dario Gil, Chief Operating Officer of IBM Research recently wrote in a blog post, the company published over 100 papers in just the past year. Here are the highlights of what is being developed now.
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Go to just about any business conference and you will see a pundit on stage. He or she will show some company that failed and explain the silly mistakes that they made, then follow-up with a few basic rules to help you avoid those pitfalls and become super successful. You leave feeling confident, because it all seems so simple and easy.
Yet look a little closer and the illusion falls away. Very few of these pundits have ever run a successful business. At the same time, many of the executives that are shown to be so silly today, were hailed as visionaries of their time, often by the same pundits that ridicule them now. Some went on to great success later on.
The truth is that managing a successful enterprise is a very hard and complex thing to do well. It can’t be boiled down to a few simple rules. For every great enterprise that does things one way, you will find one that’s equally successful that goes about things very differently. So to succeed in the long term, we often need to ignore the myths pundits love to repeat.
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In 1847, a young doctor named Ignaz Semmelweis had a major breakthrough. Working in a maternity ward, he discovered that a regime of hand washing could dramatically lower the incidence of childbed fever. Unfortunately, the medical establishment rejected his ideas and the germ theory of disease didn’t take hold until decades later.
The phenomenon is now known as the Semmelweis effect, the tendency for people to reject new knowledge that contradicts established beliefs. Whether you are a CEO trying to launch a new initiative, a political leader pushing for an important reform or a social activist advocating for a cause, you need more than a big idea to change the world.
The problem is that a new idea has to replace an old one and the status quo has inertia on its side. Even those who are easily convinced have to convince those around them and those, in turn, need to convince others still until the long chain of influence results in a change of the zeitgeist. That’s why to truly make an impact, you need small groups, loosely connected, but united by a shared purpose.
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Think of just about any major challenge we will face over the next decade and materials are at the center of it. To build a new clean energy future, we need more efficient solar panels, wind turbines and batteries. Manufacturers need new materials to create more advanced products. We also need to replace materials subject to supply disruptions, like rare earth elements.
Traditionally, developing new materials has been a slow, painstaking process. To find the properties they’re looking for, researchers would often have to test hundreds — or even thousands — of materials one by one. That made materials research prohibitively expensive for most industries.
Yet today, we’re in the midst of a materials revolution. Scientists are using powerful simulation techniques, as well as machine learning algorithms, to propel innovation forward at blazing speed and even point them toward possibilities they had never considered. Over the next decade, the rapid advancement in materials science will have a massive impact.
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Over the past few decades, we’ve come to glamorize the garage (or WeWork) startup. These days, parents take the same pride telling their neighbors that their progeny have gone to work for some fledgling enterprise that used to be reserved for a job at IBM or General Electric. Today’s celebrity CEOs tend to be founders.
We can expect that to change in the years to come. The end of Moore’s law will mean that the technologies of the future will be far more complex, less understood and more capital intensive. Large, well resourced organizations, including government entities, are much better positioned to develop these technologies than startups are.
However, this will be no return to the age of robber barons. One thing that past decades have taught us is that walled gardens are a fool’s errand and cloud computing has made them even less tenable. So it’s becoming increasingly important for large enterprises to partner with entrepreneurs and vice versa. Collaboration is quickly becoming a key competitive advantage.
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2018 was a busy year. Due the the success of my first book, Mapping Innovation, I was inundated with speaking requests that took me not only across the country, but across the world, including Bahrain, Turkey and India. It was great to hear from so many who enjoyed the book and found it to be helpful.
I spent most of the year working on my new book, Cascades: How to Create a Movement that Drives Transformational Change, which will be published in April. It is the product of 15 years of research and it was an enormous task putting everything together, but I think all the effort was worth it. I’m extremely happy with how it all turned out!
And, of course, I’ve continued to post twice a week on Digital Tonto, no matter where I am and what else I have going on. As we move on from the digital revolution to new technologies, such as genomics, materials and robotics, I’m more excited about the future than ever. Here are the articles you most liked to read and share over the past year. I hope you enjoy them!
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