This presentation will explain the basic limitations of deep learning-based methods and corrective measures that might help improve the outcome of any ML-based solution. The benefits of manual review and offline/batch training will be discussed. Attendees will gain a better understanding of the inherent limitations of the ML methods to use the technology more effectively.

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Data Week AI/ML & AnalyticsAccomplishing Rapid Closed-Captioning Across All Platforms, Using AIRussell Wise, Senior Vice PresidentArtificial intelligence (AI) and machine learning (ML) processing in the cloud today offers impressive accuracy, scalability and trainability across a variety of applications useful to production houses and content creators. To benefit fully from these services, however, users must be able to integrate AI- and ML-driven microservices into the on-premises workflows that already support day to-day operations. [bc_video video_id="6187288104001" account_id="4229317768001" player_id="BkgkXSCcOM" embed="in-page" padding_top="56%" autoplay="" min_width="0px" max_width="640px" width="100%" height="100%"]

Data Week AI/ML & AnalyticsFostering Effective Collaborative News Production in COVID-era Newsrooms using Neural AI Multimodal Recommendation TechniquesMichael Elhadad, Director of Research & DevelopmentSPEAKER BIOMichael Elhadad is a co-founder of Dalet and serves as a Member of the Management Board and Director. Mr. Elhadad has been Director of Research & Development of the group since 1996. Mr. Elhadad graduated from Ecole Centrale de Paris and has a PhD in Artificial Intelligence from Columbia University. He is the author of over 50 papers on Artificial Intelligence and Computational Linguistics.As news production teams are increasingly forced to work in a dispersed manner, technology solutions can partially alleviate the lack of co-location to create connections among journalists. We report on an experiment where AI techniques are used to recommend multi-media content to journalists when they are working on their stories. These techniques rely on dramatic, recent progress in Natural Language Processing and Vision research, including neural pre-trained Transformer models such as BERT (Bidirectional Encoder Representations from Transformers). At Dalet, we have developed a news recommendation system for journalists as a set of cloud-based SaaS APIs. In this talk we will report on user experiments with journalists that cover text and video in multiple languages...

Three Media's XEN:Pipeline is a new generation Business Content Management System that will drive transformational change across the content supply chain. Sitting at the heart of operations, its automated workflows and business processes are designed to discover, transform, curate and manage your metadata and content throughout its lifecycle, from concept through to distribution.

View a number of recent Digital Nirvana Webinars on demand

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While the impact of ML and AI have been discussed and debated for years, practical applications are fast accelerating across the media supply chain. The pace of innovation is moving quickly and with the cloud wars in full force, there are new services becoming available all the time that offer novel ways to automate tasks with ML and AI. Already, the big three cloud providers — AWS, Azure, and Google — have rolled out powerful capabilities that help with essential tasks including captioning, transcription, and even object/facial recognition to bolster compliance edits and to augment metadata. For media organizations, the implications of these solutions are vast, and we’ve already begun to see their power.  With things moving so fast, though, it’s challenging to keep up and important to have the right architecture and structure in place to take advantage of these innovations.

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We catch up with Kara Kandarakis of Triforce Entertainment to discuss how the company have adapted during the Covid19 Pandemic and the opportunities they see going forward.

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In this panel discussion with Reinhard Grandl (Head of Product, Bitmovin) & Bill McFarland (CTO, Plume), we hear about their key markets and the differences in each of these markets. We hear how Covid-19 has affected their business along with the biggest challenges they have faced during the crisis.

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In this IABM TV interview, Maria Lodolo D'Oria (Head of Sales, Metaliquid) discusses the current state of recognition technology in the broadcast and media industry.

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In this Lorenzo Zanni (Head of Insight & Analysis, IABM) and Ryan Steelberg (President, Veritone) discuss Artificial Intelligence and Machine Learning.

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