Who Wins The Battle Between ChatGPT VS. Other NLP Tools?

Natural Language Processing (NLP) has been a sought-after topic in research. Computer scientists have been working for years to make machines understand and use human-like language. The most recent AI-based chatbot, ChatGPT has taken NLP to a new level. In this article, we will talk about ChatGPT vs. other NLP tools.

What is NLP?

The discussion about ChatGPT vs. other NLP tools should begin with understanding what is NLP. It is primarily a field of computer science and Artificial Intelligence. The main focus of NLP is to make machines understand, analyze, and mimic human languages. The aim of making advancements in NLP is to narrow the gap between human-like responses and computer-generated responses.

There is a variety of applications of NLP. Some of the most crucial ones include spam detection, sentiment analysis, machine translation, content creation, etc. Due to this, NLP is becoming important in different fields, such as e-commerce, finance, healthcare, education, etc.

In the 21st century, you are already using NLP in some form or the other. For instance, virtual assistants like Siri and Alexa operate on NLP technology. They are enabled for comprehending human speech. Along with this, they are also trained for understanding the little nuances of a language, such as colloquialisms, idioms, metaphors, etc.

Tools for NLP

There is a wide range of sophisticated tools which are used for conducting NLP tasks. These tools make use of the theories and practices of linguistics. These theories are combined with models of computer science.

For instance, several traditional NLP tools are based on Python libraries. They contain tons of linguistic data which is processed and converted into human language and provides accurate answers in the human-like text.

Similarly, generative AI tools like ChatGPT operate on ChatGPT3.5 neural network architecture. As a result of this, it is capable of producing high-quality responses.

ChatGPT vs. IBM Watson

The analysis of ChatGPT vs. other NLP tools deserves a comparison between ChatGPT and IBM Watson. Let's read about the strengths and weaknesses of IBM Watson and see how it is different from ChatGPT.

IBM Watson is stored in IBM Cloud. It is a suit of several AI services. Among its various features, we have NLP tools that assist in extracting keywords, identifying categories, and analyzing the emotional tone in the text.

The major reason behind the popularity of IBM Watson is its versatility. It can be tailored to be used in different industries. In this way, you can use IBM Watson in the healthcare sector, finance sector, education sector, etc.

The ChatGPT/IBM Watson Difference

• Age: ChatGT is a new platform that was released in November 2022. On the other hand, IBM Watson is being used since 2010. Due to this, the latter is used by a huge number of organizations and institutions. Nearly, 70% of global banks use IBM Watson.
• Data Size: IBM Watson is also more comprehensive than ChatGPT. According to a rough estimate, IBM Watson can hold 36 PB (petabytes) of data. Contrastingly, the latest model of the chatbot, ChatGPT-4, only comprises 100 trillion parameters. Although it is five times larger than its previous version, ChatGPT-3, it is still a fraction of the size of IBM Watson. In this way, the IBM version holds more value in terms of use.
• Applications: Due to its huge size, IBM Watson is capable of performing more comprehensive functions. It is trained to undertake more complex NLP tasks. IBM Watson provides a better output for content generation, language translation, and technical document analysis. On the other hand, ChatGPT is still being trained for improving its NLP tools.
• Investment: Currently, ChatGPT is a free platform for NLP tools. However, if you want to use IBM Watson for NLP tasks, you may require huge investments and funds.

Who's the Winner?

In this way, it can be seen that IBM Watson can be useful for large organizations that can afford to invest heavily in NLP tools. Their income from the diverse portfolios helps them to be able to afford an expensive NLP tool like IBM Watson. However, if you are an independent user or a small organization, then ChatGPT is more useful.

ChatGPT vs. NLTK

The Natural Language Toolkit (NLTK) is yet another traditional NLP tool. Let's read about it and compare it with ChatGPT.

NLTK is a suite of programs and libraries for NLP for the English language. It is written in the programming language, Python. NLTK is a large corpus of libraries and archives of documents. Due to this, it is used by a wide range of professionals, independent researchers, and students.

NLTK manages to create such a large amount of database through community support. Apart from this, NLTK also comes with sample datasets, resources, and tutorials for language processing. As a result of this, NLTK is capable of supporting the following NLP operations:

• Lexical analysis
• Named-entity recognition
• Part-of-speech tagger
• n-gram and collocation
• tree model
• text chunker
• discourse representation

The ChatGPT/NLTK Difference

• Scope: The several operations allow this traditional NLP tool to be used in various fields, such as Artificial Intelligence (AI), cognitive science, information retrieval, linguistics, and Machine Learning models. Similarly, the NLP tools of ChatGPT can be used in different fields, such as medicine, financial analysis, education, etc. However, the latter does not offer refined results as compared to NLTK.
• Usage: NLTK is used widely. More than 32 universities in the USA use the NLP tools of NLTK. Apart from this, NLTK is taught as a course in universities across 25 countries. The toolkit garners this importance because it can support crucial NLP functions like tokenization, stemming, classification, tagging, semantic reasoning functionalities, and parsing. ChatGPT is still being trained to do these complex operations more accurately.
• Accessibility: ChatGPT is more accessible. You just need to enter simple, well-defined prompts. However, NLTK is a little difficult to use. Only professionals with the required knowledge will be able to use the NLP tools of NLTK.

