For many years, effective voice-based search technologies have eluded businesses that have tried to bring next-generation input methods to customers. Confined to basic navigation and so-called'magic words', command-based speech systems have been ineffective and hard for consumers to use. The widespread adoption of smartphones and tablets, and their minimised keyboards, has led to a renewed interest in this genre of technology however, with Apple's Siri, Amazon's Alexa and Google Now's'OK Google' progressing beyond basic menu navigation functions and striking a chord with consumers and businesses alike. In fact, any device with a microphone has potential for speech based commands, and can become an intelligent discovery system that uses a sophisticated entertainment brain to understand customer desires. This technology is important and under-explored by the TV industry, which often appears to have been left behind in terms of intuitive discovery functionality.

A reporter asked us for annoying buzzwords in the tech sector. Nathan and I had a fun email exchange on this, and naturally, ours are focused on artificial intelligence.

In 2012, Dennis Mortensen had 1,019 meetings, each of which required an average of roughly eight back-and-forth emails to schedule. Every time Mortensen comes across a contact interested in meeting with him, the CEO and founder of New York City-based artificial intelligence firm x.ai simply sends them a return email copying Amy, who takes care of the rest. "In raw numbers, I've saved about an hour every day -- an hour which I would otherwise have to use in really rudimentary work where I add not much value," Mortensen said of Amy's help scheduling meetings. Virtual assistants like Amy are becoming more common. Just as household technology platforms like Apple's "Siri" and Microsoft's "Cortana" has helped consumers navigate their lives more easily, other forms of rudimentary artificial intelligence platforms are starting to proliferate the market, many of them upending traditional business roles.

The technical potential for automation differs dramatically across sectors and activities. As automation technologies such as machine learning and robotics play an increasingly great role in everyday life, their potential effect on the workplace has, unsurprisingly, become a major focus of research and public concern. The discussion tends toward a Manichean guessing game: which jobs will or won't be replaced by machines? In fact, as our research has begun to show, the story is more nuanced. While automation will eliminate very few occupations entirely in the next decade, it will affect portions of almost all jobs to a greater or lesser degree, depending on the type of work they entail. Automation, now going beyond routine manufacturing activities, has the potential, as least with regard to its technical feasibility, to transform sectors such as healthcare and finance, which involve a substantial share of knowledge work. These conclusions rest on our detailed analysis of 2,000-plus work activities for more than 800 occupations.

Learn how to build a personal chatbot for Facebook Messenger. I have created this step by step guide so you can create your own Facebook Messenger bot without coding. Facebook Messenger has a growing audience of 900 mln. It is an awesome opportunity to showcase your work and promote your services, automate conversations and build out your personal brand. By the end of the course you will be launch and promote your personal bot.

That's what Microsoft's Project Malmo, formerly known as Project AIX, is doing right now. Publicly unveiled today on the official Mojang blog, Project Malmo has just made its open source tools available to everyone today in an effort to help others help strengthen AI in various ways. Mojang notes that Minecraft is the perfect way to educate AI when it comes to offering solutions to problems, sharpening spatial and temporal reasoning, and even collaboration. Project Malmo can offer diverse opportunities at teaching artificial intelligence software and act as a research tool that can test these theories as well. If you're interested in seeing what Project Malmo has to offer in addition to testing it out for yourself, you can download the mod for the PC/Mac edition of Minecraft here.

The code here implements the Dual LSTM Encoder model from The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems. This code uses Python 3 and Tensorflow 0.9. Download the train/dev/test data here and extract the acrhive into ./data.

In this post we'll implement a retrieval-based bot. Retrieval-based models have a repository of pre-defined responses they can use, which is unlike generative models that can generate responses they've never seen before. A bit more formally, the input to a retrieval-based model is a context (the conversation up to this point) and a potential response . The model outputs is a score for the response. To find a good response you would calculate the score for multiple responses and choose the one with the highest score. But why would you want to build a retrieval-based model if you can build a generative model? Generative models seem more flexible because they don't need this repository of predefined responses, right?

So you want to learn more about robots and artificial intelligence programming? The Deep Learning Robot kit has you covered. It comes with a Kobuki mobile base, Asus Xtion Pro 3D depth camera, speaker / microphone, and Ubuntu, Caffe, Torch, Theano, cuDNN v2, and CUDA 7.0 pre-installed. Deep Learning Robot is built on the 192-Core Nvidia Tegra K1. With Asus Xtion Pro, you can build a robot that can drive around your home and see in 3D. The microphone and speaker come handy for speech recognition and natural language research.

Microsoft has published the source code for its Project Malmo, allowing anyone to conduct artificial intelligence experiments in the world of Minecraft with a little programming. It unveiled the project, then known as AIX, back in March, but at the time only a few academics had access to the code. On Thursday the company made good on its promise to open up the source code by publishing it on Github. Minecraft, the blocky world-building game that Microsoft paid US 2.5 billion for two years ago, is an ideal place to test how artificial intelligences will interact with one another and with humans. As it's a simulation, Minecraft is a safe place to test how AIs learn to perform certain kinds of physical tasks: In Minecraft, a rogue machine or runaway car can hurt no one.