Chat GPT VS. Other Language Models: Who Do You Think Wins?

The article conducts a comparative analysis of ChatGPT vs. other language models. The language models analyzed here include BERT, XLNet, PaLM 2, and Google Bard. ChatGPT was found to have more benefits.

Gurpreet Saini

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Chat GPT VS. Other Language Models: Who Do You Think Wins?

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Table of content:

What are Language Models?
ChatGPT vs. Other Language Models: BERT
ChatGPT vs. Other Language Models: XLNet
ChatGPT vs. Other Language Models: PaLM 2
ChatGPT vs. Other Language Models: Bard

Language models are a crucial aspect of Artificial Intelligence-based technologies. A number of language models are used for their language processing and Machine Learning techniques. ChatGPT comes with GPT3.5 and GPT4 Large Language Models (LLMs), which are trained to process language. This article will discuss the difference between ChatGPT vs. other language models and provide an in-depth analysis of how these language models contribute to making AI more powerful.

We will conduct a detailed comparison of ChatGPT vs. other language models. In this way, we will be able to see whether ChatGPT carries an evolved LLM or not. It will help in predicting the future of language models and AI.

What are Language Models?

A language model is a statistical tool that is required for assigning probabilities to a sequence of words in a language. These predictions are based on the large corpora of language data fed into the system. It helps in predicting the likelihood of the occurrence of the given word in a conversational context. In this way, language models can help generate nuanced responses matching human language.

There is a wide range of uses of language models, such as:

Text generation
Machine translation
Speech recognition
Text summarization

We'll explore more about language models and their functions in the succeeding sections.

ChatGPT vs. Other Language Models: BERT

Bidirectional Encoder Representations from Transformers (BERT) belong to the category of masked language models. It was launched in 2018 by researchers at Google. As the name suggests, it is based on the transformer architecture as it is composed of Transformer encoder layers.

The ChatGPT/BERT Difference

Functions	ChatGPT	BERT
Developer/Parent company	OpenAI, which is an AI research and development company.	Google
Dataset volume	The AI-based chatbot is trained on a dataset of 45TB of text from different sources. In this way, the sheer size of the ChatGPT dataset gives it an edge over BERT.	It is trained on a dataset of a 3.4 billion word text corpus.
Size	It has 1.5 billion parameters.	It has 340 million parameters.
Supported AI tools	Jasper, ChibiAI, WriterSonic, Simplified, Kafkai, Copysmith	Google Search Engine, Huggingface Transformer Library, Microsoft Azure Cognitive Services, and Google Natural Language API
Architecture	ChatGPT is an autoregressive model due to which it only considers the left context while making predictions.	It is a bidirectional Transformer model, which means it considers both right and left context while making predictions.
Functions	Due to its large dataset and size, it can perform Natural Language Processing (NLP) tasks such as summarisation, answering questions, sentiment analysis, and language translation.	It has comparatively limited functions, such as answering questions. It is not capable of offering translation and summarisation facilities.

From this, we learn that although BERT is capable of conducting bidirectional analysis, it lacks critical functionalities which are possible in ChatGPT.

ChatGPT vs. Other Language Models: XLNet

XLNet is an advanced language model, just like ChatGPT. It was developed by Google Research based on Transformer architecture. Similar to ChatGPT, XLNet uses an autoregressive approach to process language queries.

A difference between XLNet and other language models is that the former is capable of accounting for all permutations of the input sequence during training.

The ChatGPT/XLNet Difference

Let's explore the difference between ChatGPT vs. XLNet in detail:

Functions	ChatGPT	XLNet
Dataset	In terms of size, this sophisticated AI chatbot amounts to 45TB.	This language model is trained with more than 130GB of data of high-quality text.
Architecture	The AI-powered chatbot runs on Transformer architecture. It uses an autoregressive model which allows it to consider only the left context while making predictions.	It also operates on Transformer architecture as well. However, it captures bidirectional context and dependencies efficiently. As a result, it is capable of providing accurate responses to Natural Language Processing tasks.
Performance	There are some limitations as the autoregressive approach of pretraining is not as efficient as other traditional language models.	It provides a better performance due to denoising autocoding approach of pretraining.
Sequence length limit	It has a sequence length limit. Its context length is 32, 768 tokens.	There is no sequence length limit.

