In some spare time last year I worked on reworking a story I'd written for TechTarget on the topic of machine learning and related data infrastructure. I spoke with a few users in the story, so the reworking focuses on their end-use applications, while also covering vendors and technology employed. I did this as a Sway multimedia presentation. I faltered in final completion, in that an audio track was the proverbial bridge too far. So I call it a failure (experience tells us to jump from projects that are "projects of one" but thought it wa worth posting here, for experimental purposes. To read the story it is based on please go to "Machine Learning tools pose educational challenges for users." - Jack Vaughan
Wednesday, April 12, 2017
Monday, April 10, 2017
But,it worked on my machine . . .
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Courtesy: A B. Normal |
RELATED
http://www.nature.com/nrn/journal/v18/n2/full/nrn.2016.167.html
http://www.tvworldwide.com/events/nsf/170329/default.cfm
http://www.tvworldwide.com/events/nsf/170329/default.cfm
Sunday, April 2, 2017
The evening of a playing field?
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Hand Of The Buddha |
This week, the House voted to upend Obama era FTC regulations that forbade ISPs from selling individuals' browser activity data. The group was to be put somewhat on the outside on the action of what is called big data - required to get formal permission from customers in order to sell browser histories to adtech markets - the ones dominated by Facebook and Google.
What's the difference between an ISP and a Google? Google provides a free service as part of a (admittedly murky) quid pro quo. You get free browser and free search - and you tacitly give them the right to use you as a datum. With the ISP, you pay them - and not with a lot of choice either, as they are more often than not a monopoly in your neighborhood.
The stakes ISPs stuck in the Internet are deep. It can hardly be said this legislation is the evening of a playing field. Several of the companies have pledged to ask for permissions of customers before selling their (anonymized) browser history. It's likely best alled a feel good gesture on the part of the people pulling the puppet strings of government these days. You know, "Monday, geld the EPA." "Tuesday, affirm the right to kill sleeping bears in National Parks." "Wednesday, toss the ISPs a big data bone." - Jack Vaughan
RELATED
http://www.zdnet.com/article/isps-were-not-going-to-sell-your-web-browsing-data/
http://continuations.com/post/158773876945/government-just-gave-your-isp-even-more-power-you
https://www.forbes.com/sites/thomasbrewster/2017/03/30/fcc-privacy-rules-how-isps-will-actually-sell-your-data
https://www.wired.com/2017/03/big-cables-case-selling-data-doesnt-hold/
SOURCES
Cards Against Humanity creator Max Temkin
Matthew Hogan, CEO at DataCoup
ALBERT WENGER, a partner at Union Square Ventures, author "World After Capital”
Dallas Harris, a policy fellow with consumer advocacy group Public Knowledge.
Wednesday, March 29, 2017
We have met the enemy and it is us
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“Eclairage”, in Nouveau Larousse Encyclopedia |
Many social categories were designed to control, coerce and even oppress their targets. The poor, the unmarried mother, the illegitimate child, the black, the unemployed, the disabled, the dependent elderly – none of these social categories of person is a neutral framing of individual or collective circumstances. They are instead a judgement on their place in modernity and material grounds for research, analysis and policy interventions of various kinds. Two centuries after the first big data revolution many of these categories remain with us almost unchanged and, given what we know of their consequences, we have to ask what will be their situation when this second data revolution draws to a close?
On many a dark hour I have pondered technology's impact on science...and it usually comes down to the fact that the existing social and economic order is almost definitely going to make its mark on the tools of progress, as our author's here write: Where they find reason to be fearful is the likelihood of "the continuity of ideologically informed notions of ourselves and others and the reproduction of such ideologies in and through our new digital environments." Or as Pogo would have it: We have met the enemy and it is us.
http://blogs.lse.ac.uk/impactofsocialsciences/2015/10/13/ideological-inheritances-in-the-data-revolution/
Tuesday, March 28, 2017
The science of data science
http://news.harvard.edu/gazette/story/2017/03/co-directors-of-newly-launched-harvard-data-science-initiative-discuss-new-era/
Thursday, January 26, 2017
Tuesday, January 17, 2017
Monday, December 26, 2016
Big Data Pyscho
What's going on behind that Facebook quiz? Cambridge Analytica gets a look at personality scores and, thanks to Facebook, gains access to their profiles and real names. The firm sells analytics, data, profiles. It's what they call big data psychographics.
The big data world that I work in has a sort of a hangover going on right now – some dizzy blur after a long period of heady growth. Something happened in the way of a Godsmack, on the road to Antioch, in the shape of Brexit and Donald Trump’s surprising rise. For many a wonks, it is no surprise.
Anyone who looks objectively at the data analytics of this or any day knows there is plenty of room for mistakes. As with any hot technology, there's also a lot of space for hyperbole. The journalists’ job is to keep an eye on the chance of failure at the same time he reports the assertions of people making waves with that hot technology.
