As announced earlier this month Google has now made available its new Gemini artificial intelligence API enabling developers and businesses to create custom Gemini Pro AI models for a wide variety of different applications. The launch of the Gemini API offers the ability for anyone to create innovative tools and apps harnessing the power of Google’s AI. To use the API, you need an API key. You can create a key with one click in Google AI Studio. Google AI Studio creates a new Google Cloud project for each new API key. You also can create an API key in an existing Google Cloud project.
Gemini is not a one-size-fits-all model; it comes in three sizes: Google Gemini Ultra, Pro, and Nano. The Pro version, which is the focus of this article, is now accessible via the Gemini API. This variety allows developers and enterprises to choose the model that best fits their needs and scales with their growth.
One of the major selling points of Gemini Pro is its performance. It outperforms other similarly-sized models on multiple research benchmarks. Additionally, it comes with a 32K context window for text, making it an efficient tool for processing large amounts of text data.
In terms of functionality, Gemini Pro is a powerhouse. It offers features such as function calling, embeddings, semantic retrieval, custom knowledge grounding, and chat functionality. These features make it a versatile tool that can be used in a variety of applications, from chatbots to data analysis tools.
Google Gemini API
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Gemini Pro is not just for English-speaking users. It supports 38 languages across 180+ countries and territories worldwide. This wide language support makes it a global tool that can be used by developers and enterprises all over the world.
The model is designed to accept text as input and generate text as output. However, it’s not limited to just text. A dedicated Gemini Pro Vision multimodal endpoint is also available that accepts text and imagery as input, expanding the range of applications it can be used for.
To make it easier for developers to integrate Gemini Pro into their applications, Google has provided Software Development Kits (SDKs) for the model. These SDKs support a variety of programming languages, including Python, Android (Kotlin), Node.js, Swift, and JavaScript.
To further aid developers in using Gemini Pro, Google has introduced the Google AI Studio. This free web-based developer tool allows developers to quickly develop prompts and get an API key for app development. Additionally, developers can transition from Google AI Studio to Vertex AI for a fully-managed AI platform with full data control and additional Google Cloud features.
While Gemini Pro is currently free to use within certain limits through Google AI Studio, charges will be applicable from early next year. However, the pricing details have not been disclosed at this time.
Google is not stopping at Gemini Pro. The company has plans to launch Gemini Ultra, its largest and most capable model, for highly complex tasks early next year. This future release demonstrates Google’s commitment to continually advancing their AI technology and providing developers and enterprises with the tools they need to stay at the forefront of their industries.
The introduction of the Gemini Pro API is a significant step forward in AI technology. With its advanced features, global language support, and developer-friendly tools, it’s a model that promises to revolutionize the way developers and enterprises use AI. As we look forward to the release of Gemini Ultra, one thing is clear: the future of AI is bright, and Google is leading the way.
Google has created a fantastic get started with Gemini API guide which provides more information on using it with Python, JavaScript, Swift and more. The fastest way to start using Gemini is with Google AI Studio, a web-based tool that lets you prototype and run prompts right in your browser.
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