Preferred Networks Deepens Collaboration with PyTorch Community

Preferred Networks Migrates its Deep Learning Research Platform to PyTorch

Preferred Networks releases version 6 of both the open source deep learning framework Chainer and the general-purpose matrix calculation library CuPy

Nihon Keizai Shimbun Best Awards at the Nikkei Superior Products and Services Awards 2018

Preferred Networks releases ChainerX, a C++ implementation of automatic differentiation of N-dimensional arrays, integrated into Chainer v6 (beta version) for higher computing performance

Preferred Networks releases version 5 of both the open source deep learning framework, Chainer and the general-purpose array calculation library, CuPy.

Preferred Networks wins second place in the Google AI Open Images – Object Detection Track, competed with 454 teams

Chainer awarded the Open Source Data Science Project Award Winner at ODSC East 2018

Preferred Networks released open source deep learning framework Chainer v4 and general-purpose array calculation library CuPy v4.

Preferred Networks achieved the world’s fastest training time in deep learning, completed training on ImageNet in 15 minutes,using the distributed learning package ChainerMN and a large-scale parallel computer

Preferred Networks released open source deep learning framework Chainer v3 and NVIDIA GPU array calculation library CuPy v2

Preferred Networks Launches one of Japan’s Most Powerful Private Sector Supercomputers