This Startup Is Luring Top Talent With $3 Million Pay Packages
Posted on June 27th, 2018
Tech companies should stop pretending AI won’t destroy jobs
Posted on June 26th, 2018
Nicolas Cage Is Batshit Insane, but it’ll be quite hard to outdo the current Cage meme sweeping the country.
Posted on June 25th, 2018
How E-Commerce Marketing Will Evolve in 2018
Posted on June 24th, 2018
Six months into 2018 and we are seeing another an excellent year for the e-commerce market. Social networking, multichannel trade, last mile delivery, and several other new-age company models led to $409 billion in e-commerce earnings in 2017. All things indicate that in 2018, this years sales figure could surpass $460 billion.Let us take a look at some probable contenders which can become 2018 & 2019’s big e-commerce trends:
Voice search
Lengthy text-based conversations with Chatbots are not that convenient and texting isn’t as natural for humans as speaking. With Amazon’s Alexa, Apple’s Siri, Google’s Voice Assistant, Microsoft’s Cortana and Samsung’s S Voice already being a big hit, it’s easy to conclude that possibilities with voice are endless. Clients are gradually receding from a keyword-based research on e-commerce sites. Today, 13 percent of U.S. homes have a smart speaker, and 36 percent of those homes regularly use the device to make purchases.The tendency of voice hunt will get more powerful in 2018 and 2019 as more U.S.-based clients, in addition to global clients, will purchase smart home supporters.Native language processing, AI, and the IoT will also add growth to voice-based e-commerce business. The Walker Sands 2017 Future of Retail Study found that more than 19 percent of 1,600 U.S. consumers have already made an online purchase using voice commands.
For online shop owners, this may pose a fresh challenge. They need to up their game to match and function client voice commands. As an example, if you’re a site which sells online fashion clothes, the shop should have the ability to understand long-tailed voice orders that cite the item name and possibly some details.As of mid 2018 voice is still emerging into mainstream but we can expect rapid consumer uptake once the benefits are apparent to shoppers. Search queries using voice commands will see an upward trend.Products currently being shopped by voice are lower value items, bought as a one-time purchase. Grocery (20%), entertainment (19%), electronics (17%), and clothing (8%) are the top categories of purchases. Meanwhile, only 39 percent of the consumers say they trust the personalized product suggestions from the smart speakers, and most people are just buying something they already know.
Chatbots and messengers
- 1 in 5 consumers would consider purchasing goods and services from a chatbot.
- 40% of consumers want offers and deals from chatbots.
- Consumers are willing to spend more than $400 through a chatbot.
Thanks to chatbots, artificial intelligence isn’t just for cutting-edge tech companies like IBM Watson and Google. Chatbots can come with a mix of natural language processing, machine learning, and live operators to perform all sorts of tasks that help businesses better serve their customers. They’re growing in popularity on Facebook Messenger, Skype, Slack, Kik, and other messaging platforms.From toll-free numbers to live chat, the next big leap that e-commerce marketing will take in 2018 will be chatbots. Chatbots provide a personal way of interacting with customers.eBay first started using chatbot technology by piloting a simple Facebook Messenger tool that reminds bidders 15 minutes before an auction listing is about to end. That way, they can remember to get a last-minute bid in.
Now they’ve expanded to offering ShopBot, a virtual personal shopping assistant that helps people find items they want (at the price they want) on eBay.For online shop owners, this translates into two big advantages: It saves a lot of cash that otherwise would have to understand consumer preferences from information.Small and medium scale businesses that are not able to invest in high-end chatbots can bank on Facebook Bots and similar cost-effective services. These intelligent messenger bots can do many automated tasks like personalized product suggestions, offer customized offers, notify of price drops and so on.With clever coding the existing technologies can be made into very capable digital assistants.
