A time series is a sequentially indexed representation of your historical data that can be used to solve classification and segmentation problems, in addition to forecasting future values of numerical properties, for example, air pollution level in Madrid for the last two days. This is a very versatile method often used for predicting stock prices, sales forecasting, website traffic, production and inventory analysis, or weather forecasting, among many other use cases. Soon, BigML will have time series as a new resource. Following our mission of democratizing machine learning and making it easy for everyone, we will provide new learning material for you to start with time series from scratch and become a power user over time. We start by publishing a series of six blog posts that will progressively dive deeper into the technical and practical aspects of time series with an emphasis on time series models for forecasting.

It's perhaps unsurprising, given both history and the entertainment industry, that we might be afraid of a cybernetic takeover that forces us to live locked away, "Matrix"-like, as some sort of human battery. And yet it is hard for me to look up from the evolutionary computer models I use to develop AI, to think about how the innocent virtual creatures on my screen might become the monsters of the future. Might I become "the destroyer of worlds," as Oppenheimer lamented after spearheading the construction of the first nuclear bomb? I would take the fame, I suppose, but perhaps the critics are right. Maybe I shouldn't avoid asking: As an AI expert, what do I fear about artificial intelligence?

LONDON (Reuters) - The world's leading drug companies are turning to artificial intelligence to improve the hit-and-miss business of finding new medicines, with GlaxoSmithKline unveiling a new $43 million deal in the field on Sunday. Other pharmaceutical giants including Merck & Co, Johnson & Johnson and Sanofi are also exploring the potential of artificial intelligence (AI) to help streamline the drug discovery process. The aim is to harness modern supercomputers and machine learning systems to predict how molecules will behave and how likely they are to make a useful drug, thereby saving time and money on unnecessary tests. AI systems already play a central role in other high-tech areas such as the development of driverless cars and facial recognition software. "Many large pharma companies are starting to realize the potential of this approach and how it can help improve efficiencies," said Andrew Hopkins, chief executive of privately owned Exscientia, which announced the new tie-up with GSK. Hopkins, who used to work at Pfizer, said Exscientia's AI system could deliver drug candidates in roughly one-quarter of the time and at one-quarter of the cost of traditional approaches.

The iCub robot tries to catch a ball during the Innorobo European summit, an event dedicated to the service robotics industry, in Lyon, central France, Thursday, March 15, 2012. You've probably heard of artificial intelligence by now. But what is AI, why are people talking about it now, and what will it mean for your everyday life? SunTrust recently released a report that breaks down how AI works, so let's tackle those questions one at a time. AI is what people call computer programs that try to replicate how the human brain operates.

Most economists agree that advances in robotics and AI over the next few decades are likely to lead to significant job losses. But what's less often considered is how these changes could also impact social mobility. A new report from UK charity Sutton Trust explains the danger, noting that unless governments take action, the next wave of automation will dramatically increase inequality within societies, further entrenching the divide between rich and poor. The are a number of reasons for this, say the report's authors, including the ability of richer individuals to re-train for new jobs; the rising importance of "soft skills" like communication and confidence; and the reduction in the number of jobs used as "stepping stones" into professional industries. For example, the demand for paralegals and similar professions is likely to be reduced over the coming years as artificial intelligence is trained to handle more administrative tasks.

LAS VEGAS – "Mark Minevich didn't mince words in his Rise of the Autonomous Enterprise presentation here at Interop last week: "Whoever doesn't get involved in AI will die and get phased out." Minevich, a senior advisor to the government's Council of Competitiveness in Washington D.C., ticked off several examples of companies that have transformed industries by leveraging AI technologies, including Amazon with its personalized recommendations and Tesla. "Tesla has accumulated over 750 million miles of data to make cars smarter," said Minevich. The good news is that the U.S. is widely viewed as a leader in AI. Minevich said there's more AI investment in Silicon Valley, for example, than anywhere else in the world and it's growing. Last year estimates put AI investments at $2.5 billion, a figure that's forecast to double to $5 billion 2017. Pointing to forecasts by consulting giants Accenture and McKinsey, Minevich said "AI will deliver a massive trillion-dollar economy and the U.S. ...

A quick, hassle-free way to stay on top of robotics news, our robotics digest is released on the first Monday of every month. Sign up to get it in your inbox. Let's kick off our June review by looking at some great new robotics research and development in action: Inspired by arthropod insects and spiders, Harvard Professor George Whitesides and Alex Nemiroski--a former postdoctoral fellow in Whitesides' Harvard lab--have created a type of semi-soft robot capable of standing and walking. The team also created a robotic water strider capable of pushing itself along the liquid surface. The robots are described in a recently published paper in the journal Soft Robotics.

In the summer of 2013, as Matthew Zeiler was close to finishing a Ph.D. in artificial intelligence at New York University, he seemed to have every tech giant in the palm of his hand. Zeiler had left an internship with a Google AI group a few weeks earlier when he got a call from an unknown number while he was running along the Hudson River. It was Alan Eustace, then a senior vice president of engineering at Google, who had heard about Zeiler's AI chops. Eustace wanted Zeiler to join permanently. To entice him, Eustace told him he would make an offer that was among the highest Google had ever made to a new graduate, Zeiler recalls.

When the field of artificial intelligence was founded more than five decades ago, computer scientists could only dream of the type of capabilities that an average consumer might now take for granted. We are living in a golden age of AI advances. Every day, it seems like computer scientists are making more progress in areas such as computer vision, deep learning, speech and natural language processing -- areas of AI research that have challenged the field's foremost experts for decades. Those breakthroughs are bringing to life tools including Microsoft Translator that were, only recently, the stuff of fantasy and science fiction. And these tools are, in turn, helping people in so many ways, by breaking down language barriers and facilitating communication.

Ravens can plan for future events at least as well as 4-year-old humans and some adult, non-human great apes. The birds did this in tasks they wouldn't encounter in the wild, so it isn't an adaptation to an ecological niche, but rather a flexible cognitive ability that evolved independently in birds and hominids, whose lineages diverged about 320 million years ago. Planning for future events requires the use of long-term memory for some anticipated future gain. For a long time, it was thought to be a uniquely human trait. Children begin showing such abilities when they are about 4. But it turned out that chimpanzees, bonobos and orangutans have this ability too, making tools to use later on.