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Bard: Difference between revisions
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PauloPacheco (talk | contribs) (Created page with "Bard is a conversational AI chatbot developed by Google, trained on a vast dataset of text and code to generate human-like responses to user inputs. It is a large language model (LLM) like OpenAI's ChatGPT. <ref name="”1”">[1] Fedewa, J (2023). What Is Google Bard? Hands-on With the AI Chatbot. How-to Geek. https://www.howtogeek.com/880598/what-is-google-bard/</ref> As a generative AI, it accepts prompts and performs text-based tasks such as answe...") |
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==How does it work== | ==How does it work== | ||
The use of machine learning is essential for the training process of AI chatbots like Bard. It analyzes text and predicts the next word based on what it has learned, basically functioning as a sophisticated predictive text engine. <ref name="”1”"></ref><ref name="”5”">Fowler, GA (2023). Say what, Bard? What Google’s New AI Gets Right, Wrong and Weird. The Washington Post. https://www.washingtonpost.com/technology/2023/03/21/google-bard/ </ref> Bard uses a lightweight and optimized version of Google's [[LaMDA]] ([[Language Model for Dialogue Applications]]), requiring less computing power and allowing for scaling to more users and receiving valuable feedback. This model is responsible for generating human-like responses, utilizing information from the web. <ref name="”1”"></ref><ref name="”2”"></ref><ref name="”3”"></ref><ref name="”4”"></ref> | The use of machine learning is essential for the training process of AI chatbots like Bard. It analyzes text and predicts the next word based on what it has learned, basically functioning as a sophisticated predictive text engine. <ref name="”1”"></ref><ref name="”5”">Fowler, GA (2023). Say what, Bard? What Google’s New AI Gets Right, Wrong and Weird. The Washington Post. https://www.washingtonpost.com/technology/2023/03/21/google-bard/ </ref> Bard uses a lightweight and optimized version of Google's [[LaMDA]] ([[Language Model for Dialogue Applications]]), requiring less computing power and allowing for scaling to more users and receiving valuable feedback. This model is responsible for generating human-like responses, utilizing information from the web. <ref name="”1”"></ref><ref name="”2”"></ref><ref name="”3”"></ref><ref name="”4”"></ref> | ||