Reduce AI’s Carbon Footprint - Accelerating Deep Learning Models 

#carbon-footprint #environmental-impact #deep-learning #learning-models
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Abstract:

AI-driven data centres, operating continuously and predominantly powered by fossil fuels, contribute significantly to global greenhouse gas emissions (2.5-3.7%). The widespread use of large foundation models such as ChatGPT exacerbates this environmental impact. This talk explores strategies for mitigating AI's carbon footprint through model acceleration, aiming to significantly reduce computations while maintaining the accurate of AI models. This session will spotlight various model acceleration techniques, including Model Pruning and Quantisation, and others. Last, it will outline potential future research directions in the field of model acceleration. 

 


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  • Starts 16 June 2026 11:00 PM UTC
  • Ends 05 August 2026 11:00 PM UTC
  • No Admission Charge

  Speakers

Guosheng of University of Bristol

Topic:

Reduce AI’s Carbon Footprint - Accelerating Deep Learning Models

 

AI-driven data centres, operating continuously and predominantly powered by fossil fuels, contribute significantly to global greenhouse gas emissions (2.5-3.7%). The widespread use of large foundation models such as ChatGPT exacerbates this environmental impact. This talk explores strategies for mitigating AI's carbon footprint through model acceleration, aiming to significantly reduce computations while maintaining the accurate of AI models. This session will spotlight various model acceleration techniques, including Model Pruning and Quantisation, and others. Last, it will outline potential future research directions in the field of model acceleration. 

Biography:

Dr. Guosheng Hu is a senior lecturer of AI at the University of Bristol. Before that, he served as the Head of Research at Oosto (a leading visual AI company). Prior to his role at Oosto, he was a Research Fellow in the LEAR team at NRIA Grenoble Rhone-Alpes, France. Dr. Hu earned his PhD under the supervision of Prof. Josef Kittler at the University of Surrey, UK. His expertise lies in the intersection of computer vision and efficient AI.

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Guosheng of University of Bristol

Topic:

Reduce AI’s Carbon Footprint - Accelerating Deep Learning Models

Biography:

 

 

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Agenda

 

1- Welcome 

2- Introduction to SSIT

3- Technical Talk

4- Q&A