  Since the invention of computers, communication through natural language
(actual human language) has been a dream technology. However, natural language
is extremely difficult to mathematically formulate, making it difficult to
realize as an algorithm without considering programming. While there have been
numerous technological developments, one cannot say that any results allowing
free utilization have been achieved thus far. In the case of language learning
in humans, for instance when learning one's mother tongue or foreign language,
one must admit that this process is similar to the adage "practice makes
perfect" in principle, even though the learning method is significant up to a
point. Deep learning has played a central role in contemporary AI technology in
recent years. When applied to natural language processing (NLP), this produced
unprecedented results. Achievements exceeding the initial predictions have been
reported from the results of learning vast amounts of textual data using deep
learning. For instance, four arithmetic operations could be performed without
explicit learning, thereby enabling the explanation of complex images and the
generation of images from corresponding explanatory texts. It is an accurate
example of the learner embodying the concept of "practice makes perfect" by
using vast amounts of textual data. This report provides a technological
explanation of how cutting-edge NLP has made it possible to realize the
"practice makes perfect" principle. Additionally, examples of how this can be
applied to business are provided. We reported in June 2022 in Japanese on the
NLP movement from late 2021 to early 2022. We would like to summarize this as a
memorandum since this is just the initial movement leading to the current large
language models (LLMs).