Unified Commerce
Online shopping indicated the doom of physical shops and malls. A high number of shopping malls in the USA are already shutting down. Internet shopping has stayed mainstream for the previous couple of years.In 2017 a new trend started taking shape that will become more prominent in 2018 and beyond.That’s the tendency of multichannel e-commerce. In multichannel e-commerce clients would have the choice of purchasing online and picking up their bundles via an offline destination.Not any different from ordering over the phone but Unified commerce goes a step ahead and connects all the components of e-commerce real-time. The mobile, web and the offline store—everything is brought under a single umbrella under unified commerce. Speaking of phone ordering Google has some new technology in that department also.
Video marketing
It is now the present. Video has launched its way to online shop banners and perhaps even individual product pages. Long-written product descriptions tend to be perplexing and just somewhat hard to comprehend. Even though they provide an SEO advantage, media advertising provides an upper hand over textual content using infinite reusability.Additionally, clients are more interested in seeing than studying about a product. Video marketing statistics demonstrate that videos will help attain click-through-rates around 200 to 300 percent over other kinds of articles.New kinds of media such as video are also becoming ever more common. We have smart homes in 2018 but we dont yet have smart retail in its full glory. Retail kiosks are common in 2018 but lack the richness of the emerging smart technologies.
Augmented reality
Augmented Reality in eCommerce could change things around for both customers and retailers. For clients, AR would make informed decisions which are best suited to their wants and aspirations.The IKEA Place App is an excellent example of this. It helps customers to place furniture within their spaces to understand whether the measurements are true or not. A similar app would be great for designing kitchens. IKEA even asserts that the program provides a 98 percent accuracy in setting furniture digitally in spaces. More online shops will definitely follow because this helps bring in more cost-savings from product returns in the long term.
So what will happen in 2019?
Along with chatbots, Artificial Intelligence will proceed to boost eCommerce by supplying smart product suggestions. These merchandise suggestions will be attuned to client pursuits like colour, dimensions, complete-the-look options and so forth. The AI system will derive ideas based on historic shopping habits of their client in addition to according to patterns of continuing trends.Along with the aforementioned, various other tendencies and practices of 2017 continue to be prominent in 2018. For example, all online shops would need to implement HTTPS since cybersecurity and SEO standing will come to be entirely reliant on these. Many of the API’s behind the apps also require HTTPS. It may be that in a few years HTTPS replaces HTTP. Online stores can’t skip the choice of investing in an SSL certification. They’ve become essentials to conduct an internet shop. Additionally, clients become more conscious of safety measures and how they affect their purchasing experience.
Along with voice search, augmented reality, artificial, intelligence and security, e-commerce is all set to reach a new level of experience in 2018. Get ready to be surprised by your favorite online shopping websites. Expect physical retail and the online shopping experience to merge as the smart home trend spills into smart retail.Global revenue from artificial intelligence is expected to grow rapidly from $643.7 million in 2016 to $36.8 billion by 2025. And by the looks of things, ecommerce brands will take a fair share of the pie.
Craving Yellow a young Kenyan creative innovator’s authentic soul-searching blog Will Inspire You To e-commerce success.
Posted on June 21st, 2018
She’s articulated, smart and self-aware.”I think my journeys have matured me,” she says. “Sometimes I believe I’m 30 years older than I really am.”Tongoi needed to be independent from a young age as she moved away from home, to South Africa for education, at age 17. Then it was off to the US for additional studies in political science and then to Australia for her first job — where she changed direction into social network marketing and online community administration. She finds herself back in her home country of Kenya, occupied nurturing a growing company that began when her creative character sought an outlet on the journey of self-discovery she found herself undertaking.While in the US she struck pieces on the self-portraiture of women of color and what it meant to be embodied in the manner that they were.Today Craving Yellow is surely a success by any blogger’s standards
How can you turn a successful and authentic online presence into a profitable business venture? In Tongoi’s case: By diving head-first into the opportunity, without being quite fully prepared.”It has only been four months!” She chuckles as she shares the story. In her interactions with local businesses in this area she began gaining an awareness of the business and one of her mentors asked why she wasn’t producing her own merchandise to fulfill consumer needs.This was the birth of her Craving Yellow beauty box — a product which combines the ease of carefully chosen beauty products for natural hair care and information about the best way best to stick to the treatment regime.She spent about 750,000 Kenyan shillings (US$7,400) on the goods for its first consignment of boxes using an eight-week payment arrangement.
