Artificial intelligence has never been as pervasive as it is today. From Google's self-driving cars from to Hilton's new Watson-powered hotel concierge, we are witnessing an explosion of AI capabilities. But while it may appear that machines are taking over, they are still tied to their human masters for one very important task: training. "We're in the middle of the'Big Bang' moment of AI," NVIDIA's Senior Product Manager Will Ramey says in the AISummit's new ebook on the topic. "We now have the deep neural networks, the explosion of big data, and now thanks to the leap in processing power with enhanced GPUs, we have the full package to see a real shift in the development of commercial real-world AI applications."

The International Business Communication Standards (IBCS or IBCS Standards) are practical proposals for the design of reports and presentations, meaning, in most cases, the proper conceptual, perceptual and semantic design of charts and tables.

Google's artificial intelligence (AI) division has achieved a landmark victory over the grandmaster of Chinese board game Go. The AlphaGo system beat three-time European Go champion Fan Hui 5:0 in a competition held at the company's London headquarters in October. AlphaGo was built by Google's AI division created from the 400m acquisition of London-based AI company DeepMind in 2014. The victory is notable because the complexity of Go makes it difficult for computer systems to calculate all the possible moves. Chess, for example, offers 400 possible moves after the first two, but Go offers 130,000, making it very difficult for an AI to perform those calculations to match a human opponent.

ARTIFICIAL INTELLIGENCE: Inside OpenAI, Elon Musk's Wild Plan to Set Artificial Intelligence Free Cade Metz WIRED "In the rarefied world of AI research, the brightest minds aren't driven by--or at least not only by--the next product cycle or profit margin. They want to make AI better, and making AI better doesn't happen when you keep your latest findings to yourself." ROBOTICS: When a Robot Kills, Is It Murder or Product Liability? Ryan Calo Slate "There is a fundamental similarity between the question of whether a robot can be responsible and the question of whether a robot should enjoy rights...We wouldn't say of a driverless car that it possesses a responsibility to keep its passengers safe, only that it is designed to do so. But somehow, we feel comfortable saying that a driverless car is responsible for an accident."

At Facebook's recent annual developer conference, Marc Zuckerberg outlined the social network's artificial intelligence (AI) plans to "build systems that are better than people in perception." He then demonstrated an impressive image recognition technology for the blind that can "see" what's going on in a picture and explain it out loud. From programs that help the visually impaired and safety features in cars that detect large animals to auto-organizing untagged photo collections and extracting business insights from socially shared pictures, the benefits of image recognition, or computer vision, are only just beginning to make their way into the world -- but they're doing so with increasing frequency and depth. It's busy enough that the upcoming LDV Vision Summit, an annual conference dedicated to all things visual tech, from VR and cameras to medical imaging and content analysis, is already in its third year. "The advancements in computer vision these days are creating tremendous new opportunities in analyzing images that are exponentially impacting every business vertical, from automotive to advertising to augmented reality," says Evan Nisselson of LDV Capital, which organizes the summit.

You probably have read about it. Being a man of action he is doing something about it and has founded, together with other folks a non profit organization called Open AI. Open AI has assembled some of the best talent in the Deep Learning community. They went to Joshua Benglio, who is the only one of the Deep Learning "founding fathers" not working for a software company, and asked him to name a list of the best talent working on Deep Learning. They made offers to 10 of them and 9 accepted to join the effort.

I am highlighting several recent papers that show the potential of residual neural networks. Residual neural networks, or ResNets (Deep Residual Learning for Image Recognition), are a technique Microsoft introduced in 2015. The ResNet technique allows deeper neural networks to be effectively trained. ResNets won the ImageNet competition in December with a 3.57% error score. Recently, researchers have published several papers augmenting the ResNet model with some interesting improvements.

Large-scale automated meta-analysis of neuroimaging data has recently established itself as an important tool in advancing our understanding of human brain function. This research has been pioneered by NeuroSynth, a database collecting both brain activation coordinates and associated text across a large cohort of neuroimaging research papers. One of the fundamental aspects of such meta-analysis is text-mining. To date, word counts and more sophisticated methods such as Latent Dirichlet Allocation have been proposed. In this work we present an unsupervised study of the NeuroSynth text corpus using Deep Boltzmann Machines (DBMs). The use of DBMs yields several advantages over the aforementioned methods, principal among which is the fact that it yields both word and document embeddings in a high-dimensional vector space. Such embeddings serve to facilitate the use of traditional machine learning techniques on the text corpus. The proposed DBM model is shown to learn embeddings with a clear semantic structure.

SpaceX and Tesla Motors boss Elon Musk has open-sourced OpenAI Gym, which is a kind of training gym for artificial intelligence programs. The virtual gym is created to help computer programmers improve their AI systems. The gym is under Musk's OpenAI, an artificial intelligence research organization supported by over 1 billion in commitments. OpenAI is Elon Musk's nonprofit dedicated to releasing cutting-edge AI research for free. It is also backed by other Silicon Valley heavies, including LinkedIn's Reid Hoffman, Y-Combinator founders Jessica Livingston and Sam Altman, PayPal cofounder Peter Thiel and Stripe's Greg Brockman.

And that's probably the reason he's into the Google service that automatically generates replies to incoming messages. Smart Reply, as my editor will tell you, is pretty smart (It is!--Ed.). Having analyzed millions of messages from across Google's Gmail service, it can guess how you might respond to a particular missive. That may sound impersonal, but it's useful. It lets you instantly reply to someone when you don't have time to open a laptop or even tap out a message on your smartphone.