“We predict that A.I.s will continue to improve to the point where they’re fully autonomous agents that are better than humans at everything by the end of 2027 or so.”
Organizations with semantic ambitions such as dynamic content and personalization often face practical challenges in implementing knowledge organization structures that are sophisticated enough to support them. These challenges include system constraints, fledgling governance models, and human factors.
Networking prompt and let’s ‘break the ice’- connect with someone you’ve not met before! Mingle with your peers. Take time to forge a new connection in your DAM and Semantic Data community.
Exhibition - your chance to check out the live demos, to contrast and compare. Talk to those who have the solution you might need.
How DITA can be used to break content down into logical, granular chunks to be used across publications and delivery channels A useful tool on the road to semantics
DITA in the delivery of an optimal end user experience:
Over the past five years, Yale University has built an innovative knowledge graph that connects its libraries, archives and museums in a single discovery platform, advancing the university’s core missions of teaching and research excellence.
Led by Conference Chair, Madi Weland Solomon, and with insights from the event’s speakers, this interactive roundtable is an opportunity to exchange views, share experiences, hear innovative questions, pose questions and expand one’s network - just the way to kickstart the afternoon.
All in a collaborative environment designed to increase knowledge, enhance skills, and propel careers.
For a long time much of HealthStream’s’ taxonomy has remained static, hard coded into production environments that couldn’t be updated without development efforts. As a result, changes have not been made in years due to competing priorities. As part of its evolution into a platform solution HealthStream is beginning to offer API services for taxonomy.
Overview A career spent working with photos, videos, music, and books has provided me ample opportunities to experiment with AI solutions for content tagging and metadata generation. From counting the number of people in a photo to applying keywords to kittens to writing fun facts about pop stars, AI-powered tools can perform a lot of mundane tasks. I’ve evaluated the work of these “robots” for over a decade, and I’ve recommended ways to leverage automation for scale, while still adhering to the level of quality demanded by human end users.