Bard is a conversational AI developed by Google that uses machine learning and natural language processing techniques to generate human-like text responses to various prompts. The model is designed to mimic the style and structure of human writing. In order to do so, Bard was trained on a massive text-based data set and uses a deep neural network architecture, called transformers, to learn patterns in language, understand the context of the input text and generate appropriate output.
Bard vs. ChatGPT: What’s the Difference?
Bard and ChatGPT are both large language models developed using deep neural network architectures and trained on massive amounts of text data. Google developed Bard while OpenAI developed ChatGPT. Both models can generate human-like text responses to a wide range of prompts and tasks, including conversational chat, creative writing and more.
What Does Bard Do?
Bard is capable of generating contextually correct responses on a wide variety of topics including science, math, history, literature and religion. One of Bard’s features is its ability to engage in multi-turn conversations wherein the AI can maintain a consistent topic and persona across multiple exchanges with a human user. This makes Bard particularly useful for applications like chatbots and virtual assistants.
Bard’s ability to generate creative writing also has potential for website content generation or social media posts, thereby freeing up time for content creators to focus on other high-level tasks. Furthermore, we can use Bard as a tool for language learners to practice writing in a specific language because Bard can generate output in multiple languages and styles.
How Does Bard Work?
At a high level, Bard is a deep neural network that analyzes and understands patterns in a large data set of text. Then, Bard generates new, original text output based on the previous analysis. Specifically, Bard is based on a neural network architecture called transformers. This architecture of neural networks is relatively new and was introduced in a 2017 research paper “Attention Is All You Need.” Transformers are particularly well-suited for natural language processing (NLP) tasks.
Transformers comprise a series of layers that hierarchically process the input text. Each layer builds on the previous one to extract increasingly complex information about the text. Bard first receives a prompt (or seed text) as input to generate text. The transformer’s initial layers process the input text and extract information about the text’s syntax and structure. The transformer then uses this information to generate a probability distribution over possible words or phrases that could follow the input text. To generate a response, Bard selects the most likely words or phrases from this distribution.
The distribution was determined before the conversation ever took place during Bard’s training process. Bard was trained on a massive amount of text data from a variety of different sources like books, websites and other textual materials. Bard’s training process involved a technique called unsupervised learning. When using unsupervised learning techniques, we feed large amounts of text data into a model without providing explicit labels or targets.
When the transformer model receives this text, it learns the statistical patterns and relationships between words and phrases in the text. This process allows Bard to generate coherent and contextually appropriate responses to a wide range of prompts.
In addition to unsupervised learning, Bard was also fine-tuned on specific tasks using supervised learning techniques. For example, Bard trained on a large data set of conversation transcripts to improve its ability to engage in natural language conversations with users.
Applications of Bard
Content Generation
We can use Bard to automate content generation for websites, social media accounts and other online platforms. This can help businesses and individuals save time and resources while maintaining a consistent, high-quality content stream.
Creative Writing
Bard is designed to generate creative writing like poetry, short stories and articles. This makes Bard an ideal tool for those experiencing writer’s block, authors who want to experiment with new writing styles or topics or those looking to optimize their writing processes.
Marketing and Advertising
Bard can help businesses generate creative and engaging marketing and advertising copy like taglines, slogans, marketing emails and product descriptions. These practices can help businesses attract and retain customers by quickly and efficiently creating a strong brand identity.
Education
We can use Bard in educational settings to teach students about creative writing, literature and language. Teachers can use Bard to generate writing prompts, create examples of different writing styles and structures, and provide feedback on student writing. Additionally, we can use Bard as a virtual tutor or mentor to help students with specific questions or challenges related to STEM subjects. The model could provide explanations, examples and feedback in real-time. Bard can also adjust its approach to the student’s level of understanding.
Bard vs. ChatGPT: Which Is Better?
Bard and ChatGPT have similar functions but they also have specific strengths that may make them suitable for different applications.
Language Models
Both Bard and ChatGPT use deep neural networks (specifically transformers) as natural language models. However, while Bard uses Google’s internal LaMDA (Language Model for Dialogue Applications), ChatGPT began using the GPT-3 language model and the current free version of ChatGPT still relies on the GPT-3.5 model. Paid users have access to the new and more optimized GPT-4 model. GPT-4 offers better performance in terms of understanding context, generating more coherent responses and providing more accurate information. Nevertheless, the free version of ChatGPT-3.5 remains powerful.
Training Data
The main difference between ChatGPT and Bard is the data source used to train the models. Bard continually draws information from the internet, so it will have the latest information and bases its responses to questions on more recent data. On the other hand, ChatGPT-3.5 and its newer version were trained on data that was available prior to 2021, which means ChatGPT has limited access to newer research and information. It’s not clear whether or not OpenAI plans to retrain the model on newer data in the near future.
Accuracy
Due to the fact that Bard is still in development and not available to the public, it is difficult to tell which AI will be more accurate in terms of providing facts and answers to questions and prompts.
Uses
ChatGPT is mainly used to answer questions and has also demonstrated an impressive ability to write creatively. Additionally, Microsoft integrated ChatGPT into its Bing search engine to allow users to ask the search engine direct questions instead of searching for keywords to find the best results.
In contrast, Google primarily created Bard to enhance Google’s search engine, but it’s also intended to function as an automated support tool for businesses that cannot afford (or don’t wish to hire) human support teams. In this instance, Bard could power chatbots that businesses use to provide automated support to their customers. Customers could type or speak their queries and Bard could provide helpful responses in natural language, thereby reducing the need for businesses to have large customer support teams. We can expect that Bard will be incorporated into the Chrome browser soon and Google will eventually allow third-party developers to use Bard as well.
