Tuesday, December 30. 2014The fall of GPL and the rise of permissive open-source licensesVia ZDNet -----
I know very few open-source programmers, no matter how skilled they may with the intricacies of C++, who relish learning about the ins and outs of open-source licenses. I can't blame them. Like it or not, though, picking an open-source license is a necessity. The Open Source Initiative has long provided vital open-source licensing reference information, but it still left programmers more puzzled than informed. Lately, OSI-related sites, such as Choose a License and the open-source license FAQ on GitHub, have made it easier, but some programmers haven't been bothering with any license at all.Idiots. Things have improved a little. In July 2013 when Black Duck Software found that 77 percent of projects on GitHub have no declared license. Earlier that year Aaron Williamson, senior staff counsel at the Software Freedom Law Center, discovered that 85.1 percent of GitHub programs had no license. In 2014, many GitHub programmers, using arguably the most popular code hosting system in the world, still don't use any license at all. That's a big mistake. If you don't have a license, you're leaving the door open for people to fool with your code. You may think that's just fine... just like the poor sods did who used a permissive Creative Common license for "their" photographs that they'd stored on Yahoo's Flikr only to discover that Yahoo had started to sell prints of their photos ... and keeping all the money. Maybe you're cool with that. I'm not.
Now, as Stephen O'Grady, co-founder of Red Monk, a major research group, has observed, as software is shifting to being used more in a service mode rather than deployed, you may not need to protect your code with a more restrictive license such as the GPLv3 since "if the code is not a competitive advantage, it is likely not worth protecting." Even in the case of code with little intrinsic value, however, O'Grady believes that, "permissive licenses [such as the MIT License] are a perfect alternative." So while O'Grady using Black Duck data found that "the GPL has been the overwhelmingly most selected license," these two licenses, GPLv2 and v3 are, "no longer more popular than most of the other licenses put together." Instead, "The three primary permissive license choices (Apache/BSD/MIT) ... collectively are employed by 42 percent. They represent, in fact, three of the five most popular licenses in use today." These permissive licenses has been gaining ground at GPL's expense. The two biggest gainers, the Apache and MIT licenses, were up 27 percent, while the GPLv2, Linux's license, has declined by 24 percent. This trend towards more permissive licensing is not, however, just the result of younger programmers switching to thinking of code as means to an end for a cloud services such as Software-as-a-Service (SaaS). Instead, it's been moving that way since 2004 according to a 2012 study by Donnie Berkholz, a Red Monk analyst. Berkholz learned, using data from Ohloh, an open-source code research project now known as Open Hub, that "Since 2010, this trend has reached a point where permissive is more likely than copyleft [GPL] for a new open-source project." I'm not sure that's wise, but this is 2014, not 1988. Many program's functionality are now delivered as a service rather than from a program residing on your computer. What I do know, though, is that if you want some say in how your code will be used tomorrow, you still need to put in under some kind of license. Yes, without any license, your code defaults to falling under copyright law. In that case, legally speaking no one can reproduce, distribute, or create derivative works from your work. You may or may not want that. In any case, that's only the theory. In practice you'd find defending your rights to be difficult. You should also keep in mind that when you "publish" your code on GitHub, or any other "public" site, you're giving up some of your rights. Which ones? Well, it depends on the site's Terms of Service. On GitHub, for example, if you choose to make your project repositories public -- which is probably the case or why would be on GitHub in the first place? --then you've agreed to allow others to view and fork your repositories. Notice the word "fork?" Good luck defending your copyright. Seriously, you can either figure out what you want to do with your code before you start exposing it to the world, or you can do it after it's become a problem. Me? I think figuring it out first is the smart play.
