Last week, the popular Rank Math SEO plugin received a major update that includes a new artificial intelligence system. The Content AI feature is a SaaS product that behaves like a personal writing assistant to boost search rankings. "We built Rank Math's Content AI feature to revolutionize the content production and optimization process with proprietary AI that gives SEOs and content marketers a competitive edge," said Bhanu Ahluwalia, Rank Math's CMO. The system allows users to research what their content should look like based on a keyword. This data is stored on the user's server, so the same keyword used on multiple posts does not cost extra.

CEO at Reface, an AI/ML startup shifting from the face-swapping app to the platform for creating personalized content. Last year, 64.2 zettabytes of data were created globally -- enough to fill about 1 trillion 64GB flash drives -- according to IDC. It might be hard to believe, but the total amount of digital data created over the next five years will double the amount of information developed since the birth of digital storage. The percentage of information generated synthetically may be negligible for now, but by 2030 (registration required), synthetic data is expected to completely overshadow real data in AI models. What role will synthetic media play, and what trends are exploding on the market of deep learning products?

Content production helps connect brands with customers, governments with citizens and organizations with their supporters. But, while important, content production can also be a labor- and time-intensive task. Producing articles, infographics, videos and a variety of other content requires a significant amount of work from writers and editors. With organizations producing and managing content daily, many have begun to turn to various technologies to help. One of the more capable of these technologies is AI.

As a mature 5G application scenario, video will embrace more promising prospects in the future. With 5G networks, high-quality video content such as UHD, 4K, 8K, and 120-frame videos will become popular for consumers, and VR, AR, interactive video, and AI-based video content will be their next hot videos. Paid video content will also change in intelligent distribution mode such as advertising, and the use of big data and AI can make video content target the right audience, which will improve video revenues. As 5G is widely adopted, there will be more video applications such as 4K/8K videos, VR immersive experience, AR, ultra-low latency live broadcast, high-speed mobile video communication, mobile communication in a crowded environment, as well as multimedia and IoV. In the 5G era, UHD video and ultra-high speed will greatly meet people's daily video viewing needs.

This module provides a brief introduction to the course and to the outline of topics we'll cover. This module provides a broad overview of how algorithmic approaches are being used throughout journalism including in areas like content production and computational story discovery. We'll talk about which tasks algorithms are good at, which tasks people are still better at, and about how to blend algorithms and people together in productive workflows. We'll also talk about what it means to develop computational thinking skills and how to apply them in news production. In Module two we'll get into a lot more detail on automated content production, including how it works and is used by news organizations, as well as covering its benefits and limitations so you know when it might be appropriate to deploy.

Content is a pivotal part of marketing, but original content production takes a long time. AI can help marketers during the content creation process. Technology can pick up on grammar and spelling mistakes, and some AI can even recommend a tone for directing messages at target audiences. Original media also comes from machine learning technologies. Generative adversarial networks (GANs) are known for creating realistic-looking fake images.

LAS VEGAS--"Get Ready for Machine Learning and Artificial Intelligence" is a new half-day program that will be part of The Next-Generation Media Technologies Conference at this year's NAB Show. Taking place Tuesday, April 10 from 9 a.m. to noon, the program will present six panels examining the impact of machine and artificial intelligence on production, post, filmmaking, and digital content creation. "We're looking forward to hosting some of the industries' leading creatives and technologists as they reveal how neural networks and other advancements are enabling production techniques previously thought impossible," said Chris Brown, NAB executive vice president, Conventions and Business Operations. The six sessions--taking place in North Meeting Room N257 at the Las Vegas Convention Center--will explore whether machine intelligence can increase productivity, efficiencies and creativity in production planning, animation, visual effects, post-production and localization. Panelists will also delve into the capabilities of today's neural network-based tools, and their potential to alter jobs, workflows and the nature of content itself.

We typically think of artificial intelligence (AI) within our industry in terms of processes and calculations. Media buying, for example, is ripe for intervention by sophisticated algorithms and machine learning systems. The commonly-held assumption is that developments such as these will free up humans to spend more time on creative tasks, like campaign strategy and content production. But as we move from rule-based automation to true AI, should we believe that creativity will remain a singularly human pursuit? How close is artificial intelligence to being able to carry out the role of a content marketer?

While there are plenty of dire-sounding discussions taking place these days around artificial intelligence (AI) and machine learning--and their potential to disrupt the world as we know it--this isn't technology of the future. New technologies are promising to upend the traditional ways in which content is conceived, produced, and disseminated. A Copyblogger article from as far back as 2015 noted that both Forbes and the Associated Press were producing machine-generated content. These examples are likely to both thrill and chill content marketers, depending on where they're perched along the content creation continuum--including the need to generate an increasing volume of content and to make a living from creating that content. For now, though, there is fortunately less to fear than there is to cheer, says Natalia Markova, senior web content strategist with Jellyfish, a global digital agency.

We typically think of artificial intelligence (AI) within our industry in terms of processes and calculations. Media buying, for example, is ripe for intervention by sophisticated algorithms and machine learning systems. The commonly-held assumption is that developments such as these will free up humans to spend more time on creative tasks, like campaign strategy and content production. But as we move from rule-based automation to true AI, should we believe that creativity will remain a singularly human pursuit? How close is artificial intelligence to being able to carry out the role of a content marketer?