The introduction of AI or artificial intelligence has proven to be one of the most revolutionary transitions to human’s digital existence. From cutting off human efforts to complementing essential services like healthcare or education, the contribution of AI is huge.
Though the concept of AI is nothing new, one of the most recent and hyped AI trends that have simplified human existence in yet another way is the launch of “large language model-based chatbots.”
Launched in November 2022, OpenAI ChatGPT gathered all the online attention reaching out to 100 million active users in two months. Besides, the early build-up that came with Google Bard constantly kept people engaged long before its launch in March 2023, making people wonder what extra it had to offer after the success of ChatGPT.
On the other hand, there were some ups and downs that both OpenAI and Google had to face with the launch of their AI-powered large language model-based chatbots. While it was the premium version of ChatGPT called GPT4 that made the hesitation amongst users, the rough launch of Bard delivering inaccurate information on James Webb Space Telescope (JWST) became the reason for concern for the public.
In this article, we will aim to underline all the details surrounding ChatGPT and Google Bard while highlighting the primary differences, the use cases, and other important information.
Let’s dive in!
Decoding OpenAI ChatGPT
With GPT defining Generative Pre-trained transformer, ChatGPT is an AI-powered bot that runs a conversational dialogue on user queries with the help of machine learning. As per Open AI’s CEO Sam Altman, the tool managed to reach a user base of 1 million within the first five days of its launch. Made with the objective to complement worker productivity and costs for the white-collar industry, it gained some solid momentum reaching 100 million users by January 2023.
Trained on data before September 2021, GPT 3.5 or the standard version of Chat GPT works by identifying patterns from the human-created text available on the Internet. Though the recent launch or the premium version called GPT-4 too runs on the same data, it possesses better alignment allowing more truthful yet less offensive outputs considering the intention of the user query.
However, ChatGPT holds some amazing writing capabilities allowing users to work on written code, product descriptions, crafting blogs, drafting emails, and summarizing transcripts. Besides, it holds the capacity to simplify complex information to understandable data and can even assist users with translations, jokes, memes, and social media posts.
Besides, another significant concern that bothered mainly the university professors and teachers was students using ChatGPT for writing assignments. To overcome the problem, OpenAI launched an AI text classifier, a free tool to allow the detection of AI-generated content pieces.
Digging Into Google Bard
Just like ChatGPT, Google Bard is another AI-powered chatbot that brings the best of NLP (Natural Language Processing) and Machine Learning technology. However, it draws its response from the Internet.
Earlier, all the dialogue applications done on Bard ran on LaMDA, but then Google moved it all to the next-generation language model called PaLM 2 or Pathways Language Model. The upgrade allowed conversations and outputs with improved logic and reasoning with greater common sense.
Besides, the new language model was claimed to be faster than the older version as it showcased more detailed answering to queries compared to typical results shown on Google SERPs (Search Engine Result Pages). And therefore, Bard focused on generating results that contain answers in the simplest form while providing links to the users for gathering relevant information.
Tracing the DNA of Google Assistant and Alexa, Bard held the capability to allow users to work on booking vacations, making reservations, and even doing the tasks like meal planning. Moreover, it runs on conversational language and is made public to allow users from more than 180 countries to streamline their routines in three primary languages, i.e., English, Korean, and Japanese.
ChatGPT and Bard: The Key Differences
Even though ChatGPT and Bard are both AI-based language models, users that have worked with both platforms believe that ChatGPT works as a better writer while Bard is good for research.
On top of that, Microsoft announced that ChatGPT will be available as an integration to complement large companies looking to create their own custom chatbots. And therefore, the AI-powered search functions are likely to be reflected in the Bing search engine and Edge browser. However, nothing has been announced or planned from Google’s end on launching AI chatbot functionality to its browsers.
Another interesting difference that sets Google Bard apart from ChatGPT is GPT’s training data from September 2021. On the other hand, Bard uses real-time data from the most recent research as it fetches all the information from the search engine itself.
Apart from these, there are certain technical differences between both that can be described as:
Architecture and Training Data:
- ChatGPT: ChatGPT is based on the GPT-3.5 architecture developed by OpenAI. It is a large-scale language model trained on a diverse dataset from the Internet.
