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Large Language Models (LLMs) have high electricity and water consumption due to the resource requirements of serving them to millions of users. This footprint can be reduced using methods developed by Professor Samin Aref (MIE) and his team, which produce smaller LLMs through quantizing their parameters. (image generated by ChatGPT)

How ‘slimmed-down’ large language models can reduce AI’s environmental and energy footprint

Farah Ghizzawi

How a passion for sustainable transportation brought this graduate student from Beirut to Toronto

Professor Craig Simmons receives the Engineers Canada Medal for Distinction in Engineering Education

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Attendees at the 2023 Arbor Awards celebration event pose for a photograph. From left to right: Jeanette Southwood (ChemE 8T6, MASc 8T8), Gary Vivian (EngSci 5T9), Christine Tovee (EngSci 9T3), Ann Nguyen (IndE 8T6), Ron Sidon (IndE 6T6), U of T president Meric Gertler, Manu Sud (ElecE 0T8), Victor Xin (EngSci 0T9), Ross Gillett (ElecE 8T5, MEng 9T4). (Photo: Gustavo Toledo Photography)

U of T Engineering volunteers honoured at the 2023 Arbor Awards

January 24, 2024

Two researchers seated before a computer station. The two appear to be focused on the data displayed on a monitor.

U of T Engineering researchers use generative AI to design new viral vector subspecies for gene therapy delivery

January 24, 2024

Dr. Zhe Gong walks walks past equipment that make up the electric vehicle lab station.

ECE electric vehicle systems course a first for the University of Toronto

January 23, 2024

Headshots of ECE Professors Hoi-Kwong Lo and Steve Mann arranged side by side.

Two U of T Engineering professors named IEEE Fellows

January 23, 2024

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