Later On

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Archive for February 4th, 2018

How Bikes Will Take Their Revenge on Cars and Help Us Reclaim Our Streets

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An interesting article by Marija Gavrilov at NewCo:

Big cities are going car-free. London’s Mayor Saqid Khan’s newest “London Plan” envisions that 80% of all trips in London will be made by foot, bicycle or public transport by 2041.

Without this shift away from car use, London cannot continue to grow sustainably. […] The design and layout of development should reduce the dominance of cars, and provide permeability to support active travel (public transport, walking and cycling), community interaction and economic vitality.

London is one of a number of major cities committing to the future where getting from point A to point B doesn’t depend on personal cars.

Reflected in this decision is a move towards micromobility, a trend of adopting more compact, efficient, and often shared modes of transportation in the urban setting. It is a counterweight to macromobility— transportation that relies on large vehicles for long distances and generic applications. As industry analyst Horace Dediu put it, “it’s the personal computer of 1980s.”¹

I am excited about the switch. As an enthusiastic cyclist and environmentalist, I’m quick to notice the tragedy of the commons flourishing in personal transportation, especially in the U.S. Driving in one’s own vehicle is comfortable, convenient, for some people fun. At the same time, it is seriously polluting the environment and supports a sedentary lifestyle. Both unquestionably are hurting public health outcomes.

As much as it is the means to connect, transportation has been divisive and discriminating throughout U.S. history. Observing some of the struggling areas of New Hampshire, where I happen to spend more time than I ever thought I would, has taught me that owning a car is often a prerequisite to having a job (one that barely pays for that same car).

In this article I’ll review the rise of macro- and micro- mobility in the U.S., some of the regulations that hinder micro-transportation, as well as the circumstances that could transform barriers into opportunities. Ultimately, I will briefly discuss how autonomous cars will take down the main pedestal of macromobility, the personal car.

The rise of macromobility

Macromobility was pioneered in the United States, and the rest of the world followed. The U.S. is now the second largest automobile market in the world, and in many ways represents the epicenter of macromobility — as well as the inefficiencies therein.

In the past sixty years, everyday individual mobility in the U.S. came to revolve around owning a car. Suburbia and its cars sealed the fate of American 20th century in materialism and isolation (or independence, depending how one looks at it), which de Tocqueville noted as illnesses of democracy a century earlier. Homes were decoupled from other essential places for education, work, healing, shopping, praying, and entertainment.

As James Howard Kunstler poetically notes in Geography Of Nowhere: The Rise And Decline of America’s Man-Made Landscape, automobiles have become associated with stability and freedom, winning a spot in the greater American narrative:

Some Americans were willing to give up their homes before they sold off their cars. Indeed, the car was often the best means for getting away from home and resettling elsewhere — as it was for the Okies who left their dust-blown farms in “rolling junks” and set out for California. To them, the car was more than a symbol of freedom; it embodied the elemental need of living creatures to flee adversity and seek a new home where they might thrive. . .

Continue reading. There’s quite a bit more including useful illustrations—for example, these three maps: which city is most pedestrian friendly and which most pedestrian hostile?

Written by LeisureGuy

4 February 2018 at 5:14 pm

Tackling the Internet’s Central Villain: The Advertising Business

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Farhad Manjoo reports in the NY Times:

Pretend you are the lead detective on a hit new show, “CSI: Terrible Stuff on the Internet.” In the first episode, you set up one of those crazy walls plastered with headlines and headshots, looking for hidden connections between everything awful that’s been happening online recently.

There’s a lot of dark stuff. In one corner, you have the Russian campaign to influence the 2016 presidential election with digital propaganda. In another, a rash of repugnant videos on YouTube, with children being mock-abusedcartoon characters bizarrely committing suicide on the kids’ channel and a popular vlogger recording a body hanging from a tree.

Then there’s tech “addiction,” the rising worry that adults and kids are getting hooked on smartphones and social networks despite our best efforts to resist the constant desire for a fix. And all over the internet, general fakery abounds — there are millions of fake followers on Twitter and Facebook, fake rehab centers being touted on Google and even fake review sites to sell you a mattress.

So who is the central villain in this story, the driving force behind much of the chaos and disrepute online?

This isn’t that hard. You don’t need a crazy wall to figure it out, because the force to blame has been quietly shaping the contours of life online since just about the beginning of life online: It’s the advertising business, stupid.

And if you want to fix much of what ails the internet right now, the ad business would be the perfect perp to handcuff and restrain — and perhaps even reform.

Ads are the lifeblood of the internet, the source of funding for just about everything you read, watch and hear online. The digital ad business is in many ways a miracle machine — it corrals and transforms latent attention into real money that pays for many truly useful inventions, from search to instant translation to video hosting to global mapping.

But the online ad machine is also a vast, opaque and dizzyingly complex contraption with underappreciated capacity for misuse — one that collects and constantly profiles data about our behavior, creates incentives to monetize our most private desires and frequently unleashes loopholes that the shadiest of people are only too happy to exploit.

And for all its power, the digital ad business has long been under-regulated and under-policed, both by the companies that run it and by the world’s governments. In the United States, the industry has been almost untouched by oversight, even though it forms the primary revenue stream of two of the planet’s most valuable companies, Google and Facebook.

