More on this book
Community
Kindle Notes & Highlights
We saw that radically new industries don’t start when creative entrepreneurs meet venture capitalists. They start with people who are infatuated with seemingly impossible futures.
So what makes a real unicorn of this amazing kind? 1. It seems unbelievable at first. 2. It changes the way the world works. 3. It results in an ecosystem of new services, jobs, business models, and industries.
“Siri, make me a six p.m. reservation for two at Camino.” “Alexa, play ‘Ballad of a Thin Man.’” “Okay, Google, remind me to buy currants the next time I’m at Piedmont Grocery.”
For Google to remind me to buy currants the next time I’m at my local supermarket, it has to know where I am at
“Leave now to get to the airport on time. 25 minute delay on the Bay Bridge.” or “There is traffic ahead. Faster route available.”
Once you become accustomed to each new superpower, life without it
And that gets me to the third characteristic of true unicorns: They create value. Not just financial value, but real-world value for society.
This is the true opportunity of technology: It extends human capability.
Computers used to work for humans; increasingly it’s now humans working for computers. The algorithm is the new shift boss.
But instead, corporate profits have reached highs not seen since the 1920s, corporate investment has shrunk, and more than $30 trillion of cash is sitting on the sidelines. The magic of the market is not working.
After World War II, we committed enormous resources to rebuild the lands destroyed by war, but we also invested in basic research. We invested in new industries: aerospace, chemicals, computers, and telecommunications. We invested in education, so that children could be prepared for the world they were about to inherit.
The lesson is clear: Treat curiosity and wonder as a guide to the future. That sense of wonder may just mean that those crazy enthusiasts are seeing something that you don’t . . . yet.
“Replacing materials with information” is a more powerful formulation than “replacing ownership with access.”
“digital-capital-intensive technologies are substituting for humans in the routine labor-intensive parts of manufacturing supply chains . . . and digital technologies make manufacturing mobile with little or no cost penalty, physical manufacturing activity will move toward market demand rather than toward labor, because there are efficiencies to be gained from proximity to the market.”
Steve Jobs was originally opposed to the idea of third-party apps on the iPhone. Travis Kalanick was for a long time skeptical of the peer-to-peer model.
A more recent demonstration of how old thinking holds back even smart entrepreneurs is how long it took for the Amazon Echo to arrive,
This is a key lesson for every entrepreneur. Ask yourself: What is unthinkable? And if, like Tony Fadell, you aren’t ready to push past that boundary of unthinkability because you believe the market isn’t ready, you can still prepare.
“Uber is a $3.5 billion lesson in building for how the world *should* work instead of optimizing for how the world *does* work.”
But perhaps most important, these companies have gone beyond being just hubs in a network. They have become platforms providing services on which other companies build, central to the operation and control of the network.
“He realized then that history is a wave that moves through time slightly faster than we do.” If we are honest with ourselves, each of us has many such moments, when we realize that the world has moved on and we are stuck in the past.
Permissionless networks, like open source software projects or the World Wide Web, often grow faster and more organically than those that require approval, and the web soon left MSN and AOL far behind. The web grew to hundreds of millions of websites, hosting trillions of web pages.
It is why Twitter is still struggling. Ultimately, network businesses need to develop both sides of the market. Uber, Lyft, and
I’d first noticed this with Microsoft’s abuse of its monopoly position in the personal computer industry. In the early years, there was a thriving ecosystem of application vendors built on top of Microsoft Windows; by the time Microsoft reached its zenith, it had taken over many of the most lucrative application categories, using its platform dominance to drive the former leaders out of business. Entrepreneurs naturally went elsewhere, finding opportunity in the green fields of the as-yet noncommercial Internet.
“In effect, Amazon is turning an open, public marketplace into a privately controlled one.”
“began to trade against their clients for their own account, such that now, the direct investment activities of a firm like Goldman Sachs dwarf their activities on behalf of outside customers.” The
Jeff’s first key insight was that Amazon could never turn itself into a platform unless it was itself built from the ground up using the same APIs that it would offer to external developers.
“Services do not only represent a software structure but also the organizational structure. The services have a strong ownership model, which combined with the small team size is intended to make it very easy to innovate. In some sense you can see these services as small startups within the walls of a bigger company. Each of these services require a strong focus on who their customers are, regardless whether they are externally or internally.”
