AvaGrow

 Balancing performance and memory efficiency has long been a challenge for AI models running on edge devices. Google's newly open-sourced Gemma 3n tackles this issue head-on. Designed with an efficient multimodal architecture, Gemma 3n delivers state-of-the-art capabilities while requiring minimal memory-just 2GB or 3GB depending on the variant. It redefines what’s possible for on-device AI. Key Features of Gemma 3n Multimodal from the Ground Up Gemma 3n natively supports i mages, audio, video, and text as input, with text as output. This flexibility makes it an ideal solution for a wide range of applications, from real-time transcription and translation to interactive visual understanding. Built for the Edge Two optimized configurations are available: E2B : 2GB runtime memory, equivalent to 2B effective parameters E4B : 3GB runtime memory, equivalent to 4B effective parameters Although their total parameter counts are 5B and 8B, architecture innovations make their memory requireme...

  1. Overview This document outlines the usage and specifications of the AI Text Generation API. Powered by advanced artificial intelligence models, this API can generate high-quality text based on user-provided prompts. It is ideal for use cases such as intelligent writing assistants, content creation tools, and chatbots. 2. Basic Information API Name : AI Text Generation API Version : 1.0 HTTP Method : POST Endpoint :  https://api.example.com/ai/text/generate 3. Request Parameters Parameter Type Required Description prompt string Yes Input prompt to guide the text generation max_tokens int No Maximum length of generated text, default is 100 temperature float No Controls randomness of output; range: 0–1, default is 0.7 4. Response Parameters Parameter Type Description code int Response status code (200 = success) message string Response message, empty on success data object Contains the generated text - text string The generated text content 5. Request Example Copy Copy { ...