Arguing for a ban related to human cloning research in the late 1990s, Leon Kass, chairman of George W. Bush's President's Council on Bioethics, controversially invoked "the wisdom of repugnance": the idea that disgust can be "the emotional expression of deep wisdom," cluing us in that a scientific or technological practice is nasty, sinister, a threat to our humanity. Shelley's Frankenstein takes the contrary ethical stance, showing us the hazards of repugnance--how the creature is turned violent and vengeful after rejection by people horrified at his appearance. Responsible engagement with emerging technologies ranging from iPhones and Google search to artificial intelligence and genetic engineering requires us to reject physiognomy, the age-old fallacy that we can deduce the virtue or vice of something (or someone) by assessing its exterior beauty. The sexiness of our contemporary Frankenstein's creatures captures the enormous difficulty of rejecting technological charm--after all, in Splice, Ex Machina, Her, and Westworld, the irresistible creatures come out on top, outfoxing, transcending, or physically eviscerating their hapless creators and caretakers.

Machine learning is cresting the fresh wave of 2017 HR trends. Gartner research predicts algorithms will positively alter the behavior of over one billion global workers by 2020, while over 3 million people can look forward to "roboboss" supervisors. Yvonne Bauer, Head of Predictive Analytics at SAP SuccessFactors, sees machine learning becoming more widespread this year as part of HR's steady progression from art to data-driven science. "More companies will look into machine learning, moving from individual projects to actual products built into HCM suites," she said. "Conversational interfaces like chat bots and natural language processing will emerge this year, allowing companies to change how workers interact with the system and derive insights from those activities, including what people are working on and how engaged they are."

Chief Data Officers, Chief Technology Officers, Chief Operation Officers and Heads of Innovation from the top 250 insurance and re-insurance companies form the advisory board and the panel of speakers and participants. Dozens of artificial intelligence, machine learning and IOT experts and enthusiasts will be joining the panels and debates, with some of the most senior C-level executives from the world's largest insurance giants, as well as medium size underwriters, brokers and small companies, to explore the future impact of AI and IOT on your business. In short, if you want to know what AI is going to do for you, then instechAI2020 is the place to be.

Google co-founder Sergey Brin acknowledges that he was caught off-guard by the phenomenon of artificial intelligence, which he notes now permeates key Google properties. Speaking at the recent World Economic Forum Meeting in Davos-Klosters, Switzerland, Brin, a trained computer scientist, said he didn't pay attention to AI in the 1990s because "everyone knew [AI] didn't work," he said. Brin was head of the Google X research group, which featured Google Brain, a project centered on machine intelligence, he recalled. "Fast-forward a few years, and now Brain probably touches every single one of our main projects, ranging from search to photos to ads to everything we do." The revolution in deep nets has "been very profound and definitely surprised me even though I was like right in there," said Brin, now president of Google parent company Alphabet.

Google is planning to bring artificial intelligence and machine learning tools to the diminutive Raspberry Pi this year. "Google is going to arrive in style in 2017. The tech titan has exciting plans for the maker community," said The Raspberry Pi Foundation. 'We thought we'd sell 1,000': The inside story of the Raspberry Pi The $35 Linux Raspberry Pi computer has sparked a coding revolution. "Google's range of AI and machine learning technology could enable makers to build even more powerful projects," it said.

Designing a good artificial intelligence is hard. For a company like Google, which relies heavily on AI, designing the best possible AI software is crucial. And who better to design an AI than another AI? If you said "literally anyone else" you might be right, but folks at Google's AI research lab, Google Brain, would disagree. The lab is reportedly building AI software that can build more AI software, with the goal of making future AI cheaper and easier. Currently, building a powerful AI is hard work.

AI will destroy jobs, robots will replace humans … That's what we often hear when we talk about the evolution of AI and the rise of robots. But what if Artificial Intelligence could actually boost the economy? We recently conducted a study with Censuswide and asked around 1000 British citizens how they felt about AI and its impact on the automation of their calendar management tasks. One interesting thing to notice is that 47% of professionals in the UK would be interested in using Artificial Intelligence powered assistants to gain time. And how would they spend the time they saved?

Google plans to bring its artificial intelligence, machine learning and all its other developer tools to the small computer. Google has announced its partnership with Raspberry Pi to develop a range of smart tools that will made available in 2017. The company plans to bring its artificial intelligence, machine learning and all its other developer tools to the small computer. In a blog post, Raspberry Pi said: "The tech titan has exciting plans for the maker community… Google's range of AI and machine learning technology could enable makers to build even more powerful projects." With the help of Raspberry Pi makers, suggestions of ideas will be given to Google for development direction through the creation of a survey.

Familiarize yourself with the AI technologies available today and prepare for adoption -- or face the inevitability of disruption. These days it seems like you can't open a newspaper (OK, web browser) without coming across an article on artificial intelligence (AI). Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of them. Publicized breakthroughs -- like Google AlphaGo's unprecedented victories over human Go champions -- have heralded the promise of a new golden age for AI.

Enterprise cloud usage has been in the forefront of big players for the past few years. Amazon, IBM, Google and Microsoft are expanding their offerings to serve better the enterprise users and their needs. Google announced a set of machine learning based services focused on enterprise users. Similar to upcoming Amazon EC2's Elastic GPUs and Microsoft's Azure N-Series, powered by NVidia GPUs, Google will soon offer cloud based GPUs with per minute billing focused on Machine Learning tasks. Google slashed pricing for its Cloud Vision API to 1/5, offering face, label, OCR, company logos, explicit content and landmark and image properties recognition through off the shelf algorithms and their API.