So, better than GPT4 according to the benchmarks? Looks very interesting. Technical paper: https://goo.gle/GeminiPaper Some details: - 32k context length - efficient attention mechanisms (for e.g. multi-query attention (Shazeer, 2019)) - audio input via Universal Speech Model (USM) (Zhang et al., 2023) features - no audio output? (Figure 2) - visual encoding of Gemini models is inspired by our own foundational work o…
The table is *highly* misleading. It uses different methodologies all over the place. For MMLU, it highlights the CoT @ 32 result, where Ultra beats GPT4, but it loses to GPT4 with 5-shot, for example. For GSM8K it uses Maj1@32 for Ultra and 5-shot CoT for GPT4, etc. Then also, for some reason, it uses different metrics for Ultra and Pro, making them hard to compare. What a mess of a "paper".
They simply compare the prompting strategies that work best with each model. Otherwise it would be just a comparison of their response to specific prompt engineering.