The workshop will consist of AISI technical presentations and interactive breakout discussions to inform the development of a taxonomy of tools that a foundation model may use to take actions in environments, providing a valuable shared vocabulary for future work across the ecosystem.
Drawing on a new Cornell Tech report, The Augmented City: Seeing Through Disruption, this session will explore how AI and augmented reality (AR) innovations could reshape infrastructure planning and management – from maintenance crews accessing real-time utility data to citizens visualizing proposed development impacts on their neighborhoods. We’ll explore how transit officials in Columbus, Ohio recently used AR to help win support for a ground-breaking bus rapid transit (BRT) project, and how local governments can proactively develop policies and partnerships that harness AR’s potential while protecting public spaces and privacy.
The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
Join DevOps Engineer Michael Sprague on Tuesday, February 11, 2025 for an AI-focused workshop for web developers. During the workshop Michael will evaluate three different AI tools designed for building web apps and interfaces, and discuss how they can shorten your time from concept to prototype. Hear about the strengths and shortcomings of v0, Bolt, and Replit Agent.
The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
Held Fridays from 4:00-4:30 PM via Zoom, the forum is for Cornell faculty and staff (e.g., research operational support staff) who are interested in the EMPIRE AI’s current status and future plans. Weekly forums are scheduled throughout the Spring 2025 semester starting February 14.
Please register for the series, which will then provide the Zoom link info
The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
Held Fridays from 4:00-4:30 PM via Zoom, the forum is for Cornell faculty and staff (e.g., research operational support staff) who are interested in the EMPIRE AI’s current status and future plans. Weekly forums are scheduled throughout the Spring 2025 semester starting February 14.
Please register for the series, which will then provide the Zoom link info
In this talk, Zhao will emphasize the importance of building scalable systems across the entire ML pipeline. In particular, Zhao will explore how large-scale ML training pipelines, including those deployed at Meta, require distributed data storage and ingestion systems to manage massive training datasets. Optimizing these data systems is essential as data demands continue to grow. To achieve this, Zhao will demonstrate how synergistic optimizations across the training data pipeline can unlock performance and efficiency gains beyond what isolated system optimizations can achieve.
The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
Held every other Friday from 4:00-4:30 PM via Zoom, the forum is for Cornell faculty and staff (e.g., research operational support staff) who are interested in the EMPIRE AI’s current status and future plans. Biweekly forums are scheduled throughout the Spring 2025 semester starting February 14.
Please register for the series, which will then provide the Zoom link info