Friday, December 19. 2014Bots Now Outnumber Humans on the WebVia Wired -----
Diogo Mónica once wrote a short computer script that gave him a secret weapon in the war for San Francisco dinner reservations. This was early 2013. The script would periodically scan the popular online reservation service, OpenTable, and drop him an email anytime something interesting opened up—a choice Friday night spot at the House of Prime Rib, for example. But soon, Mónica noticed that he wasn’t getting the tables that had once been available. By the time he’d check the reservation site, his previously open reservation would be booked. And this was happening crazy fast. Like in a matter of seconds. “It’s impossible for a human to do the three forms that are required to do this in under three seconds,” he told WIRED last year. Mónica could draw only one conclusion: He’d been drawn into a bot war. Everyone knows the story of how the world wide web made the internet accessible for everyone, but a lesser known story of the internet’s evolution is how automated code—aka bots—came to quietly take it over. Today, bots account for 56 percent of all of website visits, says Marc Gaffan, CEO of Incapsula, a company that sells online security services. Incapsula recently an an analysis of 20,000 websites to get a snapshot of part of the web, and on smaller websites, it found that bot traffic can run as high as 80 percent. People use scripts to buy gear on eBay and, like Mónica, to snag the best reservations. Last month, the band, Foo Fighters sold tickets for their upcoming tour at box offices only, an attempt to strike back against the bots used by online scalpers. “You should expect to see it on ticket sites, travel sites, dating sites,” Gaffan says. What’s more, a company like Google uses bots to index the entire web, and companies such as IFTTT and Slack give us ways use the web to use bots for good, personalizing our internet and managing the daily informational deluge. But, increasingly, a slice of these online bots are malicious—used to knock websites offline, flood comment sections with spam, or scrape sites and reuse their content without authorization. Gaffan says that about 20 percent of the Web’s traffic comes from these bots. That’s up 10 percent from last year. Often, they’re running on hacked computers. And lately they’ve become more sophisticated. They are better at impersonating Google, or at running in real browsers on hacked computers. And they’ve made big leaps in breaking human-detecting captcha puzzles, Gaffan says. “Essentially there’s been this evolution of bots, where we’ve seen it become easier and more prevalent over the past couple of years,” says Rami Essaid, CEO of Distil Networks, a company that sells bot-blocking software. But despite the rise of these bad bots, there is some good news for the human race. The total percentage of bot-related web traffic is actually down this year from what it was in 2013. Back then it accounted for 60 percent of the traffic, 4 percent more than today.
Thursday, December 18. 2014BitTorrent Opens Alpha For Maelstrom, Its New, Distributed, Torrent-Based Web BrowserVia TechCrunch -----
BitTorrent, the peer-to-peer file sharing company, is today opening an alpha test for its latest stab at disrupting — or at least getting people to rethink — how users interact with each other and with content over the Internet. Project Maelstrom is BitTorrent’s take on the web browser: doing away with centralised servers, web content is instead shared through torrents on a distributed network. BitTorrent years ago first made a name for itself as a P2P network for illicit file sharing — a service that was often used to share premium content for free at a time when it was hard to get legal content elsewhere. More recently, the company has been applying its knowledge of distributed architecture to tackle other modern file-sharing problems, producing services like Sync to share large files with others, Bundle for content makers to have a way of distributing and selling content; and the Bleep messaging service. These have proven attractive to people for a number of reasons. For some, it’s about more efficient services — there is an argument to be made for P2P transfers of large files being faster and easier than those downloaded from the cloud — once you’ve downloaded the correct local client, that is (a hurdle in itself for some). For others, it is about security. Your files never sit on any cloud, and instead stay locally even when they are shared. This latter point is one that BitTorrent has been playing up a lot lately, in light of all the revelations around the NSA and what happens to our files when they are put onto cloud-based servers. (The long and short of it: they’re open to hacking, and they’re open to governments and others’ prying fingers.) In the words of CEO Eric Klinker, Maelstrom is part of that line of thinking that using P2P can help online content run more smoothly. “What if more of the web worked the way BitTorrent does?” he writes of how the company first conceived of the problem. “Project Maelstrom begins to answer that question with our first public release of a web browser that can power a new way for web content to be published, accessed and consumed. Truly an Internet powered by people, one that lowers barriers and denies gatekeepers their grip on our future.” Easy enough to say, but also leaving the door open to a lot of questions. For now, the picture you see above is the only one that BitTorrent has released to give you an idea of how Maelstrom might look. Part of the alpha involves not just getting people to sign up to use it, but getting people signed up to conceive of pages of content to actually use. “We are actively engaging with potential partners who would like to build for the distributed web,” a spokesperson says. Nor is it clear what form the project will take commercially. Asked about advertising — one of the ways that browsers monetise today — it is “too early to tell,” the spokesperson says. “Right now the team is focused on building the technology. We’ll be evaluating business models as we go, just as we did with Sync. But we treat web pages, along with distributed web pages the same way other browsers do. So in that sense they can contain any content they want.” That being said, it won’t be much different from what we know today as “the web.” “HTML on the distributed web is identical to HTML on the traditional web. The creation of websites will be the same, we’re just provided another means for distributing and publishing your content,” he adds. In that sense, you could think of Maelstrom as a complement to what we know as web browsers today. “We also see the potential that there is an intermingling of HTTP and BitTorrent content across the web,” he says. It sounds fairly radical to reimagine the entire server-based architecture of web browsing, but it comes at a time when we are seeing a lot of bumps and growing pains for businesses over more traditional services — beyond the reasons that consumers may have when they opt for P2P services. BitTorrent argues that the whole net neutrality debate — where certain services that are data hungry like video service Netflix threaten to be throttled because of their strain on ISP networks — is one that could be avoided if those data-hungry services simply opted for different ways to distribute their files. Again, this highlights the idea of Maelstrom as a complement to what we use today. “As a distributed web browser, Maelstrom can help relieve the burden put on the network,” BitTorrent says. “It can also help maintain a more neutral Internet as a gatekeeper would not be able to identify where such traffic is originating.
