Battle of AI Bots: ChatGPT versus Bing Chat

The market for generative AI is predicted to reach $188.62 billion by 2032, up from $8.65 billion in 2022, at a CAGR of 36.10. Major IT corporations and startups have invested billions of dollars in Generative AI models over the last decade. In 2021, OpenAI's ChatGPT was the most popular generative AI model on the market, with over 100 million users in the first two months of operation.
Microsoft announced the debut of their own chatbot on January 7, 2023. The GPT-4 language model serves as the foundation for the new model (but with a twist). Unlike ChatGPT's GPT-3.5 model, which can only access information previous to 2021, Bing Chat has internet connectivity, allowing it to deliver more up-to-date information.
Yet that's not the end of their disputes. This article will assess the language models, highlighting how they function and their significant distinctions.

What exactly is ChatGPT?

ChatGPT is a natural language processing model driven by AI that generates human-like text. The model is built on the transformer architecture and was trained using enormous amounts of internet data. This allows it to understand natural language, respond in human-like ways, and execute a wide range of language processing tasks such as language translation, summarization, question answering, and text completion.
OpenAI, the startup behind DALL-E 2, one of the most prominent artificial AI art producers, built the model.

What about Bing Chat?

Bing Chat is a Microsoft Bing search engine and GPT-4 integration. Users may engage with the search engine using natural language thanks to the chatbot. This implies that users may ask inquiries or make requests in a conversational tone instead of inputting keywords and search queries.
According to Microsoft, the chatbot's next-generation language model (GPT-4) is quicker, more accurate, and has greater language processing capabilities than GPT-3.5. It's also the only method to get free access to OpenAI's most recent release, GPT-4.
Users are now limited to six chat turns every session, for a total of 120 talks per day.

Is Bing AI superior than ChatGPT?

Bing AI and GPT have gotten a lot of attention as two of the most popular generative AI models on the market, with consumers and industry professionals trying to find out which is the best.
Although they both use language models from the GPT series to create output, the chatbots differ significantly, making them uniquely appropriate for certain applications. This implies that, while Bing AI is often criticized for being superior to its equivalent, GPT-3.5 may be more suited to specific applications than Bing's chatbot.

Bing Chat vs. ChatGPT: Key distinctions

Here's a side-by-side comparison of the two chatbots to help you understand their applicability and operational superiority in various applications:

App compatibility and device compatibility

Both chatbots have advantages and disadvantages in terms of interoperability with various apps and devices. GPT-3.5, for example, includes an API that allows for simple integration with a variety of platforms and applications. It also includes a web version, which allows users to engage with the chatbot without installing any other software.
The paradigm also works with a variety of programming languages, including Python, Javascript, Java, and C++. This allows it to be linked into a variety of systems such as Facebook Messenger, Whatsapp, and Slack. It is also compatible with both Android and iOS smartphones.
The Bing AI Chatbot, on the other hand, was created primarily as a search engine. As a result, developers incorporated it into a variety of Microsoft products that have a search capability, such as Windows' Cortana and Office 365. Bing AI Chat, like GPT-3.5, comes with an API that allows for easy access and integration with multiple systems. It also works with a variety of programming languages.

Chat design

Both chatbots have an engaging and simple user experience that allows you to communicate with them and receive quick responses. Nevertheless, the architecture, overall layout, and front-end design of the chatbots varies.
GPT-3.5, which is built on a transformer architecture, employs deep learning to create human-like replies to user input. Bing Chat, on the other hand, provides outcomes in the form of support responses by combining machine learning and rule-based methodologies. In essence, both chatbots provide the same end goal but use a different method.
Bing Chat is a single page with a sizable user input area, and the responses are pushed to the bottom in the form of card buttons. The end result is an improved user experience for both entering text and receiving responses. You cannot retrieve previous chats unless you save them offline since whenever you close or refresh your browser, all sessions are automatically destroyed.
In contrast, GPT-3.5 has a multi-page, dark mode design that enables you to retrieve all prior conversations from the session. Every time you add a new line, the layout's tiny input area will automatically scroll higher. 


Many industry professionals evaluated the two chatbots' performance and efficacy in various benchmarks and datasets. The majority of GPT-3.5 testing focus on its language creation skills.
The chatbot performs admirably on a variety of language modeling benchmarks, including WikiText, LAMBADA, and Penn Treebank datasets. It also excels in conversational AI tasks such as the Wizard of Wikipedia datasets and Persona-Chat.
In contrast, the majority of Bing AI Chat experiments are largely focused on search-related tasks such as relevance rating and web page ranking. In terms of relevance and accuracy, the chatbot routinely surpasses major search engines such as Yahoo and Google. Although further testing are needed to compare the performance of the two chatbots, it is obvious that GPT-3.5 outperforms its rival in natural language processing and text production tasks. Similarly, Bing Chat outperforms other search-engine-related applications.


Despite their extensive capabilities and remarkable performance on a variety of tasks, both chatbots confront a number of obstacles and restrictions.
Take, for example, GPT-3.5, which, despite its remarkable performance in text production tasks, has the potential for prejudice and other ethical issues. These worries stem from the training data, which was already skewed by cultural preconceptions and stereotypes.
Similarly, Bing Chat has certain constraints, the most notable of which are transparency and accessibility. Because it is a proprietary model, all of its training and development data is not easily accessible to the general public. This makes evaluating and improving the model difficult for developers. Furthermore, its emphasis on search-related tasks may constrain its capacity to handle other natural language-related tasks.
Generative AI is transforming online searches and content production. ChatGPT and Bing Chat have shown that generative AI can be applied into a variety of platforms to simplify and improve people's interactions with computers.
Despite their many similarities and the fact that they both use GPT series language models, Bing AI chat and OpenAI's GPT-3.5 chatbot have significant variances that make them particularly appropriate for specific applications. The former is more suitable for online search applications, whilst the latter is better suited for text generating applications.
Our contestants at the Worldwide AI Hackathon are actively using language models to develop disruptive generative AI innovations so a successor (or plenty) of ChatGPT and Bing is probably in the making.

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