“It was a massive risk I took. I have done no market research. I took on these products on a verbal agreement, without a contract in place. I don’t consider myself a pro marketer. However, I did sell them in eight months,” she says.Observing that very first sales drive, a follower in the US commented on her blog asking if she could buy the beauty box. Her site platform was e-commerce allowed, but she had no agreements or plans for international delivery.”I started calling different providers for transport after the orders were ready, but then got a call from Vicky Wambui from DHL, inviting me to get a meeting,” Tongoi states.The DHL Express team were quite hands-on. They spoke Tongoi through all of the requirements and even physically helped pack the dispatch boxes at the same stage. A valuable negotiated shipping rate, provided because the organization believes in Tongoi’s vision, led to the present reality where one in every five boxes currently ordered is for international shipment.Considering that the item is a luxury high-end beauty box selling for 5,000 Kenyan shillings ($49), this has increased Craving Yellow’s potential market and made the company instantly more viable.
Tongoi admits that she’s not the stereotypical small business type. She is, at her heart, a creative person. For my organization, I think if I keep the human desire at the middle, the money will follow along with that the money is just like a thank you for the support provided and that really meets that a need has been there,” she says.In a really short space of time Craving Yellow has evolved from being a popular blog to becoming a new for organic beauty product customers — offering specially curated goods in the beauty shop or workshops on the subject from the Craving Yellow classes.Lately Tongoi added her first branded merchandise — the Craving Yellow shampoo pub and lace bonnets. This is a collaboration with well-known firms in Kenya that have a strength in particular goods and then produce these items for her.”I feel that as we get the delivery arrangements perfect and the goods on offer precisely right, the worldwide buyers would readily supersede my regional buyers — they do have the buying power,” Tongoi states of their future plans.
Google Just Launched a Smartphone Game to Teach Adults How to Code
Posted on June 15th, 2018
From programmable LEGO robots to mobile apps like Hopscotch, there’s no shortage of games and toys designed to get children interested in computer science. But when it comes to adults, the options to learn how to code start to look a lot less like fun and a lot more like classwork.
Over the past nine months, Google has been trying to change that through Grasshopper, a mobile game meant to teach adults the basic principles of coding. Although five thousand people have already graduated from Grasshopper’s JavaScript Fundamentals course while the app has been in testing, the search giant is revealing it and making it publicly available for the first time on Wednesday. The game is launching for iOS and Android out of Area 120, Google’s internal workshop for experimental projects.
Read more: How This Former Circus Performer is Turning Google Maps Into the Next Big Thing in Gaming
When developing Grasshopper, Google focused on three main barriers making it hard for adults to learn to code: Time, access, and money. The first point is particularly vital — when Google asked thousands of U.S. adults why they had given up on coding, the top answer was that they ran out of time, says Laura Holmes, founder of Grasshopper and a senior product manager at Google. Turning coding lessons into something more like a smartphone game makes them easier to fit into a busy schedule, she says. “Many of our users actually find spare moments when they’re sitting on the couch unwinding after work or in bed at night,” says Holmes. “They’re using those moments to learn how to code.”
Most people interested in learning how to code are hoping to do so to further their career, says Holmes, citing a survey of current Grasshopper users. It’s not difficult to understand why: LinkedIn’s list of the top job skills for 2018 was filled with abilities like mobile development, cloud computing, and data engineering, and in 2017, PayScale and CNN listed “mobile app developer” as the best job in America.