Tuesday, December 16. 2014We’ve Put a Worm’s Mind in a Lego Robot's BodyVia Smithsonian -----
If the brain is a collection of electrical signals, then, if you could catalog all those those signals digitally, you might be able upload your brain into a computer, thus achieving digital immortality. While the plausibility—and ethics—of this upload for humans can be debated, some people are forging ahead in the field of whole-brain emulation. There are massive efforts to map the connectome—all the connections in the brain—and to understand how we think. Simulating brains could lead us to better robots and artificial intelligence, but the first steps need to be simple. So, one group of scientists started with the roundworm Caenorhabditis elegans, a critter whose genes and simple nervous system we know intimately. The OpenWorm project has mapped the connections between the worm’s 302 neurons and simulated them in software. (The project’s ultimate goal is to completely simulate C. elegans as a virtual organism.) Recently, they put that software program in a simple Lego robot. The worm’s body parts and neural networks now have LegoBot equivalents: The worm’s nose neurons were replaced by a sonar sensor on the robot. The motor neurons running down both sides of the worm now correspond to motors on the left and right of the robot, explains Lucy Black for I Programmer. She writes: ---
--- Timothy Busbice, a founder for the OpenWorm project, posted a video of the Lego-Worm-Bot stopping and backing:
The simulation isn’t exact—the program has some simplifications on the thresholds needed to trigger a "neuron" firing, for example. But the behavior is impressive considering that no instructions were programmed into this robot. All it has is a network of connections mimicking those in the brain of a worm. Of course, the goal of uploading our brains assumes that we aren’t already living in a computer simulation. Hear out the logic: Technologically advanced civilizations will eventually make simulations that are indistinguishable from reality. If that can happen, odds are it has. And if it has, there are probably billions of simulations making their own simulations. Work out that math, and "the odds are nearly infinity to one that we are all living in a computer simulation," writes Ed Grabianowski for io9. Is your mind spinning yet?
Posted by Christian Babski
in Innovation&Society, Programming, Software, Technology
at
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Defined tags for this entry: ai, algorythm, innovation&society, neural network, programming, software, technology
Thursday, December 11. 2014Google X Nano Pill will seek cancer cells in your bodyVia Slashgear -----
Google's moonshot group Google X is working on a pill that, when swallowed, will seek out cancer cells in your body. It'll seek out all sorts of diseases, in fact, pushing the envelope when it comes to finding and destroying diseases at their earliest stages of development. This system would face "a much higher regulatory bar than conventional diagnostic tools," so says Chad A. Mirkin, director of the International Institute for Nanotechnology at Northwestern University.
Word comes from the Wall Street Journal where they've got Andrew Conrad, head of the Life Sciences team at the Google X research lab speaking during their WSDJ Live conference. This system is called "The Nano Particle Platform," and it aims to "functionalize Nano Particles, to make them do what we want." According to Conrad, Google X is working on two separate devices, more than likely. The first is the pill which contains their smart nanoparticles. The second is a wearable device that attracts the particles so that they might be counted. "Our dream" said Conrad, is that "every test you ever go to the doctor for will be done through this system." Sound like a good idea to you?
