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Apple Workshop on Privacy-Preserving Machine Learning 2024

Machine Learning Research at Apple

We develop system architectures that enable learning at scale by leveraging advances in machine learning (ML), such as private federated learning (PFL), combined with…

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Meeting customer needs with our ML platform redesign

Snorkel AI

In this article, we share our journey and hope that it helps you design better machine learning systems. Table of contents Why we needed to redesign our interactive ML system In this section, we’ll go over the market forces and technological shifts that compelled us to re-architect our ML system.

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Towards ML-enabled cleaning robots

Google Research AI blog

Combining the strengths of RL and of optimal control We propose an end-to-end approach for table wiping that consists of four components: (1) sensing the environment, (2) planning high-level wiping waypoints with RL, (3) computing trajectories for the whole-body system (i.e.,

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Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning Blog

ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. Model developers often work together in developing ML models and require a robust MLOps platform to work in.

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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning Blog

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. For more information, refer to Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data.

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Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

AWS Machine Learning Blog

There are various technologies that help operationalize and optimize the process of field trials, including data management and analytics, IoT, remote sensing, robotics, machine learning (ML), and now generative AI. The transformed data acts as the input to AI/ML services. AWS Lambda is then used to further enrich the data.

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Redesigning Snorkel’s interactive machine learning systems

Snorkel AI

In this article, we share our journey and hope that it helps you design better machine learning systems. Table of contents Why we needed to redesign our interactive ML system In this section, we’ll go over the market forces and technological shifts that compelled us to re-architect our ML system.