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## Prizes
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At HackMIT, we are looking for winning teams that successfully employ Paddle as part of their application or development process. To be considered for the prize, please be prepared to have git commit logs or other evidence showing that all the code was written during the event, and that Paddle is used.
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At HackMIT, we are looking for winning teams that successfully employ Paddle as part of their application or development process. To be considered for the grand prize, please be prepared to have git commit logs or other evidence showing that all the code was written during the event, and that Paddle is used.
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In addition, we reward teams focusing on potentially big impact and/or interesting use cases.
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## PaddlePaddle Introduction
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PaddlePaddle is a deep learning framework originally developed in Baidu, the primary search engine in China. It is widely used Baidu, including in the search engine, the advertising system, autonomous driving, speech-based AI systems, etc.
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PaddlePaddle is a deep learning framework originally developed within Baidu. It is widely used Baidu, including in the search engine, the advertising system, autonomous driving, speech-based AI systems, etc.
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In September 2016, Baidu open-sourced PaddlePaddle. It is one of the [most actively developed](https://twitter.com/fchollet/status/798566108810752001) one in the category.
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In September 2016, Baidu [open-sourced](http://www.marketwired.com/press-release/baidu-to-open-source-new-platform-for-deep-learning-community-nasdaq-bidu-2154798.htm) PaddlePaddle. Compared to other deep learning frameworks, PaddlePaddle has a focus on usability and practicality. It is one of the [most actively developed](https://twitter.com/fchollet/status/798566108810752001) deep learning frameworks.
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### Current Work on Paddle
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### Recent Work
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PaddlePaddle used to release a binary executable file that accepts a model configuration file in Python. Since February 2017, PaddlePaddle provides a [Python API](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/api.md) and the team is porting many [applications](https://github.com/paddlepaddle/models) and writing a [tutorial](http://book.paddlepaddle.org) using the API.
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The team is also rewriting the C++ core -- including an innovative conceptual model *nested blocks* other than widely accepted *graph of operators*. [TODO(wangkuiyi): link to design doc] Also the team is integrating PaddlePaddle and Kubernetes to enable very large scale [distributed training](https://github.com/PaddlePaddle/Paddle/tree/develop/doc/design/cluster_train).
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