NetApp and Software Engineering Research and Services (SERS) Laboratory at WSU announced a new research partnership on developing automated goal oriented user interfaces for the next generation of storage management software. This effort is also anticipated to recognize new e-commerce opportunities.
This nexus is formed on the respective strengths of NetApp’s natural language and user experience technologies in the computer-system storage domain (industry relevance and market opportunities), and SERS Lab’s research contributions in the area of construction and evolution of large-scale software systems, including software analytics (academic research). One of the projected outcomes is a technology to empower IT professionals to specify a system management goal in natural language and the automated solutions will determine the necessary configuration parameters and their values that optimize the desired quality metric (e.g., capacity and performance). This paradigm offers a radical shift from the ubiquitous form-based interfaces in the targeted market sphere.
Overall, the effort will include multiple phases with the foundational work already underway on data analytics of configuration parameters and building an actionable model. The concluding phase is directed toward tech transfer and to recognize upselling revenue opportunities. NetApp is currently funding this project, which involves two PIs and a Ph.D. student, and is expected to include additional contributors.
The long-term goal is to formulate an academic-industry alliance that will integrate and sustain a spectrum of activities, ranging from scientific research to industry practice to classroom education.
Mr. Chris ONeil and Dr. Huzefa Kagdi are the PIs from NetApp and WSU respectively.
Algorithms were originally developed by mathematicians for mathematicians. Thousands of years ago the Greek mathematician, Euclid, devised the very first algorithm, which was used to determine the lowest common denominator in a set of numbers.
The use of algorithms is now going through a dramatic revolution. Essentially a set of step-by-step instructions, algorithms are used in a multitude of applications we use every day. When I take a photograph, for example, the Face Detection Algorithm systematically identifies the components of a face, regardless of size or shape, and thereby enables the camera lens to focus.
A plethora of search engines, such as Alta Vista, Bing, Google, Lycos, Magellan, Yahoo! and countless others rely on algorithms. In 1995, Sergey Brin and Larry Page developed the PageRank algorithm and a more efficient search engine was born: Google. Today, this ranking algorithm is responsible for 3.5 billion web searches each day. Its efficiency relies on its ability to look at incoming links and determine the relative importance of those pages, based on the frequency of other relevant links.
Searching for IT solutions requires new algorithms to discover a “feature document.” A feature document is an expression of an IT solution that is readable by search engines for retrieval and which can execute the operations: monitor; manage; and provision.
In order to understand the complexities IT professionals face today, consider the relevance of Search Engine Optimization (SEO) to end users. Millions of web pages are available, so SEO is essential. Securing top positions for the right search terms makes it easier to find the correct solution.
Conversely, millions of solutions are available to IT professionals, yet there is no search engine available today that is able to retrieve the correct tools capable of managing the Third Platform. What are the items a search engine provides today? Typically, these include: documents, web pages, videos, maps, music, etc. Each of these items needs some type of user agent to make it usable. In order to create an IT solution, it is necessary to first understand what the demands of the user agent are. Specifically, the IT solution user agent must be able to display the solution very much like a typical web page and—more importantly—enable one or more of the following operations: monitor; manage, and provision.
Emerging from browser technology today is a new capability called “responsive UX,” which is made up of individual building blocks called widgets. Popular frameworks including Google’s Angular JS make it possible to use these widgets to create a system for executing tasks that can monitor, manage and provision an IT infrastructure.
Using these widgets it is possible to express an IT solution. This requires the widgets to enable describing the IT solution. Then, enable the IT solution to execute changes in the infrastructure. And ultimately, to enable the IT solution to be searchable in the form of a “feature document.” A feature document is an expression of an IT solution that is readable by search engines for retrieval and which can execute the aforementioned operations: monitor; manage; and provision.
The development of algorithms and other technologies comprising Artificial Intelligence (AI) are driving the paradigm shift to the Third Platform. These enabling technologies are central to creating more end-user friendly and efficient IT solutions supporting the applications consumers use every day.
AI powers everything from taking a picture or sending a text on a smart phone, to searching the web, using Facebook, taking a trip or even saving lives by enabling a donor matching database.
Demand for more innovative end-user solutions that improve efficiency and cost-savings is driving advances in—and the convergence of—enabling technologies, including AI, Search Engine Optimization (SEO), speech recognition, natural language, and an up and coming functionality One Click Provisioning (OCP), among others.
Creating a responsive User Experience (UX) technology stack to support AI-enabled applications requires the use of accurate data input about end-user behavior, patterns and practices. Whether it is supporting the speech recognition used in Siri, the auto-fill feature in a text message or when completing an online form, AI relies on an accurate model of the user’s goals and is meant to more intelligently anticipate and interpret the user’s actions based on these goals.
If accurate data are not used in its design and development, attempts to enhance the UX can backfire and alienate a user from the solution provider. For example, if a job search website repeatedly pushes irrelevant listings to my inbox, I will most likely ignore future email messages from that site. The problem is that the provider gathered incomplete or inaccurate data when they “fished” my name and address from the back door of a site where I am a registered user.
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