Google’s puzzle game won’t turn you into a programming wiz overnight. But by introducing players to the basic fundamentals through JavaScript, it may help them decide whether coding is a viable career switch for them. That’s why Google is also partnering with Coursera and LaunchCode to help players who want to continue pursuing computer science after completing the game discover appropriate courses and programs. The suggested classes should feel like a natural next step after finishing Grasshopper’s curriculum, according to Holmes. “We say, ‘Here’s the next one that fits well with what we’ve taught you,’” she says.
Read more: Why Classrooms Are Apple, Google, and Microsoft’s Next Big Battleground
The Grasshopper app itself looks simple and self-explanatory. When setting up the app, users will be able to choose how often they want to practice coding; Grasshopper suggests playing daily, but offers other options like every other day, twice per week, or no reminders at all. Like many games designed to teach coding, the puzzles themselves involve inputting lines of code to reach a goal. In the demonstration I saw, the player was asked to enter the correct code in order to complete an image of the French flag, with each string of code contributing more color to the picture. Grasshopper also quizzes students occasionally to make sure they’re comprehending the principles being taught in lessons. A friendly grasshopper named Grace — named after computer industry pioneer Grace Hopper — encourages players along the way.
Of course, Google is far from the first company to game-ify code lessons, nor is it the first to make such programs available on smartphones. Apps like Hopscotch and Lightbot may be positioned towards children, but anyone can use their puzzles to learn the basic principles of coding. Codecademy offers free courses in popular languages like JavaScript, Python and Ruby, whereas Google’s app specializes only in JavaScript.
But Holmes says Grasshopper isn’t trying to replace services like Codecademy. Instead, it aims to provide an introduction for those who may feel too intimidated to try coding in the first place. Part of the inspiration behind Grasshopper comes from Holmes’ own experience studying computer science at Stanford University. “You run up against a lot of these things as an adult, often being told that it’s too complicated, or you just don’t know where to start,” she says. “We’re trying to be the launchpad.”
By LISA EADICICCO April 18, 2018
http://time.com/5243949/google-grasshopper-game/
INTEL Made Smart Glasses That Look Normal
Posted on June 15th, 2018
Google loses Android battle and could owe Oracle billions of dollars
Posted on June 15th, 2018
Google just lost a major copyright case that could cost it billions of dollars and change how tech companies approach software development.
An appeals court said on Tuesday that Google violated copyright laws when it used Oracle’s open-source Java software to build the Android platform in 2009.
Tuesday’s ruling is the latest development in a topsy-turvy eight-year battle between Google(GOOG) and Oracle (ORCL).
Oracle first brought its case against Google in 2010, claiming that Android infringes two patents that Oracle holds on its Java software, a ubiquitous programming language powering everything from phones to websites.
In 2012, a jury determined that Java does not deserve protection under copyright law. Two years later, an appeals court overturned the ruling, raising the question of whether Google’s use of Oracle’s API violated copyright law.
Related: Facebook has lost $80 billion in market value
A jury determined in 2016 that Google’s use of Oracle’s APIs was legal under the copyright law’s fair use doctrine, which allows the free use of copyrighted material under specific circumstances. Oracle appealed the decision, and a judge took its side on Tuesday.
“There is nothing fair about taking a copyrighted work verbatim and using it for the same purpose and function as the original in a competing platform,” a panel of three Federal Circuit judges wrote in Tuesday’s opinion.
Oracle said in a statement on Tuesday that the recent “decision protects creators and consumers.” Google said it is weighing its next steps. It could appeal to the full slate of judges on the court.
“We are disappointed the court reversed the jury finding that Java is open and free for everyone,” a Google spokesman said in a statement. “This type of ruling will make apps and online services more expensive for users. We are considering our options.”
Related: Jury sides with Google in billion dollar Oracle suit
Another court will decide how much Google owes Oracle in damages.
As of 2016, Oracle was seeking about $9 billion from Google. But because APIs have become much more widespread over the years, a court could decide that Oracle deserves more, said Christopher Carani, a partner with McAndrews, Held & Malloy and a professor at Northwestern’s law school.
