Google’s Cloud Platform Updates Focus on Security Issues

During its Cloud Next 2019 developer conference, Google revealed its Advanced Protection Program would be widely released and Titan Security Keys will be more readily available in retail. The former, which is intended to prevent cyberattacks against high profile targets such as politicians and business leaders, will debut in beta for G Suite, Google Cloud Platform (GCP), and Cloud Identity customers. The Advanced Protection Program “enforces the use” of the Titan Security Key or compatible third-party hardware, blocking access to third-party accounts not approved by admin. Continue reading Google’s Cloud Platform Updates Focus on Security Issues

AWS Tool Aims to Simplify the Creation of AI-Powered Apps

Amazon introduced AWS Deep Learning Containers, a collection of Docker images preinstalled with preferred deep learning frameworks, with the aim of making it more seamless to get AI-enabled apps on Amazon Web Services. At AWS, general manager of deep learning Dr. Matt Wood noted that the company has “done all the hard work of building, compiling, and generating, configuring, optimizing all of these frameworks,” taking that burden off of app developers. The container images are all “preconfigured and validated by Amazon.” Continue reading AWS Tool Aims to Simplify the Creation of AI-Powered Apps

Google Establishes Advisory Panel to Examine AI Fairness

Google is forming the Advanced Technology External Advisory Council (ATEAC), an external eight-member advisory group to “consider some of the most complex challenges [in AI],” such as facial recognition and fairness. The move comes about a year after Google issued a charter stating its AI principles, and months after Google said it would not provide “general-purpose facial recognition APIs” before the ATEAC addresses relevant policy issues. The advisory group will hold four meetings in 2019, starting in April. Continue reading Google Establishes Advisory Panel to Examine AI Fairness

Amazon, National Science Foundation to Further AI Fairness

Amazon is teaming up with the National Science Foundation (NSF), pledging up to $10 million in research grants over the next three years to further fairness in artificial intelligence and machine learning. More specifically, the grants will target “explainability” as well as potential negative biases and effects, mitigation strategies for such effects, validation of fairness and inclusivity. The goal is to encourage “broadened acceptance” of AI, thus enabling the U.S. to make better progress on the technology’s evolution. Continue reading Amazon, National Science Foundation to Further AI Fairness

Google GPipe Library Speeds Deep Neural Network Training

Google has unveiled GPipe, an open-sourced library that makes training deep neural networks more efficient under the TensorFlow framework Lingvo for sequence modeling. According to Google AI software engineer Yanping Huang, “in GPipe … we demonstrate the use of pipeline parallelism to scale up DNN training,” noting that larger DNN models “lead to better task performance.” Huang and his colleagues published a paper on “Efficient Training of Giant Neural Networks Using Pipeline Parallelism.” Continue reading Google GPipe Library Speeds Deep Neural Network Training

Intel Describes Tool to Train AI Models With Encrypted Data

Intel revealed that it has made progress in an anonymized, encrypted method of model training. Industries such as healthcare that need a way to use AI tools on sensitive, personally identifiable information have been waiting for just such a capability. At the NeurIPS 2018 conference in Montreal, Intel showed off its open-sourced HE-Transformer that works as a backend to its nGraph neural network compiler, allowing AI models to work on encrypted data. HE-Transformer is also based on a Microsoft Research encryption library. Continue reading Intel Describes Tool to Train AI Models With Encrypted Data

Hive Builds Tailored AI Models via 700,000-Person Workforce

Hive, a startup founded by Kevin Guo and Dmitriy Karpman, trains domain-specific artificial intelligence models via its 100 employees and 700,000 workers who classify images and transcribe audio. The company uses the Hive Work smartphone app and website to recruit the people who label the data, and recently introduced three products: Hive Data, Hive Predict, and Hive Enterprise. Shortly after the product launch, Peter Thiel’s Founders Fund and other venture capital firms invested $30 million in the startup. Continue reading Hive Builds Tailored AI Models via 700,000-Person Workforce

20th Century Fox, Google Use AI to Analyze Movie Trailers

Researchers at 20th Century Fox published a paper to reveal how they are using artificial intelligence to analyze movie trailers. Published last month, the paper described Merlin, the code name for machine vision systems examining trailers frame by frame and labeling the objects and events. Then this data is compared to data from other trailers, with the idea that trailers with similar labels will attract similar kinds of people. Movie studios already cull similar data via interviews and questionnaires. Continue reading 20th Century Fox, Google Use AI to Analyze Movie Trailers

Intel AI Lab Reveals Plans to Open-Source More NLP Libraries

The Intel AI Lab, which open-sourced a library for natural language processing, plans to open-source more such libraries, to help developers and researchers speed up the process of giving virtual assistants and chatbots functions such as name entity recognition, intent extraction and semantic parsing. With new libraries, these developers can also publish research, train and deploy artificial intelligence and reproduce the latest innovations in the AI community. Intel’s first conference for AI developers was held May 23-24 in San Francisco. Continue reading Intel AI Lab Reveals Plans to Open-Source More NLP Libraries

Google’s Third-Gen Tensor Processor Unit Key to AI Ambitions

At Google’s I/O conference, chief executive Sundar Pichai reflected on the backlash against Silicon Valley companies while, at the same time, promoting the company’s advances and ambitions in artificial intelligence. Among those were specific positive solutions, such as an AI-powered software that helps diagnose eye disease, and a demonstration of what Google Assistant — in a variety of voices and accents — can do for ordinary consumers, and how Smart Compose in Gmail will suggest complete sentences to make the process speedier. Continue reading Google’s Third-Gen Tensor Processor Unit Key to AI Ambitions

NAB 2018: Machine Intelligence Toolsets in Video Workflows

Although using AI and machine learning tools in production may remain a lofty goal for some, such tools are already in use in some video workflows, from dailies through mastering. Moderated by Netflix coordinator, production technologies Kylee Peña, a panel discussion described the tools available and how they’re being used in real world applications. Google senior cloud solutions architect Adrian Graham described his company’s now-open sourced TensorFlow technology, and how it’s being used by the M&E industry. Continue reading NAB 2018: Machine Intelligence Toolsets in Video Workflows

Google, Government Partner on AI to Analyze Drone Footage

Google and the Department of Defense are exploring the use of artificial intelligence to identify objects in drone footage. The tech giant has been working with the Pentagon’s Project Maven, an initiative focused on big data and machine learning. According to sources, when the pilot project became an object of discussion at Google, some employees were angry that the company was working with the military on surveillance tech for drone operations. Google’s Eric Schmidt admitted that the tech community is concerned that the military-industrial complex will use Google’s research to kill innocent people. Continue reading Google, Government Partner on AI to Analyze Drone Footage

Amazon Debuts Intel-Powered DeepLens Camera to Teach AI

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

Google Hopeful for Chinese Re-Entry With TensorFlow for AI

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

Microsoft Intros Brainwave, Jumpstarting AI Hardware Speed

Microsoft has debuted Brainwave, a system that improves AI hardware performance, enabling machine learning at speeds beyond what’s available today with CPUs or GPUs. At the Hot Chips symposium in Cupertino, California, researchers showed off a Gated Recurrent Unit model running on Intel’s newly released Stratix 10 FPGA (field programmable gate array chip), at a speed of 39.5 teraflops without batching operations. Brainwave currently supports models constructed with Microsoft’s CNTK framework and Google’s TensorFlow framework. Continue reading Microsoft Intros Brainwave, Jumpstarting AI Hardware Speed

Page 1 of 212