- Liquid Feedback — MIT-licensed voting software from the Pirate Party. See this Spiegel Online piece about how it is used for more details. (via Tim O’Reilly)
- Putting Gestures Into Objects (Ars Technica) — Disney and CMU have a system called Touché, where objects can tell whether they’re being clasped, swiped, pinched, etc. and by how many fingers. (via BoingBoing)
- Real-time Facebook ‘likes’ Displayed On Brazilian Fashion Retailer’s Clothes Racks (The Verge) — each hanger has a digital counter reflecting the number of likes.
- Foldit Games Next Play: Crowdsourcing Better Drug Design (Nature Blogs) — “We’ve moved beyond just determining structures in nature,” Cooper, who is based at the University of Washington’s Center for Game Science in Seattle, told Nature Medicine. “We’re able to use the game to design brand new therapeutic enzymes.” He says players are now working on the ground-up design of a protein that would act as an inhibitor of the influenza A virus, and he expects to expand the drug development uses of the game to small molecule design within the next year.
O'Reilly's new site for all things related to programming.
Welcome to O’Reilly Media’s Programming blog, our resource for all things related to programming. Whether you’re a professional developer, hardcore hacker, or student, I hope this site provides you with interesting ideas, ways to learn new skills, exposure to alpha geeks, and the opportunity to interact with our talented and unique editors. The best part of my days are conversations with our editors and authors, and I’d like you to benefit from the same exchange of ideas.
We’re building this blog to meet your needs with news, information, and analysis. Whether you work on front ends, back ends, or middleware, open source software or commercial, there’s something here for you. Over the coming weeks and months we’ll be publishing how-to information, interviews, and our opinions in addition to exposing you to O’Reilly’s vast products and services.
We’ve seen an explosion of interest in the creation of software over the last two years. Groups like Codecademy promise to teach anyone willing to code, even people like Mayor Bloomberg of New York; one of the most important factors in the legal fight between Google and Oracle was a judge who knew how to code; and groups like Code for America are transforming the civic landscape.
Open source remains one of the pillars of the programming community, but we’re building a very large tent — a tent that includes Windows developers, iOS developers, Oracle developers, and more. We’ll also pay attention to non-technical issues that affect programmers: jobs, developer culture, and occasional tangents into other obsessions (like food).
O’Reilly’s readers created the world we inhabit. Now, we need to bring a new generation into that world and expand it for those already making a difference. While we have a lot of ideas for the Programming blog, we want to hear your thoughts about what you want to see on the site and how you want to participate. Please let us know what you think through the comments or email me directly.
Our new research report outlines our vision for the coming-together of software and big machines.
The big machines that define modern life — cars, airplanes, furnaces, and so forth — have become exquisitely efficient, safe, and responsive over the last century through constant mechanical refinement. But mechanical refinement has its limits, and there are enormous improvements to be wrung out of the way that big machines are operated: an efficient furnace is still wasteful if it heats a building that no one is using; a safe car is still dangerous in the hands of a bad driver.
It is this challenge that the industrial internet promises to address by layering smart software on top of machines. The last few years have seen enormous advances in software and computing that can handle gushing streams of data and build nuanced models of complex systems. These have been used effectively in advertising and web commerce, where data is easy to gather and control is easy to exert, and marketers have rejoiced.
Thanks to widespread sensors, pervasive networks, and standardized interfaces, similar software can interact with the physical world — harvesting data, analyzing it in context, and making adjustments in real-time. The same data-driven approach that gives us dynamic pricing on Amazon and customized recommendations on Foursquare has already started to make wind turbines more efficient and thermostats more responsive. It may soon obviate humans as drivers and help blast furnaces anticipate changes in electricity prices. Read more…
Being both liberal and safe in programming is hard
Recent discoveries of security vulnerabilities in Rails and MongoDB led me to thinking about how people get to write software.
In engineering, you don’t get to build a structure people can walk into without years of study. In software, we often write what the heck we want and go back to clean up the mess later. It works, but the consequences start to get pretty monumental when you consider the network effects of open source.
You might think it’s a consequence of the tools we use—running fast and loose with scripting languages. I’m not convinced. Unusually among computer science courses, my alma mater taught us programming 101 with Ada. Ada is a language that more or less requires a retinal scan before you can use the compiler. It was a royal pain to get Ada to do anything you wanted: the philosophical inverse of Perl or Ruby. We certainly came up the “hard way.”
