The development of large models has driven
various industries towards advancements in artificial intelligence.
Among them, the hottest topic isAIGC.
What exactly is AIGC? What makes it so popular?
Today, I will take you step by step
to unveil the mystery of AIGC.
Unveiling the Mystery of AIGC
Many terms related to AI have emerged online, let’s first understand the relationships between these terms.
AIGC (AI-Generated Content) refers tothe use of artificial intelligence to produce content, where AI stands for artificial intelligence, and GC stands for generated content. Currently, AIGC is mainly applied inwritten text, images, videos, audio, games, etc..
ChatGPT is a language generation model built on natural language processing technology. It automatically generates new text content, requiring only a segment of existing text as input. In contrast,MidJourney (one of the AI drawing tools)is a data processing and analysis tool designed based on graphical computing and machine learning technology, which can automate business processes through data processing.
Although ChatGPT and MidJourney differ from AIGC technology, they are specific applications built on AIGC technology. AIGC technology is a broader concept, while ChatGPT and MidJourney are specific applications of this concept. If we liken AIGC technology to a librarian, then ChatGPT and MidJourney are the librarian’s assistants. The librarian needs to manage a large amount of text and data, while tools like ChatGPT and MidJourney can handle and manage text and data more intelligently. They provide more accurate information and accelerate data analysis speed, showing greater advantages compared to traditional processing methods.
Why AIGC has Exploded in Recent Years
AIGC is a technology that utilizes foundational AI technologies and capabilities such as natural language processing and computer vision to understand external user input commands.
In terms of content form, AIGC automatically generates content in the form of text, audio, images, videos, code, multimodal, etc.
In terms of application scenarios, companies like Microsoft, Google, and Baidu are currently applying AI technology in the search field, using conversational AI to significantly enhance the search experience. For the future, it is widely believed that the search field will become one of the fastest application scenarios for AI technology. In addition, AIGC technology has also been widely applied in vertical industries such as office software, education, healthcare, urban development, and the metaverse.
What Can AIGC Do
1. AIGC Industry Chain
Computing power, algorithm models, and applications make up the AIGC industry chain.
From the launch of ChatGPT by OpenAI, we find that ChatGPT relies on the GPT large model, which in turn requires computing power training provided by Microsoft Azure supercomputing center. Therefore, AIGC industries like ChatGPT still depend on the basic framework of computing power, algorithm models, and applications.
2. ChatGPT Industry Applications
[1] ChatGPT + Finance and Securities
Customer service, investment advice, information push, risk management.
[2] ChatGPT + Manufacturing
Quality control, production planning, equipment maintenance, process improvement.
[3] ChatGPT + Healthcare
Medical consultation and diagnosis, knowledge base management, medical image recognition, health data management.
[4] ChatGPT + Education Industry
Teaching assistance, learning resource recommendations, learning assessment, thesis writing assistance.
[5] ChatGPT + Retail Industry
Customer service, marketing promotion, data analysis, inventory management.
[6] ChatGPT + Advertising Media
Content production, ad placement, audience analysis, virtual personas.
[7] ChatGPT + Power Industry
Power dispatch, equipment maintenance, power grid fine management, data management.
[8] ChatGPT + IT Industry
Customer service robots, RPA intelligent reimbursement, work summaries, intelligent code writing.
[9] ChatGPT + Transportation
Traffic prediction systems, intelligent traffic scheduling, travel planning, decision-making autonomous driving.
Source: New Machine Vision Xiaoshan Science and Technology Association
Editor: Lou Danyu
Editor in Charge:Ni Jiacheng
Final Review:Zhu Chun
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