Introduction
Gemini AI is a multi-model AI, made by Google. It has the ability to understand any video, image, text, and audio. It can generate codes according to user instructions like Chatgpt and other AI tools, But it is more advanced than other AI. Gemini comes in three versions: Nano, Pro, and Ultra. It can understand languages visually.
Which is superior? GPT vs. Claude against Gemini
According to Google, the Gemini Ultra barely beats the GPT-4 in the majority of categories, including multimodal, arithmetic, and coding. For example, it outperforms GPT by 2% in math. Nevertheless, this study cannot be compared to OpenAI’s better GPT-4 Turbo. There aren’t any studies that compare Anthropic’s Claude 2.1 at this time.
According to Google, Gemini is the first model to do better than human specialists on the 57-subject MMLU (Massive Multitask Language Understanding) test. These areas include STEM and the humanities. It scored 90% in this category compared to GPT-4’s 86.4%. Users have, however, reported anecdotal evidence that is, at best, mediocre, including numerous hallucinations and translation mistakes (as well as some concerns regarding the demo movies). Over time, after independent research has had time to complete its work, a more comprehensive picture of Gemini’s capabilities will become apparent.
Gemini surpasses both Claude and GPT in terms of multimodality.
Gemini is now leading the pack in terms of multimodality, or the capacity to comprehend several input formats.The input formats supported by the system encompass text, audio, video, and image. In contrast, only text can be entered into Claude 2.1, whereas images and text can be entered into GPT-4 with Vision (GPT-4V). Gemini and GPT-4V have the capability to generate images when provided with access to DALL-E 3.
Gemini produces far less and has a lower memory.
Claude and GPT-4 Turbo possess token windows that are more extensive compared to Gemini. Gemini has a token capability of 32k tokens, a token window of 128k tokens, and an enormous token window of 200k tokens, which is approximately equivalent to 150k words or 500 pages of text. Tokens are commonly used as a measure of a model’s ability to recall and generate content.
We still don’t know Gemini’s latency.
One important consideration when using AI models with flashy new features is latency. GPT-4 produced far better results than GPT-3.5, albeit at the expense of speed. It is evident that Google is providing three distinct Gemini versions in order to provide lower latency options at the sacrifice of functionality, but it is unclear how they compare to other models at this time.Once more, it won’t be much time until this research is finished.
How is Google Gemini AI used?
Google Bard is currently supported on Pixel devices and operates on an enhanced edition of Gemini Pro in the background. Over the next few months, Google plans to make it compatible with Chrome, Duet AI, Ads, and Search. Starting from December 13, developers can gain access to Gemini Pro through Google Cloud Vertex AI or Google AI Studio’s Gemini API. Additionally, Google has revealed that Android developers will soon have access to Gemini Nano, a new system feature included in Android 14, through AICore. The release of Gemini Ultra is expected in early 2024, following further refinement and safety testing.
In summary, a significant advancement in multimodal AI input
A single-digit percentage difference won’t really matter much to someone using ChatGPT, thus Gemini’s on-paper capabilities aren’t likely to blast GPT-4s out of the water, but the multimodal inputs are truly something else. If it isn’t already, I anticipate that OpenAI and Anthropic will hurry to incorporate native video and audio input into their feature pipelines. It will be interesting to observe how much latency each of these functions adds to the process.
External resources :
Google Gemini :
https://blog.google/technology/ai/google-gemini-ai/#introducing-gemini
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