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SimPer: Simple self-supervised learning of periodic targets

Favorite Posted by Daniel McDuff, Staff Research Scientist, and Yuzhe Yang, Student Researcher, Google Learning from periodic data (signals that repeat, such as a heart beat or the daily temperature changes on Earth’s surface) is crucial for many real-world applications, from monitoring weather systems to detecting vital signs. For example,

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Shared by Google AI Technology July 18, 2023

6 women leading the fight against climate change

Favorite We’re celebrating climate science pioneer Eunice Newton Foote and six women-led Google.org grantees building a more sustainable future. View Original Source (blog.google/technology/ai/) Here.

6 mujeres lideran la lucha contra el cambio climático

Favorite Homenajeamos a Eunice Newton Foot, científica pionera de la ciencia climática, y a 6 organizaciones beneficiarias de Google.org dirigidas por mujeres que construyen un f… View Original Source (blog.google/technology/ai/) Here.

Effectively solve distributed training convergence issues with Amazon SageMaker Hyperband Automatic Model Tuning

Favorite Recent years have shown amazing growth in deep learning neural networks (DNNs). This growth can be seen in more accurate models and even opening new possibilities with generative AI: large language models (LLMs) that synthesize natural language, text-to-image generators, and more. These increased capabilities of DNNs come with the

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Shared by AWS Machine Learning July 14, 2023