Speaker

Ameet Talwalkar, Chief Scientist at Datadog; and Associate Professor in the Machine Learning Department at Carnegie Mellon University

Event Details

Thursday April 10, 2025 (12:00 PM – 1:00 PM ET)

Location: Columbia School of Social Work, Room 903

REGISTRATION DEADLINE: The Columbia Morningside campus is open to the Columbia community. If you do not have an active CUID, the deadline to register is at 12:00 PM the day before the event.

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Talk Information

AI Needs Specialization to Generalize

Abstract: While modern AI holds great promise, the gap between its hype and practical impact remains substantial. This talk advocates for the importance of specialization to help bridge that gap—urging researchers to tailor problem formulations, modeling approaches, data collection, and evaluation methods to concrete downstream tasks. We begin by examining the limitations of existing domain-specific foundation models–for genomics, satellite imaging, and time series–that apply techniques from core AI domains such as vision and NLP with minimal specialization. We then present recent work from CMU and Datadog AI Research that advances specialized approaches across diverse tasks: solving partial differential equations, autonomously executing complex web tasks, and proactively detecting or predicting disruptions in production software systems. These efforts highlight the critical role of domain-aware design in moving beyond shiny demos and toward meaningful AI impact.