Tuesday, December 02. 2014Big Data Digest: Rise of the think-botsVia PC World -----
It turns out that a vital missing ingredient in the long-sought after goal of getting machines to think like humans—artificial intelligence—has been lots and lots of data. Last week, at the O’Reilly Strata + Hadoop World Conference in New York, Salesforce.com’s head of artificial intelligence, Beau Cronin, asserted that AI has gotten a shot in the arm from the big data movement. “Deep learning on its own, done in academia, doesn’t have the [same] impact as when it is brought into Google, scaled and built into a new product,” Cronin said. In the week since Cronin’s talk, we saw a whole slew of companies—startups mostly—come out of stealth mode to offer new ways of analyzing big data, using machine learning, natural language recognition and other AI techniques that those researchers have been developing for decades. One such startup, Cognitive Scale, applies IBM Watson-like learning capabilities to draw insights from vast amount of what it calls “dark data,” buried either in the Web—Yelp reviews, online photos, discussion forums—or on the company network, such as employee and payroll files, noted KM World. Cognitive Scale offers a set of APIs (application programming interfaces) that businesses can use to tap into cognitive-based capabilities designed to improve search and analysis jobs running on cloud services such as IBM’s Bluemix, detailed the Programmable Web. Cognitive Scale was founded by Matt Sanchez, who headed up IBM’s Watson Labs, helping bring to market some of the first e-commerce applications based on the Jeopardy-winning Watson technology, pointed out CRN. Sanchez, now chief technology officer for Cognitive Scale, is not the only Watson alumnus who has gone on to commercialize cognitive technologies. Alert reader Gabrielle Sanchez pointed out that another Watson ex-alum, engineer Pete Bouchard, recently joined the team of another cognitive computing startup Zintera as the chief innovation office. Sanchez, who studied cognitive computing in college, found a demonstration of the company’s “deep learning” cognitive computing platform to be “pretty impressive.” AI-based deep learning with big data was certainly on the mind of senior Google executives. This week the company snapped up two Oxford University technology spin-off companies that focus on deep learning, Dark Blue Labs and Vision Factory. The teams will work on image recognition and natural language understanding, Sharon Gaudin reported in Computerworld. Sumo Logic has found a way to apply machine learning to large amounts machine data. An update to its analysis platform now allows the software to pinpoint casual relationships within sets of data, Inside Big Data concluded. A company could, for instance, use the Sumo Logic cloud service to analyze log data to troubleshoot a faulty application, for instance. While companies such as Splunk have long offered search engines for machine data, Sumo Logic moves that technology a step forward, the company claimed. “The trouble with search is that you need to know what you are searching for. If you don’t know everything about your data, you can’t by definition, search for it. Machine learning became a fundamental part of how we uncover interesting patterns and anomalies in data,” explained Sumo Logic chief marketing officer Sanjay Sarathy, in an interview. For instance, the company, which processes about 5 petabytes of customer data each day, can recognize similar queries across different users, and suggest possible queries and dashboards that others with similar setups have found useful. “Crowd-sourcing intelligence around different infrastructure items is something you can only do as a native cloud service,” Sarathy said. With Sumo Logic, an e-commerce company could ensure that each transaction conducted on its site takes no longer than three seconds to occur. If the response time is lengthier, then an administrator can pinpoint where the holdup is occurring in the transactional flow. One existing Sumo Logic customer, fashion retailer Tobi, plans to use the new capabilities to better understand how its customers interact with its website. One-upping IBM on the name game is DataRPM, which crowned its own big data-crunching natural language query engine Sherlock (named after Sherlock Holmes who, after all, employed Watson to execute his menial tasks). Sherlock is unique in that it can automatically create models of large data sets. Having a model of a data set can help users pull together information more quickly, because the model describes what the data is about, explained DataRPM CEO Sundeep Sanghavi. DataRPM can analyze a staggeringly wide array of structured, semi-structured and unstructured data sources. “We’ll connect to anything and everything,” Sanghavi said. The service company can then look for ways that different data sets could be combined to provide more insight. “We believe that data warehousing is where data goes to die. Big data is not just about size, but also about how many different sources of data you are processing, and how fast you can process that data,” Sanghavi said, in an interview. For instance, Sherlock can pull together different sources of data and respond with a visualization to a query such as “What was our revenue for last year, based on geography?” The system can even suggest other possible queries as well. Sherlock has a few advantages over Watson, Sanghavi claimed. The training period is not as long, and the software can be run on-premise, rather than as a cloud service from IBM, for those shops that want to keep their computations in-house. “We’re far more affordable than Watson,” Sanghavi said. Initially, DataRPM is marketing to the finance, telecommunications, manufacturing, transportation and retail sectors. One company that certainly does not think data warehousing is going to die is a recently unstealth’ed startup run by Bob Muglia, called Snowflake Computing. Publicly launched this week, Snowflake aims “to do for the data warehouse what Salesforce did for CRM—transforming the product from a piece of infrastructure that has to be maintained by IT into a service operated entirely by the provider,” wrote Jon Gold at Network World. Founded in 2012, the company brought in Muglia earlier this year to run the business. Muglia was the head of Microsoft’s server and tools division, and later, head of the software unit at Juniper Networks. While Snowflake could offer its software as a product, it chooses to do so as a service, noted Timothy Prickett Morgan at Enterprise Tech. “Sometime either this year or next year, we will see more data being created in the cloud than in an on-premises environment,” Muglia told Morgan. “Because the data is being created in the cloud, analysis of that data in the cloud is very appropriate.”
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