The Era of Generative AI: ChatGPT vs. Bard

ChatGPT vs Bard

Generative AI has become increasingly popular because of its potential to generate original content and boost human creativity in areas ranging from images and text to music and even films. Deep learning and natural language processing advances have allowed generative AI models to create content that is frequently impossible to differentiate from human-created content.

The two most trending generative AI tools are ChatGPT and Bard. Launched a couple of weeks ago, ChatGPT bought forth a new revolution in the field of artificial intelligence and gained over 1 million users within 5 days.

To embrace the revolution, Google introduced Bard, which will be available for public use within a few weeks.
Let’s dive in to learn more about both leading generative AI tools and how they are different.

What is ChatGPT?


OpenAI created the ChatGPT AI language model. It is a subset of the Generative Pre-trained Transformer, or GPT line of language models, that are built with deep neural networks and trained on massive volumes of text data.

ChatGPT’s primary objective is to produce human-like prose in response to a specific prompt or query. It understands and responds to natural language input, which makes it suitable for a variety of applications including chatbots, customer support, and personal assistants.

ChatGPT has been trained on a huge corpus of text data ranging from books and news articles to forums and social media posts.  As a result, it can produce text that is cohesive, relevant, and contextually suitable.

GPT-2 and GPT-3 are two versions of GPT made accessible to the public by OpenAI. GPT-3 is the model’s most recent and powerful version, and it has been widely employed in a number of applications such as chatbots, content production, and language translation.

The following are examples of popular AI-generated material for ChatGPT:

  • Social media posts
  • easy explanations of difficult topics
  • Summaries of podcasts, meetings, and transcripts
  • Written code
  • Translation
  • Drafts for emails
  • Blogs
  • product descriptions
  • Law briefs
  • Even Memes and Jokes

What is Bard?


Bard is Google’s AI generative tool that uses LaMDA, Google’s Language Model for Dialogue Applications to get responses from the internet. Through this linguistic approach, Bard provides more extensive information to queries than a standard Google search. LaMDA’s lighter and second version utilizes less computational resources, allowing it to expand for more individuals to use and offer feedback.

Bard is was rolled out on February 7th and currently in beta testing. It will be available to all users in a few weeks.

Like digital assistants Siri and Alexa, Bard’s main purpose is to obtain information in a concise answer rather than a search engine results page, but with hyperlinks for users to gather further information. Bard will also serve as a personal assistant, assisting with chores such as trip planning, discovering existing reservations, and meal preparation.

What are the Differences Between ChatGPT and Bard?

Although both Bard and ChatGPT are quite similar tools, there are some notable differences between them.

Bard vs ChatGPT


At their foundation, the qualities of these two bots are very similar. Both need you to enter a question or request, and if you do, an answer will be returned. You can then ask follow-up questions or make additional requests, and the bot will keep conversing with you.

Bard is an extended version of the search engine into which they have been integrated. They add more context to answers.

ChatGPT, on the other hand, may have a broader range of applications. When utilized via its interface on OpenAI’s site, the AI chatbot may generate content for news articles, fiction poems, blogs, product descriptions, etc.

ChatGPT can also support specific programming languages, enabling it to give the code needed to develop a simple website. It is not unlikely that Bard will be unable to manage such requests, but such features have yet to be shown.


Both Bard and ChatGPT provide free versions. ChatGPT is now available for a free experimental preview on OpenAI’s website, with a paid membership model dubbed ChatGPT Plus that costs $20 per month and grants customers priority access and quicker speeds. ChatGPT Plus is only available to individuals who have been approved by OpenAI, therefore you’ll need to join the waitlist.

Bard now only offers a free model, but you must be an authorized tester to use the AI chatbot. Google revealed that some AI-based capabilities have been incorporated into products such as Lens and Maps, but Bard remains unavailable to the public. According to Google, public accessibility to Bard will be disclosed in the following weeks.


Google and OpenAI both acknowledge that Bard and ChatGPT can deliver false or improper information.

This is largely due to the way these chatbots operate. They use language models — LaMDA for Bard and GPT-3.5 for ChatGPT that require massive quantities of information to work. In the case of GPT and LaMDA, much of this information is obtained through the internet, and in the case of GPT-3.5, only until 2021, after Open AI discontinued training its language model. 

Bing’s version of GPT is more up-to-date since, like Bard AI, it draws relevant information from the internet.

There are certain drawbacks to this training, such as the fact that the data it pulls may be erroneous or prejudiced, and the bot is not necessarily trained to realize this. Chatbots are simply trained to deliver outputs connected with inputs; they cannot assess whether or not the information provided is correct or if the answer provided is free of inherent biases.