“The numbers in this case will be staggering,” he added.
The verdict is likely to eclipse the current largest copyright verdict of $1.3 billion, awarded to Oracle when it sued rival SAP in 2010.
Google isn’t the only company that stands to lose from this decision. Many others rely on open-source software to develop their own platforms. Tuesday’s ruling means that some will either have pay to license certain software or develop their own from scratch.
“The decision is going to create a significant shift in how software is developed worldwide,” Carani said. “It really means that copyright in this context has teeth.”
“Sometimes free is not really free,” he added.
— CNNMoney’s David Goldman contributed reporting.
by Danielle Wiener-Bronner @dwbronnerMarch 28, 2018: 8:44 AM ET
CNNMoney’s David Goldman contributed reporting.
http://money.cnn.com/2018/03/27/news/companies/google-oracle-case/index.html
Difference Between a coder, programmer, developer and software engineer
Posted on June 13th, 2018
The Coming Software Apocalypse
Posted on June 13th, 2018
There were six hours during the night of April 10, 2014, when the entire population of Washington State had no 911 service. People who called for help got a busy signal. One Seattle woman dialed 911 at least 37 times while a stranger was trying to break into her house. When he finally crawled into her living room through a window, she picked up a kitchen knife. The man fled.
The 911 outage, at the time the largest ever reported, was traced to software running on a server in Englewood, Colorado. Operated by a systems provider named Intrado, the server kept a running counter of how many calls it had routed to 911 dispatchers around the country. Intrado programmers had set a threshold for how high the counter could go. They picked a number in the millions.
Shortly before midnight on April 10, the counter exceeded that number, resulting in chaos. Because the counter was used to generate a unique identifier for each call, new calls were rejected. And because the programmers hadn’t anticipated the problem, they hadn’t created alarms to call attention to it. Nobody knew what was happening. Dispatch centers in Washington, California, Florida, the Carolinas, and Minnesota, serving 11 million Americans, struggled to make sense of reports that callers were getting busy signals. It took until morning to realize that Intrado’s software in Englewood was responsible, and that the fix was to change a single number.
Not long ago, emergency calls were handled locally. Outages were small and easily diagnosed and fixed. The rise of cellphones and the promise of new capabilities—what if you could text 911? or send videos to the dispatcher?—drove the development of a more complex system that relied on the internet. For the first time, there could be such a thing as a national 911 outage. There have now been four in as many years.
It’s been said that software is “eating the world.” More and more, critical systems that were once controlled mechanically, or by people, are coming to depend on code. This was perhaps never clearer than in the summer of 2015, when on a single day, United Airlines grounded its fleet because of a problem with its departure-management system; trading was suspended on the New York Stock Exchange after an upgrade; the front page of The Wall Street Journal’s website crashed; and Seattle’s 911 system went down again, this time because a different router failed. The simultaneous failure of so many software systems smelled at first of a coordinated cyberattack. Almost more frightening was the realization, late in the day, that it was just a coincidence.
“When we had electromechanical systems, we used to be able to test themexhaustively,” says Nancy Leveson, a professor of aeronautics and astronautics at the Massachusetts Institute of Technology who has been studying software safety for 35 years. She became known for her report on the Therac-25, a radiation-therapy machine that killed six patients because of a software error. “We used to be able to think through all the things it could do, all the states it could get into.” The electromechanical interlockings that controlled train movements at railroad crossings, for instance, only had so many configurations; a few sheets of paper could describe the whole system, and you could run physical trains against each configuration to see how it would behave. Once you’d built and tested it, you knew exactly what you were dealing with.
Software is different. Just by editing the text in a file somewhere, the same hunk of silicon can become an autopilot or an inventory-control system. This flexibility is software’s miracle, and its curse. Because it can be changed cheaply, software is constantly changed; and because it’s unmoored from anything physical—a program that is a thousand times more complex than another takes up the same actual space—it tends to grow without bound. “The problem,” Leveson wrote in a book, “is that we are attempting to build systems that are beyond our ability to intellectually manage.”
