Original Author: CloudY, Jam
Original editor: Vincero, YL
The related targets of the AI sector, whether it is A shares, US stocks or Crypto, have ushered in skyrocketing. In the following time, as ChatGPT was widely used, people realized its impact on the whole world, and there were new ChatGPT application scenarios and product iterations of the same type.
Even Microsoft, because of the acquisition of OpenAI and the embedment of ChatGPT into the Bing and Office ecology, has gained unlimited expectations from investors, and its stock price has skyrocketed. Until the emergence of ChatGPT 4, its super artificial intelligence made people calm down from the excitement, and began to think about the changes AI brought to their industry, as well as the potential risks after the further development of AI.
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productivity tools
AI can be seen as a productivity tool.Just like stone tools, steam engines, internal combustion engines, electric motors, computers, and the Internet are to humans, they can be used as tools to bring drastic changes in productivity and production relations to human society. What AI changes is productivity. It lowers the threshold of computer interaction for humans and improves the efficiency of repetitive production for humans. The former improves the quality of human life, and the latter alleviates obstacles to human development.
Specifically, AI technology has had a profound impact on many industries, such as smart manufacturing, healthcare, finance, transportation, education and other fields. Through AI technology, people can let machines learn and perform some non-creative tasks autonomously, which can improve production efficiency and reduce costs for some industries. For example, using AI to predict protein structures to develop new drugs, ESMFold trained by the Meta AI team has predicted more than 600 million metagenome proteins, showing the breadth and diversity of proteins in nature, which was unimaginable in the past.
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(From Goldman Sachs Global Investment Research)
This is the well-known AIGC, which will be more widely used in intelligent customer service, virtual human, games and other fields.secondary title
Technology Trends Guide
The current core applications of AI include general artificial intelligence, knowledge graph, data analysis and synthesis, autonomous driving and AIGC, etc.
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Knowledge map: Knowledge map is to represent various entities, relationships and attributes in the form of graphs to support applications such as intelligent search, recommendation and question answering.
Synthetic data: Synthetic data is data generated through machine learning and other AI techniques that can be used to train and evaluate AI models. For reasons such as privacy and security, real data is often difficult to obtain or share. Therefore, synthetic data can replace real data in some scenarios.
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(From Guohai Securities Research Institute)
Regardless of the statistics on the number and amount of financing in the market, or in terms of media attention, 2022 is undoubtedly the year when AIGC will explode. However, AIGC is still a relatively new technology, which is still in the early stages of exploration and development.
Specifically, the development stages of AIGC can be described as:
Research stage: Mainly focus on the basic principles and algorithms of AIGC, explore how to train and optimize models, and build databases.
Application stage: AIGC begins to be applied to various practical scenarios and begins to explore how to apply AIGC technology to specific fields.
Industrialization stage: AIGC began to be widely used in various industries and fields, forming its own industrial chain and supporting ecosystem.
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the core element
Data, algorithms, and computing power are the three core elements of AI development.
In terms of data, as AI technology continues to develop, the quality and diversity of data is becoming more and more important. In addition to massive application scenario data, it is also necessary to effectively clean, preprocess, and label the data in order to improve the training accuracy of the algorithm. In addition, cross-modal and cross-domain data fusion issues need to be considered in order to better mine the value and intelligence of data.
In terms of algorithms, the current development of AI technology is still in the process of continuous iteration and improvement. The future development trend will be mainly reflected in the multi-modality and large-scale model aspects of deep learning algorithms, as well as innovations in autonomous learning, knowledge transfer, and incremental learning. This will further improve the intelligence level and application range of AI algorithms, and promote the wide application of AI technology.
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distributed ledger
Blockchain is a decentralized distributed ledger.
First of all, Blockchain has non-tamperable properties, which come from the consensus mechanism at the bottom of the blockchain. Since the data on the chain is witnessed by block records and miners/verification nodes, and the blocks are connected back and forth and recorded continuously, smart contracts Once the on-chain data generated by the account and account is recorded by the block, it cannot be modified.
