The Environmental Impact of AI and Machine Learning with Amber McKenzie
What is the impact of Artificial Intelligence on the environment? Carl and Richard talk to Amber McKenzie about her examination of resource consumption when creating machine learning models. As Amber explains, using ML models is not particularly resource-intensive, but creating them is - which leads to a discussion about using technologies like transfer learning to avoid making models unnecessarily. The conversation also digs into the broader thinking about resource consumption in computing - do you know how much power your apps use?
Guests:
Amber McKenzie
Dr. Amber McKenzie is head of Data Science and Analytics at HR tech start-up Fama. With a master's degree in linguistics and a Ph.D. in computer science, she has almost 15 years of experience in data science, AI, and natural language processing (NLP). She has led a variety of projects in a number of different sectors - including military applications, healthcare, marketing, law enforcement, accounting, and adtech - during her time at the University of South Carolina, Oak Ridge National Laboratory, DialogTech, PwC. Her professional interests include NLP, machine learning, predictive modeling, and computer learning. When she does get a spare moment outside of work, she enjoys reading, board games, indoor rock climbing, and lifting weights.
Links:
- Blazor Train https://www.youtube.com/watch?v=0O-bNuQOQb8
- Google's BERT https://github.com/google-research/bert
- Microsoft Sustainability https://www.microsoft.com/en-us/corporate-responsibility/sustainability
- Amazon Sustainability https://sustainability.aboutamazon.com/environment/the-cloud?energyType=true
- Google Sustainability https://cloud.google.com/sustainability