Google Bard (AI) and Linguistics - (7th Question)

 Google Bard (AI) and Linguistics - (7th Question)

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I put the same question asked to ChatGPT to Google Bard also . Both answered that question. It may be useful for the researchers who involve in these two fields - Linguistics and AI. You could compare the both answers - by ChatGPT and Google Bard to my same question.

N. Deiva Sundaram :

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If everything from Phonology to Pragmatics of natural languages could be handled by you by the statistical pattern studies using a huge data and probability, what is the necessity for linguistic science in language studies?

ChatGPT:

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Linguistic science, including fields like phonology, morphology, syntax, semantics, and pragmatics, plays a crucial role in language studies and natural language processing (NLP) for several reasons:

1. Deeper understanding of language: Linguistics helps us understand the fundamental principles and structures of human language. It provides insights into how languages are structured, how words are formed, how sentences are constructed, and how meaning is conveyed. This understanding is essential for developing accurate and comprehensive language models.

2. Rule-based analysis: Linguistic science allows for a rule-based analysis of language. While statistical patterns are useful, linguistic rules provide a systematic framework for analyzing language phenomena, identifying grammatical errors, and generating well-formed sentences. This can enhance the accuracy and coherence of language processing systems.

3. Ambiguity resolution: Natural languages often contain ambiguous sentences that can be interpreted in multiple ways. Linguistics helps in resolving such ambiguities by applying syntactic and semantic rules to determine the most likely interpretation. This is crucial for accurate language understanding and generation.

4. Language typology: Linguistic science studies the typological variations across languages. It helps identify language-specific features, variations in sentence structures, and semantic differences. This knowledge is valuable for developing language models that can handle diverse languages and language families.

5. Language acquisition: Linguistic research contributes to our understanding of how humans acquire language. This knowledge is useful for developing language learning systems and educational tools, as well as understanding language-related disorders.

While statistical pattern studies and AI language models have made significant advancements in language processing, linguistic science provides theoretical insights, systematic frameworks, and a deeper understanding of language that complement statistical approaches. It helps ensure more accurate, robust, and comprehensive language processing systems, benefiting applications ranging from machine translation and information retrieval to dialogue systems and language generation.

Google Bard:

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The necessity of linguistic science in language studies is still very important, even if statistical pattern studies using huge data and probability could handle everything from phonology to pragmatics of natural languages. Here are some reasons why:

Linguistics provides a theoretical framework for understanding language. Statistical pattern studies can tell us what patterns exist in language, but they cannot tell us why those patterns exist. Linguistics provides the theoretical framework for understanding the underlying principles of language, such as how sounds are organized into words, how words are combined into phrases and sentences, and how sentences are used to communicate meaning.

Linguistics helps us to understand the diversity of human languages. There are over 6,000 languages spoken in the world today, and each language has its own unique features. Statistical pattern studies can help us to identify the patterns that are common to all languages, but they cannot tell us why those patterns are different across languages. Linguistics helps us to understand the reasons for the diversity of human languages, and how this diversity has shaped the way we think and communicate.

Linguistics helps us to understand the relationship between language and thought. There is a growing body of evidence that suggests that language plays a significant role in shaping our thoughts and our understanding of the world. Statistical pattern studies cannot tell us how language and thought are related, but linguistics can provide us with the theoretical framework for understanding this relationship.

In short, while statistical pattern studies can be a valuable tool for understanding language, they cannot replace the insights that can be gained from linguistic science. Linguistics provides a theoretical framework for understanding language, helps us to understand the diversity of human languages, and helps us to understand the relationship between language and thought. These are all essential insights for anyone who wants to study or use language in any way.

In addition to the above, here are some other reasons why linguistic science is still important:

Linguistics helps us to understand the history of language. By studying the patterns of change in language over time, linguists can help us to understand how languages have evolved and how they are related to each other.

Linguistics helps us to develop new technologies for language processing. Statistical pattern studies can be used to develop new technologies for speech recognition, machine translation, and other language-related applications. However, linguistic insights are essential for ensuring that these technologies are accurate and effective.

Linguistics helps us to teach language more effectively. By understanding the principles of language, linguists can develop more effective methods for teaching language to both children and adults.

In conclusion, the necessity of linguistic science in language studies is still very important, even if statistical pattern studies using huge data and probability could handle everything from phonology to pragmatics of natural languages. Linguistic science provides a theoretical framework for understanding language, helps us to understand the diversity of human languages, helps us to understand the relationship between language and thought, and helps us to develop new technologies for language processing and teaching.