With the Radeon Instinct line, AMD joins Nvidia and Intel in the race to put its chips into AI applications--specifically, machine learning for everything from self-driving cars to art. The company plans to launch three products under the new brand in 2017, which include chips from all three of its GPU families. The passively cooled Radeon Instinct MI6 will be based on the company's Polaris architecture. It will offer 5.7 teraflops of performance and 224GBps of memory bandwidth, and will consume up to 150 watts of power. The small-form-factor, Fiji-based Radeon Instinct MI8 will provide 8.2 teraflops of performance and 512GBps of memory bandwidth, and will consume up to 175 watts of power.

Artificial intelligence, machine and deep learning are some of the hottest areas in all of high-tech today. We've had a few generations of AI over the last 50 years, but in 2010, IBM kicked off the latest cycle with Watson, using brute-force, Big Data techniques to win jeopardy. The University of Toronto in 2012 pioneered Imagenet using deep learning to identify pictures. NVIDIA then began to drive the GPU-accelerated training technology of deep neural nets, and in the course of that, huge service providers opened up and announced initiatives beginning with Microsoft, Google, Apple, Samsung, and then Amazon. Chinese giants Baidu, Alibaba and Tencent are of course, involved.

thought is the contemplation of things beyond what we can sense.

In this tutorial, you discovered how to normalize and standardize time series data in Python. That some machine learning algorithms perform better or even require rescaled data when modeling. How to manually calculate the parameters required for normalization and standardization. How to normalize and standardize time series data using scikit-learn in Python. That some machine learning algorithms perform better or even require rescaled data when modeling. How to manually calculate the parameters required for normalization and standardization. How to normalize and standardize time series data using scikit-learn in Python. Do you have any questions about rescaling time series data or about this post? Ask your questions in the comments and I will do my best to answer.

Backed by sleek devices and powered by intelligent software and apps, smartphones are shaping the future of healthcare. The latest development in medical apps is the use of artificial intelligence and machine learning to analyze data and offer a diagnosis within seconds. ResApp Health, a digital healthcare solutions company based in Australia, is developing an app that can diagnose respiratory conditions with a smartphone's microphone, which acts as a stethoscope, according to MobiHealthNews. The ResAppDx app applies specially developed machine learning algorithms to the sounds, including cough sounds, which automatically identify potential respiratory conditions, including pneumonia, asthma, bronchiolitis and chronic obstructive pulmonary disease (COPD). Another company utilizing artificial intelligence advances is Beyond Verbal, which has launched a research platform that's attempting to identify biomarkers in users' voices to detect a range of health issues, including heart problems, ALS and even Parkinson's disease.

CoverGirl has released what it claims is the first influencer chatbot marketing campaign, using a program designed to emulate a real person's conversational style. The make-up brand, which was spun off to Coty from Procter & Gamble in October, invited fans to use the teen-focused messaging app Kik to interact with a chatbot version of Kalani Hilliker, a 16-year-old American dancer, model and TV personality. The chatbot was created by influencer marketing platform The Amplify and chatbot developer Automat, companies that became part of the 18-month-old network You & Mr Jones in mid-2016. "Mobile commerce will be colossal using bots," said David Jones, former Havas global CEO and founder of You & Mr Jones. "In 12 months there will be thousands of these. Traditional ads can cost thousands per click -- this is a conversation on Kik." Results so far include 14 times more conversations with the chatbot than with an average post by Ms. Hilliker, 91% positive sentiment, an average of 17 messages per conversation, 48% of conversations leading to coupon delivery and 51% click-through on coupons delivered, according to Mr. Jones.

If Hollywood is to be believed, the development of super-intelligent AI will spell the end of civilization as we know it and spark an unwinnable war between man and machine. It doesn't make for nearly as exciting entertainment, but artificial intelligence also offers tremendous upside, from the potential to deliver customized education to everyone, to improving disease diagnosis and treatment and eradicating poverty. Although AI researchers are focused these beneficial outcomes, the dystopian vision portrayed in so much science fiction is also a real possibility. At the recent Singularity University (SU) New Zealand Summit we talked with Neil Jacobstein, the former president and current chair of the Artificial Intelligence and Robotics Track at SU, about how the outcomes feared by so many can be avoided.

One of the biggest obstacles to the adoption of autonomous vehicles (AVs), is safety. The misconception that artificial intelligence is unsafe is mostly driven by media and is thankfully changing. AVs do certainly pose an original problem to insurance companies. And with the autonomous vehicle industry set to grow exponentially in the next 20 years, insurance companies are going to have to figure out a solution to the challenge, fast. The reality is that the definition of autonomous is still very gray.

CoverGirl has released what it claims is the first influencer chatbot marketing campaign, using a program designed to emulate a real person's conversational style. The make-up brand, which was spun off to Coty from Procter & Gamble in October, invited fans to use the teen-focused messaging app Kik to interact with a chatbot version of Kalani Hilliker, a 16-year-old American dancer, model and TV personality. The chatbot was created by influencer marketing platform The Amplify and chatbot developer Automat, companies that became part of the 18-month-old network You & Mr Jones in mid-2016. "Mobile commerce will be colossal using bots," said David Jones, former Havas global CEO and founder of You & Mr Jones. "In 12 months there will be thousands of these. Traditional ads can cost thousands per click -- this is a conversation on Kik." Results so far include 14 times more conversations with the chatbot than with an average post by Ms. Hilliker, 91% positive sentiment, an average of 17 messages per conversation, 48% of conversations leading to coupon delivery and 51% click-through on coupons delivered, according to Mr. Jones.

Don't worry about the robots, worry about the humans. There's a huge difference between the modest aims of the artificial intelligence (AI) and machine learning being used today, and the grand ideas of creating an artificial general intelligence that could match -- and then rapidly exceed - the capabilities of a human mind As they develop, AI and machine learning will be able to take on even more complicated tasks, but it could still be half a century or more before AI capable of human-level intelligence is built. And, then, even longer before the sort of super-intelligence emerges that excites some, terrifies others and has provided plot lines for science fiction for decades. One may (eventually) lead to the other, but conflating today's AI and machine learning with tomorrow's Skynet is not helpful. Indeed, that confusion has encouraged many to exaggerate the short-term potential of existing (and often somewhat mundane) AI and machine learning technologies.