Kavli Affiliate: Felix Fischer
| First 5 Authors: Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac
| Summary:
This report introduces a new family of multimodal models, Gemini, that
exhibit remarkable capabilities across image, audio, video, and text
understanding. The Gemini family consists of Ultra, Pro, and Nano sizes,
suitable for applications ranging from complex reasoning tasks to on-device
memory-constrained use-cases. Evaluation on a broad range of benchmarks shows
that our most-capable Gemini Ultra model advances the state of the art in 30 of
32 of these benchmarks – notably being the first model to achieve human-expert
performance on the well-studied exam benchmark MMLU, and improving the state of
the art in every one of the 20 multimodal benchmarks we examined. We believe
that the new capabilities of Gemini models in cross-modal reasoning and
language understanding will enable a wide variety of use cases and we discuss
our approach toward deploying them responsibly to users.
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