From Siri creator Dag Kittlaus comes Viv, a product that aims to be the next generation personal assistant. Kittlaus sat down with USA TODAY's Ed Baig to talk about Viv and where he thinks its headed. SAN FRANCISCO -- No matter what tech innovations Dag Kittlaus creates in the coming years, the 49-year-old speech recognition expert will be best known as the man who sold Siri to Apple CEO Steve Jobs. Now, strangely, the two figures have something else in common. According to an interview with Recode's Kara Swisher, Kittlaus reveals that in a routine screening he discovered he had the same rare type of pancreatic neuroendocrine cancer that felled Jobs in 2011.

Do you think Hollywood has lost touch with American values? Do you think Hollywood has lost touch with American values? The contentious presidential campaign was filled with accusations of elitism and bias by the media -- from the news to entertainment. Many supporters of Donald J. Trump saw his victory as a repudiation of the so-called liberal elite. So as 2017 begins, we ask: Is Hollywood representing all Americans? Are Hollywood values out of sync with American values? It's the start of a conversation we'll have all year with Hollywood's creators, consumers and observers. Most of all, we want to hear from you. Is Hollywood out of touch with your America? Here's what our critics and writers have to say: KENNETH TURAN on potent Hollywood visions that helped elect Trump TV's affluent bubble: MARY McNAMARA on Hollywood's reluctance to deal with class issues Fear of the powerful woman: JUSTIN CHANG on working women and men still behaving badly Realistic or cliche?: JEFFREY FLEISHMAN on ...

The overeager adoption of big data is likely to result in catastrophes of analysis comparable to a national epidemic of collapsing bridges. Hardware designers creating chips based on the human brain are engaged in a faith-based undertaking likely to prove a fool's errand. Despite recent claims to the contrary, we are no further along with computer vision than we were with physics when Isaac Newton sat under his apple tree. Those may sound like the Luddite ravings of a crackpot who breached security at an IEEE conference. In fact, the opinions belong to IEEE Fellow Michael I. Jordan, Pehong Chen Distinguished Professor at the University of California, Berkeley. Jordan is one of the world's most respected authorities on machine learning and an astute observer of the field. His CV would require its own massive database, and his standing in the field is such that he was chosen to write the introduction to the 2013 National Research Council report "Frontiers in Massive Data Analysis." San Francisco writer Lee Gomes interviewed him for IEEE Spectrum on 3 October 2014. IEEE Spectrum: I infer from your writing that you believe there's a lot of misinformation out there about deep learning, big data, computer vision, and the like. Michael Jordan: Well, on all academic topics there is a lot of misinformation. The media is trying to do its best to find topics that people are going to read about. Sometimes those go beyond where the achievements actually are.

Here I offer a few off-the-beaten-path interesting problems that you won't find in textbooks, data science camps, or in college classes. These problems range from applied maths, to statistics and computer science, and are aimed at getting the novice interested in a few core subjects that most data scientists master. The problems are described in simple English and don't require math / stats / probability knowledge beyond high school level. My goal is to attract people interested in data science, but who are somewhat concerned by the depth and volume of (in my opinion) unnecessary mathematics included in many curricula. I believe that successful data science can be engineered and deployed by scientists coming from other disciplines, who do not necessarily have a deep analytical background yet are familiar with data.

What major advances do you foresee in artificial intelligence in 2017? Despite the impressive progress that machine learning made in 2016, AI systems remain specialists: they cannot add new skills to their repertoires without erasing what they already know. This is the problem of catastrophic forgetting. An AI trained to recognise faces in photographs, for example, would not apply well to another visual task, such as recognising street signs. Each system would need to be trained for its own limited task.

Every year at CES, some of the world's biggest tech companies try to one-up each other. TVs get thinner and brighter. Home appliances get chattier and robots get friendlier. But this year, instead of standing out for their memorable devices, a lot of companies showed up with a shared identity: the voice of Alexa. Within a span of just two years, Amazon's cloud-based voice service has spread far beyond the Echo speaker where it first debuted.

Here's a conversation I had recently with Cleverbot. What are your views on the future of chatbots in language learning? User: What are your views on the future of chatbots in language learning? User: Do you think there is a future for chatbots in language education? Cleverbot: Sure, if you are talking about the moon. I also tried to have a conversation with Alice, the avatar from EFL Classroom Bot, listed by Larry Ferlazzo as one of'the best online chatbots for practicing English'.

If you came across an animal in the wild and wanted to learn more about it, there are a few things you might do: You might watch what it eats, poke it to see how it reacts, and even dissect it if you got the chance. Mathematicians are not so different from naturalists. Rather than studying organisms, they study equations and shapes using their own techniques. They twist and stretch mathematical objects, translate them into new mathematical languages, and apply them to new problems. As they find new ways to look at familiar things, the possibilities for insight multiply.

CHENNAI: Google DeepMind's AlphaGo, an artificial intelligence programme developed using deep neural networks and machine learning techniques, hit global headlines last year when it beat South Korean Go grandmaster Lee Sedol to win the series 4-1. However, not many know that AlphaGo has consumed a whopping 30,000 watts of power to complete the task, while the human brain consumes around 20 watts! What gives the human brain such efficiency has so far proven elusive to replicate in computers. Not surprisingly, man's most defining organ is also the least understood. Although an adult human brain weighing 1.4 kg is made up of close to 100 billion neurons, scientists do not know how many different kinds of human neurons exist.

The contentious presidential campaign was filled with accusations of elitism and bias by the media -- from the news to entertainment. Many supporters of Donald J. Trump saw his victory as a repudiation of the so-called liberal elite. So as 2017 begins, we ask: Is Hollywood representing all Americans? Are Hollywood values out of sync with American values? It's the start of a conversation we'll have all year with Hollywood's creators, consumers and observers. Most of all, we want to hear from you . Is Hollywood out of touch with your America? Here's what our critics and writers have to say: KENNETH TURAN on potent Hollywood visions that helped elect Trump TV's affluent bubble: MARY McNAMARA on Hollywood's reluctance to deal with class issues Fear of the powerful woman: JUSTIN CHANG on working women and men still behaving badly Realistic or cliche?: JEFFREY FLEISHMAN on film's working class men and women Building distrust: LORRAINE ALI on destructive TV portrayals of Muslims and how TV ...