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Telegraph: The owner of West Ham has no intention of selling the team, and the top management of the team trusts moyers.

Live on March 11th According to the Daily Telegraph, the owner of West Ham has no intention of selling the team, and the top management of the team now trusts moyers.

It is reported that David Sullivan, the owner of West Ham, said that he has no intention of selling the team, which means that moyers’s job is safe at present. At present, West Ham still has 13 games to play in the Premier League, and the fans of the team are still full of hope for West Ham. Although West Ham is currently only 16th in the Premier League standings, they are confident that they can change the current situation.

For a long time, it has been thought that Czech billionaire Clay Tynsky, who owns 27% of the club, will launch the acquisition of West Ham, but if Clay Tynsky wants to launch a comprehensive acquisition, he must obtain the consent of David Sullivan (holding 38.8%) and the family of the deceased co-owner David Gold (holding 25.1%) before starting the acquisition process. Logically speaking, Clay Tynsky is unlikely to make an offer at present, because the current situation of West Ham in the Premier League is still unclear, and if relegated to the Championship, it will obviously affect the value of the club. In addition, even if it is sold, David Sullivan will not sell West Ham at a low price. According to sources, David Sullivan has no intention of selling West Ham, and he has not even considered doing so.

West Ham are currently playing in the UEFA, and they are facing teams with average strength in this level of European war, which is completely different from their opponents in the Premier League. In last week’s UEFA competition, they beat AEK Larnaca 2-0 away, which was their ninth consecutive victory in this competition. If West Ham can win this tournament, it will be the team’s first European trophy since 1965, and more importantly, it will also ensure their qualification for the Europa League next season. However, West Ham’s performance in the Premier League is somewhat disappointing. They have not won in the past eleven away games. Although the fans shouted moyers’s dismissal after West Ham’s 4-0 defeat to Brighton, as far as the current situation is concerned, moyers’s position is still very stable. However, according to relevant media reports, West Ham is currently considering short-term and long-term substitutes to replace moyers, and Nuno Espirito Santo, Benitez and Dych are all considered as potential choices.

Moyers has one year left on his contract with West Ham, and they may end their cooperation with moyers when his contract expires. Last summer, West Ham invested 160 million pounds in the transfer market, which is the third highest transfer expenditure in the Premier League. In addition, West Ham signed Danny Ince in the winter window that year. People hope that West Ham can challenge the qualification of the Champions League instead of struggling to avoid relegation. Moyers’s team has been plagued by injuries this season, and his tactics have been questioned by people. However, the team’s offensive line scored only 23 goals in 25 games, which really made him feel a little overwhelmed. However, West Ham hopes that moyers’s experience will help the team overcome the difficulties and try to win a trophy.

Premier League: Newcastle VS Wolves. Wolves have an outstanding ability. Is it difficult for Newcastle to play an advantage?

I just wrote a German B game, and everyone should have seen it. Here, let’s talk about another Premier League focus game, Newcastle versus Wolves!

I talked to Wolves several times this season, and each time they were injured at least three or four times in the front line. Last November, it was the most serious. One game was short of five strikers, playing Tottenham Hotspur, and Wolves injured Diego Costa. Jimenez has recently returned. Although he hasn’t scored yet, he has gained an assist by playing Fulham, and his contribution has surpassed that of other Wolves centers by playing the threat made by Tottenham Hotspur.

As we all know, Wolves’ lack of forward power is very prominent this season, and Everton gave them the bottom before, but after these two games, Everton also overtook them, and Wolves finally became the team with the least goals in the Premier League.

They struggled out of the quagmire of the relegation zone, and now they have risen to the 13th place in the standings, mainly relying on the defensive end. Wolves have always been good at defense, and they are even more conservative when they are guests. They won’t let go of the attack when they play Southampton and Everton. Today, they challenge Newcastle in different places, and there is no accident or the main tone of defense. The two flanks of Wolves are the key to their solid defense and threat.

Under the training of winger Loppert Ji, Wolves’ two wingers are very strong, and playing Tottenham Hotspur on the court is a good manifestation of two points. First, they can limit their opponents’ cross, especially in the second half, it is difficult for Kane to get in touch with his teammates; Second, the Wolves’ goal came from Moutinho’s possession of the ball and his assignment to the wing, which effectively opened the defence of Tottenham, and then found an angle to hit the door quickly, which made Tottenham suffer.

Today, Newcastle, which they are going to play, is also a team that relies on a large number of wingers to attack.

In the game, St. Maximin relies on the support of Qiao Lin and Dan Bourne to dominate the left impact, while Almiron draws on the right side, and Trippier takes on the task of crossing the ball from the side or rib part. This combination is Eddie Howe’s most conventional offensive strategy.

