Describing itself as "the best and only way to chat with Werner Herzog over the Internet," WernerBot comes across as an artificial-intelligence version of a PSA about the importance of reading. Seemingly every question or statement you direct toward it will be responded to with variations on "The only thing you should be doing is reading," "READ" or "Why aren't you reading?" The only downside to this approach: We don't get to hear Herzog himself speak his responses in that soothing voice of his.

Employees of Google stand in front of the company's logo at Frankfurt book fair on October 8, 2006 in Frankfurt, Germany. Google is one of the leading companies who venture into artificial intelligence or AI. In fact, the company is very eager in their AI journey. According to new reports, Google is working on a useful AI. During the Google I/O panel last Friday, John Giannandrea, Google's head of machine learning shared the use cases, interest and research in artificial intelligence.

At the top of the corporate world, Apple and Google are in a back-and-forth battle to be No. 1. It is not clear which of the two Silicon Valley giants will emerge on top in a contest that highlights the contrast of very different business models. Apple then regained, lost and recovered the leader position in May in a battle that appears set to continue for some time. As of the end of Friday, Apple was worth some 522 billion, to 496 billion for Alphabet. The two companies have both been hugely profitable in recent years, for different reasons.

Artificial intelligence has become a larger part of our everyday lives in recent years. It's being used in medical devices, smart-home systems, and video games--to say nothing of robots and autonomous cars. And AI has even started to do what many people have feared: outsmart humans. In its June special report, The Institute dives into today's AI applications as well as its latest development: deep learning, in which machines teach themselves, then make decisions on their own. Here to answer questions about the future of AI are three experts in the field.

If you enjoy Google Play Music's recommendations based on what you listen to, you can thank researcher Douglas Eck. The former University of Montreal computer science professor used machine learning principles on that project, and is now experimenting with it to see if he can teach computers to make art and music on their own. Eck, along with a handful of Google Brain team members, is gearing up to launch Magenta on June 1. The project will involve the use of Google's open-source AI platform TensorFlow to create algorithms that can generate music. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May.

Our May meetup will be a robotics themed one with two speakers from KCL and Oxford. Inspired by the antagonistic human musculoskeletal system, the current trend in mechatronic design is to include physically compliant elements into the embodiment of robotic devices. The promise of such'soft robotic' systems, includes safety and agility. However, these offerings are tempered by the increased complexity of the system dynamics leading to difficulty in control. Learning (by demonstration or reinforcement) is often advocated as a means of dealing with this complexity, and can allow us to exploit the principles of human sensorimotor control to improve our robotic systems.

Most Machine Learning courses are given from the perspective of a researcher/academic and focus on the theory and mathematics of the machine learning models. This workshop takes the perspective of learning by working on real machine learning problems using open source tools and platforms. We'll go all the way from data preparation to the integration of predictive models in applications and their deployment in production. "Just like development where you don't need to know a thing about computability or big-O notation to write code and ship useful and reliable software, you can work machine learning problems end-to-end without a background in statistics, probability and linear algebra." The workshop is agnostic and features the best open source Python libraries (Pandas, scikit-learn, SKLL), APIs and ML-as-a-Service platforms (Microsoft Azure ML & Cortana Intelligence Suite, Amazon ML, BigML) for developers getting started in Machine Learning.

Last week, Google released Parsey McParseface, a funny name for a state-of-the-art tool aimed at one of the most difficult problems in artificial intelligence. For all that computers have accomplished in the past five years, from winning on "Jeopardy!" to defeating a Go grandmaster, they are still terrible at figuring out what people are saying. Language is one of the most complex tasks that humans perform. That's why there has been such a hullaballo over McParseface, which is pretty much a glorified sentence diagrammer. McParseface does what most students learn to do in elementary school.

Artificial intelligence has bested humanity in almost every intellectual pursuit going. They've trounced us at chess, murdered us on the TV show Jeopardy! But when it comes to poetry, computers are worse than that beret-wearing kid from high school who always rhymed "love" with "above". A poetic Turing test was recently held at Dartmouth College and the results were pretty messy. In an attempt to test the artist skills of robots, researchers from Dartmouth College pitted an artificial intelligence program designed to produce sonnets against human poets in a genteel "rap" face-off.

As we saw in our first blog post on AI Everywhere and Nowhere, defining'Artificial Intelligence' is like trying to hit a disappearing target. As soon as any aspect of AI gains widespread adoption, people fail to distinguish it as an AI technology, and it dissolves into the sea of general technology. As a result, most detractors of AI, at least until recently, have questioned the real-world applications of AI. In turn, AI never gains the respect and recognition it needs to evolve and reach its full potential. The beauty (and bane) of AI is that it is everywhere and yet nowhere – it is becoming ubiquitous in all of our interactions (at least all of our'virtual interactions'), yet most people fail to recognize and respect it.