Artificial intelligence/Machine learning
Surprisingly, the MXNet Machine Learning project was this month accepted by the Apache Software Foundation as an open-source project.
What's surprising about the announcement isn't so much that the ASF is accepting this face in the crowd to its ranks – it's hard to turn around in the software world these days without tripping over ML tools – but rather that MXNet developers, most of whom are from Amazon, believe ASF is relevant.
During the past decade, enterprises have begun using machine learning (ML) to collect and analyze large amounts of data to obtain a competitive advantage. Now some are looking to go even deeper – using a subset of machine learning techniques called deep learning (DL), they are seeking to delve into the more esoteric properties hidden in the data. The goal is to create predictive applications for such areas as fraud detection, demand forecasting, click prediction, and other data-intensive analyses.
Machine learning has become a buzzword. A branch of Artificial Intelligence, it adds marketing sparkle to everything from intrusion detection tools to business analytics. What is it, exactly, and how can you code it?
Learning the inner workings of artificial intelligence is an antidote to these worries. And this knowledge can facilitate both responsible and carefree engagement.
Dropbox has released the code for the chatbot it uses to question employees about interactions with corporate systems, in the hope that it can help other organizations automate security processes and improve employee awareness of security concerns.
"One of the hardest, most time-consuming parts of security monitoring is manually reaching out to employees to confirm their actions," said Alex Bertsch, formerly a Dropbox intern and now a teaching assistant at Brown University, in a blog post. "Despite already spending a significant amount of time on reach-outs, there were still alerts that we didn't have time to follow up on."
Red Hat News
We’re very happy to reveal that Red Hat’s Jen Krieger will be delivering a keynote at Continuous Lifecycle London, our three-day DevOps, Agile, CD and Containers conference this May.
Jen is chief agile architect at Red Hat, where she leads a department-wide DevOps movement focusing on CI/CD best practices. She has worked with the Project Atomic and OpenShift teams, and is currently guiding teams across the company into agility in a way that respects and supports its commitment to Open Source.
World Wide Technology is collaborating with Cisco, Intel and Red Hat to launch a new facility for validating full stack Network Functions Virtualisation (NFV) solutions.
Red Hat OpenShift Container Platform is a developer-focused PaaS that supports application development teams in a range of industries and business sizes.
Container-friendly Alpine Linux may get Java port
Alpine Linux, a security-focused lightweight distribution of the platform, may get its own Java port. Alpine is popular with the Docker container developers, so a Java port could pave the way to making Java containers very small.
A proposal floated this week on an OpenJDK mailing list calls for porting the JDK (Java Development Kit), including the Java Runtime Environment, Java compiler and APIs, to both the distribution and the musl C standard library, which is supported by Alpine Linux. The key focus here is musl; Java has previously been ported to the standard glibc library, which you can install in Alpine, but the standard Alpine release switched two years ago to musl because it’s much faster and more compact
OSS and Linux Foundation Work
Last week, we started by defining “Open Source” in common terms -- the first step for any organization that wants to realize, and optimize, the advantages of using open source software (OSS) in their products or services. In the next few articles, we will provide more details about each of the ways OSS adds up to a business advantage for organizations that use and contribute to open source. First, we’ll discuss why many organizations use OSS to speed up the delivery of software and hardware solutions.
There are a lot of pieces to the ongoing network transformation going up and down the stack. There's the shift away from proprietary hardware. There's the to need to manage complex network configurations. Add subscriber management and a wide range of other necessary functions. Add customer-facing services. All of those pieces need to fit together, integrate with each other, and interoperate.
This was the topic of my conversation with Heather Kirksey, who heads up the Open Platform for Network Functions Virtualization (OPNFV) project when we caught up at the Open Source Leadership Summit in mid-February. OPNFV is a Linux Foundation Collaborative Project which focuses on the system integration effort needed to tie together the many other open source projects in this space, such as OpenDaylight.
As Heather puts it: "Telecom operators are looking to rethink, reimagine, and transform their networks from things being built on proprietary boxes to dynamic cloud applications with a lot more being in software. [This lets them] provision services more quickly, allocate bandwidth more dynamically, and scale out and scale in more effectively."
One of the common criticisms of open source in general, especially when it comes to open cloud platforms such as OpenStack and ownCloud, is lack of truly top-notch documentation and training resources. The criticism is partly deserved, but there are some free documentation resources that benefit from lots of contributors.
Community documentation and training contributors really can make a difference. In fact, in a recent interview, ClusterHQ’s Mohit Bhatnagar said: “Documentation is a classic example of where crowdsourcing wins. You just can’t beat the enthusiasm of hobbyist developers fixing a set of documentation resources because they are passionate about the topic.”
Among the biggest things to land in the OpenStack Ocata cloud platform release this week is the Cells v2 code, which will help enable more scale and manageability in the core Nova compute project.
Nova is one of the two original projects (along with Swift storage) that helped launch OpenStack in June 2010. The original Nova code, which was written by NASA, enables the management of virtualized server resources.