DataGemma 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.

DataGemma Alternatives
LM-Kit.NET Reviews
LM-Kit.NET
(8 Ratings)
LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents. Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development. Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.
Learn more
Vertex AI Reviews
Vertex AI
(677 Ratings)
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
Learn more
Grounded Language Model (GLM) Reviews
Grounded Language Model (GLM)
Contextual AI has unveiled its Grounded Language Model (GLM), which is meticulously crafted to reduce inaccuracies and provide highly reliable, source-based replies for retrieval-augmented generation (RAG) as well as agentic applications. This advanced model emphasizes fidelity to the information provided, ensuring that responses are firmly anchored in specific knowledge sources and are accompanied by inline citations. Achieving top-tier results on the FACTS groundedness benchmark, the GLM demonstrates superior performance compared to other foundational models in situations that demand exceptional accuracy and dependability. Tailored for enterprise applications such as customer service, finance, and engineering, the GLM plays a crucial role in delivering trustworthy and exact responses, which are essential for mitigating risks and enhancing decision-making processes. Furthermore, its design reflects a commitment to meeting the rigorous demands of industries where information integrity is paramount.
Learn more
Gemma Reviews
Gemma
Gemma represents a collection of cutting-edge, lightweight open models that are built upon the same research and technology underlying the Gemini models. Created by Google DeepMind alongside various teams at Google, the inspiration for Gemma comes from the Latin word "gemma," which translates to "precious stone." In addition to providing our model weights, we are also offering tools aimed at promoting developer creativity, encouraging collaboration, and ensuring the ethical application of Gemma models. Sharing key technical and infrastructural elements with Gemini, which stands as our most advanced AI model currently accessible, Gemma 2B and 7B excel in performance within their weight categories when compared to other open models. Furthermore, these models can conveniently operate on a developer's laptop or desktop, demonstrating their versatility. Impressively, Gemma not only outperforms significantly larger models on crucial benchmarks but also maintains our strict criteria for delivering safe and responsible outputs, making it a valuable asset for developers.
Learn more

Integrations

View Integrations

Reviews

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Company Details

Company:
Google
Year Founded:
1994
Headquarters:
United States
Website:
blog.google/technology/ai/google-datagemma-ai-llm/

Media

DataGemma Screenshot 1
DataGemma Screenshot 1 DataGemma Screenshot 2
Recommended Products
Auth for GenAI | Auth0 Icon
Auth for GenAI | Auth0

Enable AI agents to securely access tools, workflows, and data with fine-grained control and just a few lines of code.

Easily implement secure login experiences for AI Agents - from interactive chatbots to background workers with Auth0. Auth for GenAI is now available in Developer Preview
Try free now

Product Details

Platforms
Web-Based
Types of Training
Training Docs
In Person
Training Videos
Customer Support
Business Hours
Online Support

DataGemma Features and Options

DataGemma User Reviews

Write a Review
  • Previous
  • Next