Open AI, Google, and Microsoft all want their chatbots to be integrated into their own ecosystems as soon as possible. ChatGPT is already available in three Microsoft products: Bing, Edge, and Teams.

Microsoft Teams Premium has been available for a while and includes features like AI-generated chapters and automated meeting notes to help you browse through meeting recordings more easily, and other features, all driven through the same GPT-3.5 language model as ChatGPT. It costs $10 per month per user, however, businesses may presently obtain it for $7 per month.

Microsoft has recently introduced the new Bing, an enhanced version of the Bing search engine driven by GPT-3.5. ChatGPT will be incorporated into the Opera browser in the near future.

Google’s Bard will be included in the search, although Google Search. Users will be able to search using the AI-powered chatbot, similar to Bing, rather than the usual search box. Google has also integrated AI-based technologies into Maps and Lens, albeit they are not exclusively Google Bard integrations.

However, Google has announced that third-party developers will be able to use Bard, thus it will be fascinating to observe what companies come up with. Similarly, OpenAI grants access to GPT-powered capabilities to certain firms, while only Microsoft has the rights to the source code from outside OpenAI.

Citing Sources

When it comes to the employment of generative AI tools like Bard or ChatGPT, plagiarism is a major source of concern. To function, the AI language models that run the chatbots must be developed on existing knowledge sets, which involves feeding them massive amounts of content provided by third parties.

ChatGPT, on the other hand, does not cite the generated data. When properly prompted, it can offer sources, although this is not the default setting. As a result, you must exercise extreme caution when utilizing the chatbot or risk accidentally stealing intellectual property.

Bard also does not automatically offer references for its responses.

However, Bing’s latest GPT-powered bot cites its sources. It uses annotations to cite the site from which the material was gathered, but you’ll have to press the links for further information.

A Third in the Running: ERNIE Bot

Baidu, also known as China’s Google, has revealed that it is experimenting with its own ChatGPT-style bot named Ernie Bot internally. The bot, which will be available next month, is based on its Large language models (LLMs), ERNIE, or ‘Enhanced Representation via Knowledge Integration,’ which was published in 2019.

ERNIE, a bilingual model that is anticipated to understand both Chinese and English, is capable of performing a variety of tasks like language generation and comprehension and text-to-image generation. Ernie Bot will be based on ERNIE 3.0 Titan, a language model with over 260 billion parameters, which is 50 percent more than ChatGPT.

ERNIE has a succession of advanced LLMs that can do a range of activities, and while language generation is provided by ERNIE 3.0 Titan, text-to-image generation is provided by ERNIE-ViLG.

Other Generative AI Alternatives

Following ChatGPT’s introduction into the market, prominent tech companies entered the fray by launching their generative AI tools. Jasper AI, ChatSonic, Wordtune, and OpenAssistant, are some startups embarking on their own initiatives.

The future of artificial intelligence in marketing is changing and adapting as swiftly as it began, with multiple uses besides content generation including email optimization, customer service, social media posts, and product suggestions.

What Does the Future of Generative AI Looks Like?

What Does the Future of Generative AI Looks Like?

The potential of generative AI appears bright, with numerous interesting possibilities regarding how this technology may expand and advance in the next years. Listed below are some possible sites for growth:

Ethical and societal repercussions

As generative AI advances in capability and sophistication, it will pose new social and ethical concerns concerning the use and exploitation of simulated data and media. Researchers and policymakers must collaborate to guarantee that all these technologies are used responsibly and fairly.

More Control and Modification over Generated Outputs

One limitation of existing generative models is that they frequently lacked fine-grained command over the output they produce. Researchers are investigating new methods for altering and fine-tuning such models in order to create more particular and tailored outcomes. This could lead to new applications in industries such as product design, architecture, and fashion, where the capacity to swiftly and correctly develop original designs could be incredibly beneficial.

Multimodal generative models

Another prominent field of research is the creation of generative models capable of producing outputs in numerous modalities like audio, text, images, etc. These models have the potential to enable new types of human-computer interaction as well as new methods of expressing and producing complex, multi-modal data.

Advanced and more realistic generative models

As processing power grows and researchers advance in constructing more complicated and effective neural network designs, generative models are anticipated to become more complex and capable of generating more compelling and realistic outputs. This could open up new possibilities in domains such as literature, music, and art, music, and more practical applications such as generating information for teaching other AI systems.

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