Artificial intelligence (AI) and machine learning (ML) can help the humans in DevOps break free from focusing on simple activities.

"Falsehood flies, and the truth comes limping after it," wrote Jonathan Swift over 200 years ago. If that was the case back then, before telephones and radio, let alone Twitter and Instagram, imagine how much bigger the problem is now. In fact, it's so big that "fake news" has become a hot topic for those on both sides of the political spectrum. Gartner has gone as far as predicting that by 2022, we will consume more lies than truth. But if technology has exacerbated the situation, there's hope that it may also offer remedies.

One of the most contentious aspects of AI is the meaning of'intelligence.' No one debates the meaning of the word'strength,' or belittles the idea that machines can be stronger than humans, or even tries to re-define mechanical strength to mean some mysterious physico-spiritual capability that is unique to humans. The debate around the meaning of intelligence when it crops up in any conversation on AI is extremely baffling - until we take into account the fragile psychology of humans. Somehow, we've convinced ourselves that cognitive abilities are the sole province of the human brain, while we grudgingly cede the physical realm to the machines. Every encroachment on human cognitive abilities is fiercely contested.

Toby discusses his early dreams of building thinking machines inspired by science fiction - and covers AI Ethics and current to near term applicability in intelligent systems. Toby Walsh is a leading researcher in Artificial Intelligence. He was recently named in the inaugural Knowledge Nation 100, the one hundred "rock stars" of Australia's digital revolution. He is Guest Professor at TU Berlin, Scientia Professor of Artificial Intelligence at UNSW and leads the Algorithmic Decision Theory group at Data61, Australia's Centre of Excellence for ICT Research. He has been elected a fellow of the Australian Academy of Science, and has won the prestigious Humboldt research award as well as the 2016 NSW Premier's Prize for Excellence in Engineering and ICT.

A Google service has gone down – and taken many of the largest parts of the internet down with it. Snapchat, Spotify, Discord and other major web services ran into problems because of an issue at the web giant. While Google's own websites and apps appeared to be working, the company also provides a range of service to third-parties. It appeared to be an issue with one of those technical tools that is causing the issues. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

Today, most successful AI systems require millions of points of human-labeled data, like photos of cats, to train themselves to recognize faces and objects like people do. Or they have to play games tens of thousands of times, like Google's AlphaGo Zero did.

NEC has partnered with dotData, a Silicon Valley venture in the automation of data science, to deliver artificial intelligence and data analytics solutions to the Sumitomo Mitsui Financial Group (SMBC Group) for its financial solutions. NEC has secured an exclusive license of dotData platform to provide this software across Japan. Since 2016, Sumitomo Mitsui Banking Corporation, NEC and the dotData team have been actively working to integrate AI into banking operations to develop new service offerings. As a result of this successful collaboration, the SMBC Group has decided to use dotData platform across the five group companies. Using dotData platform, the SMBC Group wants to deal with issues such as the marketing of various financial products, including credit cards and housing loans.

Researchers from the University of Southern California, Pinscreen, and Microsoft developed a deep learning-based method that can generate full 3D hair geometry from single-view images in real time. This is the first deep learning project that can render hair in real time, the team said. "Realistic hair modeling is one of the most difficult tasks when digitizing virtual humans," the researchers said. "In contrast to objects that are easily parameterizable, like the human face, hair spans a wide range of shape variations and can be highly complex due to its volumetric structure and level of deformability in each strand." Using NVIDIA TITAN Xp GPUs with the cuDNN-accelerated PyTorch deep learning framework, the researchers trained their convolutional neural network on a dataset comprised of over 40,000 different hairstyles and 160,000 corresponding 2D orientation images rendered from random views.

Certain statements included in this news release constitute forward-looking statements or forward-looking information under applicable securities legislation. Such forward-looking statements or information are provided for the purpose of providing information about management's current expectations and plans relating to the future. Readers are cautioned that reliance on such information may not be appropriate for other purposes. Forward-looking statements or information typically contain statements with words such as "anticipate", "believe", "expect", "plan", "intend", "estimate", "propose", "project" or similar words suggesting future outcomes or statements regarding an outlook. Forward-looking statements or information in this news release include, but are not limited to, management's targets for the Company's growth in 2017, as well as the size, scope, and timing of the implementation of projects currently in the pilot phase.