In the past decade, the field of neural networks has evolved very rapidly as a result of new insights obtained in the mid-2000s, when several researchers published articles on deep learning. The number of algorithms has grown rapidly. For example, there is now a whole class of algorithms often termed deep learning, deep machine learning, or deep neural networks that have become popular. This topic can be a bit confusing as “deep” is currently being used in multiple different ways.

Many popular definitions of leadership emphasize charisma, vision, or position. The darker definitions hint at manipulation or even coercion. In software companies, though, people throughout the organization are smart, well intentioned, and capable of making good decisions. So we need a different definition if we want to make our companies more flexible and smarter.

Cognitive computing is starting to impact the enterprise by changing the way data is analyzed and the manner in which employees and customers interact with computerized systems. This is happening across various industries, ranging from healthcare and retail to banking and financial services. 

Cognitive computing is starting to impact the enterprise by changing the way data is analyzed and the manner in which employees and customers interact with computerized systems. This is happening across various industries, ranging from healthcare and retail to banking and financial services. 

The challenge for the enterprise architect is to figure out what the enterprise chorus lines are; in other words, what we might think of as the “core” architecture.

Watson Ads is the first application of Watson to advertising. The goal: make ads more appealing, interactive, and engaging; in effect, heighten the consumer experience by allowing them to make more personalized, informed decisions at the point of consideration. Instead of clicking on an ad and receiving a canned marketing spiel about a product or service, consumers will be able to ask specific questions in plain natural language and receive information with real, contextual relevance to their individual needs.

A conversation is taking shape about the role of ethics in software projects, all the way from the algorithms that implement those projects to the projects themselves. Interest is especially focused on auton­o­mous vehicles, the cyber espionage and cyber warfare fields, and many consumer products such as the Web and video authoring tools that have played essential roles in new media and publishing projects — as well as terrorism and child pornography. Note that “software projects” and “system development” are used in a very broad way to encompass apps on mobile devices, complex systems running across an elaborate network of hosts, and websites and Web apps of all types and sizes.

In this article, I will try to expand upon the last clause of Kranzberg’s First Law of Technology: “Technology is neither good nor bad; nor is it neutral.” Those who claim technology is ethically neutral tend to focus attention on the underlying processes, to the exclusion of the original motivation. While I lean in this direction, I recognize that bad actor/bad faith technology provides an important exception.

This article explores and repositions ethics, trust, and responsibility in the age of autonomous machines. It begins by posing new technology-induced ethical dilemmas and suggesting that there are different moral resolution systems. Frankenstein’s monster and Asimov’s Laws of Robotics represent early attempts to come to terms with the ethics of autonomous robots, yet the role of humans and their ability to intervene invite ­ethical considerations about the impact of autonomous machines. The new uncertainties that come with the use of innovative technologies require paying more attention to the responsibility of designers for their creations. The article concludes by identifying different levels of responsibility and proposing a finer balance between trust, safety, and reliability as well as considering the interaction between users, designers, and their creations.

The purpose of this article is to explore the boundary between machine capabilities and what once seemed uniquely human. That boundary has certainly moved over the years, justifying concerns that the relatively new field of roboethics addresses. Roboethics goes beyond job losses and looks at the impact of robotization on society as a whole; that is the major topic here.

Agile requires real cultural change. Unfortunately, many people new to Agile don’t see the connection between the principles and the practices. In their eyes, Agile is just another process, something that requires following a checklist of behaviors. Other processes in their experience, such as CMMI and ITIL, never asked them to adopt a new worldview. Therefore, even if they become aware of the important connection between Agile principles and practices (which they may not), they may have no past experience in software innovation for making the connection between them.

All that has been said and written about the challenges associated with the Internet of Things (IoT) does not quite prepare you for the practical difficulties that crop up as you start implementing and deploying IoT solutions. Most of the publicly available knowledge about IoT challenges relates to high-level issues that are typically addressed through architecture and design decisions. One of our recent successful implementations, an enterprise-wide Remote Energy Management System (REMS), brought us face-to-face with an entirely new set of ground-level challenges, from data ingestion to data storage, to data processing, to data analytics and visualization.