As the number of nodes increases, geographical dispersion increases, computing power increases, or the value of pledged tokens increases, the difficulty and cost of breaking consensus will become greater. Therefore, it is difficult for centralized individuals to change the recorded content.
Secondly, on the premise that it cannot be tampered with, the smart contract based on the code allows users to interact with it without trusting anyone, and the smart contract will run the code according to the preset path to achieve the corresponding operation. This makes trustless on-chain transactions possible.
At the same time, only the corresponding account can call the assets belonging to it in the smart contract, and there is no case where other accounts transfer the assets of the original account through the smart contract. And because every operation of the original account requires a signature to confirm the identity, and the first transfer interaction even needs to Approve the smart contract to retrieve the account assets. This makes the users wallet account the carrier of their best identity (DID) and assets.
Within the framework of the consensus mechanism and smart contracts, all on-chain assets and on-chain behaviors can be recorded and confirmed, and the rights and interests generated based on them can be automatically collected into the accounts of their owners. This can directly solve the problems of true and fake Monkey King and Li Daitaos rigidity. No one can steal other peoples assets through simple Copy Paste, and no one can replace the equity owner to obtain its benefits.
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Technology Trends Guide
Layer 0-2 is the hierarchical structure of the Blockchain technology architecture, and alliance chains and private chains are different types of Blockchain application scenarios.
Layer 0: Layer 0 refers to the physical facilities and network architecture of the Blockchain, including hardware devices, network protocols, and transmission media, etc., which carry the underlying role of cross-chain information and asset resolution. Currently, Cosmos, Polkadot and LayerZero are the main technical representatives.
Layer 1: Layer 1 is the basic layer of Blockchain, also known as public chain, including Bitcoin, Ethereum, etc. The protocol design and technical implementation of Layer 1 determine the basic performance and functions of Blockchain. According to the type, it can be subdivided into EVM and non-EVM systems.
Layer 2: Layer 2 refers to protocols and solutions built on top of Layer 1 to improve Blockchain performance and expand application scenarios. Layer 2 protocols currently have 6 technologies, among which ZK Rollup and Optimistic Rollup are the mainstream. These protocols can enable Blockchain to process more transactions, increase TPS and reduce Gas fee, etc.
Consortium chain: Consortium chain is a blockchain network jointly managed and controlled by multiple organizations or institutions. These organizations usually cooperate with common interests, such as banks, insurance companies, supply chain companies, etc. Unlike the public chain, the alliance chain has limited participants and a relatively small number of nodes, so its transaction speed and security have been improved to a certain extent.
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the core element
Distributed nodes, cryptography, consensus algorithms, smart contracts, and cryptocurrencies are the core elements of Blockchain development.
Distributed nodes are the core part of Blockchain technology, which enables data to be stored and transmitted in a decentralized manner. Cryptography is an important theoretical tool to ensure the security and privacy of Blockchain. In addition, the consensus algorithm is the key to Blockchains distributed consistency. A smart contract is a computer program that can be automatically executed and can execute various logical instructions on the Blockchain. Finally, cryptocurrencies, that is, the security and anonymity of transactions are guaranteed through the use of cryptography.
Through distributed nodes, all participants can have a complete copy of the data, so that the transparency and security of the data can be guaranteed. The core technologies of Blockchain - hash functions, digital signatures and asymmetric encryption are all applications of cryptography. They can help ensure data integrity and identity authentication, while also protecting user privacy.
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The Intersection of Blockchain and AI
As a part of the Blockchain industry, under the wave of AI, we also need to think: Does AI include Blockchain in the changes to the world? If yes, what would this change be? And what impact will Blockchains decentralization and power confirmation capabilities have on AI?
