人工智能区块链项目有哪些,人工智能区块链项目名称

近年来，人工智能和区块链技术在金融、医疗、智能制造、教育等领域发挥着越来越重要的作用。这两种技术的结合，可以帮助企业更好地实现数据安全和智能化，从而改善企业的效率。下面，就让我们来看看，当前市面上有哪些人工智能区块链项目：

1. 智能合约项目： 智能合约是基于区块链技术的一种程序，能够自动执行指定的规则，比如自动执行交易、自动执行投票等。比特币的智能合约项目是最著名的，它将智能合约技术应用到了比特币的交易中。

2. 智能供应链管理项目： 这是一种基于区块链技术的智能供应链管理项目，旨在帮助企业更好地管理和维护其供应链，从而提高企业的效率。这种项目运用了人工智能技术，可以帮助企业更好地管理其供应链，从而提高企业的整体效率。

3. 智能金融项目： 智能金融是一种基于区块链技术的金融服务，它可以帮助企业更好地管理其财务，从而提高企业的效率。这种项目运用了人工智能技术，可以帮助企业更好地管理其财务，从而提高企业的整体效率。

4. 智能医疗项目： 这是一种基于区块链技术的智能医疗项目，旨在帮助医疗机构更好地管理其病人的信息，从而提高医疗机构的效率。这种项目运用了人工智能技术，可以帮助医疗机构更好地管理其病人的信息，从而提高医疗机构的整体效率。

5. 智能教育项目： 这是一种基于区块链技术的智能教育项目，旨在帮助学校更好地管理其学生的信息，从而提高学校的效率。这种项目运用了人工智能技术，可以帮助学校更好地管理其学生的信息，从而提高学校的整体效率。

以上就是当前市面上最常见的几种人工智能区块链项目，它们能够帮助企业更好地实现数据安全和智能化，从而改善企业的效率。如果您有兴趣，也可以尝试一下这些项目，看看它们能够为您带来什么样的收获。

Ⅰ Blockchain and artificial intelligence: a perfect match

Blockchain and artificial intelligence are the two hottest technology trends at present. Although the two technologies have highly different developers and applications, researchers have been discussing and exploring their combination.

PwC predicts that artificial intelligence will add $15.7 trillion to the world economy by 2030, so global GDP will grow by 14%. According to Gartner's forecast, the business value brought by blockchain technology will increase to US$3.1 trillion in the same year.

By definition, a blockchain is a distributed, decentralized, immutable ledger used to store encrypted data. Artificial intelligence, on the other hand, is the engine or “brain” that enables analysis and decision-making from collected data.

It goes without saying that each technology has its own level of complexity, but both artificial intelligence and blockchain are in a position where they can benefit and help each other.

Since both technologies can influence and act on data in different ways, their combination makes sense and can take data utilization to the next level. At the same time, integrating machine learning and artificial intelligence into blockchain, and vice versa, can enhance the infrastructure of blockchain and enhance the potential of artificial intelligence.

In addition, blockchain can make artificial intelligence more coherent and understandable, and we can track and determine why decisions are made in machine learning. Blockchain and its ledger can record all the data and variables used to make decisions under machine learning.

In addition, artificial intelligence can improve the efficiency of blockchain better than humans. As evidenced by a look at the way blockchain is currently run on standard computers, even basic tasks require significant amounts of processing power.

Intelligent computing power

If you want to run a blockchain and all its encrypted data on a computer, you need a lot of processing power. For example, the hashing algorithm used to mine Bitcoin takes a "brute force" approach, which is to systematically enumerate all possible candidates for a solution and check whether each candidate satisfies the problem statement before validating a transaction.

Artificial intelligence provides us with an opportunity to get out of this dilemma and handle tasks in a more intelligent and efficient way. Imagine a machine learning-based algorithm that, if given the proper training data, can actually improve its skills "in real time."

Create diverse data sets

Unlike artificial intelligence-based projects, blockchain technology creates a decentralized, transparent network where anyone around the world can Access these networks in a public network environment. Although the areaBlockchain technology is a ledger for cryptocurrencies, but blockchain networks are now being used in many industries to enable decentralization. For example, Singuarlitiynet is specifically focused on using blockchain technology to encourage wider distribution of data and algorithms, helping to ensure the future development of artificial intelligence and the creation of “decentralized artificial intelligence.”

SingularityNET combines blockchain and artificial intelligence to create a smarter, decentralized artificial intelligence blockchain network that can host different data sets. By creating an application programming interface on the blockchain, it will allow AI agents to communicate with each other. Therefore, different algorithms can be built on different data sets.

