The development of self-driving, or autonomous, vehicles is accelerating. Here's how they could affect consumers and companies. Autonomous vehicles (AVs) represent a major innovation for the automotive industry, but their potential impact with respect to timing, uptake, and penetration remains hazy. While high levels of uncertainty currently surround the issue, the ultimate role that AVs could play regarding the economy, mobility, and society as a whole could be profound. In an effort to look beyond today's rapidly changing predictions on AV penetration, we interviewed more than 30 experts across Europe, the United States, and Asia and combined these findings with our insights to arrive at ten thought-provoking potential implications of self-driving cars. The widespread use of AVs could profoundly affect a variety of industry sectors.

Don't miss new Futurology videos! Enchance your focus and concentration like you never thought possible: http://bit.ly/2iPoRWl Watch other videos: This Is How Quantum Computing Will Change The World: https://youtu.be/0Hlssbyc49o This Is How Artificial Intelligence Will Change The World: https://youtu.be/ngt9O_fojbc Ray Kurzweil: The Singularity Is Near: https://youtu.be/zA80t6ZSRzo

Late one Friday night in early November, Jun Rekimoto, a distinguished professor of human-computer interaction at the University of Tokyo, was online preparing for a lecture when he began to notice some peculiar posts rolling in on social media. Apparently Google Translate, the company's popular machine-translation service, had suddenly and almost immeasurably improved. Rekimoto visited Translate himself and began to experiment with it. He had to go to sleep, but Translate refused to relax its grip on his imagination. Rekimoto wrote up his initial findings in a blog post. First, he compared a few sentences from two published versions of "The Great Gatsby," Takashi Nozaki's 1957 translation and Haruki Murakami's more recent iteration, with what this new Google Translate was able to produce. Murakami's translation is written "in very polished Japanese," Rekimoto explained to me later via email, but the prose is distinctively "Murakami-style."

Poker Pro Dong Kim shown here in the first Brains vs. AI contest in 2015. Four of the world's best professional poker players will compete against artificial intelligence developed by Carnegie Mellon University in an epic rematch to determine whether a computer can beat humans playing one of the world's toughest poker games. Artificial Intelligence: Upping the Ante," beginning Jan. 11 at Rivers Casino, poker pros will play a collective 120,000 hands of Heads-Up No-Limit Texas Hold'em over 20 days against a CMU computer program called Libratus. The pros -- Jason Les, Dong Kim, Daniel McAulay and Jimmy Chou -- are vying for shares of a $200,000 prize purse. The ultimate goal for CMU computer scientists, as it was in the first Brains Vs. AI contest at Rivers Casino in 2015, is to set a new benchmark for artificial intelligence. "Since the earliest days of AI research, beating top human players has been a powerful measure of progress in the field," said Tuomas Sandholm, professor of computer science. "That was achieved with chess in 1997, with Jeopardy! in 2009 and with the board game Go just last year.

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.

Artificial intelligence chat bots are easy to write in Python with the AIML package. AIML stands for Artificial Intelligence Markup Language, but it is just simple XML. These code examples will walk you through how to create your own artificial intelligence chat bot using Python. AIML was developed by Richard Wallace. He made a bot called A.L.I.C.E.

Jack Clark and I are both lapsed technology journalists, and he writes one of my favorite new newsletters of this year, Import AI, which summarizes major research, hires and products in the space. He now works for OpenAI, alongside a team of researchers, where he handles policy, communications and partnerships. OpenAI is an AI research lab set up by former Stripe CTO Greg Brockman, Ilya Sutskever, Elon Musk, and Sam Altman. Its mission is to build safe AI, and ensure AI's benefits are as widely and evenly distributed as possible. Q: Before you joined OpenAI, you were a journalist -- like me. In fact, you called yourself the world's first and "only neural network reporter" while you were at Bloomberg. What made you decide to cross over? I think there are three things that are going to affect the world in incredibly significant ways over the next decade and they are 1) Climate change 2) CRISPR and 3) artificial intelligence.

No one today would deny that technology is a connector. When we think of technology, it usually doesn't call to mind words like "religion," "spirituality," and "morality." Miraculous as it can seem, technology is still thought of as cold steel, silicon wafers, and the engineering or code that makes it work -- soulless machinery to the core. But as technology extends into every aspect of our lives, it will force us to confront core issues previously left to the purview of religion. For some, that change will be challenging.

First of all, I would advise to think of this as a 400-page book with a WEKA appendix. Its price is about right for a 400-page machine learning textbook, and you don't even need to know that WEKA exists for the first 400 pages. I never read any of the WEKA stuff and got tons out of the textbook part. The average explanation amounts to "There's a technique called X, where you do this... it has a couple problems, but you could try fixing them in these ways." It's great for getting a lot of machine learning and data mining ideas in your head without having to get confused by learning the math behind them.

Think Stats: Exploratory Data Analysis in Python Think Stats: Exploratory Data Analysis in Python by Allen B. Downey, 2014