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Sunday, August 07, 2022

Baidu PaddlePaddle for China Industry

Baidu PaddlePaddle,   new to me, Here is a quick look.  Examining other potentials.

Baidu’s PaddlePaddle Spins AI up to Industrial Applications China’s ease with ubiquitous AI manifests at neural-net scales    By CRAIG S. SMITH   in Spectrum IEEE

TensorFlow, PyTorch, and Keras: Those three deep-learning frameworks have dominated AI for years even as newer entrants gain steam. But one framework you don’t hear much about in the West is China’s PaddlePaddle, the most popular Chinese framework in the world’s most populous country.

It is an easy-to-use, efficient, flexible, and scalable deep-learning platform, originally developed by Baidu, the Chinese AI giant, to apply deep learning to many of its own products. Today, it is being used by more than 4.77 million developers and 180,000 enterprises globally. While comparable numbers are hard to come by for other frameworks, suffice to say, that’s big.

Baidu recently announced new updates to PaddlePaddle, along with 10 large deep-learning models that span natural-language processing, vision, and computational biology. Among the models is a hundred-billion-parameter natural language processing (NLP) model called ERNIE 3.0 Zeus, a geography-and-language pretrained model called ERNIE-GeoL, and a pretrained model for compound representation learning called HELIX-GEM.

The company has also created three new industry-focused large models—one for the electric power industry, one for banking, and another one for aerospace—by fine-tuning the company’s ERNIE 3.0 Titan model with industry data and expert knowledge in unsupervised learning tasks.

Software frameworks are packages of associated support programs, compilers, code libraries, tool sets, and application programming interfaces (APIs) to enable development of a project or system. Deep-learning frameworks bring together everything needed to design, train, and validate deep neural networks through a high-level programming interface. Without these tools, implementing deep-learning algorithms would take a lot of time because otherwise reusable pieces of code would have to be written from scratch.

Baidu started to develop such tools as early as 2012 within months of Geoffrey Hinton’s deep-learning breakthrough at the ImageNet competition.

In 2013, a doctoral student at the University of California, Berkeley, created a framework called Caffe, that supported convolutional neural networks used in computer-vision research. Baidu built on Caffe to develop PaddlePaddle, which supported recurrent neural networks in addition to convolutional neural networks, giving it an advantage in the field of NLP.

The name PaddlePaddle is derived from PArallel Distributed Deep Learning, a reference to the framework’s ability to train models on multiple GPUs.

Google’s open-sourced TensorFlow in 2015 and Baidu open-sourced PaddlePaddle the next year. When Eric Schmidt introduced TensorFlow to China in 2017, it turns out China was ahead of him.

While TensorFlow and Meta’s PyTorch, open-sourced in 2017, remain popular in China, PaddlePaddle is more oriented toward industrial users.

“We dedicated a lot of effort to reducing the barriers to entry for individuals and companies,” said Ma Yanjun, general manager of the AI Technology Ecosystem at Baidu.

PyTorch and TensorFlow require greater deep-learning expertise on the part of users compared to PaddlePaddle, whose toolkits are designed for nonexperts in production environments.

“In China, many of the developers are trying to use AI in their work, but they do not have much AI background,” explained Ma. “So, to increase the use of AI in different industry sectors, we’ve provided PaddlePaddle with a lot of low-threshold toolkits that are easier to use so it can be used by a wider community.”

AI engineers normally don’t know much about industry sectors and industry-sector experts don’t know much about AI. But PaddlePaddle’s easy-to-understand code comes with a wealth of learning materials and tools to help users. It scales easily and has a comprehensive set of APIs to address various needs.  .... ' 

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