Who's the Winner?

NLTK comes across as a more advanced NLP tool here. Thus, if you are looking for a better choice in the ChatGPT vs. other NLP tools difference, then the latter has more benefits.

ChatGPT vs. spaCy

The comparison of ChatGPT vs. other NLP tools deserves a discussion on spaCy. The traditional NLP tool of spaCy uses Python library to conduct high-level NLP tasks. On the other hand, ChatGPT is assisted by Generative Pre-trained Transformer (GPT) architecture. Let's see how this difference results in offering various NLP functions.

The ChatGPT/spaCy Difference

• Usage: ChatGPT is used for conversational applications. Although it does support NLP tasks, its ability to perform them with efficiency is restricted. Contrarily, spaCy is capable of supporting more advanced operations. Some of spaCy's NLP operations include part-of-speech tagging, tokenization, and entity recognition.
• Features: spaCy offers two main NLP services namely, text mining and APIs. On the other hand, the product features of ChatGPT in terms of NLP services are vast. If we talk about some of the NLP services offered by ChatGPT, they would include AI Ad copy generator, AI summaries, AI content generation, APIs, Natural Language Generation, and Neural Networks.
• Integration: spaCy can be integrated with other technologies, such as JavaScript, CustomGPT, AutoResponder, Facebook Messenger, etc. ChatGPT can also be integrated with all the technologies which are possible with spaCy.
• Deployment: Both ChatGPT and spaCy support similar deployment platforms, such as SaaS, Apple products, Windows, and Linux.

Who's the Winner?

These points show that there are various similarities between ChatGPT and spaCy. However, as far as NLP features are concerned, ChatGPT is superior.

ChatGPT vs. Gensim

Gensim is a Python library that is widely used for topic modeling. The process of topic modeling is conducted with the help of algorithms like Latent Dirichlet Allocation (LDA). Apart from this, it is also capable of indexing texts, navigating different documents, and recognizing text similarities.

The ChatGPT/Gensim Difference

• Unsupervised information extraction: Gensim is designed specifically for unsupervised text modeling. In this way, it can conduct NLP tasks like similarity retrieval, document indexing, and topic modeling. Gensim does that by integrating NLP-based data with Word2Vec.

On the other hand, ChatGPT is a powerful tool because it can also support unsupervised learning techniques. The chatbot is supported by a powerful language model to do the task. For instance, you can use a prompt in ChatGPT and retrieve an output/response. This response can then be used in Python. In this way, ChatGPT can be seen supporting unsupervised extraction.

• Peripheral Support: The potential applications of Gensim are Word2Vec, Document2Vec, TF-IDF vectorization, Latent Semantic Analysis (LSA), and Latent Dirichlet Allocation (LDA).

On the other hand, ChatGPT cannot provide support for TF-IDF vectorization. The feature which is used in NLP for text extraction is not available in ChatGPT. The users have to use another application or software to conduct TF-IDF vectorization if they are using ChatGPT. In this way, the ChatGPT-generated text can be used for clustering, classification, and information retrieval.

Although ChatGPT does not support TF-IDF vectorization, it provides LSA. The process of LSA in NLP involves recognizing relationships between words and phrases in a text. The identification of these variables takes place by examining patterns of use, document classification, text summarisation, and information retrieval. ChatGPT is designed to undertake these NLP-based tasks.

• Working with datasets: Both ChatGPT and Gensim can work with large datasets.
• Supporting Deep Learning: Both NLP tools are based on Deep Learning algorithms.

Who's the Winner?

The answer to which NLP tool is better lies in the purpose of the use. Those who need an NLP tool that supports TF-IDF vectorization, then they should go with Gensim. Otherwise, ChatGPT is capable of offering advanced-level NLP support.

Conclusion

In this article, we analyzed various Natural Language Processing tools. We conducted a comparative analysis of traditional NLP tools with ChatGPT. We could see there is no direct answer to which NLP tool is better. The traditional NLP tools were seen as capable of conducting more complex NLP tasks. It was because they had a larger dataset.

However, ChatGPT is also catching up. It is suited well for those who want to invest little funds in NLP technology. So far, it is available free of cost. Moreover, ChatGPT does not require much knowledge of computer science and AI. You can use simple prompts and use ChatGPT NLP tools.

Hope this article on ChatGPT vs. other NLP tools was informative. If you want to know more about ChatGPT chatbots, we have brought an entire series on them. These articles discuss ChatGPT's wide range of applications in different fields. So, whether you are a professional or a student, reading those articles will surely help you grab awesome opportunities.

Stay tuned to Unstop for more such interesting articles.

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