Amazon has launched a 2.5 million competition for teams of students to create an artificial intelligence charming enough that people can chat to it about celebrity gossip and sports. The'Alexa Prize' is named after the service that powers Amazon's voice-activated smart speaker, the Amazon Echo. The goal of the inaugural competition is to build a'socialbot' for Alexa that will converse with people about popular topics and news events. The team with the highest-performing socialbot will win a 500,000 prize, while there's a 1 million for the team's university if their socialbot can chat "coherently and engagingly" with humans for 20 minutes. Up to ten teams of students will also win a 100,000 award, Alexa-powered devices, free AWS services, and support from the Alexa team.

HiringSolved, a technology company that leverages artificial intelligence and machine learning to solve problems for talent acquisition practitioners, has introduced RAI, an artificial intelligence assistant for recruiters. RAI is built upon HiringSolved's TalentFeed search engine, which uses a layered approach to search relevance, combining multiple scoring algorithms to find the best results. Similarly, RAI's flexible Knowledge Engine provides recruiters with detailed insights about companies, skills, title concentrations and specific people that can be sorted based on location, gender and more. Specifically regarding diversity, RAI is able to predict candidates' genders through HiringSolved's Diversity Search tool, which uses proprietary data that HiringSolved has access to, as opposed to relying on published statistics as most companies do. For instance, if a recruiter wants to know Google's male-female ratio, the engine analyzes every employee working for Google, predicting their gender with an error rate of 3%, and computing the ratio.

Artificial intelligence is quickly shaping up to be one of the key defining technology areas of our time. A day after announcing a new artificial intelligence partnership with IBM, Google, Facebook and Amazon, Microsoft is upping the ante within its own walls. The tech giant announced that it is creating a new AI business unit, the Microsoft AI and Research Group, which will be led by Microsoft Research EVP Harry Shum. Shum will oversee 5,000 computer scientists, engineers and others who will all be "focused on the company's AI product efforts," the company said in an announcement. The unit will be working on all aspects of AI and how it will be applied at the company, covering agents, apps, services and infrastructure.

Cortana has a new boss, and he has a problem: If Google's turning its Google Now digital assistant into a chatbot, should Microsoft do the same with Cortana? In 2014, Microsoft first unveiled Cortana, the digital assistant within Windows 10. Interacting with Cortana was simple: You asked a question, she responded. In the last few months, however, Google's Assistant has offered an alternative: a chatbot that interacts with users via an ongoing stream of text and images. In an interview with PCWorld, Shum said he hasn't ruled out adding a Cortana chatbot to its roster of digital assistants.

The "Ok Google" command has expanded since the debut of Android KitKat, allowing devices to respond in various smart ways to those two words. Now, Google Maps on Android has this ability too, whether you're in the middle of a road trip or doing something else. Once it's enabled in settings, you can choose whether it works only while Maps is open or from any screen. Say the magic phrase then follow it up with something like "find a gas station" or "How's traffic ahead?" and it will let you know. Existing Google Maps voice commands like "What's my ETA?" work too, plus new addition like the ability to turn traffic display on or off.

If you add them all up, Google actually makes a lot of gadgets. It sells Nexus phones, Chromebook Pixels, Pixel C tablets, Nest smart-home products, cardboard VR viewers, Chromecast and Chromecast Audio, pretty Wi-Fi routers, even weird custom phone cases. But you'd never think of Google as a hardware company, because there's no rhyme or reason to any of it. Some things are made for developers, others to show off how great a form factor or operating system could be. Some become really expensive doorstops. I'm sure I'm forgetting stuff, too--Google's made so many small-time moves in the gadget market that it's hard to track them all.

Deep Learning/Machine Learning (General): Companies that build computer algorithms that operate based on their learnings from existing data. Examples include predictive data models and software platforms that analyze behavioral data. Deep Learning/Machine Learning (Applications): Companies that utilize computer algorithms that operate based on existing data in vertically specific use cases. Examples include using machine learning technology to detect banking fraud or to identify the top retail leads. Natural Language Processing (General): Companies that build algorithms that process human language input and convert it into understandable representations.

Tech companies are investing heavily in artificial intelligence, and touting the financial benefits of AI-powered technologies like robots, virtual assistants and augmented reality, Now, a new study reports that artificial intelligence could dramatically boost economic growth and productivity. The Accenture report looked at 12 countries and found that AI -- or technology that senses the environment, comprehends what's happening and takes action -- could increase productivity by up to 40 percent in 2035. The report also forecasts economic growth in the U.S. could increase from 2.6 percent to 4.6 percent over the same period with the adoption of AI technologies. Among the countries that stand to make the largest gains in productivity from AI in 2035 are Sweden, Finland, the U.S. and Japan. "The impact this has is that it automates a lot of the low-level tasks and gets them done with higher satisfaction," says Accenture's chief technology officer, Paul Daugherty.

Tech companies are investing heavily in artificial intelligence, and touting the financial benefits of AI-powered technologies like robots, virtual assistants and augmented reality, Now, a new study reports that artificial intelligence could dramatically boost economic growth and productivity. The Accenture report looked at 12 countries and found that AI -- or technology that senses the environment, comprehends what's happening and takes action -- could increase productivity by up to 40 percent in 2035. The report also forecasts economic growth in the U.S. could increase from 2.6 percent to 4.6 percent over the same period with the adoption of AI technologies. Among the countries that stand to make the largest gains in productivity from AI in 2035 are Sweden, Finland, the U.S. and Japan. "The impact this has is that it automates a lot of the low-level tasks and gets them done with higher satisfaction," says Accenture's chief technology officer, Paul Daugherty.

In the series of implementing Recommendation engines, in my previous blog about recommendation system in R, I have explained about implementing user based collaborative filtering approach using R. In this post, I will be explaining about basic implementation of Item based collaborative filtering recommender systems in r. Intuition: Item based Collaborative Filtering: Unlike in user based collaborative filtering discussed previously, in item-based collaborative filtering, we consider set of items rated by the user and computes item similarities with the targeted item. Once similar items are found, and then rating for the new item is predicted by taking weighted average of the user's rating on these similar items. Let us build an algorithm to recommend movies to CHAN.