Google

Talk to Books was a new way to explore ideas and discover books

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In 2018, the Talk to Books experiment was launched, allowing users to browse book passages using a neural language model. This project demonstrated the effectiveness of language models and influenced features in various Google products. However, the experiment has now concluded and the Talk to Books platform is shutting down. Users are encouraged to explore a similar AI experience called Bard at bard.google.com, which specializes in book-related knowledge. The platform suggested some sample queries like recalling memories triggered by smells, tips on falling asleep, or TV shows with strong female leads. Additionally, it covered a wide range of topics, from historical events like World War I to personal memories from childhood. Despite the closure of Talk to Books, its impact on semantic matching and retrieval models can still be seen in various AI-driven products today.
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How To Use Google

  • Browsing book passages using experimental AI can be done by entering keywords or phrases related to the content you're looking for.
  • To engage with Talk to Books, simply type in your query or question and explore the diverse responses sourced from numerous books.
  • For an AI-driven search experience, consider visiting bard.google.com to discover a new kind of AI interaction.
  • Learning more about the effectiveness of language models can involve exploring the impact they have had on various Google products like Maps, Gmail, and more.
  • To connect with emotional memories, try identifying scents that trigger strong positive associations from your past experiences.

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Features

  • ⭐️ Talk to Books leverages a neural language model for conducting searches across a wide selection of books.
  • ⭐️ The experiment showcases the impact of semantic matching models by demonstrating their integration into popular Google services like Google Shopping, Maps, and Gmail.
  • ⭐️ Effective immediately, Talk to Books will be closing down after completing its exploration into the capabilities of AI and language models.

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