This is a demo of "LeNet 1", the first convolutional network that could recognize handwritten digits with good speed and accuracy.

It was developed between 1988 and 1993 in the Adaptive System Research Department, headed by Larry Jackel, at Bell Labs in Holmdel, NJ.

This "real time" demo shows ran on a DSP card sitting in a 486 PC with a video camera and frame grabber card. The DSP card had an AT&T DSP32C chip, which was the first 32-bit floating-point DSP and could reach an amazing 12.5 million multiply-accumulate operations per second.

The network was trained using the SN environment (a Lisp-based neural net simulator, the predecessor of Lush, itself a kind of ancestor to Torch7). We wrote a kind of "compiler" in SN that produced a self-contained piece of C code that could run the network. The network weights were array literals inside the C source code.

Shortly after this demo was put together, we started working with a development group and a product group at NCR (then a subsidiary of AT&T). NCR soon…

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