Today, deep learning is just a cool technology, but it could mean that you won't qualify for tomorrow's best-paying jobs, even if you work in IT. Artificial intelligence (AI) is already shaking things up at Google, Facebook and IBM, and it is going to affect how work is performed in all sectors. There's already been plenty of discussion about AI supplanting so-called blue-collar work, such as trucking and railroad track inspection, but it won't stop at those seemingly easier targets. For a number of reasons, white-collar jobs could be an even more inviting target for machine learning and related technologies. Many experts have highlighted the professional impact of AI and other automation technologies, but none more presciently than Richard and Daniel Susskind in their recent book "The Future of the Professions."

Reinforcement learning (RL) is is the very basic and most intuitive form of trial and error learning, it is the way by which most of the living organisms with some form of thinking capabilities learn. Often referred to as learning by exploration, it is the way by which a new born human baby learns to take its first steps, that is by taking random actions initially and then slowly figuring out the actions which lead to the forward walking motion. Note, this post assumes a good understanding of the Reinforcement learning framework, please make yourself familiar with RL through week 5 and 6 of this awesome online course AI_Berkeley. Now the question that I kept asking myself is, what is the driving force for this kind of learning, what forces the agent to learn a particular behavior in the way it is doing it. Upon learning more about RL I came across the idea of rewards, basically the agent tries to choose its actions in such a way that the rewards that is gets from that particular behavior are maximized.

Investors are on the hunt for AI startups, and 2016 is on track for record number of deals and dollar funding to private AI companies. "It is clear that 9 of 10 investors have very little idea what A.I. is so if you're a founder raising money, you should sprinkle some A.I. into your pitch deck," we noted in a recent newsletter. Use of'artificial intelligence,' 'A.I.,' 'chatbot,' or'bot' are winners now and might get you a little valuation bump or get the process to move quicker." The buzz is definitely there in the media. When we look at chatter about AI using our CBI Trends tool, which analyzes millions of media articles to track tech trends, we see that hype surrounding the space continues to grow.

Most presidential campaigns spend their time and money appealing to people who vote regularly in elections. According to a Trump campaign memo obtained by FiveThirtyEight, the campaign pursued a highly unorthodox strategy of courting unlikely voters during the primaries, focusing on people who rarely participate in GOP primary elections. The campaign relied on free media, including Trump's frequent TV appearances, to turn out regular voters, according to the memo. But survey and voter data shows that Trump won the Republican nomination thanks in large part to Republicans who typically vote in general elections, not by bringing people entirely disconnected from the electoral process to the polls. As Trump heads into the general election, the campaign's thinking during the primaries, and the ad-hoc process by which it built an operation to target and reach out to voters using data, may offer clues about how it will approach voter turnout in the fall.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

A Stanford undergrad's AI-based chatbot has already helped us with our parking tickets and various legal issues, but now his DoNotPay bot is taking on an even bigger, trickier issue. After receiving acclaim for the bot, which challenged over 160,000 tickets, Joshua Browder taught the program how to help homeless people in the UK claim their right to public housing. The user simply asks for help, and the bot will ask them a series of questions to determine how best to help them. Usually this will involve crafting a claim letter, which the bot fills in with the information that's been provided. In the end, people can save hundreds of dollars in legal advising fees when they need that money the most.

Suppose we'd like to visualize a set of joint probabilities realizable by distributions of 3 binary variables. It is a 7 dimensional regular simplex, and we could draw a lower dimensional section of it. As an example, suppose we want to find a good 2 dimensional section of a 3 dimensional regular simplex. It seems reasonable to restrict attention to sections that go through simplex center and two other points, each of which is a vertex or a center of some edge or face. There are just 2 such sections determined up to rotation/reflection For 7 dimensional simplex, we could similarly take 3 dimensional sections determined by simplex center and 3 points, each a centroid of some set of vertices.

The bot ecosystem is changing, and so are the use-cases. Fueled by the development work of Apple, Facebook, Google, Microsoft, and others, bots are becoming more intelligent and therefore capable of performing tasks previously done by humans. Not to be confused with robots, a bot is a software program designed to imitate the behavior of humans. Most bots are designed to do a specific task, whether that's crawling the web to index sites, making robocalls, serving up a weather report, or responding to a simple customer query. However, orchestration layers are required to enable seamless, transparent, rich services.

GeckoSystems' BaseBot demonstrating several times real time sense and avoid of unmapped, moving obstacles with a person unexpectedly getting in front of the mobile robot.

Apple Inc. acquired artificial intelligence startup Turi Inc. for about 200 million, according to people familiar with the situation, in the latest deal by the iPhone maker to accumulate advanced computing capabilities for its products and services. Turi helps developers create and manage software and services that use a form of AI called machine learning. It also has systems that let companies to build recommendation engines, detect fraud, analyze customer usage patterns and better target potential users, according to the Seattle-based startup's website. Apple could use this to more rapidly integrate the technology with future products. Apple's move Friday is part of a broader battle among Google, Facebook Inc. and Amazon.com