With hundreds of millions of customers shopping daily on Amazon, it’s critical they help them discover the right product from their massive catalog of products.
Amazon’s Deep Scalable Sparse Tensor Network Engine (DSSTNE or “Destiny”) is a deep learning framework built from the ground up to help researchers develop search and recommendation systems. With multi-GPU support, DSSTNE can automatically distribute computational workloads across all available GPUs, speeding up training of larger models without a lot of effort. As a result, DSSTNE can be used to build recommendations systems that model ten million unique products instead of being limited to hundreds of thousands possible with other solutions.
The DSSTNE roadmap includes support for the types of convolutional layers used in image processing, and additional recurrent layers needed for many natural language understanding and speech recognition tasks.
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Amazon Releases Open-Source Deep Learning Software
May 11, 2016
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AI-Generated Summary
- Amazon's product recommendation systems are crucial as they have hundreds of millions of customers shopping daily on their platform.
- Amazon's Deep Scalable Sparse Tensor Network Engine (DSSTNE) is a deep learning framework that helps researchers develop search and recommendation systems with multi-GPU support, allowing for faster training of larger models.
- DSSTNE has the potential to be used for various tasks beyond product recommendations, including image processing and natural language understanding tasks, as indicated by its roadmap.
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