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Galería de mapas mentales Large model classification and hierarchical mind map

Large model classification and hierarchical mind map

This is a mind map about the classification and hierarchical mind map of large models. Through the form of mind map, the classification and hierarchy of large models are clearly displayed, as well as the characteristics and application scenarios of various large models.

Editado a las 2025-02-06 15:49:26,

Gavinnblake

Large model classification and hierarchical mind map

Gavinnblake

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Large model classification and hierarchical mind map

1. Large model classification

Language Mockup (NLP)

Definition: used to process text data and understand natural language

Features: Training on a large-scale corpus to learn grammar, semantics and contextual rules

Applications: text generation, machine translation, sentiment analysis, etc.

Typical examples:

GPT Series (OpenAI)

Bard (Google)

Wen Xin Yiyan (Baidu)

Visual Mockup (CV)

Definition: for image processing and analysis

Features: Training on large-scale image data to realize visual tasks

Applications: image classification, object detection, image segmentation, pose estimation, face recognition, etc.

Typical examples:

VIT series (Google)

Wenxin UFO

Huawei Pangu CV

INTERN

Multimodal large model

Definition: Processing multiple data types (text, images, audio, etc.)

Features: Combining NLP and CV capabilities, comprehensively understand and analyze multimodal information

Application: multimodal content generation, cross-modal retrieval, etc.

Typical examples:

DingoDB multimode vector database (Jiuzhang Yunji DataCanvas)

DALL-E (OpenAI)

Wukong Drawing (Huawei)

Midjourney

2. Large model level

General Mockup L0

Definition: A large model that can be used in multiple fields and tasks

Features:

Training using massive open data and huge parameters

Finding features and rules on large-scale unmarked data

Strong generalization ability, can learn from one example and apply it to other aspects

Multi-scene tasks can be completed without fine-tuning or a small amount of fine-tuning

Metaphor: AI has completed "general education"

Industry big model L1

Definition: Large model for a specific industry or field

Features:

Use industry-related data for pre-training or fine-tuning

Improve performance and accuracy in this field

Metaphor: AI becomes an "industry expert"

Vertical big model L2

Definition: Large model for a specific task or scenario

Features:

Pre-training or fine-tuning using task-related data

Improve performance and effectiveness on this task

Metaphor: AI becomes a "task expert"