@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00229345,
 author = {Rémi, Coulom and Rémi, Coulom},
 book = {ゲームプログラミングワークショップ2023論文集},
 month = {Nov},
 note = {While training deep-learning neural networks often requires considerable amounts of computing power, inference is efficient, and can be run on small devices. Cell phones are a typical example, but they are still rather powerful. The research presented in this paper takes the challenge to the extreme by running a Go-playing convolutional neural network on the 6809 CPU, an 8-bit microprocessor launched by Motorola in 1978. The software was implemented on a Thomson MO5 microcomputer, and reached a playing strength on par with GNU Go., While training deep-learning neural networks often requires considerable amounts of computing power, inference is efficient, and can be run on small devices. Cell phones are a typical example, but they are still rather powerful. The research presented in this paper takes the challenge to the extreme by running a Go-playing convolutional neural network on the 6809 CPU, an 8-bit microprocessor launched by Motorola in 1978. The software was implemented on a Thomson MO5 microcomputer, and reached a playing strength on par with GNU Go.},
 pages = {66--69},
 publisher = {情報処理学会},
 title = {Playing Board Games with a Deep Convolutional Neural Network on the Motorola 6809 8-Bit Microprocessor},
 volume = {2023},
 year = {2023}
}