Video Language and The Machine: Words versus Meaning with Kris Hammond | Data Stories Deep Dive Ep 10

Over the past few years, we have seen tremendous progress in the area of Language Modeling. Models such as GPT-2 and Bert are able to generate text that, on a good day, read somewhat human. The only problem with them is that while the texts that they generate might read well, they are disconnected from the world. They were never designed, to tell the truth let alone the truth you need to communicate today. In this week’s episode of Data Stories Deep Dive, we will explore these models juxtaposed against systems that use language to bridge the gap between what the machine knows and what we need to understand.

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About the data storyteller:

Kris Hammond is the Chief Scientist at Narrative Science and professor of Computer Science and Journalism at Northwestern University. His areas of research include human-machine interaction, context-driven information systems and artificial intelligence. In 1999, he founded Northwestern University’s Intelligent Information Laboratory (InfoLab). At the InfoLab, his team creates technology that bridges the gap between people and the information they need.

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