Making Your Assets Mean Something!
Originally Aired - Saturday, April 13 | 11:50 AM - 12:10 PM PT
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More content! In different places! Nothing thrown away! Produce more! Faster! Cheaper! How are media enterprises to keep up with these business pressures? How do their media asset management systems evolve to provide the right content at the right time? How does a creative produce content faster using knowledge hidden in the content? How can assets be accessed from distributed locations to enrich the experience? How does one manage content growth without exploding costs? This session discusses how certain technologies such as semantic indices, Knowledge Graphs, Semantic Web and Large Language Model revolution are coming together to solve these problems. The rise of data-mesh and data-fabric design patterns holds promise to connect the variety of information sources in a much more scalable manner, to provide ever-richer information about the assets. Using graph databases to store content relationships based on standard ontologies or those defined by specific enterprises helps connect and organize the data. Use of Semantic embeddings, as well as knowledge graphs to represent related pieces of information lends meaning to the content. Storing contextually-related information now results in asset management systems moving up the DIKW (Data, Information, Knowledge, Wisdom) pyramid to now store knowledge of the content, rather than just information or metadata about the content. If one can now derive meaning from the content, it also changes the way we find new content - traditional search changes to contextual recommendations, speeding up the creative, discovery and ideation process. Natural Language Processing (NLP) technology changes the way we think of making enquiries. Queries and erstwhile UI-based commands turn into conversations with the systems, where the system acts based on the conversational input, and even replies in natural language appropriate to the creator. This presentation will illustrate these principles and include examples of these technologies at work to demonstrate how some of the cost-efficiencies and time-savings can be achieved.
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