- Bard: Bard is an AI language model developed by EleutherAI. It is based on the GPT-3 architecture and was trained using a different dataset and possibly other model enhancements or modifications.
Developer and Licensing:
- ChatGPT: ChatGPT was developed by OpenAI. As of September 2021, ChatGPT was made available to the public through an API and had free access as well as a paid subscription plan.
- Bard: Bard was developed by EleutherAI, a community-led initiative focused on open-source AI research. They work on large-scale, decentralized, and accessible AI models. EleutherAI’s model may have different licensing and availability policies compared to ChatGPT.
Model Size and Parameters:
- ChatGPT: GPT-3.5, which powers ChatGPT, has 175 billion parameters at the time of release making it one of the largest language models.
- Bard: The specifics of Bard’s model size and parameters were not mentioned in the available information up to September 2021. It’s possible that it was based on GPT-3 or another architecture, but details might have been updated or changed since then.
Use Cases and Applications:
- ChatGPT: As its name suggests, ChatGPT is designed for conversational interactions. It can be used for chatbots, content generation, answering questions, language translation, and more.
- Bard: The specific use cases and applications of Bard were not well-documented as of September 2021. However, it is likely that Bard, being a language model, could be used for similar tasks to other GPT-based models, depending on its capabilities.
Community and Development Approach:
- ChatGPT: OpenAI has its own research team and resources dedicated to the development of ChatGPT, though it actively seeks feedback from users and the wider community to improve the model.
- Bard: EleutherAI is a community-driven initiative, and its models and research are developed collaboratively by contributors from around the world. The approach emphasizes open-source principles and community involvement.
Using ChatGPT & Bard For Quality Assurance: A Perspective
GPT (Generative Pre-trained Transformer) and BARD (Benchmark for AI in Robotic Defect detection) have a lot of potential for transforming the Quality Assurance (QA) processes. GPT, with its language generation capabilities can be used for automated test case generation which can significantly reduce manual efforts and speed up the testing cycles. Moreover, providing clear and well-defined requirements, GPT can be used to create relevant test cases and gain better test coverage.
On the other hand, BARD could complement GPT by providing a comprehensive dataset for robotic defect detection. It can facilitate training and provide evaluating AI models to detect flaws in manufacturing processes, ensuring that the end products meet high-quality standards. Also, BARD’s annotated dataset includes various defect types, making AI models robust and accurate in identifying defects, reducing false positives and negatives.
Therefore, Integrating ChatGPT and BARD into QA could empower industries to achieve higher QA efficiency with minimum human errors and enhanced product reliability. More importantly, the AI-driven QA process leads to faster time-to-market, reduced operational costs, and improved customer satisfaction. Besides, it is crucial to continuously refine and validate the AI models to adapt to evolving production scenarios and maintain the highest QA standards.
Making A Choice: Which Is Better?
Though the Internet is flooded with finding the best of all, it is necessary to understand that both models are running in their early training phase. If you are looking for summarized answers, ChatGPT is the key. In case you are looking for more relevant information, you can always rely on Bard. Thus, users working on anything from writeups to marketing or quality assurance solutions need to understand their requirements and all the related pros and cons.
Talking about Bard, it offers a friendly interface that complements research and can even help you summarize web pages or aid complicated tasks like robotic defect detection. However, it lacks the functionality of tracking past requests and is prone to inaccurate results. On top of that, it offers no plugins or integration options to the users with reduced reliability.
On the other hand, those using ChatGPT tend to enjoy better writing with access to all the past conversations and ease of sharing the response with others. Above all, it can be easily integrated through plugins with popular applications and platforms. But like any other tool, it also contains its own limitations, like copying/pasting an article for summary, difficulty scanning the output, checking for all the incorrect information, and a premium to pay for using the advanced versions of the tool.
Thus, the use of any of these tools entirely depends on the purpose and intent of the user. But to sum it all up with all the other tools available in the market, it can be said that using these tools could make way for an all-new era of customer service with dynamic email optimization and user-focused social media posts.
Also Read: Benefits Of AI In Scientific Research