Data Protection

The development of artificial intelligence depends entirely on the input of data - our data. Artificial intelligence receives information about the world and what is happening in the world through data. Basically, data is the source of AI, and through it, AI will be able to continuously improve itself.

Blockchain, on the other hand, is essentially a technology that allows data to be stored encrypted on a distributed ledger. It allows the creation of fully secure databases that can be viewed by approved parties. When blockchain and artificial intelligence are combined, we have a backup system for backing up an individual’s sensitive and high-value personal data.

Medical or financial data is too sensitive to be handed over to a company and its algorithms. This data is stored on a blockchain that can be accessed by artificial intelligence, but only with permission and through appropriate procedures, to provide us with personalized recommendations while safely storing sensitive data.

Data Monetization

Another disruptive innovation that may come from combining these two technologies is data monetization. For big companies like Facebook and Google, monetizing the data they collect is a huge revenue stream.

Letting others decide how data is sold to generate profits for businesses shows that data is being commercialized, and to our detriment. Blockchain allows us to cryptographically protect our data and use it however we see fit. This also allows us to personally monetize the data if we choose, without compromising our personal information.

The same goes for artificial intelligence programs that need our data. In order to learn and develop AI algorithms, AI networks will be required to purchase data directly from their creators through data marketplaces. This would make the entire process fairer than it is now, and no tech giants can take advantage of its users.

Such a data market will also be open to small companies. Developing and delivering AI is prohibitively expensive for companies that don't generate their own data. Through a decentralized data marketplace, they will be able to access otherExpensive and privately kept data.

Trusting AI Decisions

As AI algorithms become smarter through learning, it will become increasingly difficult for data scientists to understand how these programs arrive at specific conclusions and decisions. This is because AI algorithms will be able to process incredibly large amounts of data and variables. However, we must continue to review the conclusions drawn by AI because we want to ensure they still reflect reality.

By using blockchain technology, all data, variables and processes used by artificial intelligence in decision-making have an immutable record. This makes the entire process of auditing much easier.

Through appropriate blockchain procedures, all steps from data input to conclusion can be observed, and the observing party will ensure that the data has not been tampered with. It allows people to trust the conclusions drawn by artificial intelligence. This is a necessary step because individuals and companies won’t start using AI applications if they don’t understand their capabilities and the information underlying their decisions.

The combination of blockchain technology and artificial intelligence remains a largely undiscovered area. Although the fusion of these two technologies has received considerable academic attention, there are still few projects dedicated to this groundbreaking combination.

Combining these two technologies has the potential to use data in ways never before possible. Data is a key element in developing and enhancing AI algorithms, and blockchain protects this data, allowing us to audit all the intermediate steps by which AI draws conclusions from the data, and allows individuals to monetize the data it generates.

Artificial intelligence can be incredibly revolutionary, but it must be designed with extreme care—and blockchain can help a lot with that. How the interplay between these two technologies will develop is anyone’s guess, however, its true potential for disruption is clearly present and developing rapidly.

II What is the relationship between blockchain and artificial intelligence

Blockchain and artificial intelligence have many potential correlations and interactions. They can promote each other and make up for defects, thus Make progress together.

On the one hand, at the application level, artificial intelligence technology Liang Suichen can provide the blockchain platform with more complete data processing and analysis capabilities. For example, artificial intelligence technology can help blockchain platforms conduct large-scale data mining and analysis, discover hidden correlation patterns and trends, and improve data processing efficiency and security. At the same time, blockchain technology can also provide a more accurate, real-time, and credible data source for artificial intelligence algorithms by establishing a decentralized, non-tamperable data storage and transmission mechanism, further improving its decision-making and prediction capabilities.

On the other hand, at the technical research level, blockchain technology and artificial intelligence technology also have the possibility of integrating with each other and accelerating development. For example, some researchers refer to blockchain technology asIt should be used in the decentralized artificial intelligence training and data collaboration process to solve the problems of privacy protection, data traceability and other issues in the current artificial intelligence field; some researchers are exploring how to use artificial intelligence algorithms to optimize and accelerate The blockchain transaction confirmation and on-chain data verification process further improves the development efficiency and security of blockchain technology.

In short, in the field of cross-application of blockchain and artificial intelligence, they can promote and support each other, and produce more complex and diversified technological innovation combinations, which can contribute to the development of the digital economy and enterprises. Have a positive impact.

