If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Look, nobody knows what analytics actually is anyway, so why are we still talking about it? At its most basic, analytics is simply a tool. As the old saying goes, when all you have is a hammer, everything looks like a nail. Yes, analytics is simply a way to draw meaning out of data, but just because you finally figured out how to apply gradient boosting to your ridge regression model doesn't mean you should. Once you think of analytics as a tool, a means to an end, then it's much easier to see that it's not just a tool, but an entire toolbox.
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The ability of reasoning beyond data fitting is substantial to deep learning systems in order to make a leap forward towards artificial general intelligence. A lot of efforts have been made to model neural-based reasoning as an iterative decision-making process based on recurrent networks and reinforcement learning. Instead, inspired by the consciousness prior proposed by Yoshua Bengio, we explore reasoning with the notion of attentive awareness from a cognitive perspective, and formulate it in the form of attentive message passing on graphs, called neural consciousness flow (NeuCFlow). Aiming to bridge the gap between deep learning systems and reasoning, we propose an attentive computation framework with a three-layer architecture, which consists of an unconsciousness flow layer, a consciousness flow layer, and an attention flow layer. We implement the NeuCFlow model with graph neural networks (GNNs) and conditional transition matrices. Our attentive computation greatly reduces the complexity of vanilla GNN-based methods, capable of running on large-scale graphs. We validate our model for knowledge graph reasoning by solving a series of knowledge base completion (KBC) tasks. The experimental results show NeuCFlow significantly outperforms previous state-of-the-art KBC methods, including the embedding-based and the path-based. The reproducible code can be found by the link below.
A new startup has created an artificial intelligence system capable of mimicking voices that are unprecedentedly close to the real thing. In a video from Dessa, an AI company staffed by former employees of Google, IBM, and Microsoft, multiple audio clips demonstrate a machine-learning software that parrots the voice of popular podcaster, Joe Rogan to a degree that's almost indiscernible from the real thing. In the clips, the computer-generated Rogan muses on topics like chimpanzee's who can play hockey; it pulls off some adept tongue-twisters; and it even pontificates theories about how we're all living in a simulation, which as noted by The Verge, are some of Rogan's favorite topics. Joe Rogan is one of the most popular podcasters in the world, giving AI plenty of data to choose from when trying to mimic the host's voice In a response, even Rogan himself called the demonstration'terrifyingly accurate' reports CNET. What makes the demonstration more intriguing, or perhaps scary, according to Dessa is that software like the one demonstrated channeling Rogan could soon be commonplace.
Say hello to Joe Rogan: podcaster, entertainer of problematic views, and man who believes that feeding his all chimp hockey team a diet of bone broth and elk meat will give them the power to rip your balls off. Or, at least that's what the unaware listener might believe after listening to an entirely AI-generated clip of the popular podcaster. Unlike Rogan's typical totally coherent rants, this one is a total fabrication. "The replica of Rogan's voice the team created was produced using a text-to-speech deep learning system they developed called RealTalk," explained the researchers behind the clip in a blog post, "which generates life-like speech using only text inputs." This obviously calls to mind deepfakes, the video editing tech that can convincingly edit videos to make it look like people did or said things they in fact did not.
But they'll have nothing on Rikard Grönborg, the head coach of Sweden's national hockey team who will log over 400 consecutive hours during the Ice Hockey World Championships in Slovakia … sort of. Using advanced 3D and voice technology, agency Perfect Fools created a virtual Grönborg to report live on YouTube 24 hours a day through the duration of the tournament. The coach spent hours in front of the camera so the virtual anchor could learn his voice and mannerisms. Additionally, 20 years of hockey data was analyzed so the fake Grönborg could make predictions for all of the tournament's games. The end product does look and sound a little robotic but in all fairness, it's an ambitious project, and the technology is still somewhat nascent.
ESPN is making some welcome (and arguably overdue) improvements to its ESPN service that could change how and where you watch. Its updated app now includes personalized recommendations for ESPN, starting with on-demand videos. You'll probably see more highlight clips from the latest NHL matches. Recommendations will "soon" spread to live and future events, so you might spot big matches you would otherwise miss. The company is also borrowing a page from Netflix and other services by introducing offline viewing.
If you're not into fashion, you may not recognize that name, but Karl Lagerfeld is to fashion as Wayne Gretzky is to hockey as Mick Jagger is to rock and roll as Steve Jobs is to consumer tech. He is, according to industry insiders, nothing less than a fashion god. Born in Hamburg, Germany in 1938, he designed his first line of clothing at the tender age of 17. His meteoric rise is legendary among creative directors and today at 83, he still has tremendous influence in the fashion world as creative director at Chanel and Fendi. Lagerfeld proved over decades that he had the creative vision to know what consumers would want next before they even knew themselves. He once said, "I am not a marketing person. I don't ask myself questions.
It's 2018 and the world doesn't quite look like a scene from "The Jetsons." However, technological innovation spurred by advancements in computing has allowed for artificial intelligence to bring significant changes to the way businesses operate, impacting our everyday lives. Recently acquired by L'Oreal, retail AI company ModiFace created a real-time app that takes the guesswork out of finding the perfect hair color or makeup product for consumers. Large beauty brands were able to help their customers virtually test products to select the right color or shade before buying online or in store. Sports analytics company ICEBERG uses AI to capture, visualize, and analyze game data, giving hockey coaches and their players faster insights to improve performance and plays.
Amazon is introducing new productivity tools for Alexa, including a new way for third party developers to manage reminders for customers. The new Reminders API is open to developers in all locales supported by Alexa, expanding the kinds of notifications Alexa users can get from the voice-activated assistant. With the API, customers can set reminders for information they'll want later, such as what time a store is closing, when a flight is scheduled to land or when their restaurant reservation is. When a customer is enabling a skill, they'll need to give permission for reminders; then, they need to give permission for each specific reminder they'd like to set. With the move, Amazon is seeding the developer community with features to launch more enterprise connections.