Intel AI Research is pushing the limits of artificial intelligence and computing at every level, from atomic physics to data-center orchestration. We make big bets and take a systems view of AI: our research spans foundational work in machine learning algorithms and computer architecture to applied research in computer vision, autonomous driving, and distributed learning systems.
On Training Flexible Robots using Deep Reinforcement Learning
Reinforcement Learning Coach is an an open source research framework for training and evaluating reinforcement learning (RL) agents that uses the processing power of multi-core CPUs to enable efficient training of RL agents.
Network compression can reduce the memory footprint of a neural network, increase its inference speed and save energy. Distiller provides a PyTorch environment for prototyping and analyzing compression algorithms, such as sparsity-inducing methods and low-precision arithmetic.
Natural Language Processing (NLP) Architect is an open-source Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding. It is intended to be a platform for future research and collaboration.