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The Ethics and Early Career Committee would like to invite you to our upcoming webinar on AI Ethics in Research. This will take place virtually through Zoom on Friday, March 8th at noon Pacific, 2pm Central, 3pm Eastern (https://nu.zoom.us/j/2183621123). Please join Dr. Nisheeth Vishnoi from Yale and Dr. David Danks from UC San Diego who will discuss their Research […]
Roy Fox, Assistant Professor and Director of the Intelligent Dynamics Lab at UC Irvine HDSI 123 and Zoom (Link below) Abstract: If learning from data is valuable, can learning from big data be very valuable? So far, it has been so in vision and language, for which foundation models can be trained on web-scale data to […]
Transformers learn in-context by (functional) gradient descent Xiang Cheng, TILOS Postdoctoral Scholar at MIT HDSI 123 and Zoom: https://ucsd.zoom.us/j/99334315002 Abstract: Motivated by the in-context learning phenomenon, we investigate how the Transformer neural network can implement learning algorithms in its forward pass. We show that a linear Transformer naturally learns to implement gradient descent, which enables it to […]
Abstract: Recent progress in AI can be attributed to the emergence of large models trained on large datasets. However, teaching AI agents to reliably interact with our physical world has proven challenging, which is in part due to a lack of large and sufficiently diverse robot datasets. In this talk, I will cover ongoing efforts of the Open X-Embodiment project–a collaboration between 279 researchers across 20+ institutions–to build a large, open dataset for real-world robotics, and discuss how this new paradigm is rapidly changing the field. Concretely, I will discuss why we need large datasets in robotics, what such datasets may look like, and how large models can be trained and evaluated effectively in a cross-embodiment cross-environment setting. Finally, I will conclude the talk by sharing my perspective on the limitations of current embodied AI agents, as well as how to move forward as a community.
EVENT WEBSITE 8:00 – 8:45am Breakfast 8:45 – 9:00am Welcome Remarks and Introduction to TILOS Director Yusu Wang (UCSD) and AD Translation Vijay Kumar (UPenn) 9:00 – 10:30am SESSION 1 Industry Keynote: Nicholas Roy (Zoox and MIT) TILOS Faculty Highlights: Farinaz Koushanfar (UCSD) Nisheeth Vishnoi (Yale U) 10:30 – 10:45am Break (15 minutes) 10:45am – 12:15pm SESSION 2 Industry Keynote: Nageen Himayat (Intel Labs) TILOS Faculty […]
When Wednesday July 24th 10:00am *Updated Where: HDSI 123 * Updated Zoom Info: https://ucsd.zoom.us/j/99334315002 *Updated Title: What Kinds of Functions do Neural Networks Learn? Theory and Practical Applications Abstract: This talk presents a theory characterizing the types of functions neural networks learn from data. Specifically, the function space generated by deep ReLU networks consists of compositions of functions from the […]
Talk Information Speaker: Claire Boyer (Université Paris-Saclay) Date & Time: Thursday, March 27 @ 2pm PDT Venue: HDSI 123 Title: Single location regression and attention-based models Abstract: Attention-based models, such as Transformer, excel across various tasks but lack a comprehensive theoretical understanding, especially regarding token-wise sparsity and internal linear representations. To address this gap, we introduce the single-location regression task, where […]
TITLE Foundational Methods for Foundation Models for Scientific Machine Learning| ABSTRACT The remarkable successes of ChatGPT in natural language processing (NLP) and related developments in computer vision (CV) motivate the question of what foundation models would look like and what new advances they would enable, when built on the rich, diverse, multimodal data that are […]
Our 4th Annual Industry Day will be June 2, 2025, at the Halıcıoğlu Data Science Institute at UC San Diego, the campus hub for data science. This year TILOS Industry Day will feature:
Talks from invited industry speakers sharing their perspectives on challenges in AI + Optimization + Use Domains (chips, robotics, networking)
Research highlights from TILOS team members
Panel discussions on AI Challenges for Academia—An Industry Perspective and Building Deep Tech Companies
Poster session featuring the work of TILOS trainees (students and postdoctoral scholars)
The next TILOS-HDSI seminar will be Wednesday, November 12 at 11am PST with Adam Oberman (McGill University). The title is AI Safety Theory: The Missing Middle Ground. Talk Information Speaker: Adam Oberman (McGill University) Date & Time: Wednesday, November 12 @ 11am PST Venue: HDSI 123 Abstract: Over the past few years, the capabilities of generative artificial intelligence (AI) systems have advanced rapidly. Along with the […]