AI, BI & SI—Artificial, Biological and Statistical Intelligences
- 2024-06-24 (Mon.), 11:00 AM
- Auditorium, B1F, Institute of Statistical Science；The tea reception will be held at 10:40.
- Online live streaming through Cisco Webex will be available.
- Prof. Dennis K.J. Lin
- Department of Statistics, Purdue University
Abstract
Artificial Intelligence (AI) is clearly one of the hottest subjects these days. Basically, AI employs a huge number of inputs (training data), super-efficient computer power/memory, and smart algorithms to perform its intelligence. In contrast, Biological Intelligence (BI) is a natural intelligence that requires very little or even no input. This talk will first discuss the fundamental issue of input (training data) for AI. After all, not-so-informative inputs (even if they are huge) will result in a not-so-intelligent AI. Specifically, three issues will be discussed: (1) input bias, (2) data right vs. right data, and (3) sample vs. population. Finally, the importance of Statistical Intelligence (SI) will be introduced. SI is somehow in between AI and BI. It employs important sample data, solid theoretically proven statistical inference/models, and natural intelligence. In my view, AI will become more and more powerful in many senses, but it will never replace BI. After all, it is said that “the truth is stranger than fiction, because fiction must make sense.” The ultimate goal of this study is to find out “how can humans use AI, BI, and SI together to do things better.”
Please click here for participating the talk online.
Back
