I am grateful to have the health insurance I have, and grateful for the payments they've made to resolve problems I've had. Nonetheless, I can't help but be astounded at the never-ending flow of expensive, incompetent, annoying and utterly useless interaction I have had with the company's computer systems. Why can't they (and others like them) get it right? The answer is simple: the company's leaders, like most enterprise companies, want to be leaders in technology. Today, that means funding big, publicized initiatives in AI and ML. Initiatives that will, of course, transform healthcare.

Close up view on a CPU with circuitry and binary numbers displayed on top of it. The scene is ... [ ] positioned on a blueprint surface. When you talk about AI and IBM, people typically think of Watson and, more recently, Project Debater. But IBM Research is also working on more generalized AI tools and accelerators for the data center applications. IBM Research has an AI Hardware Center up near Albany, NY which has been investigating a number of projects involving more generalized AI performance and power improvements.

The number one AI hype story this year had to be Tesla's robotaxi fleet. While other autonomous vehicle companies are dialing back their claims of near-future glory, Tesla has been pushing the propaganda volume up to an ear-splitting 11. Tesla has been touting its cars' "self-driving" abilities since 2016. At the end of last year, after selling "self-driving" vaporware for several years as an add-on feature, it looked like the company was going to take the responsible approach and stop selling the feature. They pulled the option from their web site, and basically stopped talking about it.

Recently, I sat down with Stephen Wu, a shareholder at Silicon Valley Law Group, and Peter Gillespie, a partner at Laner Muchin, to talk about one of the newest ways AI is being deployed: as a way to intelligently forecast risk and measure the development performance of software organizations. This new method of using AI can give software companies a new level of understanding of their software delivery pipeline's performance. But should you use an AI system to judge the performance of people? We discussed the ethics behind this new use of technology and what it holds for the future of performance management and software development. Here's what your team needs to understand about using AI for HR related decisions on software teams.

Researchers at the University of Wollongong, Deakin University, Monash University and Kyushu University have developed a framework that could be used to build a smart, AI-powered agile project management assistant. Their paper, pre-published on arXiv, has been accepted at the 41st International Conference on Software Engineering (ICSE) 2019, in the New Ideas and Emerging Results track. "Our research was driven by our experience working in and with the industry," Hoa Khanh Dam, one of the researchers who carried out the study, told TechXplore. "We saw the real challenges in running agile software projects and the serious lack of meaningful support for software teams and practitioners. We also saw the potential of AI in offering significant support for managing agile projects, not only in automating routine tasks, but also in learning and harvesting valuable insights from project data for making predictions and estimations, planning and recommending concrete actions."

This is a guest post written by Scott Middleton, founder and CEO of stratejos as well as part-time sausage maker. Will you still be doing your job in 5-10 years or will a robot do it for you? This is a question knowledge workers have started asking themselves as AI is becoming more capable and widely adopted. Atlassian co-founder and CEO, Mike Cannon-Brookes, has said AI will play a major role in the future of team productivity. Bank of America Merrill Lynch predicts that AI will have a $9 trillion impact on knowledge work over the coming decade.

Everyone's talking about how AI will revolutionize so many things. Most of today's discussions take place at the application level, although AI will impact software development too. Some vendors, ISVs and consultants anticipate such a shift, but they aren't able articulate the specifics yet. For years, organizations have been building software using certain types of knowledge. Now, they also have to consider the probable impacts of AI.

This is a guest post written by Scott Middleton, founder and CEO of stratejos as well as part-time sausage maker. Will you still be doing your job in 5-10 years or will a robot do it for you? This is a question knowledge workers have started asking themselves as AI is becoming more capable and widely adopted. Atlassian co-founder and CEO, Mike Cannon-Brookes, has said AI will play a major role in the future of team productivity. Bank of America Merrill Lynch predicts that AI will have a $9 trillion impact on knowledge work over the coming decade.

Collokia, machine learning company that builds seamless collaboration solutions for software developers, announced the beta launch of its new, collaborative machine-learning platform, designed to foster collaboration within software teams by enabling improved access to information and knowledge. Software teams spend a great deal of time researching technical solutions, especially when the technology they are working with is new to the team. But sifting through the vast array of information available on the Internet is cumbersome. Collokia's collaborative machine-learning platform offers an easy-to-use solution that allows software teams to easily identify, catalog, and share useful information, reducing the time spent on research and promoting increased knowledge transfer between, and within, development teams. Most collaboration platforms have cumbersome systems for information sharing, placing an extra burden on already busy teams, Collokia's platform for knowledge mapping, collection, and distribution is designed to be completely transparent and effortless.

From undergrads in music and social work, to PhDs in philosophy, to those who never graduated high school -- I've had quite a variety of co-workers during the ten years I've been in tech. Of course, in every software company you'll find your traditional computer science and engineering graduates as well. However, there's a significant and growing population of developers who took a different path to learn to code and are building a profession out of it. I hold a degree in linguistics, which in most universities is not a computational program, but an anthropological one. Required coursework includes topics such as historical and cultural language studies.