For now, Gemini Nano is only available

[likhon450@]

In theory, this should mean that Gemini understands things more intuitively. Take a phrase like “monkey business”: if an AI is simply trained to look at pictures with the words “monkey” and “business,” when asked to draw something related to that, it’s likely to draw only monkeys in suits. On the other hand, if the AI ​​is trained to understand images and linguistic nuances at the same time, then the entire model should have a deeper understanding of the linguistic and contextual connotations of the phrase.


X’d rather throw bananas. While all of this makes Google Gemini more interesting, it doesn't make it entirely unique: GPT-4 Vision (GPT-4V) is a similar multimodal model from OpenAI that has the LLM capabilities kuwait telegram data of GPT-4 in image processing (although it failed my "monkey business" test). Gemini is designed to work on almost any device. Google claims that its three versions - Gemini Ultra, Gemini Pro, and Gemini Nano - can work efficiently on everything from data centers to smartphones.


Gemini Ultra is the most powerful model designed for the most demanding tasks. It outperformed GPT-4 in LLM benchmarks such as MMLU, Big-Bench Hard, and HumanEval, and outperformed GPT-4V in multimodal benchmarks such as MMMU, VQAv2, and MathVista. It is still in the testing phase and will be released for use next year. Gemini Pro offers a balance between scalability and performance. It is designed for a variety of tasks.