Prof. Thomas Canhao Xu, Soochow University, China
Research Area: Artificial intelligence, Algorithm analysis and design, Internet-of-things, Medical imaging, Hardware/software co-design
Title: Hardware/Software Codesign of Efficient Deep Learning Algorithms
The efficiency of machine learning and deep learning algorithms is more and more important nowadays. Improving accuracy without considering model efficiency is undesirable. Deep learning algorithms on embedded devices, such as educational devices and/or educational robots, often have demanding real-time requirements. For example, object recognition systems based on cameras usually require a latency of hundreds of milliseconds to respond to events in a timely manner. Commercial embedded devices sometimes offload the machine learning algorithms to the cloud. However, network connection quality and speed are becoming another challenging constraint for these devices. Another choice is to implement a high efficient deep learning algorithm on the embedded device, which isn’t affected by the internet connection. Enabling deep learning on the embedded device is difficult. The main characteristic of embedded devices is low power, which usually means the limited computational capability of the processor and limited size of the memory. From the perspective of software/hardware codesign, in order to speed up the processing speed of deep learning and image recognition algorithms, optimizations at both the algorithmic and hardware-level are required.
Prof. Tong Li, Shenzhen University/ College of Management, Institute of Mobile Internet Things Industrialization, China
Research Area: Intelligent Decision Support System, Business Intelligence, Data Mining etc.
Title：Is Artificial General Intelligence Coming?
AGI, or artificial general intelligence, is mainly focused on the development of machines that think like people and engage in multiple uses like people. This word comes from AI. However, as the mainstream AI research is gradually moving towards the intelligence of a certain field or a certain task (such as machine vision, speech input, etc.), in order to distinguish them, general is added. It is also defined as: the AI system that matches or exceeds humans at almost all (such as at least 95%) economically valuable work.
This talk will briefly describe the landmark events of AI research and development, sort out several AI research and development paths, discuss the possibility of the arrival of AGI, and put forward some views on the future research trend of AI.