Abstract Number:
2804
Submission Type:
Late-Breaking Session
Participants:
Jiashun Jin (1), Jiashun Jin (1), David Donoho (2), Tracy Ke (3), Mengdi Wang (4), Weijie Su (5)
Institutions:
(1) Carnegie Mellon University, N/A, (2) Stanford University, N/A, (3) Harvard University, N/A, (4) Princeton University, N/A, (5) University of Pennsylvania, N/A
Chair:
Session Organizer:
Speaker(s):
Session Description:
Summary: The advancement in the AI industry has rapidly reshaped the scientific community, giving birth to a new research area called ``AI for Statistics", where the goal is to address scientific problems by combining ideas in statistics and AI. We aim to invite 4 distinguished speakers in the statistical community to discuss the DeepSeek (a very recent large language model), recent advancements in AI, and how statisticians can respond to these recent advancements. The session will discuss topics such as ``how does DeepSeek compare with other LLMs (e.g., ChatGPT, Claude, Llama, Gemini)", ``what kind of opportunity statisticians may have and how to combine ideas in statistics with AI", and ``does the success of DeepSeek provide a more affordable way for statisticians to train LLM"?
Timeliness: Since its latest version released on January 20, 2025, DeepSeek has shaken up the AI industry. It has made the headlines of news and social media, shot to the top of Apple Store's downloads, stunning investors and sinking some tech stocks including Nvidia.
What makes DS so special is that in some benchmark tasks it achieved the same or even better results as the big players in the AI industry (e.g., OpenAI's ChatGPT), but with only a fraction of the training cost. This session will discuss DeepSeek and recent advancements in AI, and how statisticians may respond to these advancements.
Audience: the session applies a very broad audience, including all researchers who are interested in learning AI and who are interested in using AI tools to help their study.
Theme:
Statistics, Data Science, and AI Enriching Society
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Applied
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I have read and understand that JSM participants must abide by the Participant Guidelines.
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I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 3, 2025. The registration fee is nonrefundable.
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