How do decentralized cloud storage and AI integrate technologically?

As AI becomes a hot topic in the market, many users are starting to experience ChatGPT and trying to use AIGC to meet their needs in work and life. In the crypto space, AI Crypto is also gradually being mentioned. This reflects the entry of AI into the crypto field and the innovative technologies and products that blockchain technology is nurturing in a decentralized environment. Today, CESS will discuss together how AI can leverage its technological advantages in the crypto space, and how the decentralized storage infrastructure of Web3 can complement AI.

What is AI and AI Crypto

AI (Artificial Intelligence) is a branch of computer science and engineering. AI systems use algorithms and statistical models to evaluate large amounts of data and make predictions or choices based on these analyses. The study of intelligent machines that can perform tasks traditionally requiring human intelligence (such as speech recognition, decision-making, and language translation) is known as AI research.

AI comes in many different forms, such as rule-based systems, machine learning (ML), and deep learning. Machine learning systems learn from data and improve over time, while rule-based systems make judgments based on a set of established rules. Many industries, including healthcare, banking, transportation, and entertainment, are using artificial intelligence. The development of AI raises ethical and social issues, such as its impact on employment and potential biases in decision-making, despite its ability to improve efficiency and create new opportunities.

AI Crypto is a type of cryptocurrency that integrates artificial intelligence technology into its operations. Unlike traditional cryptocurrencies, AI Crypto uses machine learning algorithms and natural language processing to study market patterns, make predictions, and execute automated trades. Because they have the ability to learn and adapt to market developments, investors view them as a more dynamic and responsive investment option.

The projects and platforms behind AI Crypto are actually created as dedicated platforms for AI and machine learning researchers and developers, facilitating the development and testing of new models, applications, and algorithms in a decentralized and open environment, achieving more efficient updates and iterations.

The Data Dilemma Faced by Decentralized Storage and AI

We must acknowledge that with the accelerated arrival of the Web3 era, the decentralized storage ecosystem, which is the cornerstone of its development, is also evolving at an astonishing pace. Based on blockchain technology, all data under decentralized storage is recordable, traceable, and decentralized. Some significant issues currently exist:

• The massive recording of meaningless/useless data

Distributed ledgers indiscriminately record generated data, unconsciously allowing and even incentivizing meaningless data, making it easy for large ecosystems to contain a lot of useless data.

• Efficiency issues in data usage

Behind the blocks are countless massive metadata, and although all data is open and transparent, in the absence of tools, the data is chaotic, requiring various scripts to access blocks, traverse information, etc., and then format it. Therefore, the process of processing data to meet user data needs involves common issues of high development costs and low efficiency in the final implementation.

Looking at the data industry of AI, in the entire artificial intelligence market, 15% to 30% of funding is invested in data labeling each year, and this business is growing at a rate of 30% annually. Behind the astonishing growth of the AI data industry, there are also certain problems:

• Rising labor costs

The demand for data is becoming increasingly specialized. From speech and image recognition to data labeling in various industries such as healthcare, finance, and education, higher requirements are placed on the knowledge base of labeling personnel.

• Rising business costs

Data labeling companies cannot enjoy data ownership or share the benefits of delivering data. They can only rely on labor to maintain current cash flow, with no prospects for appreciation or expansion. As competition in the industry intensifies, most labeling companies cannot operate at full capacity, increasing the likelihood of employee unemployment.

AI and Decentralized Storage Complement Each Other

In meeting the decentralized storage system's need for effective and usable data, AI can undertake a large amount of data analysis and tracking, such as quickly collecting information about the latest security incidents of companies, uncovering potential threats, and even quickly finding information about common vulnerabilities and exposed data.

Regarding the demand for third-party data labeling in the AI data industry, decentralized storage technology brings an unprecedented ability to share reliable data without the need for third parties.

Behind the data issues faced by decentralized storage and the AI data industry, both have significant advantages that fit together like a dovetail joint, complementing each other.

How AI Promotes Decentralized Storage

Improving Decision-Making

AI can analyze large amounts of data, which involves discovering patterns and trends that human analysts might overlook. With this research, traders can decide when to buy, sell, or hold more informed cryptocurrencies.

Increasing Efficiency

Many functions in the cryptocurrency market, including data analysis, market trend monitoring, and trade execution, can be automated through artificial intelligence. This can speed up transaction times on blockchain networks and save traders time.

Better Risk Management

Artificial intelligence can help traders manage risks better by assessing data and uncovering potential pitfalls. This can help traders make more informed choices about which assets to invest in and how much to invest.

Enhanced Security

By identifying potential security vulnerabilities and taking steps to prevent them, the application of artificial intelligence in the cryptocurrency market can enhance security. By doing so, the likelihood of hacking and other security issues can be reduced.

How CESS Supports AI

As previously discussed, decentralized storage requires a sustainable and efficient data production mechanism, and the continuously updated models and algorithms of artificial intelligence can meet this demand; at the same time, the AI data market needs a platform to operate a sharing economy --- decentralized storage's powerful data certification capabilities can solve this problem. CESS, as the first cloud storage network supporting large-scale commercial storage in Web3, is a leader in the field.

From the perspective of data storage, CESS's pioneering decentralized object storage (DeOSS) can provide users with high-frequency dynamic data storage needs with decentralized storage services that are fast in read/write, highly secure, scalable, and manage privacy. DeOSS can protect the availability and integrity of user data and allow users to truly control the ownership of their data. In other words, DeOSS can provide AI with a vast database for storage, real-time sharing, and dynamic updates, thus meeting more business needs.

From the perspective of data labeling, CESS can make AI data more useful. Through numerous innovative technologies and a meticulous multi-layer network architecture design, CESS achieves performance and user experience close to centralized cloud systems under the premise of decentralization; enabling data retrieval and return to approach millisecond levels, with overall data integrity, continuity, and reliability reaching extremes.

We believe that the combination of CESS's decentralized storage technology and AI technology can create infinite possibilities and potential.