Much to the disappointment of science fiction writers everywhere—and contrary to the anxieties of Elon Musk and Stephen Hawking—Tappeiner insists that robots will not be taking over the world anytime soon. “Definitely not in the next five years,” Tappeiner says. “Probably not in the next 50 years.” ... Even though robotics and automation in military research has helped to animate the spectre of killer robots, Tappeiner argues that robots will continue to serve humans for the near future, largely because current AI techniques still fall far short of the capabilities of the human brain. While machine learning excels at specific tasks like translation (Google Translate, for example, uses a technique called statistical machine translation), that intelligence is not easy to generalise.
One of the features of Spring Data Rest is exporting query methods as RESTful endpoints. That is awesome for simple cases eg. to supply your API with an endpoint to filter users by their username, you just have to write one line of code. Unfortunately those query methods are indivisible and cannot be combined with each other. That implies, that developers solving some complex cases, like queries with optional parameters, have to either write multiple query methods or write a custom method and export it with a controller. ... Second feature, that OpenRest comes with is Data Transfer Objects for POST, PUT and PATCH requests. Since Spring Data Rest is a great piece of code, one of my main principles while writing OpenRest was change as little as possible, and let users to switch it off and use basic features of Spring Data Rest when needed.
Developing a talent analytics program should start with identifying the top business challenges HR needs to address. As CFOs typically have a view across the organization, they can provide a perspective on what the business needs from HR and where to focus efforts. That information will help determine the data HR will need to collect and analyze. For example, if the challenge is to improve the leadership pipeline at the business units, what are the metrics that the business needs to make decisions around leadership? Another foundational element is the quality of the data. If you go in to an advanced analytics project with inconsistent or poor-quality data, the HR group will quickly lose credibility with stakeholders.
New technology like wearable computing, mobile apps, the Internet-of-Things (IoT) and data analytics are beginning to influence all aspects of our lives. As a consumer, it can feel like your applications are always a step ahead of you. Use navigation app Waze at a certain time of day, and it knows you are heading from the office to home, pre-populating the route. This pervasive connectivity, and abundance of information about users, places, and things play a pivotal role in creating highly contextual and efficient experiences. In the case of smart apps, the experience begins 30 secondsbefore the user taps it — it knows what the user is looking for before they do.
Norris, who is also the leader of the Ops Lab at JPL, says NASA is also working on other applications for HoloLens, like using augmented reality for inventory management. Apparently keeping track of where things are and how to find them is a big challenge on the space station, even though objects have bar codes on them and are organized with a database. NASA has prototyped an app that can be used to recognize an object and show the HoloLens wearer a path to follow that leads to where the object should be stored, Norris says. In the meantime, to get some sense of what it will be like to use HoloLens on the space station, NASA experimented with HoloLens at the Aquarius underwater research station off the coast of Key Largo, Florida, in late July and early August.
Attributing digital attacks is said to be getting easier. But it is necessarily harder than in the real, “kinetic” world. So is deciding on the scale and direction of any retaliation. Arms control is all but impossible: digital weapons have to be secret to be effective. Though officials are cagey about the details, they believe they have detected Chinese and other hackers snooping on (and perhaps interfering in other ways with) computers and networks which run important infrastructure. Efforts to strengthen the systems involved are under way; the creaky power grid is a particular worry. Working out who is ahead is hard. America is doubtless making similar efforts on infrastructure networks in Russia and China—which may be in some ways more vulnerable to attack.
To be able to perform true unit testing we need to isolate mvc features from rendering the view, which means no authorization, no model binding, no request validation, no filter actions, no method selectors, and no action invocation. You should only need to specify specify the view content, the view model, view data, temp data, bundles, etc... and a controller context because razor happens to need one to expose UrlHelper and HtmlHelper. So why not use Razor Engine or similar? simply because Razor Engine has a distinct application where MVC features are not needed, ie. Razor Engine does not support the view '~/Views/Home/Index.cshtml' from the default ASP.NET MVC project template, but if you need full support of razor features then we need something else, that is where Xania.AspNet.Simulator comes into play.
With the fluency model, it is not really the case. What you have is four different stops on a journey and any one of those stops can be right for any team, depending on what they need and what their organization needs. Figuring out exactly what fluency your team has, takes some experience. We have distilled down four core metrics – they are not sufficient conditions, but if you do not have these capabilities, then you are probably not fluent. So, for a one star teams, the teams that are focused on value which means talking in terms of business value. So, if you have a team and they are not talking in terms of business value, they are not showing progress in terms of business value, they are not giving their business partners the chance to change direction, change the order of stories, for example,
Whether VMware will remain relevant as IT migrates to the cloud is “a really interesting question,” Miniman said. “First of all, this shift to cloud is a long term thing. We’re talking one of these ten-year swings. Wikibon’s latest research on it is, in ten years, it’s a third of the enterprise spend.” There’s time to adapt. VMware is “doing a great job of trying to make things more efficient, and they listen to their customers,” he said. He pointed to the company’s progress with VSAN and NSX. “However, I worry about VMware ignoring the impact of AWS and Azure." Initiatives like Pivotal’s Cloud Foundry (a well-funded offshoot developed by VMware) are promising, he said. “But I feel like they’re kind of trying to run out the clock on some stuff they’re doing, and not pushing as aggressively in some of the new technologies as fast.
Some enterprises will be predominantly at one extreme or the other. Based on the research, there is a likely expectation that EA teams in Japan, the US, and some Western European countries — such as Switzerland, Ireland, Germany, Italy, England, Sweden, Austria, and the Netherlands — will produce results comparatively quickly. EA teams in other countries with slower-paced cultures, such as most Mediterranean and Arab countries, are more likely to work at a comparatively gentle or slow pace. The key point is that pace is relative — it is likely to be comparatively fast or comparatively slow, but there will always be some EA environments with a mixture of both fast and slow, and some that fluctuate between the two extremes.
Quote for the day: “Everyone is gifted, but some people never open their package.” -- Wolfgang Riebe