- Rinderpest Eradicated — only the second disease that mankind has managed to eradicate. This one was a measles-like virus that killed cattle and caused famines. A reminder of how astonishingly difficult it is to eradicate disease, but what a massive victory it is when it happens. (via Courtney Johnston)
- Magnetic South — the 6.3 earthquake that trashed Christchurch, New Zealand, has presented the city with a tabula rasa (or, rather, tabula rubble) for the rebuild: what should they build, how, and where? The good citizens are working on this question in many ways, one of which is this online game based on Institute for the Future’s Foresight Engine.
- TOPS-20 in a Box — write FORTRAN code on an emulated PHP-10 running TOPS-20 and, most delightfully, play the original Adventure as written by Crowther and finished by Woods. It’s like emulating the Big Bang for text adventures. When you’re done, admire the scholarship in this analysis of the original to see how much Woods added. (Text adventures are the game version of command-line interfaces, and we still have much to learn from them)
- Why Does Modern Perl Avoid UTF-8 By Default? (StackOverflow) — check out the very long and detailed answer by my coauthor, Tom Christiansen, on exactly how many thorns and traps lie in wait for the unwary “it should just WORK”er. Skip down to the “Assume Brokenness” section for the full horror. Tom’s been working with linguists and revising the Unicode chapters of the Camel, so asking “why can’t it just work” is like asking a war veteran “why don’t you just shoot all the bad guys?”.
The Direct Project is poised to become the first health Internet platform.
Given the way that healthcare is financed in the U.S., it's reasonable to expect that many doctors will have a Direct email address to communicate with other doctors and their patients in a few years.
From healthcare to finance to emergency response, data holds immense potential to help citizens and government.
The explosion of big data, open data and social data offers new opportunities to address humanity's biggest challenges. The open question is no longer if data can be used for the public good, but how.
Explaining cutting edge social media to the last industry to computerize.
As patients and practitioners gather on Twitter, the service has evolved into a peer-to-peer healthcare marketplace. That's why Twitter co-founder Biz Stone's keynote at HIMSS is so fitting.
A merging of artificial intelligence and healthcare is tougher than many realize.
People will eventually get better care from artificial intelligence, but for now, we should keep the algorithms focused on the data that we know is good and keep the doctors focused on the patients.
Disease-B-Gone, Quake Game, Text Adventures, and Unicoddling
Tables to Charts, Crowdsourcing Incentives, Domain Boondoggles, and Conquering Complexity
- Chartify — jQuery plugin to create Google charts from HTML tables. (via Rasmus Sellberg)
- Designing Incentives for Crowdsourcing Workers (Crowdflower) — In a tough turn for the sociologists and psychologists, none of the purely social/psychological treatments had any significant effects at all.
- The gTLD Boondoggle — ICANN promised back in 1998 that they would bring the world lots of new domains. So far they haven’t, the world has not come to an end, and the Internet has not collapsed. The absence of demand for new TLDs from actual users (as opposed to domain promoters and the occasional astroturf) is deafening. What we do see is a lot of concern that there will be more mistakes like .XXX, and pressure from governments both via the GAC and directly to ensure it doesn’t happen again. It’s a bugger when you go hunting for a new product’s domain name and realize “all the good ones are taken”, but that’s an argument against domain squatters/speculators not an argument for opening up new top-level-domain vistas.
- Atul Gawande’s Medical School Commencement Address (New Yorker) — every lesson in here about healthcare is just as applicable to software development. Read it. (via Courtney Johnston)
Machine-to-machine applications: what they are, what they do, and why they need their own networks.
In machine-to-machine communications, devices and sensors connect with each other or a central server rather than with human beings. Two M2M experts discuss M2M's applications in this interview.
Gamification's Failures, Crowdsourced Clinical Study, Traceability, and Faster Web
- Kathy Sierra Nails Gamification — I rarely link to things on O’Reilly sites, and have never before linked to something on Radar, but the comments here from Kathy Sierra are fantastic. She nails what makes me queasy about shallow gamification behaviours: replacing innate rewards with artificial ones papers over shitty products/experiences instead of fixing them, and don’t get people to a flow state. what is truly potentially motivating for its own sake (like getting people to try snowboarding the first few times… The beer may be what gets them there, but the feeling of flying through fresh powder is what sustains it, but only if we quit making it Just About The Beer and frickin teach them to fly). (via Jim Stogdill)
- Patient Driven Social Network Refutes Study, Publishes Its Own Results — The health-data-sharing website PatientsLikeMe published what it is calling a “patient-initiated observational study” refuting a 2008 report that found the drug lithium carbonate could slow the progression of the neurodegenerative disease amyotrophic lateral sclerosis or ALS. The new findings were published earlier this week in the journal Nature Biotechnology. (via mthomps)
- Corporate Transparency — learn where, when and by whom your chocolate bar was made, from which chocolate stock, etc. This kind of traceability and provenance information is underrated in business. (via Jim Stogdill)
- SPDY — Google’s effort to replace HTTP with something faster. It has been the protocol between Chrome and Google’s servers, now they hope it will go wider. All connections are encrypted and compressed out of the box.
Healthcare Data, C64 Emulator, Python Machine Learning, and Startup Success Stats
- E-Referral Evaluation Interim Findings — in general good, but note this: The outstanding system issues are an ongoing source of frustration and concern, including […] automated data uptake from the GP [General Practitioner=family doctor] PMS [Patient Management System], that sometimes has clearly inaccurate or contradictory information. When you connect systems, you realize the limitations of the data in them.
- c64iphone (GitHub) — the source to an iPhone/iPad app from the store, released under GPLv3. It incorporates the Frodo emulator. Sweet Freedom.
- mlpy — machine learning Python library, a high-performance Python package for predictive modeling. It makes extensive use of NumPy to provide fast N-dimensional array manipulation and easy integration of C code. (via Joshua Schachter)
- What is The Truth Behind 9 Out of 10 Startups Fail? (Quora) — some very interesting pointers and statistics, such as Hall and Woodward (2007) analyze a dataset of all VC-backed firms and show the highly skewed distribution of outcomes. VC revenue averages $5 million per VC-backed company. Founding team averages $9 million per VC-backed company (most from small probability of great success). The economically rational founding team would sell at time of VC funding for $900,000 to avoid the undiversified risk. (via Hacker News)