We make a major error when we think of AI as a technology, or perhaps as just another technology. This error can turn out to be a costly mistake. Specifically, using the term "technology" to describe artificial intelligence can influence us to ignore the perils of AI, to accept it as we have accepted other technologies, and to incorrectly assume that in the past 3 centuries we have acquired enough experience to deal with technological revolutions. AI is different and hence it should be approached completely differently. Most importantly it should be approached humbly – and with an understanding that this is not something we have dealt before.

Can artificial intelligence improve government accountability? Last year Bass provided an excellent overview of the role big data can play in increasing government accountability. His analysis covered the current state of affairs and the problems with achieving the goal of a transparent government (Bass, 2015). In an amazing and eye-opening manner, he showed that while data can increase government accountability, numerous unresolved issues remain that must be overcome before we can have higher transparency. One of the major issues identified by Bass is the fact that many stakeholder (including journalists, agencies, members of congress, and others) don't want greater transparency.

Todoist is one of the more full-featured to-do services out there, and it's available on nearly every platform out there. Whether you use Mac or Windows, iOS or Android, Todoist has you covered. It works much like you'd expect: you can ask Alexa to add items to the various lists that you have in your Todoist account, and you can also ask it to tell you everything that's on your to-do list for that day. And Alexa works with Todoist's natural language processing, so you can ask it to add things to your list "tomorrow" or "next Wednesday" and it'll know just what you're asking it for. It's not clear if you'll be able to tell Alexa to add items to specific projects or to-do lists in your account -- they probably get added to whatever your default list is for you to sort out on your phone or computer.

I hear a lot of complaints about machine learning from business clients. It's too complicated is one of them. Machine learning is complex by nature. The more that complexity spills over to users and executive management, the more turned off to machine learning they become. I've seen it happen in real time.

On January 7, 2016, I attended University of Toronto's machine learning conference entitled, "Machine Learning and the Market for Intelligence". It was a tremendously informative and exhilarating experience! Geoff Hinton, one of the world's foremost researchers in this field, presented his ideas, as did several other top-notch authors and researchers. Jerry Kaplan, the author of "Humans Need Not Apply", provided an energetic and impassioned view of why he believes AI-regulation is not as important as execution at this stage of ML (machine learning) technology. Venture Capitalists from the valley made the trip up north, to discuss how they were assessing startups which use ML to build applications for diverse industries such as HR, logistics, healthcare, and medical research.

Holy Dress, which was created by Melissa Coleman in collaboration with Leonie Smelt and Joachim Rotteveel, centers around a speech recognition system that analyzes voice stress as an indicator of untruthfulness.

This year has seen both artificial intelligence (AI) along with bots dominate tech news based on the advancements that have been taking place in both areas. We're just beginning to see the possibilities and implications that both of these technologies will bring in our near futures. People have been contemplating ways to leverage these technologies for creating a presence for people that have died long before they began dominating the news. Several years ago I discovered Lifenaut and found myself intrigued and imagining a future where a digital version of myself would exist long after I died. The service allows you to upload documents, photos, videos, additional data as well as connect to your social accounts.

I'm going to describe how the gains we make in artificial intelligence could ultimately destroy us. And, in fact, I think it's very difficult to see how they won't destroy us or inspire us to destroy ourselves. And yet if you're anything like me, you'll find that it's fun to think about these things. And that response is part of the problem. One of the things that worries me most about the development of AI at this point is that we seem unable to marshal an appropriate emotional response to the dangers that lie ahead.

N-myristoyltransferase (NMT) catalyzes the transfer of myristate to the amino-terminal glycine of a subset of proteins, a co-translational modification involved in trafficking of substrate proteins to membrane locations, stabilization and protein-protein interactions. It has been studied and validated pre-clinical drug target for fungal and parasitic infections. In the present study, machine learning approach, docking studies and CoMFA analysis has been integrated with the objective of translation of knowledge into pipelined workflow towards the identification of putative hits through screening of large compound libraries. In the proposed pipeline, the reported parasitic NMT inhibitors have been used to develop predictive machine learning classification models. Simultaneously, TbNMT complex model was generated to establish relationship between binding mode of inhibitors for LmNMT and TbNMT through molecular dynamics simulation studies.

An assemblage of technological breakthroughs are rapidly morphing to create massive changes in how businesses operate. Artificial intelligence (AI), blockchain and Internet of Things (IoT) are just three of eight crucial "megatrends" that strategy consulting firm PricewaterhouseCoopers (PwC) says is going to significantly distort business. Those new forces should clearly be planned for. And although the consulting firm's advice is aimed at generalized CEOs, it's IT and technical teams that will have to lay the groundwork. Robots, augmented reality (AR), 3D printing, drones and virtual reality (VR) are also among PwC's pick of "essential eight technologies" that the firm says in its report (PDF) (released during the summer) need to be considered by company chiefs to move their operations forward.