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Description

DataGemma signifies a groundbreaking initiative by Google aimed at improving the precision and dependability of large language models when handling statistical information. Released as a collection of open models, DataGemma utilizes Google's Data Commons, a comprehensive source of publicly available statistical information, to root its outputs in actual data. This project introduces two cutting-edge methods: Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG). The RIG approach incorporates real-time data verification during the content generation phase to maintain factual integrity, while RAG focuses on acquiring pertinent information ahead of producing responses, thereby minimizing the risk of inaccuracies often referred to as AI hallucinations. Through these strategies, DataGemma aspires to offer users more reliable and factually accurate answers, representing a notable advancement in the effort to combat misinformation in AI-driven content. Ultimately, this initiative not only underscores Google's commitment to responsible AI but also enhances the overall user experience by fostering trust in the information provided.

Description

Introducing Gemma 3n, our cutting-edge open multimodal model designed specifically for optimal on-device performance and efficiency. With a focus on responsive and low-footprint local inference, Gemma 3n paves the way for a new generation of intelligent applications that can be utilized on the move. It has the capability to analyze and respond to a blend of images and text, with plans to incorporate video and audio functionalities in the near future. Developers can create smart, interactive features that prioritize user privacy and function seamlessly without an internet connection. The model boasts a mobile-first architecture, significantly minimizing memory usage. Co-developed by Google's mobile hardware teams alongside industry experts, it maintains a 4B active memory footprint while also offering the flexibility to create submodels for optimizing quality and latency. Notably, Gemma 3n represents our inaugural open model built on this revolutionary shared architecture, enabling developers to start experimenting with this advanced technology today in its early preview. As technology evolves, we anticipate even more innovative applications to emerge from this robust framework.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Gemini
Gemini Enterprise
Gemini Nano
Gemini 1.5 Flash
Gemini 1.5 Pro
Gemini 2.0
Gemini 2.0 Flash
Gemini Enterprise Agent Platform
Gemini Pro
Gemma
Google AI Edge
Google AI Edge Gallery
Google AI Studio
Google Cloud Platform
Hugging Face
JAX
Keras
Ollama
OpenCode
PyTorch

Integrations

Gemini
Gemini Enterprise
Gemini Nano
Gemini 1.5 Flash
Gemini 1.5 Pro
Gemini 2.0
Gemini 2.0 Flash
Gemini Enterprise Agent Platform
Gemini Pro
Gemma
Google AI Edge
Google AI Edge Gallery
Google AI Studio
Google Cloud Platform
Hugging Face
JAX
Keras
Ollama
OpenCode
PyTorch

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Google

Founded

1994

Country

United States

Website

blog.google/technology/ai/google-datagemma-ai-llm/

Vendor Details

Company Name

Google DeepMind

Founded

2010

Country

United Kingdom

Website

deepmind.google/models/gemma/gemma-3n/

Product Features

Product Features

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