“In the early days of online media, the choice was essentially made — give it away for free, and advertising would produce the revenue,” said Randall Rothenberg, the chief executive of the Interactive Advertising Bureau, a trade association that represents companies in the digital ad business. “A lot of the things we see now flow out from that decision.”

Mr. Rothenberg’s organization has long pushed for stronger standards for online advertising. In a speech last year, he implored the industry to “take civic responsibility for our effect on the world.” But he conceded the business was growing and changing too quickly for many to comprehend its excesses and externalities — let alone to fix them.

“Technology has largely been outpacing the ability of individual companies to understand what is actually going on,” he said. “There’s really an unregulated stock market effect to the whole thing.” . . .

Continue reading.

Written by LeisureGuy

4 February 2018 at 3:28 pm

Amazon is making AI an everyday tool

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Extremely interesting article in Wired by Steven Levy:

IN EARLY 2014, Srikanth Thirumalai met with Amazon CEO Jeff Bezos. Thirumalai, a computer scientist who’d left IBM in 2005 to head Amazon’s recommendations team, had come to propose a sweeping new plan for incorporating the latest advances in artificial intelligence into his division.

He arrived armed with a “six-pager.” Bezos had long ago decreed that products and services proposed to him must be limited to that length, and include a speculative press release describing the finished product, service, or initiative. Now Bezos was leaning on his deputies to transform the company into an AI powerhouse. Amazon’s product recommendations had been infused with AI since the company’s very early days, as had areas as disparate as its shipping schedules and the robots zipping around its warehouses. But in recent years, there has been a revolution in the field; machine learning has become much more effective, especially in a supercharged form known as deep learning. It has led to dramatic gains in computer vision, speech, and natural language processing.

In the early part of this decade, Amazon had yet to significantly tap these advances, but it recognized the need was urgent. This era’s most critical competition would be in AI—GoogleFacebookApple, and Microsoft were betting their companies on it—and Amazon was falling behind. “We went out to every [team] leader, to basically say, ‘How can you use these techniques and embed them into your own businesses?’” says David Limp, Amazon’s VP of devices and services.

Thirumalai took that to heart, and came to Bezos for his annual planning meeting with ideas on how to be more aggressive in machine learning. But he felt it might be too risky to wholly rebuild the existing system, fine-tuned over 20 years, with machine-learning techniques that worked best in the unrelated domains of image and voice recognition. “No one had really applied deep learning to the recommendations problem and blown us away with amazingly better results,” he says. “So it required a leap of faith on our part.” Thirumalai wasn’t quite ready—but Bezos wanted more. So Thirumalai shared his edgier option of using deep learning to revamp the way recommendations worked. It would require skills that his team didn’t possess, tools that hadn’t been created, and algorithms that no one had thought of yet. Bezos loved it (though it isn’t clear whether he greeted it with his trademark hyena-esque laugh), so Thirumalai rewrote his press release and went to work.

Thirumalai was only one of a procession of company leaders who trekked to Bezos a few years ago with six-pagers in hand. The ideas they proposed involved completely different products with different sets of customers. But each essentially envisioned a variation of Thirumalai’s approach: transforming part of Amazon with advanced machine learning. Some of them involved rethinking current projects, like the company’s robotics efforts and its huge data-center business, Amazon Web Services (AWS). Others would create entirely new businesses, like a voice-based home appliance that would become the Echo.

The results have had an impact far beyond the individual projects. Thirumalai says that at the time of his meeting, Amazon’s AI talent was segregated into isolated pockets. “We would talk, we would have conversations, but we wouldn’t share a lot of artifacts with each other because the lessons were not easily or directly transferable,” he says. They were AI islands in a vast engineering ocean. The push to overhaul the company with machine learning changed that.

While each of those six-pagers hewed to Amazon’s religion of “single-threaded” teams—meaning that only one group “owns” the technology it uses—people started to collaborate across projects. In-house scientists took on hard problems and shared their solutions with other groups. Across the company, AI islands became connected. As Amazon’s ambition for its AI projects grew, the complexity of its challenges became a magnet for top talent, especially those who wanted to see the immediate impact of their work. This compensated for Amazon’s aversion to conducting pure research; the company culture demanded that innovations come solely in the context of serving its customers.

Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.

It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in a recommendations system that now runs on a totally new machine-learning infrastructure. Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.

“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”

Maybe the force.

The Alexa Effect

The flagship product of Amazon’s push into AI is its breakaway smart speaker, the Echo, and the Alexa voice platform that powers it. These projects also sprang from a six-pager, delivered to Bezos in 2011 for an annual planning process called Operational Plan One. One person involved was an executive named Al Lindsay, an Amazonian since 2004, who had been asked to move from his post heading the Prime tech team to help with something totally new. “A low-cost, ubiquitous computer with all its brains in the cloud that you could interact with over voice—you speak to it, it speaks to you,” is how he recalls the vision being described to him.

But building that system—literally an attempt to realize a piece of science fiction, the chatty computer from Star Trek—required a level of artificial intelligence prowess that the company did not have on hand. Worse, of the very few experts who could build such a system, even fewer wanted to work for Amazon. Google and Facebook were snapping up the top talent in the field. “We were the underdog,” Lindsay, who is now a VP, says. . .

Continue reading.

Written by LeisureGuy

4 February 2018 at 9:16 am

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