What AI Technologies Can You Apply To Your Own Research? -Advice from a Computer Scientist-

Kameda H

Published on: 2021-09-26

Abstract

Since about ten years ago, Artificial Intelligence (AI) technology has been affirmatively and successfully applied to a wide range of fields, for example, image recognition processing. Especially, Deep Learning technology gives many outcomes and impacts to our society. I also adopt the AI algorithm GAN (Generative Adversarial Network, 2014) to build a new iPSC-derived cancer stem cells detecting system [1-3].?But in the field of Artificial Intelligent research there are still many other interesting technologies with much amount of potential for you to succeed. For example, AIs of Natural Language Processing (NLP), i.e., 1) Information Retrieval for web pages, patent document, and answers to questions, 2) Document Clustering including mail filtering, and recommendation, 3) Extraction for keywords, genre-oriented expressions, and relationship, and 4) Transformation including translation, summarizing, text production, dialogue production, and so on. Nowadays, among them, two attractive NLP AI technologies have emerged; Bert (Bidirectional Encoder Representations from Transformers, 2018) and GTP (GTP-2, 2019 and GTP-3, 2020) [4-6]. Bert is proposed by Google based on a new deep learning technology “Transformer,” which processes natural language text by far more accurately than previous AIs. GPT-2 and GPT-3 are also the same kind of powerful AIs and freely available, which are proposed by OpenAI group. With these AIs, you may build many kinds of useful tools for your research at a relatively low cost, for example, to classify document, to extract key knowledge, to translate, and so on. But deep learning AIs have some weak points. One of them is that AI cannot analyze and explain causality. That is to say, AI cannot tell us what a cause of the results is nor on what ground AI made such a decision. AI system is just a black box, i.e., we pay attention only to input and output. As you’d know, even in statistics there have not yet been any theory of causality. But scientists like you are strongly interested in causality.