However, there is little quick linkage between Newcastle’s two wingers. Usually, they finish on one side, pass the ball back to the middle and split the side again, thus completing the change of attack direction. In this way, the opponent will have enough space and time to complete the defensive position selection and coordination.

Therefore, we can see that Newcastle can only score in the middle of the Premier League in the case of strong impact, which has seriously dragged down their progress. Today, Wolves, with good defense and strong wingers, may not play easily.

What’s more, Newcastle are short of suspended Jorington today, and Scheer may not be able to play. Jolington played like a duck to water after being transformed into a midfielder, and was successfully elected as the MVP player in February. He has both physical fitness and speed, and he has a strong sense of position. He can form an effective strong point in Newcastle midfield and support the impact of St. Maximin, which is the key to Eddie Howe’s tactical implementation. Without him, Newcastle’s left threat will drop a lot.

As for Fabian Schell, the defense is also quite stable this season. His air confrontation ability is the strongest in the team, and he can also serve the ball. His long-range shooting ability is excellent. Without him, the loss may not be limited to the defensive end.

As we all know, Newcastle are the team with the fewest goals conceded in the Premier League, with a strong defense, and goalkeeper Pope is also the goalkeeper with the most goalkeepers in the Premier League. According to the front line of Wolves, it is really too difficult to break their goal.

But as we said earlier, Newcastle’s attack problem is also relatively objective. Under the restriction of Wolves’ flank, it may not be so easy for Newcastle to play an advantage. It is my current opinion that Newcastle will join Wolves or shake hands with both sides. What’s your opinion?

The ultimate chat computer chats and finds that it has surpassed human beings. What will the future world be like?

Recently, there is a very hot thing called ChatGPT (Chinese is called chat generation pre-training transformation model). In fact, it is an AI artificial intelligence chat robot program.

It was born as hot as a supernova explosion, surpassing Apple, Google and Tesla. . .

So I also tried to chat with it for a day, looking for all kinds of questions and soul torture to see how this artificial intelligence is different from the previous one.

Chinese is an abstruse language, especially ancient Chinese, which is difficult for ordinary people to understand, let alone create.

So I gave GPT a question with reading+creation. The GPT answers as follows:

Preface to Linjiangxian-Tengwang Pavilion

The mountains and rivers here are also wonderful. The prosperity of the river table is beautiful! People who are on the outside are more lovely. If you don’t believe me, look at the height of this pavilion. There are clouds under the sky, and the water of the Yangtze River and the beach of white sand stones are fascinating. The people on the pavilion are so intoxicated that in the middle of the night, it seems that they can go straight to the sky, board the heavens and see the four seas.

However, I feel this way. As soon as I get here, I have deeply felt the culture of the river table, and its depth is as deep as the sea. Scholars, poets and singers, all have their own character and stand out from the rest of the world. Not only Huan Yi, Yang Zun and others, but also Shao Minghuang’s talents, Jin Dynasty and Tang Dynasty, all of them took advantage of this piece of land and became famous all over the world.

I have been admiring it for a long time since I lived here. Every desire to cultivate Tao Zhu, keep humble, in order to achieve. And repeatedly in the middle of the night, intoxicated with the joy of literati, listening to the talents of the group, quite emotional. Today, thanks to a visit, I paid a visit to this pavilion with reverence and opened a new chapter.

Linjiangxian, the name of the immortal, came here this time, like a fairy tour. Looking through your literature and listening to the words of literati, my heart is happy and I can’t help myself. The ink in the pen, unexpectedly from the initial sloppy, gradually to the magnificence, profound meaning, magnificent. It’s not surprising that it’s a one-step show.

Is to give it, spare time, come here. It’s not an insult to visit, nor is it a superficial move. If you want to talk about it, you can only encourage everyone with the origin of culture and the culture of Jiangnan. I hope that in the future, we can learn from each other and make progress together in cultural exchanges, so as to inherit the aspirations of our ancestors and achieve the great cause of Chinese civilization.

No typos or grammatical mistakes were found in the whole passage. The level has surpassed that of human (me) [covering my face]. . .

I found a math problem in the college entrance examination online, and GPT quickly gave an answer. . . I don’t know if there is anything wrong [covering my face] because I don’t understand anything except Chinese.

ChatGPT’s development company, OpenAI, has another professional AI painting program, Stable Diffusion, but it only supports inputting English prompts. If English is not good, there will be many difficulties in creation.

But now that I have GPT, I chat with it and tell it my own painting idea. Then I ask it for hints, and copy the hints into the stable difference, resulting in the following works. . .

There’s a dialogue in the 139th sentence of the comic book "The Demon Discharger at the End", which is a bit difficult. I’ll test it.

