U of T ENGINEERING

U of T Engineering News

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Inspired by nature, temperature-responsive building facades could help reduce energy use from heating and cooling

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

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Alumnus entrepreneur’s challenge to engineering undergraduates: do something game changing

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Student startups compete for $42,000 in funding at Entrepreneurship Hatchery demo night

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Molly Shoichet to lead U of T’s science and engineering engagement activities

September 18, 2014

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