Digital solutions are intelligently and seamlessly wrapping themselves around the complex lives of consumers in a bid to deliver deeply personalized services as and when required. Consumer expectations of the digital world are heightened by the resulting experiences, which ultimately creates further demands on organizations. If we wish to take advantage of this virtuous cycle, we must gaze into the future and consider the complex systems of interactions that will emerge between more demanding humans and smarter technologies. 

Digital solutions are intelligently and seamlessly wrapping themselves around the complex lives of consumers in a bid to deliver deeply personalized services as and when required. Consumer expectations of the digital world are heightened by the resulting experiences, which ultimately creates further demands on organizations. If we wish to take advantage of this virtuous cycle, we must gaze into the future and consider the complex systems of interactions that will emerge between more demanding humans and smarter technologies. 

If we could for a moment ignore the terms "enterprise architecture" and what does or does not constitute one, and "solution or system architecture" and what does or does not constitute one, we might reach some agreement on the concepts that underlie enterprise architecture. In that spirit, here is my take on enterprise architecture, without using the word (until the end).

During this webinar, Cutter Senior Consultants Murray Cantor and John Heintz introduced a process for applying next generation agile planning to your software delivery process, so you can gain an accurate view of your current status, make modifications where necessary, and improve your odds of success. Learn how to overcome the uncertainties of software features release planning by taking an estimate — and its margin of error — and using it to your advantage.

During this webinar, Cutter Senior Consultants Murray Cantor and John Heintz introduced a process for applying next generation agile planning to your software delivery process, so you can gain an accurate view of your current status, make modifications where necessary, and improve your odds of success. Learn how to overcome the uncertainties of software features release planning by taking an estimate — and its margin of error — and using it to your advantage.

I have often joked that data warehouses are as unfriendly to business users as physical warehouses are to shoppers. The reality is perhaps grimmer: data warehouse designs took no cognizance of the actual processes at work within human beings when making decisions. Data lakes, despite metaphors of recreational use and dipping in for data, actually pay as little attention to the mental processes involved in decision making as did data warehousing.

The habits of thought that we learn and practice as we conduct EA can influence our thinking and behavior in broad aspects of our lives. Indeed, wise use of EA can train us to be better thinkers; unwise use can reinforce our bad habits. This Executive Update explores how we should revisit the original intent of EA and bring the human element back into EA practice. Not because we failed in our attempt to automate enterprise architecture (thank goodness), but because it is the right thing to do.

This article presents three examples of companies that have successfully pursued a strategy for using technical debt assessment as the basis for better technical and business decisions.

From the school of business, a belief emerged that the needs of business must drive technology, not the other way around. From the school of engineering, there is a belief that technology should shape the business. Naturally, the school of business typically wins. Yet speaking as digital business strategists, this is a gross oversimplification. Every organization has operational needs and line-of-business (LOB) concerns, all of which advance incrementally on decadal cycles.

By asking the CEOs of some of the most successful and influential companies in the world, such as GE and Google, a clear definition of innovation manage­ment emerges. The definition addresses the need to quickly and effectively implement organizational goals and objectives to remain competitive and the desire to strengthen advantages through the adoption of innovative ideas, products, processes, and business models.[1]

I've been researching how banks and other financial institutions are using cognitive systems. The short story is that cognitive systems like IBM Watson, Expert System's Cogito, and Microsoft's Cognitive Services — as well as industry-specific commercial solutions built upon these and other providers' cognitive platforms — are increasingly being utilized in banking and finance.

Cutter’s Digital Transformation & Innovation Bootcamp is designed to help executive teams upend the reflex thinking that prevents essential change, take a fresh and creative look at opportunities, and dive deeply into what they need to do to succeed. Cutter Consortium Fellow, Professor Karim Lakhani will guide participants through a 2-day examina­tion of how digital innovation is transforming our business landscape.

The current market for Internet of Things (IoT) platforms is quite unsettled, consisting of a broad range of providers offering a large number (and somewhat confusing array) of IoT implementation products. These range from independent providers marketing comprehensive standalone IoT platforms and services to major enterprise software vendors whose IoT platforms are designed to build on, or integrate with, their various ERP, CRM, database, and other enterprise applications. Products in the standalone category include comprehensive IoT platforms in the form of platform as a service (PaaS) offerings designed to ­provide the infrastructure and facilities necessary for developing, connecting, and managing IoT-connected products and applications.