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Decentralized AI Research (1): The Development History and Core Technical Concepts of Artificial Intelligence
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2024-12-10 19:02 6,008

Decentralized AI Research (1): The Development History and Core Technical Concepts of Artificial Intelligence

Introduction

In the digital era, artificial intelligence (AI) has become the key to promoting technological innovation and social progress strength. The development of AI is not only a technological advancement, but also an extension of human wisdom. AI has been the hottest topic in the venture capital industry and capital markets in the past period of time.

For this topic, we will share our research results in three articles. This article is the first of them and will take you through the history of AI. , exploring its core technical concepts and looking into the future of decentralized AI.

We also welcome entrepreneurs and project parties in this direction to contact us.

The development history of AI

Artificial Intelligence (AI for short) is a The discipline that studies how to simulate, extend and expand human intelligence through computers and software is the study of intelligent agents (Intelligent Agents) that receive perceptions from the environment and perform actions.

The concept of artificial intelligence can be traced back to the Dartmouth Conference in 1956. This marked the official start of AI research. Since then, AI has gone through several important development stages:

•Initial stage (1950s-1960s): Early research mainly focused on symbolic AI, Attempts to simulate human thinking through logic and symbolic processing. AI research during this period was limited by computing power, but it laid the theoretical foundation of AI.

•Exploration and Application (1970s-1980s): The rise of expert systems that encode human expert knowledge for problem solving in specific domains. During this period, AI began to show its application potential in medical, financial and other fields.

•Resurgence of AI (1990s-2000s): The popularity of the Internet and the emergence of big data have provided AI with abundant data resources and promoted the development of AI. AI technology during this period began to be used in medical diagnosis, financial analysis and other fields, showing its broad application potential.

•Deep learning era (2010s-present): Deep learning revolution, deep learning models represented by convolutional neural networks and recurrent neural networks have made breakthroughs in the fields of image recognition, speech recognition and other fields. During this period AI technology is widely used in commercial fields such as autonomous driving, intelligent assistants, and personalized recommendations, achieving large-scale commercialization

The core technical concept of AI

The core technical concepts of AI cover many aspects from basic algorithms to complex system construction:

• Machine learning: Algorithms trained on data, enabling systems to learn and improve without being explicitly programmed. Advances in machine learning algorithms, especially improvements in methods such as support vector machines and decision trees, have been significant Improved the performance of the AI ​​system

•Deep learning: A large-scale machine learning method based on neural networks, usually with a multi-layer network structure. For example, Convolutional Neural Network (CNN) is used for image recognition, Recurrent Neural Network (RNN) and Transformer are used for natural Language processing.

•Natural Language Processing (NLP): Technology that enables computers to understand, interpret and generate human language. The development of NLP technology, such as machine translation, sentiment analysis and chatbots, has greatly improved the naturalness of human-computer interaction and efficiency.

• Computer vision: Technology that enables computers to acquire, process, and understand visual information from images or videos. Advances in computer vision technology, such as facial recognition, autonomous driving, and medical image analysis, are opening up new opportunities for AI in security, transportation, Provides technical support for applications in medical and other fields

What is decentralized AI

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Decentralized AI represents the combination of AI and blockchain, realizing the training and use of AI models through distributed computing resources and data storage.

The rise of decentralized AI is mainly due to the widespread application of generative AI and the enthusiasm of the real world, and various projects have accelerated their entry into this field.

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The synergy of artificial intelligence and blockchain

Artificial intelligence and blockchain have many synergistic effects. The combination of the two brings new opportunities for industry development, including but not limited to:

•Enabling method: Improve contract decision-making, introduce economic models, and use Token to motivate ecological participants to contribute. This combination not only improves the efficiency of the AI ​​model, but also promotes the healthy development of the ecosystem through the economic incentive mechanism. p>

•NFT market and DeFi market: generation and identification in the NFT market, and monitoring of lending risks in the DeFi market. The application of AI technology has improved the efficiency and security of these markets. At the same time, it also provides new application scenarios for the development of AI technology.

The architecture of decentralized AI is mainly divided into four layers: model layer, training layer, data layer and computing power layer.

The model layer supports the development, sharing and trading of decentralized AI models; the training layer reduces the cost of AI model training through smart contracts; the data layer uses blockchain to store and manage data; the computing power layer provides distributed computing Resources to support efficient training and inference of AI models

Conclusion

The development of AI technology not only promotes technological progress, but also brings revolutionary changes to the business field. With the continuous advancement of technology, AI is gradually penetrating into all aspects of our lives. The relationship between blockchain and artificial intelligence The combined decentralized AI is also one of the current hot spots and has broad market prospects.

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