Google is pulling YouTube from Amazon’s smart speaker Echo Show, saying it is doing so because Amazon won’t sell Google products including its Home speaker, Chromecast streaming device and some Alphabet Nest products. Google also states that Amazon won’t make its Prime Video shows available for Chromecast. The move escalates an ongoing battle between the two behemoths whose business interests now overlap. In addition to Echo Show, Google plans to block YouTube on Amazon Fire TV’s media streaming device beginning January 1. Continue reading Google Removes YouTube From Amazon Fire TV, Echo Show

In May, research project Google Brain debuted its AutoML artificial intelligence system that can generate its own AIs. Now, Google has unveiled an AutoML project to automate the design of machine learning models using so-called reinforcement learning. In this system, AutoML is a controller neural network that develops a “child” AI network for a specific task. The near-term goal is that AutoML would be able to create a child that outperforms human versions. Down the line, AutoML could improve vision for autonomous vehicles and AI robots. Continue reading Google Intends to Advance Machine Learning With its AutoML

On November 29 at the AWS re:Invent conference, Amazon Web Services introduced its AWS DeepLens, a video camera whose main purpose is to teach developers how to program AI functions. The camera comes loaded with different AI infrastructures and AWS infrastructure such as AWS Greengrass Core and a version of MXNet. Developers can also add their own frameworks like TensorFlow. The 4-megapixel camera can shoot 1080p HD video and offers a 2D microphone system for recording sound, in the form factor of an action camera on top of an external hard drive. Continue reading Amazon Debuts Intel-Powered DeepLens Camera to Teach AI

Mozilla unveiled Project DeepSpeech and Project Common Voice to leverage the capabilities of speech recognition. The company says it has just reached “two important milestones” in the project out of its Machine Learning Group. Mozilla is releasing its open source speech recognition model, which it states is nearly as accurate as what humans can perceive from the same recordings, and is also unveiling the world’s second largest publicly available voice dataset, with contributions by almost 20,000 people around the world. Continue reading Mozilla Intros Open-Source Speech Recognition, Voice Dataset

To compete in the profitable cloud-computing arena, Amazon Web Services debuted 20 new machine-learning tools this week at the AWS re:Invent conference in Las Vegas. Tools include speech recognition and algorithms to automate decisions. The move helps Amazon compete better with Google and Microsoft, both of which are using their expertise in AI and machine learning to cut into its market share. Machine learning will also help potential developers that can’t create these capabilities on their own. Analysts estimate that Amazon dominates the cloud with a 44 percent market share. Continue reading AWS Expands Cloud Efforts with New Machine-Learning Tools

Snap Inc. just unveiled a remake of Snapchat that, thus far, has been identifiable for its posts that disappear after 24 hours, smaller social circles and human editing and curation. In its new incarnation, Snapchat separates the social and media into two parts. On the left side of the app, users will see chats and stories shared with friends. On the right side, they’ll find content from DIY creators, publishers, celebrities and Snap-curated content. Part of the reason for the redo is Snap’s disappointing user and revenue numbers. Continue reading Snapchat Redesign Aims to Curb Fake News, Boost Revenue

Two things you may be tired of hearing about by now: AI and blockchain. However, we would be remiss if we didn’t mention a unique and ambitious project marrying the two to challenge the power of the giants of the AI Age. SingularityNET is a blockchain-powered “Internet of AI” where AI and machine learning applications can be created, combined, and “rented” to solve problems as part of a decentralized marketplace powered by blockchain. This blog post from one of the founders of SingularityNET digs deeper, but it’s a BYOGS (“bring your own grain of salt”) kind of party. Continue reading SingularityNET: Where Artificial Intelligence Meets Blockchain

Amazon Web Services announced a new service called Amazon Sumerian during the kick-off event for its AWS re:Invent conference in Las Vegas. The service was created for developers to quickly and easily build virtual reality, augmented reality and 3D applications with minimal coding for a range of platforms including browsers, head-mounted displays, mobile devices and digital signs. Initially, Sumerian-built apps will run on any browser that supports WebGL or WebVR rendering, which includes Google’s Daydream, HTC Vive, Oculus Rift and iOS devices. Continue reading AWS Debuts Amazon Sumerian to Build VR, AR and 3D Apps

