eventSeminar
Tim de Silva | AI Financial Advice: Supply, Demand, and Life Cycle Implications
SeminarOct 07, 202612:00 PM - 1:15 PM
October
07
2026
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This session covers the foundational knowledge of GPUs, including their architecture, functionality, and applications in computing. It provides an introduction to GPU computing through the lens of the Marlowe SuperPod and prepares learners for advanced topics such as GPU-accelerated data science and machine learning.
Location: CoDa W401
This session covers the foundational knowledge of GPUs, including their architecture, functionality, and applications in computing. It provides an introduction to GPU computing through the lens of the Marlowe SuperPod and prepares learners for advanced topics such as GPU-accelerated data science and machine learning.
Location: CoDa W401
For 9/23 and 10/7 only, sessions are at the David Packard Electrical Engineering Building, Room 101. Each session features a different Stanford speaker; talk titles are announced by the organizers.
For 9/23 and 10/7 only, sessions are at the David Packard Electrical Engineering Building, Room 101. Each session features a different Stanford speaker; talk titles are announced by the organizers.
HAI Weekly Seminar
One unsolved problem in democratic theory is how we can reconcile the twin goals of quality deliberation and mass participation. Both are arguably conditions for the full legitimacy of a democratic system. Quality deliberation, as a process through which laws and policies are generated, in theory promises good governance (output-legitimacy) as well as, at the very least, good reasons for the laws and policies put forward. Mass participation, by contrast, is a condition for the democratic input-legitimacy of the system, namely its capacity to take into account people’s needs and preferences. Unfortunately, thus far, it has proven impossible to reconcile those two goals as the quality of deliberation diminishes past a relatively low threshold of participants (a few hundreds, perhaps a few thousand people) and mass participation, on the other hand, is not conducive to the thoughtful, informed exchanges smaller numbers afford. In this presentation, Hélène Landemore explores the ways in which Artificial Intelligence may help bridge that gap, at least up to a point.
Hélène LandemoreProfessor of Political Science, Yale University
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