Cable company Comcast will add'eye control' to its suite of accessibility features, allowing physically disabled viewers to operate TV's using only their gaze. By partnering with popular makers of eye-gaze hardware, Comcast said its feature will allow users to do just about anything that can be done with a physical remote, including using the guide, scheduling recordings, and navigating other menus. Popular systems like those made by Tobii Assistive Technology use special cameras to track the movement of people's eyes and then translate those movements onto a screen. Using eye-reading hardware and software, Comcast is allowing people with physical disabilities to control their TV's with their gaze Each time someone gazes at a button, the corresponding action is initiated in Comcast's interface. Comcast's inclusion of those technologies mark a first among large telecom providers and also further add to a host of other features rolled out by the company throughout the last several years.
New York: Continuing its mission to build trusted partnerships with advertisers and publishers, Verizon Media today announced an innovative new omnichannel insights tool for its industry-leading demand-side platform (DSP). Powered by machine learning, the new tool is designed to give advertisers clarity on their omnichannel programmatic ecosystem, with robust performance insights and optimization recommendations for each channel, ad format and exchange. According to a recent survey by Advertiser Perceptions, among advertisers, "transparency" is the most important word of 2019, with brands rightfully seeking more insights into campaign performance and media quality than ever before. Similarly, 60% of US advertising executives cite a lack of transparency as the biggest challenge for digital spend optimization. "At Verizon Media, trust and transparency are more than just buzzwords," said Iván Markman, Chief Business Officer at Verizon Media.
Cisco on Monday debuted a series of software enhancements designed to put AI and machine learning deeper into the network. Key features include new network automation and analytics tools that are meant to help enterprise IT teams glean more insights and visibility from network data. On the visibility side, new machine learning features collect relevant data from local networks and correlates it against aggregate deidentified data, creating individualized network baselines that constantly adapt as more devices, users and apps are added. Meanwhile, Cisco's ML is also correlating network data against baselines to uncover potential network issues and alert IT before problems occur. Cisco is also touting new machine-reasoning algorithms for improved troubleshooting, giving IT admins and network engineers the ability to detect and correct issues and vulnerabilities more quickly.
Cisco helps IT teams better understand network behavior and predict issues with new artificial intelligence and machine learning capabilities. Since its introduction two years ago, Cisco's intent-based networking has reinvented how networks are built and managed. Cisco is furthering this effort through multidomain integrations designed to provide end-to-end security, segmentation and application experience. Cisco is delivering these new software advancements via software subscriptions, granting customers access to ongoing innovation. SAN DIEGO, California – Cisco Live U.S. – Today, Cisco announces software innovations designed to make managing and securing networks easier.
Data scientists are constantly searching for newer techniques and methodologies that can unlock the value of big data and distill this data further to identify additional insights which could transform productivity and provide business differentiation. One such area is Artificial Intelligence/Machine Learning (AI/ML), which has seen tremendous development with bringing in new frameworks and new forms of compute (CPU, GPU and FPGA) to work on data to provide key insights. While data lakes have historically been data intensive workloads, these advancements in technologies have led to a new growing demand of compute intensive workloads to operate on the same data. While data scientists want to be able to use the latest and greatest advancements in AI/ML software and hardware technologies on their datasets, the IT team is also constantly looking at enabling these data scientists to be able to provide such a platform to a data lake. This has led to architecturally siloed implementations.
Artificial intelligence (AI) has been a huge growth enabler for many industries, due to its ability to streamline business processes, reduce operation costs and automate tedious tasks. The evolution of technologies such as cloud computing, big data, and internet of things (IoT) could enable further market growth in the AI sector, which my company predicts will be worth $190.61 billion by 2025. In its latest update, Tractica forecasted (paywall) that annual worldwide AI software revenue alone could reach $105.8 billion by 2025. As AI continues to grow and expand its reach -- something I've written about previously -- I believe that the marketing, security, health care, and automotive industries are poised to be the top four end-user industries to experience the most significant impact during the next five years. Today, companies are leveraging AI to enhance major marketing applications -- such as copywriting, dynamic pricing, virtual assistants, consumer behavior prediction and others.
Network providers agree that they need to develop effective mechanisms for collecting, structuring and analyzing the huge volumes of data that AI is capable of amassing. A key takeaway from the report is that the early adopters of AI who find solutions to the challenges of today and tomorrow will have a clear first-mover advantage. It is our belief that AI will open up exciting opportunities for the mobile communications sector, as it can be utilized to create a more personal approach for customers, while helping to manage the costs of deploying and maintaining networks.
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Network providers agree that they need to develop effective mechanisms for collecting, structuring and analyzing the huge volumes of data that Artificial Intelligence is capable of amassing. A key takeaway from the report is that the early adopters of Artificial Intelligence who find solutions to the challenges of today and tomorrow will have a clear first-mover advantage. It is our belief that Artificial Intelligence will open up exciting opportunities for the mobile communications sector, as it can be utilized to create a more personal approach for customers, while helping to manage the costs of deploying and maintaining networks.
Cisco announced today that it was open-sourcing the MindMeld conversation AI platform, making it available to anyone who wants to use it under the Apache 2.0 license. MindMeld is the conversational AI company that Cisco bought in 2017. The company put the technology to use in Cisco Spark Assistant later that year to help bring voice commands to meeting hardware, which was just beginning to emerge at the time. Today, there is a concerted effort to bring voice to enterprise use cases, and Cisco is offering the means for developers to do that with the MindMeld tool set. "Today, Cisco is taking a big step towards empowering developers with more comprehensive and practical tools for building conversational applications by open-sourcing the MindMeld Conversational AI Platform," Cisco's head of machine learning Karthik Raghunathan wrote in a blog post.