At the same time, compared with other translation software, GPT not only translated the literal meaning, but also showed the meaning it understood. . . Moreover, the dialog box of AI has no word limit, and it can translate an article, a contract or even a book.

program

GPT can also be programmed directly. I tell it the idea, and then it starts to "create" a game for me.

I wrote a large piece of code "beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep beep. So the first game I created was born. . .

After a night of testing, I found that this GPT has existed in different dimensions compared with the previous artificial intelligence software (siri and the like) [stunned]

In fact, there are many things GPT can do, such as reading contracts, generating contracts, making PPT of tabular data, writing articles and writing scripts. . . Too much, too much. . .

ChatGPT was born only three months ago, and it is still evolving. Every question and answer is training and learning for GPT.In this regard, Google has issued a CODE RED alert, which is the first time in Google’s history, which is equivalent to a country being threatened by nuclear weapons. Major technology companies have said that they want to release their own AI products. . .

If a new scientific and technological revolution is coming, it must be an artificial intelligence revolution. I don’t know what the world will become in the future. I just hope that artificial intelligence can help human civilization evolve at a higher speed. (End)

Italian media: Rome has raised the offer of salary reduction and renewal for smolin, and the new annual salary is the same as at present.

Live on March 12, according to the report of Il Tempo, Rome has raised its offer to renew smolin’s contract, and the current annual salary for renewal is the same as that of the existing contract.

Roma don’t want to lose smolin, and his contract will expire at the end of the season. According to "Il Tempo", Rome has sent an important signal that they have raised their previous offer for renewal.

Rome has offered a two-year contract before, but the annual salary is lower than the current 3.5 million euros.

Considering that the player wants to stay, Roma decided to offer a two-year contract at the current annual salary, and the bonus is very easy to get.

(Stewed Sydney with rock sugar)

Where to study abroad? Stanford University has become the first choice for many China students for the following reasons.

Stanford University is a world-famous private research university located in Stanford, California, USA. Founded in 1885, it is widely regarded as one of the most prestigious universities in the world. It is famous for cultivating some of the most talented and influential graduates. Its world-class research facilities and strong concern for innovation are only part of the reasons why students from all over the world flock to its hall every year.

1. Close to Silicon Valley

One of the most striking aspects of Stanford is its proximity to Silicon Valley, the center of the technology industry. This proximity means that students can take advantage of the huge network of technology companies and startups in the region, many of which are actively recruiting graduates from Stanford University. For example, many graduates continue to work for companies such as Google, Apple and Facebook, just to name a few. In addition, many students started their own technology companies while studying at Stanford University, and the university provided them with the support they needed to start their own businesses.

2. Interdisciplinary research

Another advantage of Stanford University is its emphasis on interdisciplinary research. The university is firmly committed to interdisciplinary cooperation and encourages students to pursue their interests in various fields. This enables students to get a comprehensive education and prepare them for a wide range of careers. In addition, the university’s partnership with local enterprises, governments and other organizations means that students can obtain a huge network of resources to help them further achieve their research goals.

3. At the forefront of cutting-edge research

Stanford University is also famous for its commitment to cutting-edge scientific research. The university has a rich history of innovation, and its faculty and students have made many pioneering contributions in the fields of science, engineering and medicine. For example, in the early days of the Internet, researchers at Stanford University played an important role in developing ARPANET, the predecessor of the modern Internet. Recently, researchers at Stanford University have been at the forefront of artificial intelligence, robotics and biotechnology.

4. Advantages of artificial intelligence

One of Stanford’s most striking scientific research achievements is its work in the field of artificial intelligence. In recent years, the university has been at the forefront of the progress of deep learning, which is a subset of artificial intelligence and has been proved to be very effective in solving complex problems. For example, researchers at Stanford University have developed a deep learning algorithm that can accurately diagnose diseases based on medical images and translate speech from one language to another with high precision. These advances have the potential to completely change many industries and improve the lives of millions of people around the world.

5. Characteristics of robot field

In addition to its work in artificial intelligence, Stanford University is also famous for its cutting-edge research in the field of robotics. The university has a long history of innovation in this field, and its researchers are at the forefront of developing new and improved robots for wide applications. For example, researchers at Stanford University have developed robots that can perform complex tasks in dangerous environments, such as exploring deep-sea trenches or defusing bombs. These advances may greatly improve the safety and efficiency of many industries.

In a word, Stanford University is a world-renowned research institution, which is highly respected for its commitment to interdisciplinary research, attention to innovation and breakthrough scientific achievements. Its location in Silicon Valley provides students with unparalleled opportunities to enter the technology industry, and its partnership with local organizations means that students can obtain a huge network of resources. With great emphasis on scientific research and commitment to interdisciplinary cooperation, Stanford University is an ideal place for students interested in pursuing a career in science, engineering or medicine.