AISense, a company that offers a voice transcription service, is partnering with videoconferencing service Zoom to bring a product to market in 2018 that will provide automatic transcriptions for Zoom’s customers. AISense’s technology uses machine learning to provide a full text record of what is said, and Zoom’s videoconferencing is its first practical use. AISense also just raised $10 million in Series A funding led by Horizons Ventures, with Draper Associates, Draper Dragon, David Cheriton, and Bridgewater Associates. Continue reading AISense Teams Up with Zoom for Voice Transcription Product

Former Instagram employees Chris Cunningham and Alex Karpenko have been working on Rylo, a new $500 software-based camera for the last two years. Rylo is a dual-lens 360-degree camera that solves three problems specific to video capture: the video needs to be stable, level and looking at the right thing. Rylo’s two lenses each capture a 195-degree field of view, which the camera stitches together into a single sphere. The imagery in that single sphere can be post-produced in one of three ways. Continue reading Rylo 360-Degree Camera Touts Computational Photography

Google Senior Fellow Jeff Dean, who works on the Google Brain team, recently highlighted AutoML (for machine learning), a project aimed at using AI-empowered machines to build other AI machines, removing humans from the equation. The need for AI algorithms grows as its capabilities are becoming important to a wide range of industries. But only an estimated 10,000 people worldwide have the education, expertise and ability to construct those algorithms, and Facebook, Google and Microsoft pay millions of dollars for them. Continue reading Google Project Aims to Use AI to Develop More AI Algorithms

In 2012, University of Toronto professor Geoffrey Hinton and two grad students showed off artificial neural networks, a technology that empowered machines to understand images. Google hired Hinton and his grad students six months later; Hinton now splits his time between Google and the university. Although neural networks now underlie speech transcription and many other tasks, Hinton isn’t enthused over the technology he helped launch. Instead, he’s now bullish on an “old” idea that could help reshape artificial intelligence. Continue reading Google’s Geoff Hinton Tests Capsule Networks as AI Solution

Google exited China in 2010, but is now making another pitch to re-enter by promoting its TensorFlow software for building artificial intelligence solutions. Sources say that parent company Alphabet has added staff to look for potential AI investments among Chinese companies. The online Chinese market is the biggest in the world, but Google faces challenges there, not just with homegrown rivals such as Baidu, but the fact that China’s firewall keeps domestic developers from accessing Google’s cloud computing services. Continue reading Google Hopeful for Chinese Re-Entry With TensorFlow for AI

Waiting for a video to buffer may become an annoyance of the past. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are working on streaming algorithms that use AI to improve load rates and, thus, reduce buffering. Dubbed Pensieve, the new technology relies on machine learning to navigate the often-chaotic and ever-changing conditions of networks in real-time, based on a system of rewards (when the video loads smoothly) and penalties (when it’s interrupted). Meanwhile, Netflix is working on its own AI solution to address buffering. Continue reading MIT and Netflix Testing AI-Based Algorithms to Curb Buffering

SMPTE kicked off its 2017 Annual Technical Conference & Exhibition on Monday with an all-day symposium on artificial intelligence and its emerging role in entertainment production and distribution. Among the day’s presentations, SMPTE’s Richard Welsh presented a compelling primer on AI, Google’s Jeff Kember discussed the differences between supervised and unsupervised systems, Hitachi Vantara’s Jay Yogeshwar addressed using machine learning and AI for production workflow, Yvonne Thomas of Arvato Systems looked at the value of effective data analytics, Greg Taieb of Deluxe addressed language localization for multilingual distribution, and Aspera co-founder Michelle Munson examined next generation network design. Continue reading SMPTE: Industry Leaders Gather to Discuss the Future of AI