Grant Imahara visits Cyberdyne, a robotics company located near Tokyo, to see HAL in action. No, not that HAL--it stands for Hybrid Assistive Limb and works with the brain and the body to augment mobility. The process, called cybernic treatment, can help people recover lost bodily functions. Dr. Yoshiyuki Sankai, CEO and President of Cyberdyne speaks with Grant about what makes the technology unique, how it works, and its real-world results. During his visit, Grant gets a demonstration of HAL.

Get my free AI Demo! Advances in technology and the resulting volume of data that PR and comms personnel have to work with has increased exponentially. Big data means people are spending more time managing information, rather than taking actions based on the insights it creates. In most industries, it isn't a question of if artificial intelligence should be implemented, but when. Competition in the information age is fast and fierce. If you're able to harness the potential of AI, you're going to grab that much needed edge. First, you need to know what artificial intelligence is. The term artificial intelligence was first used in 1956, as part of the Dartmouth Workshop. On a simple level, it describes a computer that reproduces human functions.

This article is the second part (click here for part one) in our series about the role of AI in customer support. The explores how digitization, digital self-service, and distributed digital advisors are disrupting a series of industries and creating a series of business opportunities to realize transformative value propositions, business models, services, and new revenue streams. The second-part delves further into the impact of AIOps and machine automation on a range of different careers and considers how we can prepare further for the occupational changes of the future. Many of the critical building blocks of computing -- microchip density, processing speed, storage capacity, energy efficiency, download speed, etc. -- have been improving at exponential rates over the last decade According to the authors of The Second Machine Age, Erik Brynjolfsson and Andrew McAfee: "We've also recently seen great progress in natural language processing, machine learning (the ability of a computer to automatically refine its methods and improve its results as it gets more data), computer vision, simultaneous localization and mapping, and many of the other fundamental challenges of the discipline." Administration tasks have evolved to largely self-service over the last few decades with technology removing the need for typing pools, copyists, and mailroom clerks.

Errol Morris feels that Thomas Kuhn saved him from a career he was not suited for--by having him thrown out of Princeton. In 1972, Kuhn was a professor of philosophy and the history of science at Princeton, and author of The Structure of Scientific Revolutions, which gave the world the term "paradigm shift." As Morris tells the story in his recent book, The Ashtray, Kuhn was antagonized by Morris' suggestions that Kuhn was a megalomaniac and The Structure of Scientific Revolutions was an assault on truth and progress. To say the least, Morris, then 24, was already the iconoclast who would go on to make some of the most original documentary films of our time. After launching the career he was suited for with The Gates of Heaven in 1978, a droll affair about pet cemeteries, Morris earned international acclaim with The Thin Blue Line, which led to the reversal of a murder conviction of a prisoner who had been on death row. In 2004, Morris won an Academy Award for The Fog of War, a dissection of former Secretary of Defense Robert McNamara, a major architect of the Vietnam War. His 2017 film, Wormwood, a miniseries on Netflix, centers on the mystery surrounding a scientist who in 1975 worked on a biological warfare program for the Army, and suspiciously fell to his death from a hotel room. The Ashtray--Morris explains the title in our interview below--is as arresting and idiosyncratic as Morris' films.

If you think it's been a problem up to this point, the fight against fake news is about to get a whole lot harder. That is thanks to artificial intelligence technology which is making the creation of so-called "deep fake" videos more convincing at a frankly terrifying rate. The latest development comes from an international team of researchers, lead by Germany's Max Planck Institute for Informatics. They have created a deep-learning A.I. system which is able to edit the facial expression of actors to accurately match dubbed voices. In addition, it can tweak gaze and head poses in videos, and even animate a person's eyes and eyebrows to match up with their mouths -- representing a step forward from previous work in this area.

Machine learning is one of those technologies that is invariably around us but one that we might not even comprehend. For instance, machine learning is employed to resolve issues like deciding if an email that we got is spam or a genuine one, how cars can drive on their own, and what product someone is likely to purchase. Every day, we tend to see these sorts of machine learning solutions in action. This definition brings up the key component of machine realizing, specifically that the framework figures out how to tackle the issue from illustration information, instead of us composing a particular rationale. This is a noteworthy advancement for how writing a computer program is finished.

When researchers working on developing a machine learning-based tool for detecting fake news realized there wasn't enough data to train their algorithms, they did the only rational thing: They crowd-sourced hundreds of bullshit news articles and fed them to the machine. The algorithm, which was developed by researchers from the University of Michigan and the University of Amsterdam, uses natural language processing (NLP) to search for specific patterns or linguistic cues that indicate a particular article is fake news. This is different from a fact checking algorithm that cross-references an article with other pieces to see if it contains inconsistent information – this machine learning solution could automate the detection process entirely. No offense to the Michigan/Amsterdam team but building an NLP algorithm to parse sentence structure and hone in on keywords isn't exactly the bleeding edge artificial intelligence work that drops jaws. Getting it to detect fake news better than people, however, is.

The camera is the eye for many automated devices and the computer is the brain -- but researchers at Stanford University recently combined the two in an attempt to make smart cameras more compact. A team of graduate students recently created an artificially intelligent camera that doesn't need a large, separate computer to process all the data -- because it's built into the optics itself. Current object recognition technology uses A.I. on a separate computer to run the images or footage through algorithms to identify objects. As the Stanford researchers explain, driverless cars have a large computer in the trunk in order to recognize when a pedestrian steps out in front of the car's path. Those computers are big, require lots of energy and are often slow.

Most of the artificial intelligence used for translation, tagging photos on Facebook, and optimizing the best route for navigation relies on humans feeding the AI some information to start. We show the algorithms which sentences are equivalent in other languages, what a person looks like in different photos, and how to plot the ideal course for a car. But some AI researchers are exploring how to give algorithms a sense of curiosity, so they can learn without any human guidance. New research from OpenAI, the non-profit AI lab founded by Elon Musk, Sam Altman, and other Silicon Valley bigwigs, in collaboration with researchers from UC Berkeley and the University of Edinburgh, has found that when an AI algorithm is given a simple definition of curiosity, it can, without any human-provided information, explore more than 50 video games--and even beat some of them. But curiosity comes with a cost.

Google Assistant wants to tell you some good news. A new skill aims to give users a reprieve from the oft-depressing daily news cycle by making it easier for them to find more uplifting headlines. Now, users can ask Google Assistant to'Tell me something good,' and it will trigger a'daily dose of good news,' according to the search giant. Google says the skill is launching as an'experimental feature' that's now available on any devices that are equipped with Assistant, such as phones, smart displays and the Google Home, the firm's voice-activated smart speaker. Assistant will serve up stories that are primarily focused around people who are doing things to help their communities and the world, Google explained.