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Thanks to the acceleration of the miniaturization of sensors, we are now able to digitize four senses—sight, sound, touch, and hearing—and are working on the fifth:
This vast expansion in our ability to sense our environment and turn it into digitized data was made possible by breakthroughs in materials science and nanotechnology that created sensors so small, cheap, smart, and resistant to heat and cold that we could readily install them and fasten them to measure stress under extreme conditions and then transmit the data.
This new industrial nervous system, argued Ruh, was originally accelerated by advances in the consumer space—such as camera-enabled smartphones with GPS.
“The old approach was called ‘condition-based maintenance’—if it looks dirty, wash it,” explained Ruh. “Preventive maintenance was: change the oil every six thousand miles, whether you drive it hard or not.” The new approach is “predictive maintenance” and “prescriptive maintenance.”
There are patterns that a human mind could not find, because the signals are so weak early on that you won’t see them. But now that we have all this processing power, those weak signals just pop out at you. And so as you get that weak signal, it now becomes clear that it is an early indication that something is going to break or is becoming inefficient.”
Think about that. The intuition about how a machine is operating on a factory floor used to come from working there for thirty years and being able to detect a slightly different sound signature emanating from the machine, telling you something might not be exactly right. That is a weak signal. Now, with sensors, a new employee can detect a weak signal on the first day of work—without any intuition. The sensors will broadcast it.
Having this system at their fingertips made the farmers more productive not only in expanding their herds—“you get a huge improvement in conception rates,”
“we no longer need to build physical changes into every product to improve their performance, we just do it with software. I take a dumb locomotive and throw sensors and software into it, and suddenly I can do predictive maintenance, I can make it operate up and down the tracks at the optimal speeds to save gasoline,
He once famously observed: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” That needn’t be the case today.
Guessing is officially over.
“Any idea what that number represents?” he asked the audience.
And therein lies a really important story about how a combination of storage chips hitting the second half of the chessboard and a software breakthrough named after a toy elephant put the “big” into “big data” analytics.
Remember that name: Hadoop. It has helped to change the world—but with a huge assist from Google.
He also found that programming would be the best way to pay off his student loans.
You would just scan everything and then search it. Xerox had this paper-oriented view of the world. It was the classic example of a company that could not move away from its cash cow—paper was its lifeblood—and it was trying to figure out how to move paper into the digital world. That was its rationale for looking into search. This is before the Web happened.”
That was a lot—and for a while it leapfrogged everyone. That was happening around 1995 to ’96. Google showed up shortly thereafter [in 1997] with a small search engine, but claiming much better methods. And gradually it proved itself.”
Google’s true genius, said Cutting, was “to describe a storage system that made one thousand drives look like one drive, so if any single one failed you didn’t notice,” along with a software package for processing all that data they were storing in order to make it useful.
In plain language, Google’s two design innovations meant we could suddenly store more data than we ever imagined and could use software applications to explore that mountain of data with an ease we never imagined.
Soon enough, Facebook and Twitter and LinkedIn all started building on Hadoop. And that’s why they all emerged together in 2007! It made perfect sense. They had big amounts of data streaming through their business, but they knew that they were not making the best use of it. They couldn’t.
Clicks could already be recorded, but until Hadoop came along no one besides Google could do much with the data.
Hadoop’s system, which is open source and run by everyone else, leveraging millions of cheap servers to do big data analytics.
Hadoop scaled big data thanks to another critical development as well: the transformation of unstructured data.
Hadoop enabled data analysts to search all that unstructured data and find the patterns. This ability to sift mountains of unstructured data, without necessarily knowing what you were looking at, and be able to query it and get answers back and identify patterns was a profound breakthrough.
That is why Hadoop is now the main operating system for data analytics supporting both structured and unstructured data.
“with large scale you miss out on agility, personalization, and customization, but big data now allows you all three.”
But it took Apple and Microsoft’s much more marketable implementations for these ideas to change the world.”
But Microsoft was born on this proposition—that people should not just pay one time for the software to be developed as part of a machine; rather, each individual user should pay to have the capabilities of each software program.
“Software is this magical thing that takes each emerging form of complexity and abstracts it away.
APIs are the actual programming commands by which computers fulfill your every wish.
“APIs make possible a sprawling array of Web-service ‘mashups,’ in which developers mix and match APIs from the likes of Google or Facebook or Twitter to create entirely new apps and services,”
When you search for nearby restaurants in the Yelp app for Android, for instance, it will plot their locations on Google Maps instead of creating its own maps,” by interfacing with the Google Maps API.
“since the user never notices when software functions are handed from one underlying Web service to another … APIs, layer by layer, hide the complexity of what is being run inside an individual computer—and the transport protocols and messaging formats hide the complexity of melding all of this together horizontally into a network.”
GitHub is the most popular platform for fostering collaborative efforts to create software.
Imagine a place that is a cross between Wikipedia and Amazon—just for software: You go online to the GitHub library and pick out the software that you need right off the shelf—for,
You end up with a virtuous cycle for the rapid learning and improving of software programs that drives innovation faster and faster.
GitHub is now the world’s largest code host.
Git, he explained, is a “distributed version control system” that was invented in 2005 by Linus Torvalds, one of the great and somewhat unsung innovators of our time.
“Think of Wikipedia—that’s a version control system for writing an open-source encyclopedia,”
The only rule is that any improvements have to be shared with the whole community.
The open-source model hosted by GitHub “is a distributed version controlled system: anyone can contribute, and the community basically decides every day who has the best version,” said Wanstrath.
“Say you wanted to post a program called ‘How to Write a Column,’ ” he explained to me. “You just publish it under your name on GitHub. I would view that online and say: ‘Hey, I have few points I would like to add.’
And if you like it, you press the ‘merge’ button. And then the next viewer sees the aggregate version. If you don’t like all of it, we have a way to discuss, comment, and review each line of code. It
“When I use Uber,” concluded Wanstrath, “all I am thinking about now is where I want to go. Not how to get there. It is the same with GitHub. Now you just have to think about what problem do you want to solve, not what tools.” You can now go to the GitHub shelf, find just what you need, take it off, improve it, and put it back for the next person. And in the process, he added, “we are getting all the friction out. What you are seeing from GitHub, you are seeing in every industry.”
Moore’s law was viewed as the magic carpet we were riding, and then we discovered we could use software and literally accelerate Moore’s law.”
Qualcomm is to mobile phones what Intel and Microsoft together were to desktops and laptops—the primary inventor, designer, and manufacturer of the microchips and software that run handheld
smartphones and tablets.
In the 1980s, the mobile phone business was just emerging. The first generation, or 1G phones, were analog devices that received and transmitted over FM radio.
The next generation, 2G phones, were based on the emerging European standard for digital cellular networks, which was called GSM (Global System for Mobile) and used TDMA (Time Division Multiple Access) as its communication protocol.
The EU then tried to lobby the rest of the world to use that standard, propelled by European companies such as Ericsson and Nokia.
On the basis of his previous research, Jacobs thought that a protocol called Code Division Multiple Access, or CDMA, might be the best way to move forward,
