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How climate tech startups are building foundation models with Amazon SageMaker HyperPod
- Climate tech startups are utilizing generative AI models to develop solutions for the climate crisis, including carbon capture and ecosystem preservation.
- These startups are leveraging Amazon SageMaker HyperPod, which provides scalable compute infrastructure for training complex models efficiently.
- Startups building foundation models (FMs) focus on areas like sustainable material discovery and geological modeling using extensive environmental datasets.
- Amazon Web Services (AWS) supports climate tech startups with advanced computational capabilities through SageMaker HyperPod for model training.
- Climate tech startups adopting generative AI have been addressing specific climate challenges like weather prediction, material discovery, and ecosystem monitoring.
- Orbital Materials, for instance, has achieved significant improvements in material design for carbon capture through their generative AI model 'Orb'.
- Hum.AI is utilizing SageMaker HyperPod for earth observation by training models on extensive satellite data to predict ecosystems and biodiversity changes.
- SageMaker HyperPod's infrastructure helps startups like Orbital and Hum.AI optimize their model training process for enhanced performance and efficiency.
- Amazon SageMaker HyperPod streamlines the training of climate-focused foundation models, allowing startups to focus on innovation rather than infrastructure management.
- Climate tech startups are becoming more sustainable in their computing practices by monitoring energy consumption and incorporating renewable energy sources.
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