WeAreDevelopers LIVE • Apr 21, 2023

Optimizing your AI/ML workloads for sustainability

Sohan Maheshwar

Deployment accounts for nearly 90% of a machine learning model's energy usage. Discover how to systematically engineer your cloud architecture to balance powerful AI capabilities with planetary limitations.

Starting at 16:03 · Watch from the beginning

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Matching moments

4:24 min

Balancing heavy compute demands with environmental sustainability goals

Mike Butcher

Mike Butcher +3 · World Congress 2024

1:39 min

Balancing human-centric AI collaboration with environmental sustainability practices

Madalena Costa

Madalena Costa · World Congress 2024

1:25 min

Addressing the sustainability and power consumption of AI

Christian Heilmann

Christian Heilmann · World Congress 2026 Europe

4:03 min

Managing massive power consumption scaling in AI data centers

Stephan Gillich

Stephan Gillich +3 · World Congress 2024

3:13 min

Assessing the energy demands versus sustainability benefits of computation

Alexander Gerfer

Alexander Gerfer +3 · World Congress 2026 Europe

4:48 min

Establishing cross-chain accountability for sustainable machine learning usage

Alexander Gerfer

Alexander Gerfer +3 · World Congress 2026 Europe

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Upcoming sessions on this topic

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