- Nautilus — elegantly-designed science web ‘zine. Includes Artificial Emotions on AI, neuro, and psych efforts to recognise and simulate emotions.
- A Short Essay on 3D Printing — This hands-off approach to culpability cannot last long. If you design something to go into someone’s bathroom, it will make it’s way into their childs mouth. If someone buys, downloads and prints a case for their OUYA and they suffer an electric shock as a result, who is to blame? If a person replaces their phone case with a 3D printed one, and it doesn’t survive a drop to the floor, what then? We need to create a new chain of responsiblity for this emerging, and potentially very profitable business. (via Near Future Laboratory)
- Zuckerberg’s FWD.us PAC (Anil Dash) — One of Mark Zuckerberg’s most famous mottos is “Move fast and break things.” When it comes to policy impacting the lives of millions of people around the world, there couldn’t be a worse slogan. Let’s see if we can get FWD.us to be as accountable to the technology industry as it purports to be, since they will undoubtedly claim to have the grassroots support of our community regardless of whether that’s true or not.
- Pirate Economics — four dimensions of pirate institutions. Not BitTorrent pirates, but Berbers and arr-harr-avast-ye-swabbers nautical pirates. Pirate crews not only elected their captains on the basis of universal pirate suffrage, but they also regularly deposed them by democratic elections if they were not satisfied with their performance. Like the Berbers, or the US constitution, pirates didn’t just rely on democratic elections to keep their leaders under check. Though the captain of the ship was in charge of battle and strategy, pirate crews also used a separate democratic election to elect the ship’s quartermaster who was in charge of allocating booty, adjudicating disputes and administering discipline. Thus they had a nascent form of separation of powers.
Artificial Emotions, 3D Printing Culpability, Mr Zuckerberg Buys Washington, and Pirate Economics
Android software development at a crossroads
Apps have to get bigger and more ambitious. A key question for the developer community is how do you create big, integrated, multi-functional, configurable apps for the mobile enterprise? Curiously, Facebook is providing some answers by not using HTML5 and not attempting to make a cross-platform app. Go native, go big, and go deep.
Facebook Home is a harbinger of serious mobile apps
Facebook Home has earned positive reviews—in many cases from reviewers who had tired of Facebook and the intrusiveness of Facebook’s privacy policies and practices. Facebook Home is an example of a new kind of Android software development. It spans a variety of functions as a suite of cooperating software. It uses Android’s intent filters, high-level interprocess communication (IPC), shared databases (
ContentProvider components) and remote APIs to bond together a software product that replaces many of the standard parts of Android—as they are meant to be replaced.
Facebook Home isn’t some kind of rogue hack, nor is it a “fork” of AOSP, as Kindle Fire is. Facebook Home is a tour de force of correct Android application architecture. It takes over your phone, interface by interface, always playing by the rules, and it does so for justifiable reasons: for putting Facebook’s functionality everywhere you want to perform communications and social media functions.
Moreover, Facebook Home simply can’t be done on iPhone. iOS has a specific vision of apps that is separate from system software, while Android’s frameworks are the basis of both applications and system software. Facebook Home was built with this difference in mind: It replaces key elements of the Android system user experience. It is a suite of communicating apps. The word “app” doesn’t sufficiently describe it.
Motivated Learning, Better Hadoopery, Poignant Past Product, and Drone Imagery
- Teaching Programming to a Highly Motivated Beginner (CACM) — I don’t think there is any better way to internalize knowledge than first spending hours upon hours growing emotionally distraught over such struggles and only then being helped by a mentor. Me, too. Not struggle for struggle’s sake, but because you have built a strong mental map of the problem into which the solution can lock.
- Corona (GitHub) — Facebook opensources their improvements to Hadoop’s job tracking, in the name of scalability, latency, cluster utilization, and fairness. (via Chris Aniszczyk)
- One Man’s Trash (Bunnie Huang) — Bunnie finds a Chumby relic in a Shenzhen market stall.
- Dronestagram — posting pictures of drone strike locations to Instagram. (via The New Aesthetic)
Obstacles for big data, big data intelligence, and a privacy plugin puts Google and Facebook settings in the spotlight.
Here are a few stories from the data space that caught my attention this week.
Big obstacles for big data
For the latest issue of Foreign Policy, Uri Friedman put together a summarized history of big data to show “[h]ow we arrived at a term to describe the potential and peril of today’s data deluge.” A couple months ago, MIT’s Alex “Sandy” Pentland took a look at some of that big data potential for Harvard Business Review; this week, he looked at some of the perilous aspects. Pentland writes that to be realistic about big data, it’s important to look not only at its promise, but also its obstacles. He identifies the problem of finding meaningful correlations as one of big data’s biggest obstacles:
“When your volume of data is massive, virtually any problem you tackle will generate a wealth of ‘statistically significant’ answers. Correlations abound with Big Data, but inevitably most of these are not useful connections. For instance, your Big Data set may tell you that on Mondays, people who drive to work rather than take public transportation are more likely to get the flu. Sounds interesting, and traditional research methods show that it’s factually true. Jackpot!
“But why is it true? Is it causal? Is it just an accident? You don’t know. This means, strangely, that the scientific method as we normally use it no longer works, because there are so many possible relationships to consider that many are bound to be ‘statistically significant’. As a consequence, the standard laboratory-based question-and-answering process — the method that we have used to build systems for centuries — begins to fall apart.”
Pentland says that big data is going to push us out of our comfort zone, requiring us to conduct experiments in the real world — outside our familiar laboratories — and change the way we test the causality of connections. He also addresses issues of understanding those correlations enough to put them to use, knowing who owns the data and learning to forge new types of collaborations to use it, and how putting individuals in charge of their own data helps address big data privacy concerns. This piece, together with Pentland’s earlier big data potential post, are this week’s recommended reads.
Square cab fares, Wal-Mart looks to beat Amazon to the same-day punch, and a major player update in the mobile payments war.
Here are a few stories that caught my attention in the commerce space this week.
Square may be courting cabs
Square not only is gearing up to launch in Starbucks stores in November — it may also be looking to enter the New York City taxi cab market. Ryan Mac reports at Forbes this week that negotiations may be underway:
“Late Monday, private company expert PrivCo said that the San Francisco-based startup and the city of New York will be announcing an official partnership with the city of New York to implement Square’s payment systems across the city’s cabs. If negotiations are completed as expected, said New York City-based PrivCo, the partnership may be announced as early as this month.”
Mac reports that neither Square nor New York City’s Taxi & Limousine Commission (TLC) would confirm that a deal was in place, but he notes Square has been testing iPad credit card swipers with TLC since March.
As to its forthcoming foray into Starbucks, Lisa Baertlein at Reuters reports that further innovations are in the works even ahead of the launch. At launch, customers will be able to pay for a coffee by having a barcode scanned off a smartphone, but plans are already in the works to use Square’s GPS to identify a customer in a Starbucks location, who can then pay by giving his or her name to the cashier. Also, Cliff Burrows, president of Starbucks’ Americas region, told Baertlein that by summer 2013, customers will have the option and ability to tip using the technology.