In this Summit 2016 keynote presentation, Federico Pigni demonstrates both strategic and tactical opportunities made possible by DDS.

Research and discovery are big application areas for applying cognitive techniques, including for financial market analysis, marketing, and product development. Several versions of IBM’s Watson technology, in the form of focused applications, are now being utilized by banking and financial companies in these roles. In addition, commercial cognitive solutions such as Kenshoo, targeted specifically at supporting financial market research, are also available.

The transformation to an Agile culture starts with an understanding of what we mean by culture.

Rather than having a team of testers manually testing the code for defects, invest in writing good auto­mated tests that can validate that each feature works as expected. When this happens, testers won’t scramble to keep up with developers, and developers won’t be waiting on testers.

Robert Ogilvie takes a broader look at some of the themes already developed and considers the likely role of cognitive computing in the near future. He suggests that automation has gone through three phases: a robotic phase, in which computers performed rote tasks; a social phase, in which computers have facilitated communication and collaboration; and a cognitive phase, in which computers are learning to use knowledge to solve intellectual problems. He alludes that most of the new cognitive systems will interact with and aid human performers. Rather than replace human managers, Ogilvie implies, cognitive computing applications will make existing managers more knowledgeable and better able to respond to a broader range of challenges. He goes on to offer an inspiring vision of cognitive computing applications that help individuals and teams focus their attention on the challenging ­problems that are really worthy of consideration. 

Robert Ogilvie takes a broader look at some of the themes already developed and considers the likely role of cognitive computing in the near future. He suggests that automation has gone through three phases: a robotic phase, in which computers performed rote tasks; a social phase, in which computers have facilitated communication and collaboration; and a cognitive phase, in which computers are learning to use knowledge to solve intellectual problems. He alludes that most of the new cognitive systems will interact with and aid human performers. Rather than replace human managers, Ogilvie implies, cognitive computing applications will make existing managers more knowledgeable and better able to respond to a broader range of challenges. He goes on to offer an inspiring vision of cognitive computing applications that help individuals and teams focus their attention on the challenging ­problems that are really worthy of consideration. 

In her article, Karolina Marzantowicz explores how computers learn. It turns out that teaching a cognitive application is rather like mentoring a new associate: setting tests, offering hints, and doling out lots of ­reinforcement as the application learns more and provides better answers. She discusses some of the different techniques required for acquiring basic knowledge, for learning a natural language, and for learning to make sense of images. 

In her article, Karolina Marzantowicz explores how computers learn. It turns out that teaching a cognitive application is rather like mentoring a new associate: setting tests, offering hints, and doling out lots of ­reinforcement as the application learns more and provides better answers. She discusses some of the different techniques required for acquiring basic knowledge, for learning a natural language, and for learning to make sense of images. 

This Executive Update offers an overview of potential vulnerabilities in your apps and websites that handle location, along with some ideas of what you can do to fix, prevent, or otherwise manage these vulnerabilities.

One of the biggest organizational design (OD) challenges facing many organizations is the switch from the more structured, hierarchical forms that were effective in the Industrial Age to more fluid, networked structures that are more appropriate in the Information Age. This is an often unspoken transition that lies at the heart of many enterprise architecture (EA) projects.

Aravind Ajad Yarra gives us his own description of the history of natural language interface development and goes on to consider what kind of architecture is required to support conversational interfaces. Without getting into coding details, Yarra provides a good overview of the challenges developers will face as they seek to develop conversational interfaces for ­business applications.

Aravind Ajad Yarra gives us his own description of the history of natural language interface development and goes on to consider what kind of architecture is required to support conversational interfaces. Without getting into coding details, Yarra provides a good overview of the challenges developers will face as they seek to develop conversational interfaces for ­business applications.

In recent years, those using AI to improve software development have focused on creating specialized tools that can aid developers in specific tasks. By combining software development capabilities with an ability to ­dialog with developers, the new tools are making the development process easier. Indeed, author Donald Reifer believes that in five years’ time, cognitive computing approaches will enable machines to autonomously perform many of the intellectual tasks of software development, and he offers three scenarios for which this might be the case: software requirements definition, test automation, and “roll your own release.” 