First of all, AI as a productivity tool can lower the technical threshold, so naturally it can also lower the technical threshold in the Blockchain industry and increase its production efficiency.
Secondly, AIGC will also free games and metaverses from stylized settings, bringing new narratives and gameplay to Blockchain.
The blockchain smart contract will be able to define the fields and scope that AI can involve, or limit the authority of AI to avoid its excessive development.
At the same time, the decentralization of Blockchain can provide AI with the resource sharing and allocation of underlying data and computing power required for training models.
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What AI Means for Blockchain
First of all, AI as a tool can lower the threshold of content creation.Let every ordinary person be able to show their creativity without technical restrictions, and output high-quality content or NFT works. This includes, but is not limited to, NFT creation, game asset creation, metaverse modeling, code building, and more.
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(from A16Z research)
Secondly, it is to lower the technical threshold of code writing.The code is divided into two directions, one is to issue projects and deploy smart contracts, and the other is to hackers or hackers. These two directions belong to the two ends of confrontation generation, that is to say, we can use AI for natural language programming and deploy the smart contracts we need, while the other party can also use AI to analyze the contract code and launch attacks. In this way, we will be able to use AI to iterate the deployed contract code, thereby forming involution and helping the entire industry to build more complete and reliable code. On this basis, you can put more thoughts on optimizing the architecture of the blockchain or designing the entire project, or on the economic model to enrich the gameplay of the project and innovate the entire business level.
Similarly, when AI simplifies the entire technical threshold, complex operations in the past will be widely used.For example, revolving loans, flash loans, optimal mining strategies, automatic income acquisition, and judgment of the exit time of top mines. The entire path can be completed by AI. AI can independently program, select the path, and deploy it directly. Just like the skill cards of Yu-Gi-Oh, we only need to use the skill cards, and then the skills will appear and produce effects by themselves. This can delegate operations that required a high threshold in the past to ordinary users. Taking MEV as an example, if we want to obtain the value of MEV, we need to write a clip robot for MEV. When ordinary people can do it, Then there is no profit margin, because when everyone can do it, they need to fight for Gas. Due to the principle of game theory, the value of MEV will be squeezed dry by the high Gas fee, which will eventually lead to unprofitability and reduce the impact of MEV . This is the decentralization of technology to force the industry to optimize.
Or to promote the popularization of blockchain technology. According to Footprint Analytics data, the current number of active Ethereum users is only 320,000, which is less than a fraction of Internet users. The biggest problem is that users do not have the need to enter the blockchain, and a small number of users who need it are also blocked by complex on-chain interactions. In addition, in the past, when uploading data to the chain or using blockchain-based tickets and certificates, it was necessary to set up a blockchain system or pay a large amount of gas fees. This cost is huge. Now, based on AI technology, we can realize blockchain construction at low cost or optimize the data usage path on the chain to reduce gas fees. Therefore, wherever rights confirmation and information transparency are required, blockchain technology can be used and smart contracts can be deployed. Therefore, the interactive system simplified by AI will bring a large number of users to the Blockchain industry.
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The Role of Blockchain in AI
There is a certain deviation between the decentralized nature of Blockchain and the centralized nature of the current AI technology development, but it is this deviation that provides a solution to the problems faced by AI.
Modern AI and big data technologies are largely centralized, that is, they are usually controlled by a few large companies or organizations, which have powerful technologies and resources, and have the power to determine market trends and user behavior. This kind of centralization makes people have to believe that AI will actually follow instructions and execute honestly when using AI. Therefore, there are certain risks and problems in the development and application of AI, such as privacy leaks, algorithm bias, data abuse, and so on.
However, Blockchains distributed and decentralized features can just solve these problems. Through smart contracts, the data sets that AI can use and the scope of operations can be limited to prevent AI from doing evil; at the same time, nodes can be established to monitor AI behavior , if it does evil, the supervisor can report and confiscate the computing power used by AI, so that AI can only do behaviors that promote human development, and prevent AI from excessive use and ultra vires.
