- Eight Docker Development Patterns (Vidar Hokstad) — patterns for creating repeatable builds that result in as-static-as-possible server environments.
- How to Make More Published Research True (PLOSmedicine) — overview of efforts, and research on those efforts, to raise the proportion of published research which is true.
- Gearpump — Intel’s “actor-driven streaming framework”, initial benchmarks shows that we can process 2 million messages/second (100 bytes per message) with latency around 30ms on a cluster of 4 nodes.
- Foundations of Data Science (PDF) — These notes are a first draft of a book being written by Hopcroft and Kannan [of Microsoft Research] and in many places are incomplete. However, the notes are in good enough shape to prepare lectures for a modern theoretical course in computer science.
How do we manage systems that are too large to understand, too complex to control, and that fail in unpredictable ways? Read more...
Recreation.gov should be a platform, not a silo.
President Obama’s well-publicized national open data policy (pdf) makes it clear that government data is a valuable public resource for which the government should be making efforts to maximize access and use. This policy was based on lessons from previous government open data success stories, such as weather data and GPS, which form the basis for countless commercial services that we take for granted today and that deliver enormous value to society. (You can see an impressive list of companies reliant on open government data via GovLab’s Open Data 500 project.)
Based on this open data policy, I’ve been encouraging entrepreneurs to invest their time and ingenuity to explore entrepreneurial opportunities based on government data. I’ve even invested (through O’Reilly AlphaTech Ventures) in one such start-up, Hipcamp, which provides user-friendly interfaces to making reservations at national and state parks.
A better system is sorely needed. The current reservation system, managed by the Active Network / Reserve America is clunky and almost unusable. Hipcamp changes all that, making it a breeze to reserve camping spots. Read more…
New issue: bioreactors and food production, modeling a worm's brain on a computer and letting it drive a robot, and more.
The fifth issue of BioCoder is here! We’ve made it into our second year: this revolution is in full swing.
Rather than talk about how great this issue is (though it is great), I’d like to ask a couple of questions. Post your answers in the comments; we won’t necessarily reply, but we will will read them and take them into account.
- We are always interested in new content, and we’ll take a look at almost anything you send to BioCoder@oreilly.com. In particular, we’d like to get more content from the many biohacker labs, incubators, etc. We know there’s a lot of amazing experimentation out there. But we don’t know what it is; we only see the proverbial tip of the iceberg. What’s the best way to find out what’s going on?
- While we’ve started BioCoder as a quarterly newsletter, that’s a format that already feels a bit stodgy. Would you be better served if BioCoder went web-native? Rather than publishing eight or 10 articles every three months, we’d publish three or four articles a month online. Would that be more useful? Or do you like things the way they are?
And yes, we do have a great issue, with articles about a low-cost MiniPCR, bioreactors and food production, and what happens when you model a worm’s brain on a computer and let it drive a robot. Plus, an interview with Kyle Taylor of the glowing plant project, the next installment in a series on lab safety, and much more. Read more…
The revolutionary thing about desktop machines is that they'll make experimentation easier.
“Mr. Frankel, who started this program, began to suffer from the computer disease that anybody who works with computers now knows about,” [Richard] Feynman later explained. “The trouble with computers is you play with them.”
— George Dyson, describing the beginning of the Manhattan Project’s computing effort in Turing’s Cathedral.
I’ve been reading George Dyson’s terrific history of the early development of the digital computer, and the quote above struck me. Even when they were little more than room-sized adding machines that had to be painstakingly programmed with punchcards, computers offered an intoxicating way to experiment. Most programmers can probably remember their first few scripts and the thrilling feeling of performing millions of operations in seconds. Computers let us take some abstracted human process and repeat it quickly, at almost no cost, with easy modification along the way. Read more…
Trina Chiasson argues that data has arrived at the same threshold as coding: code or be coded; learn to use data or be data.
Arguments from all sides have surrounded the question of whether or not everyone should learn to code. Trina Chiasson, co-founder and CEO of Infoactive, says learning to code changed her life for the better. “These days I don’t spend a lot of time writing code,” she says, “but it’s incredibly helpful for me to be able to communicate with our engineers and communicate with other people in the industry.”
Though helpful for her personally, she admits that it takes quite a lot of time and commitment to learn to code to any level of proficiency, and that it might not be the best use of time for everyone. What should people commit time to learn? How to use data. Read more…
From unique data applications to factories of the future, here are key insights from Strata + Hadoop World New York 2014.
Experts from across the data world came together in New York City for Strata + Hadoop World New York 2014. Below we’ve assembled notable keynotes, interviews, and insights from the event.
Unusual data applications and the correct way to say “Hadoop”
Hadoop creator and Cloudera chief architect Doug Cutting discusses surprising data applications — from dating sites to premature babies — and he reveals the proper (but in no way required) pronunciation of “Hadoop.”
Liza Kindred on the evolving role of data in fashion and the growing relationship between tech and fashion companies.
In this podcast episode, I talk with Liza Kindred, founder of Third Wave Fashion and author of the new free report “Fashioning Data: How fashion industry leaders innovate with data and what you can learn from what they know.” Kindred addresses the evolving role data and analytics are playing in the fashion industry, and the emerging connections between technology and fashion companies. “One of the things that fashion is doing better than maybe any other industry,” Kindred says, “is facilitating conversations with users.”
Gathering and analyzing user data creates opportunities for the fashion and tech industries alike. One example of this is the trend toward customization. Read more…