Life and work are the same, and the robot provides you with perfect service!

Baidu launched the AI chat robot service "Wen Xin Yi Yan", what impact has it brought to people’s lives? Let’s discuss it.

First of all, this chat robot can make people get information more conveniently. Through the dialogue with robots, people can quickly get the information they need, without having to search and filter it themselves as before, saving a lot of time and energy.

In addition, this robot can answer all kinds of questions in a conversational way, whether it is writing code to correct bugs, answering scientific questions, or writing papers and articles.

Chat robots can solve people’s questions in some professional fields. For example, in the medical field, people can get their own health status through conversations with chat robots, or consult the treatment plans for some common diseases.

In the field of education, chat robots can be used as an auxiliary teaching tool to help students solve problems in their studies or provide some learning resources.

In addition, the chat robot can also be used as an intelligent customer service to help enterprises solve the problems of customer feedback and complaints.

In a word, the appearance of chat robots can not only facilitate people to obtain information, but also be applied to various fields to help people solve various problems.

In the future, the development of chat robots will become more and more intelligent and personalized, and become an indispensable part of people’s lives.

Secondly, Wen Xin can become people’s intelligent assistant in a word. This robot can provide people with speech recognition, intelligent translation, speech synthesis and other functions, which can help people communicate better and cross language barriers. In addition, Wen Xin Yi Yan can also be used as an entertainment tool to play games, chat and share fun.

Wen Xin Yi Yan has a wide range of entertainment functions, which can provide users with a variety of chat modes, such as simple question-and-answer games and simulated chatting with users. At the same time, this robot can also generate various types of interesting content, such as songs, jokes, poems, etc., so that users can enjoy more entertainment in their leisure time.

In addition, Wenxin can also combine virtual reality technology to create a more realistic virtual experience for users. For example, users can experience immersive travel scenes, participate in virtual reality games and so on through Wenxin.

On the whole, Wen Xin Yi Yan is not only a practical intelligent tool, but also provides users with more colorful entertainment experiences, making their lives more convenient and interesting.

With the rapid development of artificial intelligence technology, robots play an increasingly important role in people’s lives. However, compared with the convenience it brings, people also need to pay attention to the risks that robots may bring. First of all, it is very important to protect the security of personal information.

When using a robot like Wenxin Yiyan, people need to be careful not to disclose their sensitive information, such as bank account information and personal identity information. If this information falls into the hands of criminals, it will cause huge property and spiritual losses.

Secondly, the robot’s answer also needs to be verified. Although such a robot as Wenxin Anya has powerful natural language processing ability, it is still a program written based on programming language. Therefore, its answer may be limited by the program code, resulting in misjudgment and other problems.

Finally, with the continuous progress and update of technology, people need to know and learn the latest technologies and functions in time. Only in this way can we make better use of these robots and make better use of their convenience and advantages. Therefore, when using a robot like Wen Xin Yi Yan, we need to be vigilant, understand the advantages and disadvantages of the robot, and use and control it appropriately.

In short, Baidu’s chat bot service "Wenxin Yiyan" has brought a lot of convenience and possibilities to people’s lives, and we expect it to be constantly improved and innovated in the future development.

When two siri start to communicate, do they talk to each other?

Produced by Tiger Sniffing Technology Group

Author | Qi Jian

Editor | Chen Yifan

Head picture | |FlagStudio

"One morning, your AI assistant sent me an interview invitation, so I asked my AI assistant to handle it. The latter thing was done by two AI systems. After many rounds of dialogue between them, the date was finalized and the conference room was booked. There was no human participation in the whole process. "

This is Michael Wooldridge’s picture of the future. He is a British AI scientist and is currently a professor of computer science at Oxford University.

What will happen to our society when artificial intelligence can communicate with each other?

During the one-hour conversation, woodridge was very interested in this topic. He is one of the top scholars in the world in the research of multi-agent systems, and "collaboration between AI" is his key research direction.

In Wooldridge’s view, although artificial intelligence has become more and more like human beings and even surpassed human beings in some fields, we still have a long way to go from real artificial intelligence, whether it is AlphaGO, which defeated human beings, or ChatGPT, which answered like a stream.

When most people are immersed in the phenomenal innovation created by OpenAI, Wooldridge appears much calmer. ChatGPT shows the power of neural network, but also shows its bottleneck-it can’t solve the huge power consumption and computing power problem, and the unsolvable AI "black box" problem."Although the deep neural network can often answer our questions perfectly, we don’t really understand why it answers like this."

