The quest to give machines human-level intelligence has been around for decades, and it has captured imaginations for far longer -- think of Mary Shelley's Frankenstein in the 19th century. Artificial intelligence, or AI, was born in the 1950s, with boom cycles leading to busts as scientists failed time and again to make machines act and think like the human brain. But this time could be different because of a major breakthrough -- deep learning, where data structures are set up like the brain's neural network to let computers learn on their own. Together with advances in computing power and scale, AI is making big strides today like never before. Get the entire 10-part series on Timeless Reading in PDF.

I had a conversation with BuzzSumo co-founder Steve Rayson who said writing algorithms are available for purchase, have been bought, and are in use by major platforms. And, they are creating well-written, data-backed articles, he said. I knew the AI landscape was evolving in the industry: But just how much would it really affect content creation? I took a data-driven look at the reality. How much has AI been implemented behind the scenes for content creation?

Robert Weideman, Executive Vice President and General Manager of Nuance Enterprise, notes that, 'When you think of conversational AI, you need to think of a person. Literally, we're trying to mimic a human agent. Consumers also expect conversations they have to flow from one channel to another – so they don't have to backtrack or repeat themselves.' Understanding emotions is key to this, and the technology is not light years away. Futurist Ray Kurzweil, a leading AI scientist, said in an interview with Wired that a machine understands that kind of complex natural language, it becomes, in effect, conscious, and said that he believes this moment to be in just 2029, when machines will have full'emotional intelligence, being funny, getting the joke, being sexy, being loving, understanding human emotion. That's actually the most complex thing we do.

There was an interesting discussion initiated by Peter Schoof at BPM.com: So? How big of an impact do you think artificial intelligence will have on processes in 2018? Artificial intelligence is a multi-dimensional subject area. It can be broadly classified as a blend of machine learning, predictive/adaptive analytics, NLP, text analytics, voice pattern recognition, image analytics, deep learning, graph analytics, robotics, and much more. The current state of adoption of AI complementing business processes in an enterprise is a bit chaotic with discussions, debates, PoCs, R&D, etc. Hopefully, the coming year will mark a more structured and focused approach. AI implementation is not new for the enterprise in terms of processes -- they are already using AI in one form or another (magnitudes may differ).

Titir Pal, Director, Solutions, Absolutedata AnalyticsBig Data is moving to a new stage of maturity that promises great business impact and industry disruption over the course of the coming decade. As Big Data capabilities mature, organizations are now combining the agility of Big Data processes with the scale of Artificial Intelligence (AI) to accelerate the business value and returns. The convergence of Big Data with AI has emerged as the single most important development that is shaping the future of how business extract value from their data and analytics capabilities. The availability of greater volumes and sources of data is enabling capabilities in AI and machine learning. Digital capabilities have moved data from batch to real-time, on-line, always-available access.

For the past 90 years, TIME magazine has named a'Person of the Year'. The result is based on who has had the most influence on the news, leading to some controversial but entirely justified selections including Adolf Hitler and Josef Stalin. Last year, Donald Trump received the title over resounding favourite Narendra Modi. This year the Crown Prince of Saudi Arabia, Mohammed bin Salman, topped the reader's poll with a clear majority. Despite this, history repeated itself yet again when the #MeToo Campaign was announced as TIME's final choice. So, despite various online polls and predictions, it's notoriously difficult to know who will be picked.

In 2017, the predictive ability of artificial intelligence (AI) powered many new tools and platforms. So what does 2018 have in store for AI? I asked some marketers to find out. Gregg Johnson, CEO of Invoca, a call tracking and analytics service, says that 2018 will be "the year the voice trend becomes undeniable." "As people increasingly trade typing for talking, we'll see more companies invest in developing for voice interfaces," Johnson said.

Audio Analytic, the pioneer of sound recognition software and hearables manufacturer Bragi, today announced a partnership to collaborate on incorporating sound recognition capabilities into Bragi devices. The companies share a vision of how embeddable intelligent sound recognition can bring new levels of usability, convenience and safety to earphone users. At January's Consumer Electronics Show 2018 (CES) Audio Analytic, will use their conversation detection demonstration, developed with Bragi, to illustrate how sound recognition can help consumers seamlessly move between a rich audio experience and spontaneous interactions with their friends and important events around them. Bragi is a pioneer in the smart hearables category. The company manufactures wireless earphones with sensors and intelligence that enable features including real-time translation, fitness tracking, music, and gesture controls.

As described in our recent announcement about AI pioneer Randy Goebel joining the ROSS team as an advisor, Goebel is a professor in the Department of Computing Science at the University of Alberta, a founder and researcher with the Alberta Machine Intelligence Institute (AMII) and is involved with the development of the University of Alberta Google DeepMind relationship, the group behind AlphaGo. Goebel's theoretical work on abduction, hypothetical reasoning and belief revision is internationally acclaimed and his recent application of practical belief revision and constraint programming to scheduling, layout, and web mining has had widespread impact across multiple industry verticals. More recently, Goebel has been working on the application of machine learning to visual explanation and natural language processing, with focus on legal reasoning. He has previously held faculty appointments at the University of Waterloo and the University of Tokyo, and is actively involved in academic and industrial collaborative research projects in Canada, Australia, Malaysia, Europe and Japan. Goebel is on the advisory boards of the German Research Centre for AI, the Japan Science and Technology Organization and the Japanese National Institute for Informatics.

I am currently working on nlp and this is another research work that I encountered - https://arxiv.org/abs/1706.03762 It's the "Attention is all you need" paper. I am pretty sure most of the folks would have already read it (reddit:)). With this one in the light now, what do you think? Is it possible that the fully connected neural network is itself the key?