Evolution of Natural Language Processing Technology: Not Just Language Processing Towards General Purpose AI
Masahiro Yamamoto

TL;DR
This paper discusses the evolution of NLP technology from language processing to general-purpose AI, highlighting deep learning's role in achieving unprecedented results and practical applications.
Contribution
It provides a technological overview of recent NLP advancements, emphasizing how deep learning enables models to learn complex tasks without explicit programming.
Findings
Deep learning has enabled NLP models to perform arithmetic and image explanation tasks.
Large textual data training leads to models that embody the 'practice makes perfect' principle.
The paper summarizes recent NLP developments leading to large language models.
Abstract
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…
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Taxonomy
TopicsNatural Language Processing Techniques
