- Australian Filter Scope Creep — The Federal Government has confirmed its financial regulator has started requiring Australian Internet service providers to block websites suspected of providing fraudulent financial opportunities, in a move which appears to also open the door for other government agencies to unilaterally block sites they deem questionable in their own portfolios.
- Embedding Actions in Gmail — after years of benign neglect, it’s good to see Gmail worked on again. We’ve said for years that email’s a fertile ground for doing stuff better, and Google seem to have the religion. (see Send Money with Gmail for more).
- What Keeps Me Up at Night (Matt Webb) — Matt’s building a business around connected devices. Here he explains why the category could be owned by any of the big players. In times like this I remember Howard Aiken’s advice: Don’t worry about people stealing your ideas. If it is original you will have to ram it down their throats.
- Image Texture Predicts Avian Density and Species Richness (PLOSone) — Surprisingly and interestingly, remotely sensed vegetation structure measures (i.e., image texture) were often better predictors of avian density and species richness than field-measured vegetation structure, and thus show promise as a valuable tool for mapping habitat quality and characterizing biodiversity across broad areas.
After a sojourn into the virtual, Silicon Valley is turning back to the real world.
In this episode of the Radar podcast series, Jon Bruner and I are joined by Mike Loukides as we muse more on software and the physical world. No coffee shop clatter in the background this time around as we were forced by geography and time to talk on the phone, but I still managed to have a good cup from my favorite local cafe in my hand. In the course of our conversation, we discovered that Mike drinks tea, so this may be his last appearance.
Our discussion ranges from the declining cost of 3D printing to ham radio antenna design. Along the way, we touch on the ease with which data scientists can build data sensing motes with open source and open hardware components. We hope you enjoy listening as much as we enjoyed talking.
Talks with the Association for Computing Machinery, Open Technology Institute, and Open Source Initiative.
Taking advantage of a recent trip to Washington, DC, I had the privilege of visiting three non-profit organizations who are leaders in the application of computers to changing society. First, I attended the annual meeting of the Association for Computing Machinery’s US Public Policy Council (USACM). Several members of the council then visited the Open Technology Institute (OTI), which is a section of New America Foundation (NAF). Finally, I caught the end of the first general-attendance meeting of the Open Source Initiative (OSI).
In different ways, these organizations are all putting in tremendous effort to provide the benefits of computing to more people of all walks of life and to preserve the vigor and creativity of computing platforms. I found out through my meetings what sorts of systemic change is required to achieve these goals and saw these organizations grapple with a variety of strategies to get there. This report is not a statement from any of these groups, just my personal observations.
Internet Filter Creep, Innovating in E-Mail/Gmail, Connected Devices Business Strategy, and Ecology Recapitulates Photography
Glass Face, Hardware Pricing: High, Hardware Pricing: Hard, Medical Image Search
- Facial Recognition in Google Glass (Mashable) — this makes Glass umpty more attractive to me. It was created in a hackathon for doctors to use with patients, but I need it wired into my eyeballs.
- How to Price Your Hardware Project — At the end of the day you are picking a price that enables you to stay in business. As @meganauman says, “Profit is not something to add at the end, it is something to plan for in the beginning.”
- Hardware Pricing (Matt Webb) — When products connect to the cloud, the cost structure changes once again. On the one hand, there are ongoing network costs which have to be paid by someone. You can do that with a cut of transactions on the platform, by absorbing the network cost upfront in the RRP, or with user-pays subscription.
- Dicoogle — open source medical image search. Written up in PLOSone paper.
Privacy: Gone in 150ms, Pen-Testing Tablet, Low-Level in Lua, and Metaphor Identification Shootout
- Behind the Banner — visualization of what happens in the 150ms when the cabal of data vultures decide which ad to show you. They pass around your data as enthusiastically as a pipe at a Grateful Dead concert, and you’ve just as much chance of getting it back. (via John Battelle)
- pwnpad — Nexus 7 with Android and Ubuntu, high-gain USB bluetooth, ethernet adapter, and a gorgeous suite of security tools. (via Kyle Young)
- Terra — a simple, statically-typed, compiled language with manual memory management [...] designed from the beginning to interoperate with Lua. Terra functions are first-class Lua values created using the terra keyword. When needed they are JIT-compiled to machine code. (via Hacker News)
- Metaphor Identification in Large Texts Corpora (PLOSone) — The paper presents the most comprehensive study of metaphor identification in terms of scope of metaphorical phrases and annotated corpora size. Algorithms’ performance in identifying linguistic phrases as metaphorical or literal has been compared to human judgment. Overall, the algorithms outperform the state-of-the-art algorithm with 71% precision and 27% averaged improvement in prediction over the base-rate of metaphors in the corpus.
Making sense of the hype-cycle scuffle.
The big data world is a confusing place. We’re no longer in a market dominated mostly by relational databases, and the alternatives have multiplied in a baby boom of diversity.
These child prodigies of the data scene show great promise but spend a lot of time knocking each other around in the schoolyard. Their egos can sometimes be too big to accept that everybody has their place, and eyeball-seeking media certainly doesn’t help.
POPULAR KID: Look at me! Big data is the hotness!
HADOOP: My data’s bigger than yours!
SCIPY: Size isn’t everything, Hadoop! The bigger they come, the harder they fall. And aren’t you named after a toy elephant?
R: Backward sentences mine be, but great power contains large brain.
SQL: Oh, so you all want to be friends again now, eh?!
POPULAR KID: Yeah, what SQL said! Nobody really needs big data; it’s all about small data, dummy.
The fact is that we’re fumbling toward the adolescence of big data tools, and we’re at an early stage of understanding how data can be used to create value and increase the quality of service people receive from government, business and health care. Big data is trumpeted in mainstream media, but many businesses are better advised to take baby steps with small data.