We are pleased to introduce the ability to export high-resolution keyframes from Azure Media Service's Video Indexer. Whereas keyframes were previously exported in reduced resolution compared to the source video, high resolution keyframes extraction gives you original quality images and allows you to make use of the image-based artificial intelligence models provided by the Microsoft Computer Vision and Custom Vision services to gain even more insights from your video. This unlocks a wealth of pre-trained and custom model capabilities. You can use the keyframes extracted from Video Indexer, for example, to identify logos for monetization and brand safety needs, to add scene description for accessibility needs or to accurately identify very specific objects relevant for your organization, like identifying a type of car or a place. Let's look at some of the use cases we can enable with this new introduction.

Multi-language speech transcription was recently introduced into Microsoft Video Indexer at the International Broadcasters Conference (IBC). It is available as a preview capability and customers can already start experiencing it in our portal. More details on all our IBC2019 enhancements can be found here. Multi-language videos are common media assets in the globalization context, global political summits, economic forums, and sport press conferences are examples of venues where speakers use their native language to convey their own statements. Those videos pose a unique challenge for companies that need to provide automatic transcription for video archives of large volumes.

At Microsoft, our mission is to empower every person and organization on the planet to achieve more. The media industry exemplifies this mission. We live in an age where more content is being created and consumed in more ways and on more devices than ever. At IBC 2019, we're delighted to share the latest innovations we've been working on and how they can help transform your media workflows. Read on to learn more, or join our product teams and partners at Hall 1 Booth C27 at the RAI in Amsterdam from September 13th to 17th.

This article was originally published in the Summer 2019 issue of The Record. Subscribe for FREE here to get the next issue delivered directly to your inbox. Imagine no longer having to browse endless TV channels in a bid to find what you want to watch. How amazing would it be if your content provider knew you so well that it created dynamic TV channels especially for you, based on what it's learnt from your tastes and preferences? Thanks to the rise of artificial intelligence (AI), this scenario is now entirely possible.

Azure Data Box Disk, an SSD-based solution for offline data transfer to Azure, is now generally available in the US, EU, Canada, and Australia, with more country/regions to be added over time. Each disk is an 8 TB SSD that can copy data up to USB 3.1 speeds and support the SATA II and III interfaces. The disks are encrypted using 128-bit AES encryption and can be locked with your custom passkeys. When this feature is enabled, you will be able to copy data to Blob Storage on Data Box using blob service REST APIs. The following Azure IoT Hub Device Provisioning Service features are now generally available: Symmetric key attestation support; Re-provisioning support; Enrollment-level allocation rules; and Custom allocation logic.

Any organization that has a large media archive struggles with the same challenge – how can we transform our media archives into business value? Media content management is hard, and so is content discovery at scale. Content categorization by topics is an intuitive approach that makes it easier for people to search for the content they need. However, content categorization is usually deductive and doesn't necessarily appear explicitly in the video. For example, content that is focused on the topic of'healthcare' may not actually have the word'healthcare' presented in it, which makes the categorization an even harder problem to solve.

Artificial intelligence (AI) tends to divide public opinion; some favor the developments made in tech, while others worry we've gone too far. Tony Emerson, head of global entertainment at Microsoft quashed fears and answered questions from The Drum editor Stephen Lepitak during the Edinburgh Television Festival, when he spoke about the company's decision to invest in entertainment. He admitted that the company wasn't actively involved in the sector, but revealed that it works closely with and provides services to entertainment organizations, which explains the launch of its Video Indexer tool. Video Indexer promises to bolster the entertainment industry by streamlining processes and freeing up manpower. Humans have felt continually threatened by the potential of AI, but Emerson clarified that technology will always act as an assistant to human creativity and will only help to relieve labor-intensive jobs.

Earlier today, we announced the general availability (GA) of Video Indexer. This means that our customers can count on all the metadata goodness of Video Indexer to always be available for them to use when running their business. However, this GA is not the only Video Indexer announcement we have for you. In the time since we released Video Indexer to public preview in May 2018, we never stopped innovating and added a wealth of new capabilities to make Video Indexer more insightful and effective for your video and audio needs. The Video Indexer portal already includes insights and timeline panes that enables our customers to easily review and evaluate media insights.

The participants in Spafax's first hackathon were split into two teams and given two days to create a basic working prototype for a digital product aimed at improving the passenger experience. One was challenged to experiment with chatbots, while the other looked at new ways to harness machine learning. By applying a new technology called Language Understanding Intelligence Service (LUIS) to a chatbot, the team found that, with a little training the bot could start to intelligently identify new greeting phrases not previously input by the development team. Using Microsoft Azure's Cognitive Services, the team was also able to incorporate speech and image recognition into the chatbot. For example, they created a bot where you could upload an image of a famous actor.

Microsoft Azure is a cloud computing service that has its own machine learning service, known as Cognitive Services. It is split into five categories: Vision, Speech, Language, Knowledge, and Search, with each category containing several tools, for a total of 26. Under Vision, there are six tools: Computer Vision, Content Moderator, Custom Vision Service, Emotion API, Face API, and Video Indexer. As the title suggests, the focus here is on the Face API tool. With Face Identification, you must first create a PersonGroup object.