It is therefore a good time for us to consider the recent article penned by Sue Halprin for the New York Review of Books, which starts with a vignette describing the number of data points - 98 - that Facebook collects on each of a gazillion members. There is some hilarity, as the writer uncovers the false persona a Facebook might construct about here – or you, or me.
Halpren learns by digging into Facebook that the uber site mistakenly views here a guy, probably a gay guy because she tend to evince gay guy characteristics. That is one that algorithm hath writ because Halpren reads The New York Times (and the New York Review of Books.
She writes that the big data proponents want us to believe that data analysis will deliver to us a truth that is free of messiness or idiosyncrasy. Truth is full of such, but humans are prepared to gloss over.
Data science today tends toward the reductive – it puts people in compartments. Studies prove this! And underlying the whole big data wave is advertising. Which has always had an aspect of whimsy and subterfuge? In the days of old, we sent our children to school to learn this to protect them. To often now the kids are sent to the better schools to figure out how to exploit the subterfuge. According to Halpren, we need to recognize the fallibility of human beings is written into the algorithms that they write. - Jack Vaughan
They Have Right Now Another You - NYRB
The big data world that I work in has a sort of a hangover going on right now – some dizzy blur after a long period of heady growth. Something happened in the way of a Godsmack, on the road to Antioch, in the shape of Brexit and Donald Trump’s surprising rise. For many a wonks, it is no surprise.
Anyone who looks objectively at the data analytics of this or any day knows there is plenty of room for mistakes. As with any hot technology, there's also a lot of space for hyperbole. The journalists’ job is to keep an eye on the chance of failure at the same time he reports the assertions of people making waves with that hot technology.
It is therefore a good time for us to consider the recent article penned by Sue Halprin for the New York Review of Books, which starts with a vignette describing the number of data points - 98 - that Facebook collects on each of a gazillion members. There is some hilarity, as the writer uncovers the false persona a Facebook might construct about here – or you, or me.
Halpren learns by digging into Facebook that the uber site mistakenly views here a guy, probably a gay guy because she tend to evince gay guy characteristics. That is one that algorithm hath writ because Halpren reads The New York Times (and the New York Review of Books.
She writes that the big data proponents want us to believe that data analysis will deliver to us a truth that is free of messiness or idiosyncrasy. Truth is full of such, but humans are prepared to gloss over.
Data science today tends toward the reductive – it puts people in compartments. Studies prove this! And underlying the whole big data wave is advertising. Which has always had an aspect of whimsy and subterfuge? In the days of old, we sent our children to school to learn this to protect them. To often now the kids are sent to the better schools to figure out how to exploit the subterfuge. According to Halpren, we need to recognize the fallibility of human beings is written into the algorithms that they write. - Jack Vaughan
They Have Right Now Another You - NYRB
Thursday, December 1, 2016
Hedger with time on hands bets he can improve boffin computing
Retired billionaire hedge fund manager James H. Simons will fund a research institute to apply advanced computing techniques to scientific problems.
A New York Times story by Kenneth Chang, says Simons feels he has identified a weakness in academia, where science students in research so often turn to computer programming only because it is necessary to their research.
As they move up or out of their profession their software tool creations go too. No V.2.'s
The software that derives from the “Flatiron Institute’s” efforts will be made available for all scientists, it is said. Up first: Computational biology. Big data analytics seems to be a special focus.
I am not sure about the premise. So many great programmers started as students in the sciences! So much in high performance computing was driven by academic scientist too.
Many of the recent advances in big data have happened beyond the ken of science and academia, it’s true. But Spark? Machine learning? Well, much of that work came out of the academy.
From a press release:
Would it be good to have a new effort that served as a new hub for advances in scientific computation? Yes. This will be an interesting development to watch. – Jack Vaughan
A New York Times story by Kenneth Chang, says Simons feels he has identified a weakness in academia, where science students in research so often turn to computer programming only because it is necessary to their research.
As they move up or out of their profession their software tool creations go too. No V.2.'s
The software that derives from the “Flatiron Institute’s” efforts will be made available for all scientists, it is said. Up first: Computational biology. Big data analytics seems to be a special focus.
I am not sure about the premise. So many great programmers started as students in the sciences! So much in high performance computing was driven by academic scientist too.
Many of the recent advances in big data have happened beyond the ken of science and academia, it’s true. But Spark? Machine learning? Well, much of that work came out of the academy.
From a press release:
The FI is the first multidisciplinary institute focused entirely on computation. It is also the first center of its kind to be wholly supported by private philanthropy, providing a permanent home for up to 250 scientists and collaborating expert programmers all working together to create, deploy and support new state-of-the-art computational methods. Few existing institutions support the combination of scientists and programmers, instead leaving programming to relatively impermanent graduate students and postdoctoral fellows, and none have done so at the scale of the Flatiron Institute or with such a broad scope, at a single location...The institute will hold conferences and meetings and serve as a focal point for computational science around the world.
Would it be good to have a new effort that served as a new hub for advances in scientific computation? Yes. This will be an interesting development to watch. – Jack Vaughan
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