Lines just keep falling into place when you remember that the beautiful ones are yet to be born. The path to innovation initially appears less trodden until an initial discovery, and then a myriad of inspiration and updates keeps occurring not necessarily from the same source, but from other sources.
This is the current tale of machine learning applications like ChatGPT which was created by Open AI in 2022 as a generative tool from the numerous chevrons of Artificial Intelligence [AI].
In this post, I will be delving into another vein of valor in the business of machine learning, called Bard. At the end of this read, you will understand what Bard is, what it does, what it stands for, and its possible drawbacks.
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What is Bard?
"Bard" is a text generation model developed by Google. It is a state-of-the-art language model that uses machine learning to generate high-quality natural language text. Bard is part of Google's AI research efforts and is designed to improve various natural language processing tasks, such as language translation, language understanding, and language generation.
Bard is an example of a large-scale neural language model, similar to other models such as GPT-3 designed by Open AI, which has been trained on massive amounts of text data to generate human-like responses to a given prompt or input.
How does Google Bard work?
Google’s Bard conversational AI is powered by LaMDA and built on Transformer, just like other similar generative machine learning applications. LaMDA is Google's Language Model for Dialogue Applications, which applies machine learning to chatbots to engage in "free-flowing" conversations as intended.
Google's Bard was derived from the modification of a controversial LaMDA bot called "sentient." According to the release, the initial version of Bard will utilize a lightweight model of LaMDA since it requires less computing power and can be scaled to more users.
Bard will draw on all the information from the web to respond to conversations.
What can Bard do differently than ChatGPT?
Bard and ChatGPT are both large language models developed by OpenAI and Google, respectively, and they share some similarities in terms of their abilities. However, there are also some differences between them, like the training data used to develop each model.
Bard was trained on a large corpus of books and other written works, while ChatGPT was trained on a wider range of data, including web pages, online forums, and social media. This difference in training data can affect the types of language that each model is most skilled at generating.
Another difference is the size of the models. Bard is a relatively small model, with only 1.7 billion parameters, compared to the much larger GPT-3, which has 175 billion parameters. This size difference can affect the complexity and quality of the language generated by the models.
Has Bard been released?
Bard is yet to be released and is currently at its testing stage by some trusted testers. Bard, just like similar AI solutions, is one of the most anticipated applications at the moment, especially when it appears three tech giants [OpenAI, Google, and Baidu] are struggling for the position of the best AI to match with users' experiences.
What question did Bard get wrong?
Although still in its testing stage, Bard has received scrutiny after it failed to provide a correct answer when inquired about in an advertisement.
In the advertisement, Bard is prompted with the question, "What new discoveries from the James Webb Space Telescope can I tell my 9-year-old about?"
Bard provided two correct answers. However, its final response seemed inaccurate. This flaw alone has led to a further downward slope in Google's stock.
Conclusion.
The goals and intended applications of each model may also differ. Bard was designed to generate high-quality literary text, such as poetry, prose, and video, while ChatGPT was designed with a broader range of applications in mind, including chatbot interactions, question-answering, programming, and language translation.
It is essential to note that even state-of-the-art language models such as Bard and others are fallible, especially at their testing stage, and may make errors by generating responses that are inappropriate or inaccurate in some contexts.
However, Bard is currently ongoing research and development, and their performance is continually being evaluated and assessed by researchers and other experts in the field before its grand release.
Let us be patient with them... at least till the release date.
Comments (2)
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Jun 11, 2024
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