I’m not sure that the hard way was any better: a language that protects you from yourself doesn’t teach you much about the problems you can create.
But perhaps we are in need of an inversion of philosophy. Where Internet programming is concerned, everyone is quick to quote Postel’s law: “Be conservative in what you do, be liberal in what you accept from others.”
The fact of it is that being liberal in what you accept is really hard. You basically have two options: look carefully for only the information you need, which I think is the spirit of Postel’s law, or implement something powerful that will take care of many use cases. This latter strategy, though seemingly quicker and more future-proof, is what often leads to bugs and security holes, as unintended applications of powerful parsers manifest themselves.
My conclusion is this: use whatever language makes sense, but be systematically paranoid. Be liberal in what you accept, but conservative about what you believe.
Ford's OpenXC platform opens up real-time drivetrain data.
OpenXC (Ford Motor) — Ford has taken a significant step in turning its cars into platforms for innovative developers. OpenXC goes beyond the Ford Developer Program, which opens up audio and navigation features, and lets developers get their hands on drivetrain and auto-body data via the on-board diagnostic port. Once you’ve built the vehicle interface from open-source parts, you can use outside intelligence — code running on an Android device — to analyze vehicle data.
Of course, as outside software gets closer to the drivetrain, security becomes more important. OpenXC is read-only at the moment, and it promises “proper hardware isolation to ensure you can’t ‘brick’ your $20,000 investment in a car.”
Still, there are plenty of sophisticated data-machine tieups that developers could build with read-only access to the drivetrain: think of apps that help drivers get better fuel economy by changing their acceleration or, eventually, apps that optimize battery cycles in electric vehicles.
Drivers with Full Hands Get a Backup: The Car (New York Times) — John Markoff takes a look at automatic driver aides — tools like dynamic cruise control and collision-avoidance warnings that represent something of a middle ground between driverless cars and completely manual vehicles. Some features like these have been around for years, many of them using ultrasonic proximity sensors. But some of these are special, and illustrative of an important element of the industrial Internet: they rely on computer vision like Google’s driverless car. Software is taking over some kinds of machine intelligence that had previously resided in specialized hardware, and it’s creating new kinds of intelligence that hadn’t existed in cars at all. Read more…
Unraveling what programming will need for the next 10 years.
Programming is changing. The PC era is coming to an end, and software developers now work with an explosion of devices, job functions, and problems that need different approaches from the single machine era. In our age of exploding data, the ability to do some kind of programming is increasingly important to every job, and programming is no longer the sole preserve of an engineering priesthood.Over the course of the next few months, I’m looking to chart the ways in which programming is evolving, and the factors that are affecting it. This article captures a few of those forces, and I welcome comment and collaboration on how you think things are changing.
Where am I headed with this line of inquiry? The goal is to be able to describe the essential skills that programmers need for the coming decade, the places they should focus their learning, and differentiating between short term trends and long term shifts. Read more…
If we're going to build useful applications on top of the industrial Internet, we must ensure the components interoperate.
One of the most interesting points made in GE’s “Unleashing the Industrial Internet” event was GE CEO Jeff Immelt’s statement that only 10% of the value of Internet-enabled products is in the connectivity layer; the remaining 90% is in the applications that are built on top of that layer. These applications enable decision support, the optimization of large scale systems (systems “above the level of a single device,” to use Tim O’Reilly’s phrase), and empower consumers.
Given the jet engine that was sitting on stage, it’s worth seeing how far these ideas can be pushed. Optimizing a jet engine is no small deal; Immelt said that the engine gained an extra 5-10% efficiency through software, and that adds up to real money. The next stage is optimizing the entire aircraft; that’s certainly something GE and its business partners are looking into. But we can push even harder: optimize the entire airport (don’t you hate it when you’re stuck on a jet waiting for one of those trucks to push you back from the gate?). Optimize the entire air traffic system across the worldwide network of airports. This is where we’ll find the real gains in productivity and efficiency.
So it’s worth asking about the preconditions for those kinds of gains. It’s not computational power; when you come right down to it, there aren’t that many airports, aren’t that many flights in the air at one time. There are something like 10,000 flights in the air at one time, worldwide; and in these days of big data, and big distributed systems, that’s not a terribly large number. It’s not our ability to write software; there would certainly be some tough problems to solve, but certainly nothing as difficult as, say, searching the entire web and returning results in under a second. Read more…
What's interesting isn't software as a thing in itself, but software as a component of some larger system.
