AI2018

Сравнение Google TPUv2 и Nvidia V100 на ResNet-50
AI accelerator
eSilicon deep learning ASIC in production qualification
Бенчмарк нового тензорного процессора Google для глубинного обучения
Специализированный ASIC от Google для машинного обучения в десятки раз быстрее GPU
В MIT разработали фотонный чип для глубокого обучения
Machine Learning Series
Visual Computing Group
source{d} tech talks — Machine Learning 2017
10 Alarming Predictions for Deep Learning in 2018
Эксперименты с malloc и нейронными сетями
LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks
HiPiler: Visual Exploration Of Large Genome Interaction Matrices With Interactive Small Multiples
Deep Learning Hardware Limbo
OpenAI
Inside OpenAI
Math Deep learning
Facebook and Microsoft introduce new open ecosystem for interchangeable AI frameworks

Inside AI Next-level computing powered by Intel AI Intel® Nervana™ Neural Network Processor

Intel® Nervana™ Neural Network Processor: Architecture Update Dec 06, 2017
AI News January 2018
Andrej Karpathy

MIT 6.S094: Deep Reinforcement Learning for Motion Planning

RI Seminar: Sergey Levine : Deep Robotic Learning

Tim Lillicrap — Data efficient deep reinforcement learning for continuous control
Intermediate Python
Tensors and Dynamic neural networks in Python with strong GPU acceleration http://pytorch.org
Tutorial for beginners https://github.com/GunhoChoi/Kind-PyTorch-Tutorial
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
PyTorch documentation
Transfering a model from PyTorch to Caffe2 and Mobile using ONNX
ONNX is a new open ecosystem for interchangeable AI models.
Open Neural Network Exchange https://onnx.ai/
Intermediate Python Docs
K-Means Clustering in Python
In Depth: k-Means Clustering
K-means Clustering in Python
Clustering With K-Means in Python
Unsupervised Machine Learning: Flat Clustering K-Means clusternig example with Python and Scikit-learn
ST at CES 2018 — Deep Learning on STM32


Configuring Marlin 1.1