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What is Gemma?

Gemma encompasses a series of innovative, lightweight open models inspired by the foundational research and technology that drive the Gemini models. Developed by Google DeepMind in collaboration with various teams at Google, the term "gemma" derives from Latin, meaning "precious stone." Alongside the release of our model weights, we are also providing resources designed to foster developer creativity, promote collaboration, and uphold ethical standards in the use of Gemma models. Sharing essential technical and infrastructural components with Gemini, our leading AI model available today, the 2B and 7B versions of Gemma demonstrate exceptional performance in their weight classes relative to other open models. Notably, these models are capable of running seamlessly on a developer's laptop or desktop, showcasing their adaptability. Moreover, Gemma has proven to not only surpass much larger models on key performance benchmarks but also adhere to our rigorous standards for producing safe and responsible outputs, thereby serving as an invaluable tool for developers seeking to leverage advanced AI capabilities. As such, Gemma represents a significant advancement in accessible AI technology.

What is DataGemma?

DataGemma represents a revolutionary effort by Google designed to enhance the accuracy and reliability of large language models, particularly in their processing of statistical data. Launched as a suite of open models, DataGemma leverages Google's Data Commons, an extensive repository of publicly accessible statistical information, ensuring that its outputs are grounded in actual data. This initiative unveils two innovative methodologies: Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG). The RIG technique integrates real-time data validation throughout the content creation process to uphold factual correctness, while RAG aims to gather relevant information before generating responses, significantly reducing the likelihood of inaccuracies often labeled as AI hallucinations. By employing these approaches, DataGemma seeks to provide users with more trustworthy and factually sound answers, marking a significant step forward in the battle against misinformation in AI-generated content. Moreover, this initiative not only highlights Google's dedication to ethical AI practices but also improves user engagement by building confidence in the material presented. By focusing on the intersection of data integrity and user trust, DataGemma aims to redefine the standards of information accuracy in the digital landscape.

Media

Media

Integrations Supported

AiAssistWorks
C
CodeMender
DiffusionGemma
F#
GaiaNet
Gemma 3n
HTML
Jan
Kotlin
Locally AI
Ollama
Python
SQL
TranslateGemma
Unmixr
Unsloth
VESSL AI
Visual Basic

Integrations Supported

Gemini 1.5 Flash

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

ai.google.dev/gemma

Company Facts

Organization Name

Google

Date Founded

1994

Company Location

United States

Company Website

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

Categories and Features

AI Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

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