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 on Flamingo (Alayrac et al., 2022), CoCa (Yu et al., 2022a), and PaLI (Chen et al., 2022)
- output images using discrete image tokens (Ramesh et al., 2021; Yu et al., 2022b)
- supervised fine tuning (SFT) and reinforcement learning through human feedback (RLHF)
I think these are already more details than what we got from OpenAI about GPT4, but on the other side, still only very little details.
(nitter: https://nitter.net/a_a_cabrera/status/1732454328307511807#m)
It was very grounding to understand how disk capacity has grown over time.
No. 0% fault of the author and 100% the fault of the Wikipedia editor. Generally speaking, people who are unwilling to ensure the accuracy of their work don't deserve the privilege to do that work.
For example, replacing "that's two part name, I want one part name" with "those are compound names, I want a single-part name." Note that the only change is changing "two part" to "compound."
Results look much more reasonable with that: I apologize for misunderstanding your request earlier. Here are some single-part name options for a Diablo 2 Necromancer:
Vex Kain Zoltar Mordecai Stryfe Xander Grimoire Lazarus Zephyr Azrael