Based on this analysis, it can be seen that XLNet gives tough competition to ChatGPT. It overcomes the limitations which are seen in other traditional language models such as BERT.

Read more about AI: A Double-Edged Sword? Know The Advantages And Disadvantages Of AI

ChatGPT vs. Other Language Models: PaLM 2

The Pathways Language Model 2 (PaLM 2) is the latest language model introduced by Google. It is the successor of PaLM, a powerful language model which was used for a wide variety of applications. The state-of-the-art language model is capable of processing high-level language tasks, such as reasoning, coding, and supporting multilingual translation.

The ChatGPT/PaLM 2 Difference

Let's explore the difference between ChatGPT vs. PaLM 2 in detail:

Functions	ChatGPT	PaLM 2
Dataset size	The dataset size of ChatGPT is 45TB.	The PaLM 2 language model comprises a massive 540 billion parameters. Additionally, it has the largest TPU-based system configuration with more than 6000 chips.
Multilinguality	It is a multilingual chatbot. It uses Machine Learning techniques to understand, generate, and translate text in more than 50 languages.	It is trained on texts from multiple languages. It has training in more than 100 languages, which allows it to understand, generate, and translate texts. It also allows for studying and comprehending advanced linguistic features, such as riddles, poems, idioms, etc.
Features	ChatGPT can offer the following NLP services: text generation, text classification, question answering, machine translation, sentiment analysis, and Named Entity Recognition (NER).	PaLM 2 can do the following operations: Natural Language understanding, common-sense reasoning, in-context reading comprehension, question answering, code completion, semantic parsing, summarisation, logical inference chains, pattern recognition, and joke explanation.

Here we saw some of the crucial differences between ChatGPT and PaLM 2. It is difficult to determine which language model is better. Both showcase advanced features of language processing and Machine Learning abilities. The use and benefits of the particular language model depend on the purpose.

ChatGPT vs. Other Language Models: Bard

Bard is Google's latest contribution to the list of language models. Just like ChatGPT, it is also a conversational generative AI chatbot. Although it met with some criticism due to a wide range of glitches when it was launched, the subsequent improvements were made by the developers to overcome it.

The ChatGPT/Bard Difference

We have provided some basics differences between ChatGPT vs. Bard in detail:

Functions	ChatGPT	Bard
Accessibility	It is accessible through the website of OpenAI.	The users need a Google account to access Google Bard.
Architecture	It is based on generative AI technology known as Generative Pre-Trained Transformer (GPT).	Google Bard AI is based on Language Model for Dialogue Applications (LaMDA).
Data archives	Its responses are based on data till 2021.	Its responses are based on real-time information from Google Search.
Multilinguality	It is a multilingual chatbot that can support at least 50 languages. In this way, it can produce faster responses in human-like language.	It is also a multilingual AI system that can support 40 languages. It helps Bard create human-like responses.

Google Bard AI is a fairly new AI system, launched in the initial months of 2023. Hence, it is too early to determine whether it provides strong competition to ChatGPT or not.

Learn more about the difference between ChatGPT and Bard: Google Bard vs ChatGPT: Comparison Of Features & Uses Of The Competing Chatbots

We analyzed some of the popular language models for AI-based technologies. Each language model has some advantages and limitations. However, for those who want to use a free chatbot with easy access, then ChatGPT is a good option. It comes with a massive dataset which allows it to perform a wide range of language tasks.

Hope this article was enlightening. We will continue to provide more articles on ChatGPT and related AI-based technologies to help you grab endless opportunities.

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Edited by

Gurpreet Saini

Sr. Associate Content Writer

An avid reader and an ambitious traveller, I like to curate stories. The instinctive desire to explore the unchartered territories of the unknown and unseen inspires me to find wonder in the cosmos. I find solace in the embrace of nature, and hope to create an environment of peace wherever I go.