Generative AI: the mind-blowing, the scary, and what to do now

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Generative AI: the mind-blowing, the scary, and what to do now
In collaboration with the Human Centered Computing Lab by Jana Diesner.
Keynote Talk
11 Jul 2024
A

Discover the Future of AI with Professor Martin Hilbert

Join us for an enlightening session with Professor Martin Hilbert from the University of California, Davis, as he delves into the transformative power and potential pitfalls of Large Language Models (LLMs). In this era marked by rapid technological advances, LLMs have surpassed the Turing test and are now reshaping industries from education to politics with their ability to derive meaning from mere language statistics.This talk will explore the significant productivity boosts AI has brought to fields like coding and discuss the broader implications of automating knowledge creation. What does the rise of AI mean for human uniqueness in knowing and understanding? Join us as we explore these questions and more, offering a comprehensive look at both the opportunities and challenges presented by the digital age.

About Martin Hilbert

Professor Martin Hilbert is renowned for his groundbreaking research on the societal implications of digitalization. With a dual doctorate in Economic and Social Sciences and Communication, his contributions range from pioneering studies on global information volumes to strategic digital planning with the United Nations. His insights have informed digital strategies in over twenty countries and continue to influence both academia and industry discussions worldwide.

Join us for a vibrant discussion delving into promising avenues and potential challenges on the horizon of AI technologies.

TL;DR

Join us on July 11 at 12 PM for a compelling talk by University of California, Davis, Professor Martin Hilbert on the transformative role of Large Language Models in sectors ranging from education to politics, exploring both their vast potential and emerging challenges. Discover how AI is reshaping our world as we delve into the complexities and impacts of language automation.