Any project at Amazon is designed via a “working backwards” process. That is, the company, famous for its focus on the customer, starts with a press release that describes what the finished product
tell people, ‘Don’t follow my orders. Follow the orders I would have given you if I were there and knew what you know.’”
effectively, a team is promising a result, not how they will achieve it. As in Afghanistan, high autonomy is required by the rapidly changing conditions of a fast-growing Internet service.
Jeff saw instantly that CS reps had knowledge that would be useful to retail but it was siloed. So he suggested the use of a mechanism like the Andon Cord—which was eventually implemented.”
The key idea is that a company is now a hybrid organism, made up of people and machines.
The Internet itself was originally a government-funded project. So was the Interstate Highway System. Not to mention that the government funded the original computer and memory chip development that gave us Silicon Valley, the research behind Siri and self-driving cars, and actually provided much of the capital for building out Elon Musk’s bold ventures in electric vehicles, rooftop solar, and commercial space travel.
As we’ve discussed, creating a thick marketplace is the first requirement of any platform. This is not a given. A thick marketplace requires both producers (in Apple’s case, app developers) and consumers.
In Concrete Economics, Stephen Cohen and Brad DeLong review the lessons of history, going back to Alexander Hamilton and identifying the role of government intervention in each great step forward in the American economy.
success of Google’s core search service. Its insight, that “simple models and a lot of data trump more elaborate models based on less data,”
Deep learning uses layers of recognizers. Before you can recognize a dog, you have to be able to recognize shapes. Before you can recognize shapes, you have to be able to recognize edges, so that you can distinguish a shape from its background.
When you focus on outcomes rather than rules, you can see that there are multiple ways to achieve comparable outcomes, and sometimes new ways that provide better outcomes. Which approach is best should be informed by data. Unfortunately, it isn’t just government that is unwilling
both argue that we need to develop a new classification for workers—we might call them “dependent contractors.” This new classification might allow some of the freedoms of independent contractors, while adding some of the protections afforded to employees.
The idea that something with a high production value, shared by millions, could be without a shred of truth really wasn’t in her matrix of possibilities.” The notion that the video could have been created by an anonymous Trump supporter was just not part of her mental map.
Her solution: Google should stop linking to these pages immediately. “Google’s business model is built around the idea that it’s a neutral platform.
But Cadwalladr ignored the scale at which Google operates, and the way that scale fundamentally changes the necessary solution.
In addition to the Russian-sponsored social media disinformation campaigns, the Trump campaign’s Project Alamo used highly targeted disinformation to discourage Clinton voters from going to the polls. These posts were referred to as “dark posts” by Brad Parscale, who led the campaign’s social media efforts, private posts whose viewership is tightly targeted so that,
“They’re capturing people and then keeping them on an emotional leash and never letting them go.”
One Russian botnet uncovered in December 2016 was creating targeted videos that were generating $3–5 million per day in ad revenue from fake video views by programs masquerading as users.
“That is, operate at a faster tempo to generate rapidly changing conditions that inhibit your opponent from adapting or reacting to those changes and that suppress or destroy his awareness. Thus, a hodgepodge of confusion and disorder occur to cause him to over- or under-react to conditions or activities that appear to be uncertain, ambiguous, or incomprehensible.”
“It takes a machine to get inside the OODA loop of another machine.”
“Cracks were the centerpiece of the investigation. They could not be eliminated. They were everywhere, permeating the structure, too small to be seen. The structure could not be made perfect, it was inherently flawed, and the goal of engineering design was not to certify the airframe free of cracks but to make it tolerate them.”
Where de Havilland tried in vain to engineer a plane where the materials were strong enough to resist all cracks and fatigue, Boeing realized that the right approach was to engineer a design that allowed cracks, but kept them from propagating so far that they led to catastrophic failure. That is also Facebook’s challenge. Their goal is to find a way for the plane to fly faster, but fly safely.
There is a similar, very powerful technique for small groups meeting in the physical world, which we’ve often used to discuss contentious issues among the staff and fellows at Code for America. It’s called a “Human Spectrogram.” The group stands together in the middle of a large room. Someone makes a statement, and those who agree strongly with it move to the far end of the room. Those who disagree move to the other end of the room. People whose views are less polarized can arrange themselves anywhere in between.
