Elon Musk has not been shy about his trepidations regarding the onset of artificial intelligence. The billionaire co-founder of PayPal pypl and CEO of Tesla tsla and SpaceX has often aired his misgivings about the technological advancement. He's even backed a non-profit research organization, Open AI, that aims to ensure the tech is developed ethically and safely. Now, in a video teaser shared exclusively with Fortune, Musk clarifies what he deems is the "biggest risk" that AI poses to humanity. The clip is a short segment from Lo and Behold, the latest film by German filmmaker Werner Herzog, due out this week. In it, Musk conjures a dystopian future usurped by profit-seeking AI warmongers.

Earlier this year, Adobe took the wraps off its new Adobe Marketing Cloud, touting new data science capabilities like Adobe Analytics' Segment IQ, which uses machine learning to help marketers gain deep insight into audience segments. On Wednesday, Adobe advanced Segment IQ another step with the release of Segment Comparison for Analysis Workspace. Segment Comparison for Analysis Workspace is the first in what Adobe promises will be a series of audience analysis and discovery tools within Segment IQ. It uses machine learning techniques to perform automated analysis on every metric and dimension to which you have access. Nate Smith, senior product marketing manager, Adobe Analytics, says this allows Segment Comparison to uncover the key characteristics of the audience segments that are driving your company's KPIs.

Humans are fairly sophisticated when it comes to understanding the complex meanings beneath the spoken or written word. For example, we can tell that a statement like, "My car had a flat. Brilliant!" is sarcastic, not actually brilliant. And with the help of machine learning, computers are beginning to get better at reading between the lines of our tweets, Facebook updates, and email messages, resulting in a new kind of analytics: sentiment analysis. Sentiment analysis, also known as opinion mining, seeks to determine the attitude of an individual or group regarding a particular topic or overall context – be it a judgment, evaluation, or emotional reaction – from text, video, or audio data.

In acoustic modelling Artificial Neural Networks can be used as an alternative approach to Hidden Markov Models for phoneme recognition. A pre-processed feature vector is fed into the input layer of a neural network. The goal is to correctly match different phones to phonems, which can then be further processed in the language model. The dynamic nature of speech is an impairing factor when using artificial neural networks for phonem recognition. Traditional neural networks require the phones to be perfectly aligned in time to allow for flawless allocation.

Why can't the insurance business be more like Netflix? In my opinion, the transformation of insurance services and products by digitalisation will be nothing short of mind-blowing. Nonetheless, there is a great deal that insurers can learn from the machine learning technology behind the success of some top 21st century digital service brands. These brands are businesses that thrive by constantly absorbing detail about their customers' likes, dislikes, tastes and even locations and travel patterns. This informs how TripAdvisor or Netflix tailor their suggestions for places to stay or eat or content that you might like to watch.

Nano-AI: Nanotech powered compute hardware could surpass the GPU and lead to big breakthroughs in Deep Learning, enabling stochastic processes even beyond bleeding edge work like that in the press today. Imagine nano-enabled hardware with capabilities beyond IBM's creation of the world's first artificial phase-change neurons or Intel's acquistion of Nervana, a hardware-accelerated deep-learning-as-a-service, an automated software-generating startup that Android creator Andy Rubin's Playground incubator said when it was acquired "will replace most of the explicitly designed software we use today."

Since Facebook announced a bot developer framework and distribution platform in April, the media has been hyperventilating over its impact. I know we're a big part of this, and I don't apologize. Bots, as a new (or revisited) paradigm for human-computer interaction, are here, and we're observing hundreds of companies, billions in funding, and thousands of bots flying in your browsers and messaging apps. You can download the full landscape here, and more rich data is coming soon. This article is part of the Bots Landscape.

Businesses face an ever increasing challenge to protect their assets from cyber criminals. The sophistication and frequency of attacks continue to elevate as these criminals take advantage of rapidly advancing technologies. Even using the latest machine driven security systems, it is becoming increasingly difficult for businesses to differentiate between a genuine employee or website visitor and a criminal seeking to breach or bring down their network and systems. Cyber security professionals are facing the prospect that they have reached a glass ceiling in terms of what humans can achieve. Does the future of cyber security defence now depend of robots?

Artificial intelligence can find, map poverty, researchers ... Ai Weiwei exhibit extended until Sept. 11 at Warhol

We all remember Watson from Jeopardy, right? It's not just Jeopardy that Watson is used for. Watson is famous for its cognitive computing system. Cognitive computing is another name for artificial intelligence. In other words, Watson learns.