AI that surpasses human beings is often called "strong artificial intelligence", while AI with universal human intelligence level is called Artificial general intelligence (AGI).Wooldridge described AGI in his book "The Complete Biography of Artificial Intelligence": AGI is roughly equivalent to a computer with all the intellectual abilities possessed by an ordinary person, including the abilities of using natural language to communicate, solve problems, reason and perceive the environment, and it is at the same or higher level of intelligence as an ordinary person. The literature about AGI usually does not involve self-consciousness or self-consciousness, so AGI is considered as a weak version of weak artificial intelligence.

However, the "weak" AGI is far from the contemporary artificial intelligence research.

"ChatGPT is a successful AI product. It is very good at tasks involving language, but that’s all. We still have a long way to go from AGI. " In a conversation with Tiger Sniff, woodridge said that deep learning enables us to build some AI programs that were unimaginable a few years ago. However, these AI programs that have made extraordinary achievements are far from the magic to push AI forward towards grand dreams, and they are not the answer to the current development problems of AGI.

Michael Wooldridge is a leading figure in the field of international artificial intelligence. He is currently the dean of the School of Computer Science of Oxford University, and has devoted himself to artificial intelligence research for more than 30 years. He served as the chairman of the International Joint Conference on Artificial Intelligence (IJCAI) from 2015 to 2017 (which is one of the top conferences in the field of artificial intelligence), and was awarded the highest honor in the British computer field-the Lovelace Medal in 2020, which is regarded as one of the three influential scholars in the British computer field.

ChatGPT is not the answer to building AGI.

Before the appearance of ChatGPT, most people thought that general artificial intelligence was very far away. In a book entitled "Intelligent Architecture" published in 2018, 23 experts in the field of AI were investigated. When answering "Which year has a 50% chance to realize general artificial intelligence", Google Engineering Director Ray Kurzweil thought it was 2029, while the time given by iRobot co-founder Rodney Brooks was 2200. The average time point predicted by all the 18 experts who answered this question is 2099.

However, in 2022, Elon Musk also expressed his views on realizing AGI in 2029. He said on Twitter, "2029 feels like a pivotal year. I’d be surprised if we don’t have AGI by then. (I feel that 2029 is a crucial year. I would be surprised if we didn’t have AGI then) "

In this regard, Gary Marcus, a well-known AI scholar, put forward five criteria to test whether AGI is realized, including: understanding movies, reading novels, being a chef, reliably carrying more than 10,000 lines of bug-free code according to natural language specifications or through interaction with non-professional users, and arbitrarily extracting proofs from mathematical literature written in natural language and converting them into symbol forms suitable for symbol verification.

Now it seems that the general big model represented by ChatGPT seems to have taken a big step towards AGI. The task of reading novels and movies seems to be just around the corner. In this regard, Professor Michael Wooldridge believes that at present, it is still difficult for human beings to achieve AGI in 2029.

Tiger sniffing: AI experts like AlphaGo have defeated human beings, but their abilities have great limitations in practical application. Today’s general big model seems to be breaking this situation. What do you think of the future development of expert AI and AGI?

Michael Wooldridge:Symbolic artificial intelligence is a mode of early artificial intelligence, that is, assuming that "intelligence" is a question about "knowledge", if you want an intelligent system, you just need to give it enough knowledge.

This model is equivalent to modeling people’s "thinking", which led the development of artificial intelligence from 1950s to the end of 1980s, and eventually evolved into an "expert system". If you want the artificial intelligence system to do something, such as translating English into Chinese, you need to master the professional knowledge of human translators first, and then use the programming language to transfer this knowledge to the computer.

This method has great limitations,He can’t solve the problem related to "perception". Perception refers to your ability to understand the world around you and explain things around you.For example, I am looking at the computer screen now. There is a bookshelf and a lamp next to me. My human intelligence can understand these things and environments, and can also describe them. However, it is very difficult to get the computer to carry out this process. This is the limitation of symbolic artificial intelligence, which performs well on the problem of knowledge accumulation, but not well on the problem of understanding.

AI recognizes cats as dogs.

Another method is artificial intelligence based on mental model. If you look at the animal’s brain or nervous system under a microscope, you will find a large number of neurons interconnected. Inspired by this huge network and neural structure, researchers tried to model the structure in the animal brain and designed a neural network similar to the animal brain. In this process, we are not modeling thinking, but modeling the brain.

Symbolic artificial intelligence of "modeling thinking" and neural network of "modeling brain" are two main artificial intelligence modes. With the support of today’s big data and computing power, the development speed of neural network is faster, and ChatGPT of OpenAI is a typical example of neural network.

The success of ChatGPT has further enhanced people’s expectations for deep neural networks, and some people even think that AGI is coming. Indeed, AGI is the goal of many artificial intelligence researchers, but I think we still have a long way to go.Although ChatGPT has a strong general ability when it comes to language issues, it is not AGI, it does not exist in the real world, and it cannot understand our world.

