linkstream2 microblog

Even Amazon, a Colossus, Has Its Limits, by @mims
https://www.WSJ.com/articles/the-limits-of-amazon-1514808002 Quote: “Imagine the data-collecting power of $FB wedded to the supply-chain empire of $WMT — that’s $AMZN.” But I thought Wal-mart was pretty good at data collection & analytics!

QT:{{”
All of these moves fit into Amazon’s core mission as a data-driven instant- gratification company. Its fanaticism for customer experience is enabled by every technology the company can get its hands on, from data centers to drones. Imagine the data-collecting power of Facebook wedded to the supply-chain empire of Wal-Mart—that’s Amazon. “}}

#Estonia, the Digital Republic
https://www.NewYorker.com/magazine/2017/12/18/estonia-the-digital-republic Great description of an advanced nation built on a public rather than private computing infrastructure (X-road). Systems built on a national ID card. Laws & tech explicitly protect personal info even from a casual glance.

QT:{{”
““Let me show you how,” Beljuskina said, and led me into a room filled with medical equipment and a computer in the corner. She logged on with her own I.D. If she were to glance at any patient’s data, she explained, the access would be tagged to her name, and she would get a call inquiring why it was necessary.
…
“Instead of setting up prisoner transport to trial—fraught with security risks—Estonian courts can teleconference defendants into the courtroom from prison.”

…
Lift99, which houses thirty-two companies and five freelancers, had industrial windows, with a two-floor open-plan workspace. Both levels also included smaller rooms named for techies who had done business with Estonia. There was a Zennström Room, after Niklas Zennström, the Swedish entrepreneur who co-founded Skype, in Tallinn. There was a Horowitz Room, for the venture capitalist Ben Horowitz,”
…
“In what may have been the seminal insight of twenty-first-century Estonia, Martens realized that whoever offered the most ubiquitous and secure platform would run the country’s digital future—and that it should be an elected leadership, not profit-seeking Big Tech. …
“Kaevats told me it irked him that so many Westerners saw his country as a tech haven. He thought they were missing the point. “This enthusiasm and optimism around technology is like a value of its own,” he complained. “This gadgetry that I’ve been ranting about? This is not important.” He threw up his hands, scattering ash. “It’s about the mind-set. It’s about the culture. It’s about the human relations—what it enables us to do.””
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QT:{{”

After being harassed by spam calls, a telephone geek took matters into his own hands and devised a way to keep the person on the other end of the line engaged endlessly…..

“The idea is to keep the telemarketer on the call for as long as possible. The longer the conversation goes on, the more eccentric the robot becomes. In one sequence, the robot tells the telemarketer that a bee landed on his arm, and asks the telemarketer to keep talking as he focuses on the bee.

After seeing that the service worked, Mr. Anderson made it freely available to anyone; it works with landlines (with conference call or three-way calling service) and cellphones. To send telemarketing calls to the robot, add the phone number 214-666-4321 to your address book. Then, the next time you get a call from a telemarketer, patch the number in, merge the calls and put your phone on mute while the robot does the talking.”
“}}

A Robot That Has Fun at #Telemarketers’ Expense
https://www.NYTimes.com/2016/02/25/fashion/a-robot-that-has-fun-at-telemarketers-expense.html Quote: “The idea is to keep them on…as long as possible….The next time you get a call from a telemarketer, patch…in” 214-666-4321 & merge calls

The Serial-Killer Detector
https://www.NewYorker.com/magazine/2017/11/27/the-serial-killer-detector Journalist finds subtle yet predictive crime patterns with the computer. Wonder if #DeepLearning would be helpful here? Probably not // #CrimeMap

Qt:{{‘
A former journalist, equipped with an algorithm and the largest collection of murder records in the country, finds patterns in crime. “}}

Interesting reading. Noted the: Durst’s, Spitzer’s, Ferries, Red Hook
https://mobile.nytimes.com/2017/12/01/realestate/how-the-ferry-is-changing-the-brooklyn-queens-waterfront.html

What Does @Tesla’s Automated #Truck Mean for Truckers?
https://www.Wired.com/story/what-does-teslas-truck-mean-for-truckers/ What does it mean for drivers?! I guess: much safer highways & fewer tailgated & terrorized motorists!

Mapping #AirPollution with new mobile sensors
https://www.EDF.org/airqualitymaps Quote: “Any business that relies on heavy-duty diesel trucks can pose a health risk to its neighbors.”

QT:{{”
“This is one of several spots that caught our interest: High levels of pollutants in an area that includes homes, and this playground, close to industrial warehouses. Any business that relies on heavy-duty diesel trucks can pose a health risk to its neighbors.”
“}}

The Man Who Knows Whether Any Startup Will Live or Die
https://www.Wired.com/2015/01/growth-science Quote: “You can’t trust the model until you get all the intuition out of it.” Not sure I agree!

QT:{{”
“Swapping out your drafty old windows for new energy efficient ones could save you a bundle in the long-term, but not everyone wants to spend the time and money to retrofit their entire home or office building. Indow Windows offers inserts that can improve efficiency without the cost or hassle of replacing the windows entirely. “Some other startups have tried this, and some of the big guys are trying to respond, but there’s a lot more innovation required to pull this off than most people suspect,” Thurston says. “In a very short timeframe Indow has zoomed up to become the market leader.”

…
His approach is based on turning various pieces of qualitative information—such as whether a company is a “first mover” or “fast follower” in a market—into quantitative data that he can plug into a spreadsheet. That requires a degree of human judgement, but this also requires a certain amount of rigor or consistency.

“You can’t trust the model until you get all the intuition out of it,” Thurston says. “The hard part of that is translating the qualification into yes or no questions,” he says. “How do you define the market? How do you define first mover?””

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The Future of DNA Seq.
http://www.Nature.com/news/the-future-of-dna-sequencing-1.22787 Apps v Tech. QT: “Platforms for…#sequencing have changed dramatically…Yet the trajectories of other technologies…Internet, digital
photography…suggest…real disrupters will be the resulting applications, not the new tech”

QT:{{”
Killer applications –
Over the years, the platforms for DNA sequencing have changed dramatically (see ”). Yet the trajectories of other technologies for which there is a seemingly insatiable demand — smartphones, the Internet, digital photography — suggest that the real disrupters will be the resulting applications, not the new technologies.

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New Theory Cracks Open the Black Box of #DeepLearning
https://www.QuantaMagazine.org/new-theory-cracks-open-the-black-box-of-deep-learning-20170921/ Highlights the importance of a compression phase for generalization

QT:{{”
“Then learning switches to the compression phase. The network starts to shed information about the input data, keeping track of only the strongest features — those correlations that are most relevant to the output label. This happens because, in each iteration of stochastic gradient descent, more or less accidental correlations in the training data tell the network to do different things, dialing the strengths of its neural connections up and down in a random walk. This
randomization is effectively the same as compressing the system’s representation of the input data. As an example”
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