The software did exactly what it was told to do. The reason it failed is that it was told to do the wrong thing.
Our standard framework for thinking about engineering failures—reflected, for instance, in regulations for medical devices—was developed shortly after World War II, before the advent of software, for electromechanical systems. The idea was that you make something reliable by making its parts reliable (say, you build your engine to withstand 40,000 takeoff-and-landing cycles) and by planning for the breakdown of those parts (you have two engines). But software doesn’t break. Intrado’s faulty threshold is not like the faulty rivet that leads to the crash of an airliner. The software did exactly what it was told to do. In fact it did it perfectly. The reason it failed is that it was told to do the wrong thing. Software failures are failures of understanding, and of imagination. Intrado actually had a backup router, which, had it been switched to automatically, would have restored 911 service almost immediately. But, as described in a report to the FCC, “the situation occurred at a point in the application logic that was not designed to perform any automated corrective actions.”
This is the trouble with making things out of code, as opposed to something physical. “The complexity,” as Leveson puts it, “is invisible to the eye.”
The attempts now underway to change how we make software all seem to start with the same premise: Code is too hard to think about. Before trying to understand the attempts themselves, then, it’s worth understanding why this might be: what it is about code that makes it so foreign to the mind, and so unlike anything that came before it.
Technological progress used to change the way the world looked—you could watch the roads getting paved; you could see the skylines rise. Today you can hardly tell when something is remade, because so often it is remade by code. When you press your foot down on your car’s accelerator, for instance, you’re no longer controlling anything directly; there’s no mechanical link from the pedal to the throttle. Instead, you’re issuing a command to a piece of software that decides how much air to give the engine. The car is a computer you can sit inside of. The steering wheel and pedals might as well be keyboard keys.
Like everything else, the car has been computerized to enable new features. When a program is in charge of the throttle and brakes, it can slow you down when you’re too close to another car, or precisely control the fuel injection to help you save on gas. When it controls the steering, it can keep you in your lane as you start to drift, or guide you into a parking space. You couldn’t build these features without code. If you tried, a car might weigh 40,000 pounds, an immovable mass of clockwork.
Software has enabled us to make the most intricate machines that have ever existed. And yet we have hardly noticed, because all of that complexity is packed into tiny silicon chips as millions and millions of lines of code. But just because we can’t see the complexity doesn’t mean that it has gone away.
The programmer, the renowned Dutch computer scientist Edsger Dijkstra wrote in 1988, “has to be able to think in terms of conceptual hierarchies that are much deeper than a single mind ever needed to face before.” Dijkstra meant this as a warning. As programmers eagerly poured software into critical systems, they became, more and more, the linchpins of the built world—and Dijkstra thought they had perhaps overestimated themselves.
“Software engineers don’t understand the problem they’re trying to solve, and don’t care to.”
What made programming so difficult was that it required you to think like a computer. The strangeness of it was in some sense more vivid in the early days of computing, when code took the form of literal ones and zeros. Anyone looking over a programmer’s shoulder as they pored over line after line like “100001010011” and “000010011110” would have seen just how alienated the programmer was from the actual problems they were trying to solve; it would have been impossible to tell whether they were trying to calculate artillery trajectories or simulate a game of tic-tac-toe. The introduction of programming languages like Fortran and C, which resemble English, and tools, known as “integrated development environments,” or IDEs, that help correct simple mistakes (like Microsoft Word’s grammar checker but for code), obscured, though did little to actually change, this basic alienation—the fact that the programmer didn’t work on a problem directly, but rather spent their days writing out instructions for a machine.
