ChatGPT Killed the Streaming Formula
No spam. Just Hang Dallas.
For a decade, streaming platforms poured enormous resources into learning your taste and predicting what you'd watch next. Then people started asking a chatbot instead, and the machine that ran the industry began to lose its grip. Yunhe Feng, who directs UNT's Responsible AI Lab and has co-authored research on ChatGPT's impact on streaming media, walks through what actually changed, why the old formulas stopped working, and what it means when a conversation replaces a recommendation.
What this talk is about
The Hang Theory. A lecture series by Hang Dallas.
One speaker. One big idea. One good room.
Where · Times Ten Cellars.
For a decade, streaming platforms poured enormous resources into learning your taste and predicting what you'd watch next. Then people started asking a chatbot instead, and the machine that ran the industry began to lose its grip. Dr. Yunhe Feng, who directs UNT's Responsible AI Lab and has co-authored research on ChatGPT's impact on streaming media, walks through what actually changed, why the old formulas stopped working, and what it means when a conversation replaces a recommendation.
How the night goes
Doors at 6:30 PM. Claim a seat, settle in.
We kick things off around 6:55 PM.
Dr. Feng takes the floor at 7:00 PM.
Questions from the room near 7:45 PM.
Then we linger. Meet the speaker, meet each other, around 8:00 PM.
Out by 8:30 PM.
Who's speaking
Yunhe Feng
Dr. Yunhe Feng is an Assistant Professor in the Department of Computer Science and Engineering (CSE), University of North Texas (UNT), Denton, TX; a Tier-One (R1) Research University as per Carnegie Classification, where he directs the Responsible AI Laboratory (RAIL). His research interest lies in Responsible AI, Mobile Security and Privacy, and Social Media. Dr. Feng is particularly interested in: Designing algorithms and models to enhance fairness, accountability, transparency, ethics, security, and privacy in AI. Investigating the societal impacts of AI by putting humans and society in the loop. Applying AI in cross-domain applications (e.g., smart manufacturing and smart agriculture). Dr. Feng's research has been sponsored by both academic and industrial grants, including Kaggle's Open Data Research Grant, Google Cloud & Harvard Global Health Institute COVID-19 Research Credits, UW-Microsoft Azure Cloud Computing Credits, UW Strategic Research Fund, and NSF-funded XSEDE (Extreme Science and Engineering Discovery Environment) Startup Allocation. He has received several fellowships and awards, including UW Data Science Fellowship, UTK Min H. Kao Fellowship (the highest departmental award), UTK EECS Department Excellence Fellowship, a Best Paper Award by IEEE BigDataSecurity'18, and two Best Paper/Presentation Nominations by IEEE CloudCom'17 and ACM UbiComp'20. Dr. Feng's research has been covered internationally by news outlets, including Financial Times, Business Insider, Yahoo! Finance, UW News, AAAS EurekAlert, and ACM Tech News. Before joining UNT, Dr. Feng was a Postdoctoral Fellow/Scholar with Dr. Chirag Shah at the University of Washington (UW), Seattle (2020-2022). He received his Ph.D. in Computer Science in 2020 from the University of Tennessee, Knoxville (UTK). Dr. Feng also worked as a deep learning research intern (Summer 2018) and research assistant (Dec. 2018 - Sep. 2019) at Oak Ridge National Laboratory, where he led the interdisciplinary research project of DeepWelding. Dr. Feng obtained his B.E. in Computer Science & Technology and M.E. in Computer Technology from Beijing University of Technology in 2011 and 2014, respectively. Dr. Feng is affiliated with UW Responsibility in AI Systems and Experiences (RAISE) and serves as Associated Editor for Information Matters. He also serves as PC for AAAI, TPC for ICWSM, GLOBECOM, HPCC, etc.
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Times Ten Cellars · Dallas, TX