Ⅲ Blockchain and artificial intelligence will become peerless twins in the future

Blockchain and artificial intelligence will become peerless in the future Shuangjiao
Our current era needs change and innovation, and blockchain, artificial intelligence, and new retail are the products of the innovation of the era that have become popular in recent years. These are all things that we are proud of. of. Blockchain and artificial intelligence have become the two most discussed concepts in 2018. Blockchain and artificial intelligence, both have loyal supporters in various industries. Which technology better represents the future development direction of technology?
In the past year, blockchain has An epoch-making technology has entered the public eye dazzlingly. It is considered to be the most likely technology to bring about disruptive changes at present, and is enthusiastically pursued by venture capital and capital with keen sense of smell.

Whether AlphaGo beats the human Go world champion, unmanned supermarkets open stores, or self-driving cars continue to hit the road, artificial intelligence has become the protagonist of daily news. With Google announcing the establishment of AI China in China Center, promoting the development of artificial intelligence has been written into the government work report. Today, China has become a major player in the world's artificial intelligence industry. 2017 was a wonderful year and was called the "first year of application" of blockchain and artificial intelligence. It can be predicted that blockchain and artificial intelligence will still be in the spotlight in 2018, attracting great attention from all parties.
So what exactly are blockchain and artificial intelligence? Blockchain is a decentralized medium that brings an innovative value storage and circulation model, while artificial intelligence makes machines like humans Create value, it is a new value creation system. Therefore, blockchain represents the future production relations, and AI represents the future productivity. From the popularity of "blockchain at three o'clock" in the circle of friends in the early morning, to the 2018 government work report's extensive explanation of artificial intelligence and blockchain, these two cutting-edge technologies that have firmly captured people's attention are so different. So much so that any attempt to combine the two will inevitably arouse the curiosity and doubts of the world.
Blockchain and blockchain technology are two different circles. We often say that the currency circle and the chain circle are a common division. The currency circle discusses the growth value of the currency, while the chain circle discusses the Pure technology, so sometimes it is said that the concept of blockchain is greater than blockchain technology. Actually blockChain technology is relatively not difficult, and its technology can be used in many places, but it is precisely its technology that sometimes limits its development. On the contrary, the problem faced by artificial intelligence is how to coexist with humans. Artificial intelligence is promoting the progress and development of the times in many aspects, but human society is not really ready to welcome the arrival of the era of artificial intelligence, whether it is in terms of human consciousness, ethics, laws and regulations, or social management. There is still a long way to go.
The rapid advancement of artificial intelligence technology forces humans to develop further and innovate continuously instead of standing still.

IV Discussing technological changes - the evolution of artificial intelligence, the Internet of Things, and blockchain

I have read a lot of reports about blockchain recently and feel that blockchain is very popular. It has many similarities with the popularity of artificial intelligence and the Internet of Things. The following are some personal opinions:

1. The emergence of artificial intelligence, the Internet of Things, and blockchain are all human exploration of the future.

Human beings are a very peculiar group. There will always be a group of people who will find an exit in our era, so that we can feel that society is functioning normally. Because of the explosion of technology, people's desire for innovation is unprecedented. Regardless of the outcome, the starting point of these desires is always good.

On the one hand, the popularity of artificial intelligence is due to the development of these three aspects, which we often call deep learning, big data, and computing power; on the other hand, the Internet has been developing for decades and requires new technologies. Things emerge to take over the consequences of the development of the Internet, such as big data and some inefficient Internet mechanisms. The Internet has been developing for so many years, and during this period we can also see some new things being invented or mentioned, such as the Internet of Things. However, it gradually faded over time. At the beginning, when the Internet of Things appeared, many people thought that the Internet of Things was the next exit for mankind after the Internet. Later, many problems emerged, such as limitations in data processing capabilities and limitations in sensor intelligence, and the Internet of Things was gradually marginalized. Then came the emergence of solutions to problems in the development of the Internet of Things - artificial intelligence.

On the whole, the development of these technologies has either been truly successful, or it has led to some new problems, and the solutions to these new problems have formed new technologies. This reminds me of what Mr. Wang Qiang of ZhenFund said: It is the questions, not the answers, that change the world.

After so many years of development of human society, there is always a problem that needs to be solved, and that is decentralization. It is worth explaining that the blockchain is not completely decentralized, but only an improvement in efficiency, which also has costs. Many media reports today are misleading in themselves.

2. Who is the next exit between blockchain and the Internet of Things?

The author believes that the Internet of Things is the next exit for mankind. Compared with blockchain, the Internet of Things is more likely to become a new outlet, because the previous wave gave it certain advantages in policy, and compared with the Internet, the Internet of Things is a decentralized network. Here is an explanation of what a decentralized network is. The Internet is a platform-centric network. Communication between people must be concentrated on a platform. This platform is what we often call a trust mechanism. The Internet of Things is a decentralized network. Sensor devices self-organize into a network. This network node is no longer an enterprise or a platform. In other words, the platform distributes and optimizes centralized rights, making each node possible to become the center.

