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

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

Keep up on the latest Engineering News

Subscribe to our Skulematters newsletter on Linkedin

Latest news

Hydrogeological technicians collect core samples from a hydrocarbon-contaminated aquifer near Barrie, Ont. Professor Elizabeth Edwards (ChemE) and her partners — including SiREM, a company that offers site remediation products and services — have developed bacterial cultures designed to clean up such sites by breaking down contaminants such as benzene, toluene and xylene. (Photo: Courtney Toth)

Contamination-eating microbes are ready for action

August 7, 2019

$PetePeter Stogios manipulates a protein crystal mounted on an X-ray diffractometer. He and his team are researching a less expensive way of making cell-based meat. (Photo: Nick Iwanyshyn)r Stogios manipulates a protein crystal mounted on an X-ray diffractometer. He and his team are researching a less expensive way of making cell-based meat (photo by Nick Iwanyshyn)$