In recent years, those using AI to improve software development have focused on creating specialized tools that can aid developers in specific tasks. By combining software development capabilities with an ability to ­dialog with developers, the new tools are making the development process easier. Indeed, author Donald Reifer believes that in five years’ time, cognitive computing approaches will enable machines to autonomously perform many of the intellectual tasks of software development, and he offers three scenarios for which this might be the case: software requirements definition, test automation, and “roll your own release.” 

This issue of Cutter Business Technology Journal is focused on cognitive computing. Cognitive computing is a term that is similar to, but currently more popular than, artificial intelligence (AI), and it refers to all those innovations in computing that are being driven by various types of AI research. Now is the time to start thinking about how to transform your organization with cognitive computing.

This issue of Cutter Business Technology Journal is focused on cognitive computing. Cognitive computing is a term that is similar to, but currently more popular than, artificial intelligence (AI), and it refers to all those innovations in computing that are being driven by various types of AI research. Now is the time to start thinking about how to transform your organization with cognitive computing.

Watson Virtual Agent is an important development because it aims to streamline the process of implementing intelligent agents and bots.

An effective EA Program session is the best way to ensure that a project gets started correctly. Cutter's EA Program sessions help establish a project's team values, vision, mission, objectives, project community, measures of success, scope and boundaries, committed resources, and working agreements.

Cloud is on everyone’s mind. If you are in the throes of cloud procurement — facing challenges around cost reduction, centralized billing, and agility — then buying indirect offers significant advantages. The objectives of unlocking lower pricing to reduce costs and negotiating suitable procurement terms to improve agility are best achieved by buying cloud indirectly. It is the role of cloud brokers, resellers, and distributors to help customers get the best deal. To negotiate preferred terms as an enterprise cloud buyer, consider buying through an IT distributor or reseller. As we explore in this Executive Update, it is time to start buying cloud as an organization, not as an individual. That means taking a long-term view of how you continually monitor, optimize, and manage the procurement of cloud infrastructure.

Cloud is on everyone’s mind. If you are in the throes of cloud procurement — facing challenges around cost reduction, centralized billing, and agility — then buying indirect offers significant advantages. The objectives of unlocking lower pricing to reduce costs and negotiating suitable procurement terms to improve agility are best achieved by buying cloud indirectly. It is the role of cloud brokers, resellers, and distributors to help customers get the best deal. To negotiate preferred terms as an enterprise cloud buyer, consider buying through an IT distributor or reseller. As we explore in this Executive Update, it is time to start buying cloud as an organization, not as an individual. That means taking a long-term view of how you continually monitor, optimize, and manage the procurement of cloud infrastructure.

Projects are successful when the entire team has the same cohesive vision for the solution. Failure to understand the solution's goal will have rippling effects throughout the project and can lead to failure. It's imperative that the architect and the Agile team members be aligned.

In keeping with digital transformation’s principle of viewing a business holistically across a variety of contexts, viewing how a business delivers stakeholder value is a key element of this holistic perspective. Stakeholders are first and foremost customers, but they also include business partners, other third parties, and internal resources. The value stream provides a nontechnical, value-driven, end-to-end perspective that includes all of the enabling capabilities and participating stakeholders required to deliver the value proposition for that value stream.

AlphaGo is a major breakthrough in cognitive computing; it is a software application that can successfully play the hardest strategy game that people play and can beat human experts at it.

One of the top areas that business architecture teams struggle with is articulating the value of business architecture. Their challenges have less to do with building the business architecture blueprint or even applying it to various scenarios, and more to do with getting the buy-in to be able to do so in the first place. This is partially due to circumstances related to the discipline and its increasing maturity, but also related to the way we communicate.

For enterprises disrupting the marketplace, technology is the key enabler that is helping them create new business models and processes.