As for the blockchain, the decentralization that its core technology demands is still too urgent. However, in some fields, this kind of decentralization demand is still welcome, such as finance, house leasing and other business needs that are suitable for the p2p model. The author believes that the biggest reason why the next exit is the Internet of Things is that compared to the blockchain, the decentralization of the Internet of Things is softer.

3. Artificial intelligence, the Internet of Things, and blockchain will eventually be applied to life.

This sentence may sound a bit nonsense. However, the premise that technology can be applied to life is that the technology itself can solve a series of problems that exist in life. From an economic point of view, all technologies revolve around two words: efficiency. No matter how people view artificial intelligence, the Internet of Things, and blockchain today, one thing is certain: existence is value.

As for the time dimension, we can feel or see that after more than a year of hype, artificial intelligence is gradually being implemented in the industry. Personally, 2018 should be the first year for artificial intelligence to embrace the industry. On the one hand, technology companies and traditional companies are also actively cooperating. On the other hand, new media related to artificial intelligence are also promoting the implementation of artificial intelligence, such as: New Wisdom.

Needless to say about the Internet of Things, the previous government also favored the Internet of Things in policy formulation and related planning. Moreover, in the past few years, commercial applications of the Internet of Things have been developing well. But, it's not as good as I thought before. I believe that with the cooperation of artificial intelligence, the Internet of Things industry will develop rapidly in the future.

For blockchain, it may take a long time to eliminate the bubble. Today’s blockchain bubble is too serious. In addition to market bubbles, blockchain also has to face very severe challenges. Supervision, these issues will take a long time to resolve. Personally, I think it will take longer for blockchain to be implemented in the industry than artificial intelligence. As for many companies today, it is better to concentrate on doing things than to join in the fun. When supervision is unclear, problems are prone to arise in joining the heat.

IV What is data annotation?| "Artificial Intelligence + Blockchain" Popular Science Question 5

When the previous question talked about deep learning, we mentioned a very key term: data annotation.

To explain clearly what data annotation is, we have to mention the special group of "data annotators". The term "artificial intelligence" may seem unfathomable, but the big data collection work currently provided for machine learning is still based on the labor-intensive artificial intelligence data annotation industry. The content of those people who sit in front of computers and are called "workers behind artificial intelligence" every day is actually not fundamentally different from many assembly line workers in the 1980s.

This is a fact and there is no need to argue.

According to incomplete statistics, the number of "data annotators" employed nationwide has reached 100,000, and the number of part-time workers is close to 1 million.

Behind the scorching and shining artificial intelligence, the data annotation industry, as a basic support, appears to be extremely rough and unsophisticated. No wonder some people say: The so-called artificial intelligence means that there is as much intelligence as there are artificial people.

So what exactly is data annotation?

To understand data annotation, you must first understand that artificial intelligence actually partially replaces human cognitive functions. Think back to how humans learn. For example, when we were young and we knew apples, our mother came to you with an apple and told you that it was an apple. When you meet an apple again in the future, you will know: Oh, this big, red, sour and sweet thing is called "apple".

By analogy with machine learning, we have to teach the machine to recognize an apple, but of course it cannot taste it. We can only give it a picture of an apple, and of course the machine can’t understand what it is! We must first have a picture of an apple with the word "apple" labeled on it and then give it to the machine to learn. Although the machine has fast processing speed and good memory, its IQ is almost zero in terms of association, analogy and inferences. The machine has learned the apple in picture A, but if you take another apple picture B that the machine has never learned before, it may not recognize it. Because we say that there are no two identical leaves in the world, then naturally there are no two identical apples. then what should we do? We learn a large number of different apple pictures for the machine, let the machine capture the features in these same annotations, and then give the machine a strange applepicture, it might be able to recognize it.

Suppose we have 1,000 pictures labeled "Apple", then we can take 900 pictures as the training set and 100 pictures as the test set. The machine learns a model by capturing the features in 900 apple pictures, and then we identify the remaining 100 pictures that the machine has not seen. Then we can test the machine's recognition through the learning of the previous 900 pictures. How accurate is Apple?

In short, data annotation is when humans use computers and other tools to classify, frame, annotate, mark, and label various types of data including text, pictures, voices, videos, etc. Properties of labels work.

Artificial intelligence is fed by big data, and data annotation is a very important part of forming valuable massive data. How to efficiently motivate and organize more people to participate in data contribution will be the key to the success of future technology companies.

Next issue: What is a knowledge graph? | "Artificial Intelligence + Blockchain" Popular Science Question 6