For example, if you start a conversation with ChatGPT now, you will go on vacation after saying one sentence. When you come back from a week’s trip, ChatGPT is still waiting patiently for you to enter the next content. It won’t realize that time has passed or what changes have taken place in the world.

Tiger Sniff: Do you think the prediction of realizing AGI in 2029 will come true?

Michael Wooldridge:Although ChatGPT can be regarded as a part of general AI to some extent, it is not the answer to building AGI. It is just a software combination that is built and optimized to perform a specific, narrow-minded task. We need more research and technological progress to realize AGI.

I am skeptical about the idea of realizing AGI in 2029. The basis of human intelligence is "being able to live in the material world and social world". For example, I can feel my coffee cup with my hands, I can have breakfast, and I can interact with anyone. But unfortunately, AI not only can’t do this, but also can’t understand the meaning of any of them. AGI has a long way to go before AI can perceive the real world.

Although the computer’s perception and understanding ability is limited, it still learns from experience and becomes an assistant to human decision-making. At present, as long as AI can solve problems like a "human assistant", what’s the point of arguing whether a computer system can "perceive and understand"?

We will eventually see a world built entirely by AI.

From driverless cars to face recognition cameras, from AI painting and AI digital people to AI writing codes and papers, it won’t take long. As long as it involves technical fields, whether it is education, science, industry, medical care or art, every industry will see the figure of artificial intelligence.

When talking about whether ChatGPT is often used, Professor Wooldridge said that ChatGPT is part of his research, so it will definitely be used frequently. However, in the process of using it, he found that ChatGPT is really a good helper for basic work and can save a lot of time in many repetitive tasks.

Tiger Sniff: Do you use ChatGPT at work? What do you think of ChatGPT Plus’s subscription mode?

Michael Wooldridge:I often use ChatGPT. I think in the next few years, ChatGPT and the general macro model may emerge thousands of different uses, and even gradually become general tools, just like web browsers and email clients.

I am also a subscriber of ChatGPT Plus. But for the price of $25, I think different people have different opinions. Every user will know whether ChatGPT is suitable for them and whether it is necessary to pay for the enhanced version only after trying it in person. For some people, they may just find it interesting, but they prefer to do things by themselves at work. For me, I find it very useful and can handle a lot of repetitive desk work. However, at present, I regard it more as part of my research.

Tiger sniffing: A new PaaS business model with big model capability as the core is being formed in today’s AI market. OpenAI’s GPT-3 gave birth to Jasper, while ChatGPT attracted Buzzfeed. Do you think a new AI ecosystem will be formed around the general big model?

Michael Wooldridge:ChatGPT has a lot of innovations at the application level, and it may soon usher in a "big explosion" of creativity.I think in a year or two, ChatGPT and similar applications will land on a large scale.Complete simple repetitive copywriting work such as text proofreading, sentence polishing, induction and summary in commercial software.

In addition, in multimodal artificial intelligence, we may see more new application scenarios. For example, a large language model combined with image recognition and image generation may play a role in the AR field. Based on the understanding of video content of large model, AI can be used to quickly generate summaries for videos and TV dramas. However, the commercialization of multimodal scenes may take some time.But we will eventually see all kinds of content generated by AI, even virtual worlds created entirely by AI.

Tiger Sniff: What conditions do you think are needed to build a company like OpenAI from scratch?

Michael Wooldridge:I think it is very difficult to start a company like OpenAI from scratch. First of all, you need huge computing resources, purchase tens of thousands of expensive top-level GPUs, and set up a supercomputer dedicated to AI. The electricity bill alone may be costly. You can also choose cloud services, but the current price of cloud computing is not cheap. Therefore, it may cost millions of dollars to train AI every time, and it needs to run for several months or even longer.

In addition, a huge amount of data is needed, which may be the data of the whole internet. How to obtain these data is also a difficult problem. Data and computing power are only the foundation, and more importantly, it is necessary to gather a group of highly sophisticated AI R&D talents.

Tiger Sniff: Which company is more powerful in AI research and development? What do you think of the technical differences between countries in AI research and development?

Michael Wooldridge:The players on this track may include internet companies, research institutions, and perhaps the government, but they are not public. At present, there are not many players who have publicly announced that they have the strength of big models, and even one hand can count them. Large technology companies are currently developing their own large-scale language models, and their technologies are relatively advanced.

So I don’t want to judge who is stronger,I don’t think there is obvious comparability between the models. The difference between them mainly lies in the rhythm of entering the market and the number of users.OpenAI’s technology is not necessarily the most advanced, but they are one year ahead in marketization, and this year’s advantage has accumulated hundreds of millions of users for him, which also makes him far ahead in user data feedback.

