人工智能，是指计算机系统具备从听说读写到搜索、推理、决策和回答问题等类人智能的能力。即， 感知、理解、决策的能力。

人工智能历史

过去经历了2次高潮与2次低谷

网络和云计算所支持的计算能力

基于大数据的机器学习的算法进步

阅读材料：

1. The rebirth of neural networks-ISCA-2010 rebirth_NN

四个层面

目标与功能分类

语音识别 机器视觉 智能问答

核心技术分类

特定算法 机器学习算法 深度神经网络

软件工具

TensorFlow / Caffe / Torch

底层硬件分类

可编程逻辑阵列 FPGA / 通用图形处理器 GPGPU / 通用处理器 CPU 群集

国际研究

Googel_Brain (Jeff Dean)

Facebook_AI-Research (Yann LeCun)

OpenAI (Ilya Sutskever)

机器学习

Machine Learning

scikit-learn

1. Jordan, M. I., and T. M. Mitchell. "Machine learning: Trends, perspectives, and prospects." Science 349, no. 6245 (2015): 255-260. Machine_learning_science_2015

卷积神经网络

Deep Neural Networks，简称DNN

Stanford Deep Learning tutorials DL_tutorials

入门导读

1. LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. "Deep learning." Nature 521(7553), pp:436-444, 2015. Deep_Learning_Nature
2. Jeff Dean, Large-Scale Deep Learning for Intelligent Computer Systems, WSDM 2016. WSDM_keynote
3. Jeffrey Dean et al. "Large scale distributed deep networks." Advances in Neural Information Processing Systems. 2012.
4. TensorFlow: A System for Large-Scale Machine Learning, OSDI 2016. TensorFlow_OSDI2016_paper TensorFlow_paper

深度学习工具

谷歌

TensorFlow

Google_TensorFlow_whitepaper

微软

CNTK_Microsfot

CNTK

百度

dmlc_mxnet

基于深度学习的机器感知

语音识别

语音识别（Automatic Speech Recognition），简称ASR

Google Speech

1. Google Speech Processing from Mobile to Farfield, CHiME 2016. Google_Speech_Processing

Long short term memory neural network (LSTM)

1. Long short term memory neural computation, Neural computation 9 (8), 1735-1780, 1997. LSTM

Connectionist temporal classification (CTC)

1. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks, ICML 2006.

计算机视觉

计算机视觉（Computer Vision），简称 CV

• Object Detection

R-CNN (Region-based Convolutional Network method)

1. Region based convolutional networks for accurate object detection and segmentation. TPAMI, 2015.
2. Rich feature hierarchies for accurate object detection and semantic segmentation, CVPR 2014.

Fast R-CNN (Fast Region-based Convolutional Network method)

1. Fast R-CNN, ICCV 2015.

Faster R-CNN (Faster Region-based Convolutional Network method)

1. Faster R-CNN Towards real-time object detection with region proposal networks, NIPS, 2015.

[fast-rcnn https://github.com/rbgirshick/fast-rcnn]

自然语言理解

自然语言理解（Natural Language Processing），简称NLP

智能问答

整合语音识别ASR，计算机视觉CV和自然语言处理NLP的问答系统QA。

实验室探究课-智能问答与智能系统