All About Bard
🟢The large language model is a statistical tool trained on vast amounts of text to predict word combinations with statistical probability. Although efforts are made to improve accuracy and remove problematic answers, it is not connected to a specific database and may generate invented information. The model is designed to be a creative companion and a tool for brainstorming and imagination, not for providing factual or specific answers. Google search is recommended for factual inquiries, while the language model, Bard, is intended to help users think of new ideas and concepts.
🟢Bard is a versatile tool designed for various creative and productive tasks related to text. It can assist with
writing emails,
speeches,
and coding,
making it useful for overcoming writer's block, providing starting points for research or writing.
Summarise long articles or evaluate their strengths and weaknesses.
Its true strength lies in its ability to generate highly personalised creative content.
🟢For instance, it can be used to create bedtime stories tailored to individual children's interests and preferences. Bard can develop unique stories based on a child's favourite things, like
unicorns,
ice cream, or
specific colours.
personalised training programs
brainstorming ideas
Teaching children fractions or conceptualising a new book.
Describe the plot of their book and ask Bard to suggest potential endings.
🟢 Overall, Bard serves as a supportive companion for a wide range of imaginative and practical endeavours.
writing emails,
speeches,
and coding,
making it useful for overcoming writer's block, providing starting points for research or writing.
Summarise long articles or evaluate their strengths and weaknesses.
Its true strength lies in its ability to generate highly personalised creative content.
🟢For instance, it can be used to create bedtime stories tailored to individual children's interests and preferences. Bard can develop unique stories based on a child's favourite things, like
unicorns,
ice cream, or
specific colours.
personalised training programs
brainstorming ideas
Teaching children fractions or conceptualising a new book.
Describe the plot of their book and ask Bard to suggest potential endings.
🟢 Overall, Bard serves as a supportive companion for a wide range of imaginative and practical endeavours.
Google collaborates with academia on various levels, and the research conducted at its R&D centre in Israel plays a crucial role in the development of Bard and generative artificial intelligence. The focus is not just on adapting the model to Hebrew but also on core research areas, developing training methods, and enhancing the model's results. Despite the limited supply of texts in Hebrew, the team employed several processes like tuning, fine-tuning, reinforcement learning, and human feedback to improve the quality of the model's responses.
🟢 The release of Bard in Hebrew and 40 other languages was a significant milestone, driven by the demand for Google products worldwide. Hebrew was among the prioritised languages based on user needs.
🟢 Training a large language model in Hebrew presented challenges, including dealing with gender differentiation in the language. Efforts were made to minimise bias and ensure the model responds in neutral language, avoiding unnecessary gender distinctions.
🟢 To write effective prompts for Bard, users are encouraged to emphasise their preferences explicitly. Providing feedback and adjustments to initial responses helps improve subsequent interactions. Trial and error is encouraged, and users can offer clarifications or specific instructions to refine the model's output.
🟢 Training a large language model in Hebrew presented challenges, including dealing with gender differentiation in the language. Efforts were made to minimise bias and ensure the model responds in neutral language, avoiding unnecessary gender distinctions.
🟢 To write effective prompts for Bard, users are encouraged to emphasise their preferences explicitly. Providing feedback and adjustments to initial responses helps improve subsequent interactions. Trial and error is encouraged, and users can offer clarifications or specific instructions to refine the model's output.
https://www.aidigitalminds.com/2023/07/all-about-bard.html
