- ShareFest — peer-to-peer file sharing in the browser. Source on GitHub. (via Andy Baio)
- Media for Thinking the Unthinkable (Bret Victor) — “Right now, today, we can’t see the thing, at all, that’s going to be the most important 100 years from now.” We cannot see the thing. At all. But whatever that thing is — people will have to think it. And we can, right now, today, prepare powerful ways of thinking for these people. We can build the tools that make it possible to think that thing. (via Matt Jones)
- McKinsey Report on Disruptive Technologies (McKinsey) — the list: Mobile Internet; Automation of knowledge work; Internet of Things; Cloud technology; Advanced Robotics; Autonomous and near-autonomous vehicles; Next-generation genomics; Energy storage; 3D Printing; Advanced Materials; Advanced Oil and Gas exploration and recovery; Renewable energy.
- The Only Public Transcript of the Bradley Manning Trial Will be Produced on a Crowd-Funded Typewriter — [t]he fact that a volunteer stenographer is providing the only comprehensive source of information about such a monumental event is pretty absurd.
In-Browser p2p, Thinking About The Future, Disruptive Tech, and Crowdsourcing Transcription
Facebook scraping could lead to machine-generated spam so good that it's indistinguishable from legitimate messages.
A recent blog post inquired about the incidence of Facebook-based spear phishing: the author suddenly started receiving email that appeared to be from friends (though it wasn’t posted from their usual email addresses), making the usual kinds of offers and asking him to click on the usual links. He wondered whether this was a phenomenon and how it happened — how does a phisherman get access to your Facebook friends?
The answers are “yes, it happens” and “I don’t know, but it’s going to get worse.” Seriously, my wife’s name has been used in Facebook phishing. A while ago, several of her Facebook friends said that her email account had been hacked. I was suspicious; she only uses Gmail, and hacking Google isn’t easy, particularly with two-factor authentication. So, I asked her friends to send me the offending messages. It was obvious that they hadn’t come from my wife’s account; they were Yahoo accounts with her name but an unrecognizable email address, exactly what this blogger had seen.
How does this happen? How can a phisher discover your name and your Facebook friends? I don’t know, but Facebook is such a morass of weird and conflicting security settings that it’s impossible to know just how private or how public you are. If you’ve ever friended people you don’t know (a practice that remains entirely too common), and if you’ve ever enabled visibility to friends of friends, you have no idea who has access to your conversations.
Interesting Themes, Distributed Systems Failure Modes, Gesture Sensing Through Wifi, and Bad Taste Agile
- OATV Fund III Pitch Deck (Slideshare) — contains a list of what they were investing in, and what they want to invest in with the new round. Then: Quantified self; Internet subsystems; Smart networks of things; Manipulation and visualization of big data; sustainability; Maker movement. Now: Quantified Self Pro; Maker Pro; Hacking Education; Hidden Economies; Operations as Competitive Advantage; A Router in Every Pocket; The Internet Operating System. The move to “Pro” interests me, too. (via Bryce Roberts)
- The Network is Reliable — Many applications silently degrade when the network fails, and resulting problems may not be understood for some time—if they are understood at all. [...] much of what we know about the failure modes of real-world distributed systems is founded on guesswork and rumor. [...] In this post, we’d like to bring a few of these stories together. We believe this is a first step towards a more open and honest discussion of real-world partition behavior, and, ultimately, more robust distributed systems design.
- Wisee (PDF) — recognising gestures using disturbances in the (wifi) force. Our results show that WiSee can identify and classify a set of nine gestures with an average accuracy of 94%. (via BoingBoing)
- Why Your Users Hate Agile Development (IT World) — What developers see as iterative and flexible, users see as disorganized and never-ending. Here’s how some experienced developers have changed that perception. (via Slashdot)
WeatherSpark, a great nerdy way to see the weather forecast.
- Urban Outfitters and Anthropologie are based in a beautiful campus on the site of the Philadelphia Navy Yard.
- George Dyson’s excellent Turing’s Cathedral is a history of early computing. (Related to another part of our conversation, about legacy systems, he has also written about companies that still use punch cards.)
- The New Yorker on efforts to find the legendary White City in Honduras using laser rangefinders.
Tom Stuart's new book will shed light on what you're really doing when you're programming.
Understanding Computation started from Tom’s talk Programming with Nothing, which he presented at Ruby Manor in 2011. That talk was a tour-de-force: it showed how to implement a more-or-less complete programming system without using any libraries, methods, classes, objects, or even control structures, assignments, arrays, strings, or numbers. It was, literally, programming with nothing. And it was an eye-opener.
Shortly after I saw the conference video, I talked to Tom to ask if we could do more like this. And amazingly, the answer was “yes.” He was very interested in teaching the theory of computing through Ruby, using similar techniques. What does a program mean? What does it mean for something to be a program? How do we build languages that can handle ever more flexible abstractions? What kinds of problems can’t we solve computationally? It’s all here, and it’s all clearly demonstrated via Ruby code. It’s not code that you’d ever use in a real application (trust me, doing arithmetic without numbers, assignments, and control statements is ridiculously slow). But it is code that will expand your mind and leave you with a much better understanding of what you’re doing when you’re programming.
It's not the data itself but what you do with it that counts.
This post originally appeared on Cumulus Partners. It’s republished with permission.
Quentin Hardy’s recent post in the Bits blog of The New York Times touched on the gap between representation and reality that is a core element of practically every human enterprise. His post is titled “Why Big Data is Not Truth,” and I recommend it for anyone who feels like joining the phony argument over whether “big data” represents reality better than traditional data.
In a nutshell, this “us” versus “them” approach is like trying to poke a fight between oil painters and water colorists. Neither oil painting nor water colors are “truth”; both are forms of representation. And here’s the important part: Representation is exactly that — a representation or interpretation of someone’s perceived reality. Pitting “big data” against traditional data is like asking you if Rembrandt is more “real” than Gainsborough. Both of them are artists and both painted representations of the world they perceived around them.
The problem with false arguments like the one posed by Hardy is that they obscure the value of data — traditional data and big data — and the impact of data on our culture. I’m now working my way through “Raw Data” is an Oxymoron, an anthology of short essays about data. I recommend it for anyone who is seriously interested in thinking about the many ways in which data has influenced (and continues influencing) our lives. I especially recommend “facts and FACTS: Abolitionists’ Database Innovations,” by Ellen Gruber Garvey. As its title suggests, the essay focuses on what proves to be an absolutely fascinating period of U.S. history in which the anti-slavery movement harvested data from real advertisements in Southern newspapers to paint a vivid and believable picture of the routine horrors inflicted by the slave system on real human beings.
That 19th century use of data mining built support for the anti-slavery movement, both in the U.S. and in England. The data played a key role in making the case for abolishing slavery — even though it required the bloodiest war in U.S. history to make abolition a fact.
Data itself has no quality. It’s what you do with it that counts.