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Paper Reading - Gemini: A Family of Highly Capable Multimodal Models

Paper Discussion led by: Akshika Wijesundara PhD

Abstract: Google researchers recently unveiled Gemini, a ground breaking family of multimodal AI models capable of understanding and reasoning across images, audio, video, and text. The largest Gemini model, Ultra, achieved human-expert performance on several benchmarks and advanced the state of the art across a range of multimodal tasks.

In this paper reading, we will discuss key details from Google's paper introducing Gemini models. Topics will include:

  • The Gemini model architectures and how they achieve cross-modal understanding
  • Performance benchmarks and state-of-the-art results across text, image, audio, and video tasks
  • Applications and use cases enabled by Gemini's multimodal reasoning
  • Approaches to responsible deployment of large language models like Gemini

This paper provides a comprehensive overview of the exciting new capabilities of Google's Gemini project. Whether you're an AI researcher, engineer, or simply curious about the state of the art in multimodal AI, join us for an in-depth look at this new model family.

Paper link: https://arxiv.org/abs/2312.11805
Event link: https://www.jointaro.com/event/paper-reading-gemini-a-family-of-highly-capable-multimodal-models/