There's no doubt in my mind that machine learning (ML) as part of a data science strategy can help revolutionize many aspects of everyday life. Below I highlight a few examples of how different industries are able to leverage machine learning for competitive differentiation and customer benefit. There are tens of thousands of daily published journals and papers across the world. It is impractical for every clinician to read and absorb these. ML can help identify patterns and correlations that humans alone would otherwise miss -- possibly resulting in diagnosis and treatment plans that are suboptimal.
Startup Instana, which has quietly been developing application performance management (APM) tools for containers and microservices, is officially releasing its first commercial offering this week, adding artificial intelligence and automation into the DevOps process. The company is detailing the product -- also called Instana -- at Dockercon Europe on Tuesday. The goal is to speed-up the development, testing, deployment and maintenance of new applications, especially those applications deployed in containers or through microservices, as enterprises move toward their goal of digital transformation. "The digitization or digital transformation trend that is going on is not about being big, it's simply about being fast," Pete Abrams, the co-founder and COO of Instana, told Enterprise Cloud News before the October 17 launch. "The people that can code-up, deploy and operate new business services the fastest are showing themselves to be the winner, and that is a massive competitive advantage."
The latest update to Microsoft's flagship Windows 10 computer software has been made available to consumers for the first time. The update has various new features including a native app called Paint 3D, an image and video editing app called Story Remix and a feature called Timeline that enables users to pick up on tasks they were previously working on. The'Fluent Design' redesign is part of an effort to modernise the operating system and will be rolled out from today. Users are recommended to back up their computer before downloading an update and Microsoft will send an alert when it is available. Microsoft first revealed the new feature during the second day of its Build developer conference in Seattle in May.
Pedro Galveia, Yard and Ship Planner and Port Consultant at Yilport Sotagus in Lisbon explained roughly how automation will break down among the differently sized terminals in a new video. Observations can be made regarding three main areas of terminal automation: the Ship-to-Shore (STS) cranes, the stacking area and the gates. Galveia explains in the video: "For bigger terminals above 4-5 million moves per year, global terminal operators behind them will put pressure to automate the STS cranes. "Terminals with a half-million moves will search for process automation and clean flows in their STS cranes. Read a related paper by Automated Terminal Systems about how efficient handling for mega-ships requires some level of automation.
Windows 10 after two years: Was the upgrade worth it? After a little more than two years, Microsoft has finally settled into a rhythm with its new, fast-paced development cadence for Windows 10. Check Settings System About to see full details about the current Windows 10 installation. What Microsoft's marketers are calling the Fall Creators Update (officially version 1709) begins arriving on desktop PCs today via Windows Update and will soon be available for download at all the usual places. The final build number for this release is 16299.
There's a major roadblock to deeper market penetration of enterprise robotics, and a new generation of early career computer scientists and more seasoned software engineers may hold the answer. I recently had a chance to speak with Maya Cakmak, assistant professor at the University of Washington, Computer Science & Engineering Department, where she directs the Human-Centered Robotics Lab. To understand PbD, consider collaborative robots from companies like ABB and Kuka. The units consist of articulated arms that can be programmed to help workers do a variety of things, such as pick and place objects, test devices and components, and perform simple but precise manufacturing tasks. So-called "cobots" are relatively inexpensive and operate alongside humans, and many of the use cases involve small- to mid-sized businesses.
The endless parade of emerging technology is gaining the attention of large enterprises and startups alike. The Internet of Things, artificial intelligence, machine learning, natural language processing, robotic process automation, and cognitive computing – all of these digital innovations and more are generating a range of disruptive innovation that is bridging gaps of unfulfilled customer demand. Does it make sense to spend limited resources to take advantage of these same technologies? According to the IDC Analyst Connection, "Analytics for SMBs: Sharpen Operations, Capitalize on Business Opportunities," such investments can bring a level of automation, electronic monitoring, and sensor-enabled insight not seen anywhere outside of the SMB segment. While the largest firms are busy refining processes in response to market dynamics, SMBs are close enough to customers and the competitive environment to effectuate change with tremendous speed and agility.
Blocks, a Theano framework for training neural networks Caffe, a deep learning framework made with expression, speed, and modularity in mind. It can model arbitrary layer connectivity and network depth. Any directed acyclic graph of layers will do. Training is done using the back-propagation algorithm. ConvNet, a Matlab based convolutional neural network toolbox - a type of deep learning, can learn useful features from raw data by itself.
What if you could create an accurate summary of a lengthy article at the touch of a button? What if you could quickly scroll through a bibliography, filtered to show only the citations relevant to your needs? What if you could get your research out into the world faster, and have that knowledge built upon sooner? Science and technology are generating more data than ever faster than ever, so it's getter harder and harder to keep up and manage this information. Therefore, it's crucial to find ways to automate the discovery and interpretation of the information we need – and only that information.
No, I'm not talking about the 1975 Supertramp album, but research from a global leader in the test automation space demonstrating the "acute pressure" facing businesses to deliver apps in the Internet of Things (IoT) and digital era. It reveals that half of companies in the US and the UK admit to releasing apps before completing "quality testing." And, enterprises are being urged by the British CEO spearheading the test automation firm's endeavours to rethink test automation to avoid the "app scrapheap." But are matters getting to a crisis in the apps space? In the survey commissioned by Testplant, a UK headquartered firm with a R&D presence in Boulder, Colorado, which provides what is touted as user-centric, digital automation intelligence solutions to enhance the quality and performance of the digital experience, canvassed 750 development team leaders in Britain and the United States to derive its findings.