We present Kaolin, a PyTorch library aiming to accelerate 3D deep learning research.
Deep Neural Network (DNN) is powerful but computationally expensive and memory intensive, thus impeding its practical usage on resource-constrained front-end devices.
We propose Asymmetric Convolution Block (ACB), an architecture-neutral structure as a CNN building block, which uses 1D asymmetric convolutions to strengthen the square convolution kernels.
To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems, as well as comparisons with humans.
Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets.
SOTA for Language Modelling on Text8 (using extra training data)
Face detection and alignment in unconstrained environment is always deployed on edge devices which have limited memory storage and low computing power.
We present a large, tunable neural conversational response generation model, DialoGPT (dialogue generative pre-trained transformer).