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Description

The latest advancement, GPT-4 with vision (GPT-4V), allows users to direct GPT-4 to examine image inputs that they provide, marking a significant step in expanding its functionalities. Many in the field see the integration of various modalities, including images, into large language models (LLMs) as a crucial area for progress in artificial intelligence. By introducing multimodal capabilities, these LLMs can enhance the effectiveness of traditional language systems, creating innovative interfaces and experiences while tackling a broader range of tasks. This system card focuses on assessing the safety features of GPT-4V, building upon the foundational safety measures established for GPT-4. Here, we delve more comprehensively into the evaluations, preparations, and strategies aimed at ensuring safety specifically concerning image inputs, thereby reinforcing our commitment to responsible AI development. Such efforts not only safeguard users but also promote the responsible deployment of AI innovations.

Description

Ming-Flash Omni 2.0, developed by Ant Group, represents a comprehensive large language model that operates on a cohesive multimodal framework, emphasizing a philosophy of “modal unity + task unity.” This model, as a part of the Ming series, is engineered to facilitate an integrated understanding and generation of content across various modalities, including text, images, audio, and video, thus eliminating the need for multiple specialized models to perform distinct tasks such as seeing, hearing, speaking, and drawing. Progressing from its predecessors, Ming-Light Omni and Ming-Flash Omni Preview, this iteration advances from validating a unified architecture and scaling to hundreds of billions of parameters to implementing a Data Scaling approach that achieves state-of-the-art performance in open-source environments across numerous benchmarks. Notably, the model encompasses four essential capability modules: image-text comprehension, video interpretation, speech generation, and image creation or manipulation. To enhance image-text understanding, Ming employs structured knowledge graphs that contribute to a more nuanced visual perception. This innovative approach not only broadens the model's applicability but also sets a new standard in the field of artificial intelligence.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

2Slash
AI-FLOW
AIForAll
AiAssistWorks
ChatGPT
Claude Code
GPT-4
GPT-4o
Hermes Agent
Kilo Code
Make Real
OpenAI
OpenClaw
OpenRouter
SheetMagic
ShotSolve
ZenMux

Integrations

2Slash
AI-FLOW
AIForAll
AiAssistWorks
ChatGPT
Claude Code
GPT-4
GPT-4o
Hermes Agent
Kilo Code
Make Real
OpenAI
OpenClaw
OpenRouter
SheetMagic
ShotSolve
ZenMux

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

OpenAI

Founded

2015

Country

United States

Website

openai.com/research/gpt-4v-system-card

Vendor Details

Company Name

Ant Group

Founded

2014

Country

China

Website

developer.ant-ling.com/en/docs/models/ming/

Product Features

Computer Vision

Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration

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