Specifically, for the sharing and confirmation of the underlying data required for AI training, Blockchain allows users to choose whether to provide their own data for AI model training, which will require the further development of zk technology to achieve non-disclosure of personal data. Information is provided at the same time as user data. The entire process of data collection, storage and sharing will be built on decentralized nodes to ensure data security and availability, and to confirm the data source. In this way, when the AI trained and formed using these data generates income, part of the income can be given to the data owner as a dividend according to the data involved, ensuring the rights and interests of the data provider. The aforementioned generation and sharing of AI training data can also take advantage of Blockchain’s decentralization, security, and transparency features to ensure data privacy and security.
Users who provide prompts for AI operation can also obtain part of the benefits generated by calling their prompts based on their ownership of the prompts. In this way, the interests of AI data owners and AI operation prompt owners are guaranteed at the same time.
Another thing worth mentioning is computing power mining. The establishment of an AI model requires not only a large amount of data, but also computing power for training, but the computing power in the world is in short supply. Then the computing power can be centralized in a decentralized form to establish a cloud computing mining pool, subsidize the computing power provider through computing power mining, and then sell it to the training of the AI model in the form of auction, so that the limited computing power can obtain the maximum utilization rate , while ensuring the security and reliability of the calculation. More importantly, we can also integrate data, algorithms, and computing power to establish an AI as a Service protocol to provide AI model building services for users in need with its own advantages of decentralization and reusability. Then, from data acquisition, to data processing, to algorithm selection and computing power call, all are carried out through an ecology, which can avoid the risk of centralization while ensuring the advantages of the supply chain.
In addition to the construction of AI models, when we focus on the application of AI, we can find that problems such as piracy, manuscript washing, and virtual humans brought about by AIs super learning ability are not a problem in front of Blockchain. The artwork is recorded on the chain in the form of NFT, and its unique smart contract address can prove the authenticity of the artwork. In addition to the artwork itself, the value of a work of art also depends on the identity of its creator, just like the imitation of Van Goghs sunflowers by later generations is not worth a penny, and the blockchain can prove which sunflower is By Van Gogh. The knowledge graph, one of the AI applications, can also build a distributed knowledge graph based on the blockchain, and ensure that the data in it will not be tampered with, deleted or impersonated.
The problem of AI constructing avatars using personal past data can also be solved using OAT or SBT. Any behavior on the chain has a corresponding record, and the OAT or SBT created for the relevant record is also unique, and its identity can be defined based on the OAT or SBT in the account, which benefits from the immutability of the blockchain. Everything is recorded in each subsequent block, and it is impossible to fabricate behaviors that did not exist in the past out of thin air.
All in all, AI as a productivity tool can accelerate the development and popularization of the Blockchain industry, and AIGC has brought new directions and narratives to the Metaverse and NFT sectors, but AI can only replace repetitive work, lower technical thresholds, and cannot improve key technologies. innovation. Therefore, the changes AI brings to Blockchain will only stay at the application layer.
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Reference
[ 1 ] Large language model emerging evolutionary information, accelerating protein structure prediction Frontiers of Science
[ 2 ]《How AI Can Help Build Web3》crypto.com
[ 3 ] AIGC: A Revolution in Content Productivity Guohai Securities
[ 4 ]《Mastering Bitcoin》Andreas Antonopoulos
[ 5 ]《Bitcoin: A Peer-to-Peer Electronic Cash System》Satoshi Nakamoto
[ 6 ]《Ethereum White Paper》Vitalik Buterin
[ 7 ]《Challenges and Recent Advances》Blockchain-Based Payment Channel Networks
[8] Thoughts on The Impact of AI Explosion on Creators and NFT
[9] AIGC Dilemma and the Way to Break the Web3 Circle
[10] Beyond Web3, the Fantastic Drifting of AIGC, the New Favorite of Capital
