Beginning with the status of Artificial Intelligence, we will continue by envisioning the development of AI over the coming years, before discussing the implications of Rise of AI for us as a whole. See our preliminary program and check out our AI Topics.

AI's next frontier requires ethics built through policy. With one foot in its science fiction past and the other in the new frontier of science and tech innovations, AI occupies a unique place in our cultural imagination. Will we live into a future where machines are as intelligent -- or frighteningly, more so -- than humans? We have already witnessed AI predict the outcome of the latest U.S. presidential election when many policy wonks failed. Perhaps we are further along than we thought.

Video viewability is a top priority for video publishers who are under pressure to verify that their audience is actually watching advertisers' content. In a previous post How Deep Learning Video Sequence Drives Profits, we demonstrated why image sequences draw consumer attention. Advanced technologies such as Deep Learning are increasing video Viewability through identifying and learning which images make people stick to content. This content intelligence is the foundation for advancing video machine learning and improving overall video performance. In this post, we will explore some challenges in viewability and how deep learning is boosting video watch rates.

IBM has produced a glossy multimedia website (see below) to expound the possibilities under the label "IBM 5 in 5: five innovations that will help change our lives within five years." And analog, MEMS and sensors are prominent. But digital electronics will also have its say in the form of big data and artificial intelligence. The full list is artificial intelligence; hyperspectral imaging; microfluidic lab-on-chips, networks of novel sensors and something IBM calls "macroscoping." Amongst the developments IBM researchers are predicting – and a slightly disconcerting prediction at that – is that what we say and write could be monitored and used as indicators of our mental health and physical well-being. Patterns of speech and writing and how they change over time, analysed by cognitive systems, could provide tell-tale signs of early-stage developmental disorders, mental illness and degenerative neurological diseases.

With China making rapid progress in artificial intelligence (AI)-based research, it is imperative that India view AI as a critical element of its national security strategy, recommends an August 2016 report titled India and the Artificial Intelligence Revolution. Thanks to the increasingly digital economy, fuelled by improving education and globalization, the Indian consumer is unknowingly the country's biggest beneficiary of recent advances in AI, notes the report. From utilizing various applications powered by AI to using a range of online services such as Amazon Marketplace and Netflix that learn from consumers' online behaviour to make intelligent product and service recommendations, consumers are readily engaged with the proliferation of AI in India, whether they appreciate it or not. Indian academics, public researchers, labs, and entrepreneurs face a different challenge than the corporations that dominate the space--the infrastructure necessary for an AI revolution in India has been neglected by policymakers. While lack of physical infrastructure is certainly a major impediment, India's AI development also suffers from the paucity of the necessary cultural infrastructure, which is key for recent advances from lab to marketplace in AI.

In 2008, engineering student Samay Kohli wanted to build a humanoid robot, but his professor told him it would not be possible. Along with his fellow student Abhay Singhal, not only did they achieve that task, but they have also built GreyOrange, a multi-national robotics company based in India and operating across Asia. "We've done some stuff that India was not supposed to do," Mr Kohli told the BBC. "People are not supposed to build hardware, robot products, out of India and we've been able to do that." So how did GreyOrange grow from an engineering classroom to an international robotics player?

SANAA/ADEN – Suspected U.S. drone strikes have killed three alleged al-Qaida operatives in Yemen's southwestern Bayda province, security and tribal officials said, the first such killings reported in the country since Donald Trump assumed the U.S. presidency Friday. The two Saturday strikes killed Abu Anis al-Abi, an area field commander, and two others, the officials said, speaking on condition of anonymity as they were not authorized to release the information to journalists. U.S. drone strikes against suspected al-Qaida targets have been commonplace in the years since the Sept. 11, 2001, attacks on New York and Washington, as a retaliatory measure against the group. The use of unmanned aircraft as well as airstrikes in the Arab world's poorest country rose dramatically under President Barack Obama, with data from the Britain-based Bureau of Investigative Journalism showing spikes in attacks, especially in 2012 and 2016. On Thursday, U.S. intelligence officials said as many as 117 civilians had been killed in drone and other counterterror attacks in Pakistan, Yemen and elsewhere during Obama's presidency.

The trend and seasonality can be accounted for in a linear model by including sinusoidal components with a given frequency. However, finding the appropriate frequency for each sinusoidal component requires a little more digging. This post shows how to use fast Fourier transforms to find these frequencies. For the purposes of this post, we will only focus on the T(t) and S(t) components. The actual model fitting will be done in a separate post.

This text provides R tutorials on statistics including hypothesis testing, ANOVA and linear regressions. It fulfills popular demands by users of r-tutor.com for exercise solutions and offline access. Part III of the text is about Bayesian statistics. It begins with closed analytic solutions and basic BUGS models for simple examples. Then it covers OpenBUGS for Bayesian ANOVA and regression analysis.

AI can improve customer personalization, identify patterns and connections that humans can't, and answer questions about banking issues in real-time. Financial institutions are already finding success with AI. However, what may be'amazing' today will be table stakes in the near future. Artificial intelligence (AI) is not new to banking. If we consider that the definition of AI is the ability for machines to interact and learn to do tasks previously done by humans, the history of AI goes back to the 50s in the banking industry.