One of Marc Andreessen’s many accomplishments was the seminal essay “Why Software is Eating the World.” In it, the creator of Mosaic and Netscape argues for his investment thesis: everything is becoming software. Music and movies led the way, Skype makes the phone company obsolete, and even companies like Fedex and Walmart are all about software: their core competitive advantage isn’t driving trucks or hiring part-time employees, it’s the software they’ve developed for managing their logistics.
When I look at what excites me, I see a much bigger world than just software. I’ve already argued that biology is in the process of exploding, and the biological revolution could be even bigger than the computer revolution. I’m increasingly interested in hardware and gadgetry, which I used to ignore almost completely. And we’re following the “Internet of Things” (and in particular, the “Internet of Very Big Things”) very closely. I’m not saying that software is irrelevant or uninteresting. I firmly believe that software will be a component of every (well, almost every) important new technology. But what grabs me these days isn’t software as a thing in itself, but software as a component of some larger system. The software may be what makes it work, but it’s not about the software. Read more…
Salesforce's recent investments suggest it's building a developer-centric suite of tools for the cloud.
Have you ever seen Salesforce’s “no software” graphic? It’s the word “software” surrounded by a circle with a red line through it. Here’s a picture of the related (and dancing) “no software” mascot.
Now, if you consider yourself a developer, this is a bit threatening, no? Imagine sitting at a Salesforce event in 2008 in Chicago while Salesforce.com’s CEO, Marc Benioff, swiftly works an entire room of business users into an anti-software frenzy. I was there to learn about Force.com, and I’ll summarize the message I understood four years ago as “Not only can companies benefit from Salesforce.com, they also don’t have to hire developers.”
The message resonated with the audience. Salesforce had been using this approach for a decade: Don’t buy software you have to support, maintain, and hire developers to customize. Use our software-as-a-service (SaaS) instead. The reality behind Salesforce’s trajectory at the time was that it too needed to provide a platform for custom development.
Salesforce’s dilemma: They needed developers
This “no software” message was enough for the vast majority of the small-to-medium-sized business (SMB) market, but to engage with companies at the largest scale, you need APIs and you need to be able to work with developers. At the time, in 2008, Salesforce was making moves toward the developer community. First there was Apex, then there was Force.com.
In 2008, I evaluated Force.com, and while capable, it didn’t strike me as something that would appeal to most developers outside of existing Salesforce customers. Salesforce was aiming at the corporate developers building software atop competing stacks like Oracle. While there were several attempts to sell it as such, it wasn’t a stand-alone product or framework. In my opinion, no developer would assess Force.com and opt to use it as the next development platform.
This 2008 TechCrunch article announcing the arrival of Salesforce’s Developer-as-a-Service (DaaS) platform serves as a reminder of what Salesforce had in mind. They were still moving forward with an anti-software message for the business while continuing to make moves into the developer space. Salesforce built a capable platform. Looking back at Force.com, it felt more like an even more constrained version of Google App Engine. In other words, capable and scalable, but at the time a bit constraining for the general developer population. Don’t get me wrong: Force.com wasn’t a business failure by any measure; they have an impressive client list even today, but what they didn’t achieve was traction and awareness among the developer community. Read more…
What does winning look like? No enemy has been vanquished, but open source is now mainstream and a new norm.
I heard the comments a few times at the 14th OSCON: The conference has lost its edge. The comments resonated with my own experience — a shift in demeanor, a more purposeful, optimistic attitude, less itching for a fight. Yes, the conference has lost its edge, it doesn’t need one anymore.
Open source won. It’s not that an enemy has been vanquished or that proprietary software is dead, there’s not much regarding adopting open source to argue about anymore. After more than a decade of the low-cost, lean startup culture successfully developing on open source tools, it’s clearly a legitimate, mainstream option for technology tools and innovation.
And open source is not just for hackers and startups. A new class of innovative, widely adopted technologies has emerged from the open source culture of collaboration and sharing — turning the old model of replicating proprietary software as open source projects on its head. Think Git, D3, Storm, Node.js, Rails, Mongo, Mesos or Spark.
We see more enterprise and government folks intermingling with the stalwart open source crowd who have been attending OSCON for years. And, these large organizations are actively adopting many of the open source technologies we track, e.g., web development frameworks, programming languages, content management, data management and analysis tools.
We hear fewer concerns about support or needing geek-level technical competency to get started with open source. In the Small and Medium Business (SMB) market we see mass adoption of open source for content management and ecommerce applications — even for self-identified technology newbies.