“The problem is that software engineers don’t understand the problem they’re trying to solve, and don’t care to,” says Leveson, the MIT software-safety expert. The reason is that they’re too wrapped up in getting their code to work. “Software engineers like to provide all kinds of tools and stuff for coding errors,” she says, referring to IDEs. “The serious problems that have happened with software have to do with requirements, not coding errors.” When you’re writing code that controls a car’s throttle, for instance, what’s important is the rules about when and how and by how much to open it. But these systems have become so complicated that hardly anyone can keep them straight in their head. “There’s 100 million lines of code in cars now,” Leveson says. “You just cannot anticipate all these things.”
In September 2007, Jean Bookout was driving on the highway with her best friend in a Toyota Camry when the accelerator seemed to get stuck. When she took her foot off the pedal, the car didn’t slow down. She tried the brakes but they seemed to have lost their power. As she swerved toward an off-ramp going 50 miles per hour, she pulled the emergency brake. The car left a skid mark 150 feet long before running into an embankment by the side of the road. The passenger was killed. Bookout woke up in a hospital a month later.
The incident was one of many in a nearly decade-long investigation into claims of so-called unintended acceleration in Toyota cars. Toyota blamed the incidents on poorly designed floor mats, “sticky” pedals, and driver error, but outsiders suspected that faulty software might be responsible. The National Highway Traffic Safety Administration enlisted software experts from NASA to perform an intensive review of Toyota’s code. After nearly 10 months, the NASA team hadn’t found evidence that software was the cause—but said they couldn’t prove it wasn’t.
It was during litigation of the Bookout accident that someone finally found a convincing connection. Michael Barr, an expert witness for the plaintiff, had a team of software experts spend 18 months with the Toyota code, picking up where NASA left off. Barr described what they found as “spaghetti code,” programmer lingo for software that has become a tangled mess. Code turns to spaghetti when it accretes over many years, with feature after feature piling on top of, and being woven around, what’s already there; eventually the code becomes impossible to follow, let alone to test exhaustively for flaws.
“If the software malfunctions and the same program that crashed is supposed to save the day, it can’t.”
Using the same model as the Camry involved in the accident, Barr’s team demonstrated that there were more than 10 million ways for key tasks on the onboard computer to fail, potentially leading to unintended acceleration.* They showed that as little as a single bit flip—a one in the computer’s memory becoming a zero or vice versa—could make a car run out of control. The fail-safe code that Toyota had put in place wasn’t enough to stop it. “You have software watching the software,” Barr testified. “If the software malfunctions and the same program or same app that is crashed is supposed to save the day, it can’t save the day because it is not working.”
Barr’s testimony made the case for the plaintiff, resulting in $3 million in damages for Bookout and her friend’s family. According to The New York Times, it was the first of many similar cases against Toyota to bring to trial problems with the electronic throttle-control system, and the first time Toyota was found responsible by a jury for an accident involving unintended acceleration. The parties decided to settle the case before punitive damages could be awarded. In all, Toyota recalled more than 9 million cars, and paid nearly $3 billion in settlements and fines related to unintended acceleration.
There will be more bad days for software. It’s important that we get better at making it, because if we don’t, and as software becomes more sophisticated and connected—as it takes control of more critical functions—those days could get worse.
The problem is that programmers are having a hard time keeping up with their own creations. Since the 1980s, the way programmers work and the tools they use have changed remarkably little. There is a small but growing chorus that worries the status quo is unsustainable. “Even very good programmers are struggling to make sense of the systems that they are working with,” says Chris Granger, a software developer who worked as a lead at Microsoft on Visual Studio, an IDE that costs $1,199 a year and is used by nearly a third of all professional programmers. He told me that while he was at Microsoft, he arranged an end-to-end study of Visual Studio, the only one that had ever been done. For a month and a half, he watched behind a one-way mirror as people wrote code. “How do they use tools? How do they think?” he said. “How do theysit at the computer, do they touch the mouse, do they not touch the mouse? All these things that we have dogma around that we haven’t actually tested empirically.”
