Difference in Chat GPT Vs Google Bard
The AI chatbot market has a new entrant with Google’s Bard. It puts Open AI’s Chat GPT directly in competition.
Bard is a conversational AI tool that lets users ask a question or make a request and receive a human-like response. It uses a language model that draws information from the internet, providing more details to the questions asked.
1. Data Source
When it comes to data sources, the key difference between Google Bard and Chat GPT is that Bard has access to a lot more information than Chat GPT. This means it can provide more accurate information to users, as well as be integrated with Google’s search engine, giving it an edge over Chat GPT, which is supported by Microsoft.
Another difference between the two is that Bard has access to a wide variety of information, as opposed to Chat GPT which only has knowledge of events up to 2021. This can potentially make Bard more reliable and able to handle more users.
Lastly, while Chat GPT is a product of Open AI, Google Bard is a new AI language model that was developed by Google. This model has been trained on a large amount of text data, which gives it a better understanding of the way language works in different contexts and languages.
This is why it can deliver more accurate information than Chat GPT, which often makes up facts and embellishes stories to make them appear true. This can cause a problem for consumers who are looking for information on important topics.
It also causes a hallucination rate of between 15% and 20%, which is pretty bad when you’re trying to get an accurate answer.
The main reason for this is that most of the text data used in Chat GPT come from text generated by humans, whereas most of the data for Bard comes from sources on the internet. This is why it can deliver more up-to-date information than Chat GPT, which is limited to data generated by human writers up to 2021.
In addition to utilizing a plethora of textual data, Google’s Bard AI will also be able to break up complex ideas into easy-to-digest bits of information. This will help spread knowledge in an easily digestible format and encourage learning. The goal is to help people understand complicated concepts and ideas, which can be difficult for younger generations to grasp.
2. Language Model
Artificial intelligence (AI) has become an increasingly important tool in modern society, with a growing number of organizations using AI to automate routine tasks and improve decision-making. AI technologies are also being used to create chatbots, which are used to interact with customers via chat and other digital channels.
A number of different AI models are being used for various AI applications, including language processing. While GPT-3 is a popular choice for human-like text generation, Google BARD has been developed to understand customer queries and provide relevant responses.
Whether you’re looking for a new language model or want to compare and contrast a few different options, it’s essential to understand the difference between GPT-3 and Google BARD. There are many factors to consider when choosing the right model for your application, including the type of language task you need to perform and the performance requirements.
The most significant difference between GPT-3 and Google BARD is the approach to language processing. While GPT-3 is primarily designed to generate human-like text, Google BARD uses a combination of machine learning and natural language understanding technology to understand the intent behind user queries and provide relevant responses.
Both GPT-3 and Google BARD have proven to be effective in generating high-quality language. However, the type of language task you need to perform will determine which model is right for you.
While GPT-3 is a powerful language model that can be tuned for a variety of different language tasks, Google BARD has been proven to be effective in generating high-quality human-like text. This makes it a great choice for businesses that need to generate consistent, human-like text in a short amount of time.
Another key difference between GPT-3 and Google BARD involves their training data. Open AI’s Chat GPT was trained on a large corpus of internet text data, which gives it a deep understanding of the way language is used in various contexts. On the other hand, Google Bard was trained on a smaller set of text data.
Both Chat GPT and Google Bard will be able to answer questions in a conversational dialogue. They will use the internet as their database of knowledge to provide information to users. However, they will differ in a few ways, including the amount of training data they’ve used and their language model architectures.
3. Dialogue Model
In the past week, Microsoft has announced its integration of OpenAI’s ChatGPT language model into its Bing search engine and Google has released a new chatbot, Bard. This is the latest in a string of advancements by both companies as they try to stake their claim in the growing world of artificial intelligence.
The key difference between the two chatbots is that Bard makes use of a broader range of data than ChatGPT does, which will mean it can provide more accurate and detailed answers to questions. The information comes from all over the web and will be continually updated.
Bard, like Bing, will also offer more context to the answers it delivers than the text prompts that ChatGPT produces. This is expected to make Bard more trustworthy and useful to users, according to Pichai.
Similarly, Bard will be able to break down complex concepts into simple, conversation-starting chunks that can be digested easily. This could help to make knowledge more accessible and motivate people to learn more.
But both GPT and Bard can be a little misleading at times, as they are based on large-scale language models that can sometimes generate biased or incorrect information. This mainly depends on how the chatbot is designed to function and what it’s trained on.
Both Google and OpenAI admit that the chatbots can deliver inaccurate or incomplete information. They’re working to improve this, though.
While ChatGPT is known for its ability to generate logical and contextually suitable writing, it can also be used to exaggerate stories and make factual errors. This can lead to misinformation, and even infringement on intellectual property rights.
In contrast, Bard uses a language model called LaMDA to create more dialogue-based responses. The LaMDA network is based on an open-source natural language processing system that allows it to understand the structure of sentences and words.
Both the ChatGPT and Bard language models are extremely information-intensive, and this means they have to be able to draw information from the internet at all times. The ChatGPT model can only access data from up until 2021, while Bard can draw from all of the internet.
4. Response Format
Google has been making a lot of noise with its new AI chatbot tool Bard, which is available to select “trusted testers.” The company claims that this experimental service could help people perform tasks like planning a baby shower, comparing two Oscar-nominated movies, or explaining discoveries by NASA to a 9-year-old child.
The service works like a normal chatbot, with users simply entering a prompt or request and the chatbot responding with a human-like response. It then continues the conversation if they continue asking questions or making requests.
However, it’s important to note that Chat GPT only pulls data from 2021 sources, which could be outdated depending on the topic. This means that it’s not always the most up-to-date information, which could be problematic for marketers looking to draw inspiration for a blog post or to create a strong first draft for a piece of content.
Despite its limitations, Chat GPT is an important tool for marketers who are working on content creation. It can help marketers answer questions such as, “What are the pros and cons of AI?” or “Write a blog post on the pros and cons of AI.”
In addition to its ability to give quick answers to simple queries, Chat GPT is also capable of drawing inspiration for longer pieces of content. If a marketer is unsure of how to write about an issue, they can ask the chatbot for some guidance, and then re-write the article on their own using a more nuanced understanding of the subject.
This can help them avoid pitfalls that could come with writing a long blog post. Especially when there are multiple different perspectives on an issue, this type of response can be extremely helpful in crafting a piece of content that is both thoughtful and relevant to the user.
It also allows marketers to draw on recent events and conversations, allowing them to make their content more relevant to the reader. In the case of a chatbot like Chat GPT, this could mean a quick response to an issue such as Google’s latest round of layoffs.