At present, the United States has always dominated the field of artificial intelligence. Whether it is Google or Microsoft, or even DeepMind, which was founded in the United Kingdom, now belongs to the American Alphabet (Google’s parent company).

However, in the past 40 years, China’s development in the field of AI has also been quite rapid.In the AAAI Conference (american association for artificial intelligence Conference) in 1980, there was only one paper from Hongkong, China.But today, the number of papers from China is equivalent to that from the United States.

Of course, Britain also has excellent artificial intelligence teams, but we don’t have the scale of China. We are a relatively small country, but we definitely have a world-leading research team.

This is an interesting era, and many countries have strong artificial intelligence teams.

Deep learning has entered a bottleneck.

When people discuss whether ChatGPT can replace search engines, many people think that ChatGPT’s data only covers before 2021, so it can’t get real-time data, so it can’t be competent for search tasks. But some people think that,In fact, the content of our daily search is, to a large extent, the existing knowledge before 2021. Even if the amount of data generated after that is large, the actual use demand is not high.

In fact, the amount of data used by ChatGPT is very large. Its predecessor GPT-2 model is pre-trained on 40GB of text data, while GPT-3 model is pre-trained on 45TB of text data. These pre-training data sets include various types of texts, such as news articles, novels, social media posts, etc. The large model can learn language knowledge in different fields and styles. Many practices have proved that ChatGPT is still a "doctor" who knows astronomy above and geography below, even with data before 2021.

This has also caused people to worry about the data of large-scale model training. When we want to train a larger model than ChatGPT, is the data of our world enough?futureWill the Internet be flooded with data generated by AI, thus forming a data "snake" in the process of AI training?

Ouroborosaurus is considered as "meaning infinity"

Tiger sniffing: You mentioned in your book that neural network is the most dazzling technology in machine learning. Nowadays, neural network leads us to keep moving forward in algorithms, data, especially computing power. With the progress of technology, have you seen the bottleneck of neural network development?

Michael Wooldridge:I think neural networks are facing three main challenges at present. The first is data. Tools like ChatGPT are built from a large number of corpus data, many of which come from the Internet. If you want to build a system 10 times larger than ChatGPT, you may need 10 times the amount of data.But is there so much data in our world? Where do these data come from? How to create these data?

For example, when we train a large language model, we have a lot of English data and Chinese data. However, when we want to train small languages, for example, in a small country with a population of less than 1 million like Iceland, their language data is much smaller, which will lead to the problem of insufficient data.

At the same time, when such a powerful generative AI as ChatGPT is applied on a large scale, a worrying phenomenon may occur. A lot of data on the Internet in the future may be generated by AI.When we need to use Internet data to train the next generation of AI tools, we may use data created by AI.

The next question is about computing power. If you want to train a system that is 10 times bigger than ChatGPT, you need 10 times of computing power resources.In the process of training and use, it will consume a lot of energy and produce a lot of carbon dioxide.This is also a widespread concern.

The third major challenge involves scientific progress, and we need basic scientific progress to promote the development of this technology.Just increasing data and computing resources can really push us further in the research and development of artificial intelligence, but this is not as good as the progress brought by scientific innovation. Just like learning to use fire or inventing a computer, we can really make a qualitative leap in human progress. In terms of scientific innovation, the main challenge facing deep learning in the future is how to develop more efficient neural networks.

In addition to the above three challenges, AI needs to be "interpretable". At present, human beings can’t fully understand the logic behind neural networks, and the calculation process of many problems is hidden in the "black box" of AI.Although neural networks have been able to give good answers, we don’t really understand why they give these answers.This not only hinders the research and development of neural networks, but also makes it impossible for humans to fully believe the answers provided by AI. This also includes the robustness of AI, and to use AI in this way, we need to ensure that the neural network will not collapse and get out of control in an unpredictable way.

Although the development bottleneck is in front of us, I don’t think we will see the subversion of neural networks in the short term.We don’t even know how it works yet, so it is still far from subversion.But I don’t think neural network is the answer of artificial intelligence. I think it is only one component of "complete artificial intelligence", and there must be other components, but we don’t know what they are yet.

Tiger sniffing: If computing power is one of the important factors in the development of AI, what innovative research have you seen in the research and development of AI chips?

Michael Wooldridge:Computing power is likely to be a bottleneck in the development of AI technology in the future. The energy efficiency ratio of the human brain is very high. The power of the human brain when thinking is only 20W, which is equivalent to the energy consumption of a light bulb. Compared with computers, such energy consumption can be said to be minimal.

There is a huge natural gap between AI system and natural intelligence, which needs a lot of computing power and data resources. Humans can learn more efficiently,But this "light bulb" of human beings is always only 20W, which is not a very bright light bulb.

