AlexNet, the AI model that started it all, released in source code form - for all to download

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There are many stories of how artificial intelligence came to take over the world, but one of the most important developments is the emergence in 2012 of AlexNet, a neural network that, for the first time, demonstrated a huge jump in a computer's ability to recognize images.

Thursday, the Computer History Museum (CHM), in collaboration with Google, released for the first time the AlexNet source code written by University of Toronto graduate student Alex Krizhevsky, placing it on GitHub for all to peruse and download.

"CHM is proud to present the source code to the 2012 version of Alex Krizhevsky, Ilya Sutskever, and Geoffery Hinton's AlexNet, which transformed the field of artificial intelligence," write the Museum organizers in the readme file on GitHub.

Krizhevsky's creation would lead to a flood of innovation in the ensuing years, and tons of capital, based on proof that with sufficient data and computing, neural networks could achieve breakthroughs previously viewed as mainly theoretical. 

The code, which weighs in at a scant 200KB in the source folder, combines Nvidia CUDA code, Python script, and a little bit of C++ to describe how to make a convolutional neural network parse and categorize image files.

The Museum's software historian, Hansen Hsu, spent five years negotiating with Google, which owns the rights to the source, to release the code, as he describes in his essay about the legacy of AI and how AlexNet came to be.

 

 

https://www.zdnet.com/article/alexnet-the-ai-model-that-started-it-all-released-in-source-code-form-for-all-to-download/