The findings surprised him. “Visual Studio is one of the single largest pieces of software in the world,” he said. “It’s over 55 million lines of code. And one of the things that I found out in this study is more than 98 percent of it is completely irrelevant. All this work had been put into this thing, but it missed the fundamental problems that people faced. And the biggest one that I took away from it was that basically people are playing computer inside their head.” Programmers were like chess players trying to play with a blindfold on—so much of their mental energy is spent just trying to picture where the pieces are that there’s hardly any left over to think about the game itself.
Computers had doubled in power every 18 months for the last 40 years. Why hadn’t programming changed?
John Resig had been noticing the same thing among his students. Resig is a celebrated programmer of JavaScript—software he wrote powers over half of all websites—and a tech lead at the online-education site Khan Academy. In early 2012, he had been struggling with the site’s computer-science curriculum. Why was it so hard to learn to program? The essential problem seemed to be that code was so abstract. Writing software was not like making a bridge out of popsicle sticks, where you could see the sticks and touch the glue. To “make” a program, you typed words. When you wanted to change the behavior of the program, be it a game, or a website, or a simulation of physics, what you actually changed was text. So the students who did well—in fact the only ones who survived at all—were those who could step through that text one instruction at a time in their head, thinking the way a computer would, trying to keep track of every intermediate calculation. Resig, like Granger, started to wonder if it had to be that way. Computers had doubled in power every 18 months for the last 40 years. Why hadn’t programming changed?
The fact that the two of them were thinking about the same problem in the same terms, at the same time, was not a coincidence. They had both just seen the same remarkable talk, given to a group of software-engineering students in a Montreal hotel by a computer researcher named Bret Victor. The talk, which went viral when it was posted online in February 2012, seemed to be making two bold claims. The first was that the way we make software is fundamentally broken. The second was that Victor knew how to fix it.
Bret victor does not like to write code. “It sounds weird,” he says. “When I want to make a thing, especially when I want to create something in software, there’s this initial layer of disgust that I have to push through, where I’m not manipulating the thing that I want to make, I’m writing a bunch of text into a text editor.”
“There’s a pretty strong conviction that that’s the wrong way of doing things.”
Victor has the mien of David Foster Wallace, with a lightning intelligence that lingers beneath a patina of aw-shucks shyness. He is 40 years old, with traces of gray and a thin, undeliberate beard. His voice is gentle, mournful almost, but he wants to share what’s in his head, and when he gets on a roll he’ll seem to skip syllables, as though outrunning his own vocal machinery.
Though he runs a lab that studies the future of computing, he seems less interested in technology per se than in the minds of the people who use it. Like any good toolmaker, he has a way of looking at the world that is equal parts technical and humane. He graduated top of his class at the California Institute of Technology for electrical engineering, and then went on, after grad school at the University of California, Berkeley, to work at a company that develops music synthesizers. It was a problem perfectly matched to his dual personality: He could spend as much time thinking about the way a performer makes music with a keyboard—the way it becomes an extension of their hands—as he could thinking about the mathematics of digital signal processing.
By the time he gave the talk that made his name, the one that Resig and Granger saw in early 2012, Victor had finally landed upon the principle that seemed to thread through all of his work. (He actually called the talk “Inventing on Principle.”) The principle was this: “Creators need an immediate connection to what they’re creating.” The problem with programming was that it violated the principle. That’s why software systems were so hard to think about, and so rife with bugs: The programmer, staring at a page of text, was abstracted from whatever it was they were actually making.
“Our current conception of what a computer program is,” he said, is “derived straight from Fortran and ALGOL in the late ’50s. Those languages were designed for punch cards.” That code now takes the form of letters on a screen in a language like C or Java (derivatives of Fortran and ALGOL), instead of a stack of cards with holes in it, doesn’t make it any less dead, any less indirect.
To Victor, the idea that people were trying to understand cancer by staring at a text editor was appalling.
Continue to the full article here…
https://www.theatlantic.com/technology/archive/2017/09/saving-the-world-from-code/540393/
