Ishneet Kaur Dua
Responsible & Environmentally Sustainable GenerativeAI Enthusiast
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Ishneet has reached wide audiences through her writing and speaking engagements. She has authored eight popular blogs focused on sustainability in the cloud computing space which have amassed over 100,000 views. She was also a featured speaker at both the 2022 and 2023 AWS Re:Invent conferences, using these prominent stages to outline strategies for optimizing cloud workloads to reduce carbon footprints. In addition, Ishneet spoke at the 2022 and 2023 Cadence Live conferences about sustainability in tech. She also organized a "Code Green" hackathon at AWS Re:Invent 2021, bringing together 400 attendees to innovate around environmental sustainability.
Ishneet has established herself as a go-to expert on leveraging AI and machine learning to combat climate change, pollution, and other sustainability challenges. Ishneet has also directly trained hundreds of engineers and technologists on how to adopt more sustainable practices. This includes leading nationwide sustainability bootcamps and localized training sessions in the San Francisco area focused on responsible and eco-friendly approaches to AI and machine learning. Through her prolific writing, speaking, and training, Ishneet has demonstrated a passion for and commitment to advancing sustainability in the tech sector. As the industry continues prioritizing greener ways of operating, her expertise and advocacy will no doubt continue making an impact.
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Optimizing Generative AI Workloads for Sustainability in AWS
Abstract: With the increasing complexity, scale, and adoption of GENAI workloads , it is crucial to consider their environmental impact. This chalk talk provides environmental sustainability insights that are specific to large language models and how machine learning operations MLOPS is critical to sustainable optimization. In particular, we discuss practical best practices for different customization scenarios including training models from scratch, fine-tuning with additional data using full or parameter-efficient techniques, retrieval augmented generation (RAG) and prompt engineering.
Ishneet Kaur Dua
Responsible & Environmentally Sustainable GenerativeAI Enthusiast
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