Therefore, the challenge we face is how to make neural networks and machine learning technologies (such as ChatGPT) more efficient. At present, no matter from the point of view of software or hardware, we don’t know how to make neural network as efficient as human brain in learning, and there is still a long way to go in this regard.

When the system talks to the system directly.

Multi-agent system is an important branch of AI field, which refers to a system composed of multiple agents. These agents can interact, cooperate or compete with each other to achieve a certain goal. In multi-agent system, each agent has its own knowledge, ability and behavior, and can complete the task by communicating and cooperating with other agents.

Multi-agent system has applications in many fields, such as robot control, intelligent transportation system, power system management and so on. Its advantage is that it can realize distributed decision-making and task allocation, and improve the efficiency and robustness of the system.

Nowadays, with the blessing of AI big model, multi-agent systems and LLM in many scenarios can try to combine applications, thus greatly expanding the boundaries of AI capabilities.

Tiger sniffing: What are the points that can be combined with the AI big model and multi-agent system of the current fire?

Michael Wooldridge:My research focuses on "what happens when artificial intelligence systems communicate with each other". Most people have smartphones and AI assistants for smartphones, such as Siri, Alexa or Cortana, which we call "agents".

For example, when I want to reserve a seat in a restaurant, I will call the restaurant directly. But in the near future, Siri or other intelligent assistants can help me complete this task. Siri will call the restaurant and make a reservation on my behalf. And the idea of multi-agent system is,Why can’t Siri communicate directly with another Siri?Why not let these AI programs communicate with each other? Multi-agent system focuses on the problems involved when these AI programs communicate with each other.

The combination of multi-agent system and large model is the project we are studying. In my opinion, there is a very interesting work to be done in building a multi-agent+large language model. Can we gain higher intelligence by making large language models communicate with each other? I think this is a very interesting challenge.

For example, we need to make an appointment for a meeting now. You and I both use Siri to communicate, but you like meetings in the morning and I like meetings in the afternoon.When there is a dispute between us, how can Siri, representing you and me, work together to solve this problem?Will they negotiate? When AI not only talks to people, but also talks to other AI systems, many new problems will arise. This is the field I am studying, and I believe that multi-agent system is the future direction.

Another interesting question about multi-agents and large language models is, if AI systems only communicate with each other, do they not need human language? Can we design more effective languages for these AI systems?

However, this will lead to other problems, and we need to formulate rules for the exchange of these agents and AI programs.How should human beings?Managing an artificial intelligence society composed of AI?

Siri’s question and answer

AI can’t go to jail instead of human beings.

Michael Faraday, a British scientist, invented the electric motor in 1831, and he didn’t expect the electric chair as a torture device. Karl Benz, who obtained the automobile patent in 1886, could not have predicted that his invention would cause millions of deaths in the next century. Artificial intelligence is a universal technology: its application is only limited by our imagination.

While artificial intelligence is developing by leaps and bounds, we also need to pay attention to the potential risks and challenges that artificial intelligence may bring, such as data privacy and job loss. Therefore, while promoting the development of artificial intelligence technology, we also need to carefully consider its social and ethical impact and take corresponding measures.

If we can really build AI with human intelligence and ability, should they be regarded as equal to human beings? Should they have their own rights and freedoms? These problems need our serious consideration and discussion.

Tiger sniffing: The Chinese Internet has an interesting point: "AI can never engage in accounting or auditing. Because AI can’t go to jail. " AIGC also has such problems in copyright. AI can easily copy the painting and writing styles of human beings, and at the same time, the creation made by human beings using AI also has the problem of unclear ownership. So what do you think of the legal and moral risks of artificial intelligence?

Michael Wooldridge:The idea that AI can’t go to jail is wonderful. Some people think that AI can be their "moral agent" and be responsible for their actions. However, this idea obviously misinterprets the definition of "right and wrong" by human beings. Instead of thinking about how to create "morally responsible" AI, we should study AI in a responsible way.

AI itself cannot be responsible. Once something goes wrong with AI, those who own AI, build AI and deploy AI will be responsible. If the AI they use violates the law, or they use AI for crimes, then it must be human beings who should be sent to prison.

In addition, ChatGPT needs to strengthen supervision in privacy protection. If ChatGPT has collected information about the whole Internet, then he must have read information about each of us. For example, my social media, my books, my papers, comments made by others on social media, and even deleted information. AI may also be able to paint a portrait of everyone based on this information, thus further infringing or hurting our privacy.

At present, there are a lot of legal discussions about artificial intelligence, not just for ChatGPT. The legal issues of artificial intelligence have always existed and become increasingly important, but at present, all sectors of society are still discussing and exploring this.

I think ChatGPT or other AI technologies will become more and more common in the next few years. However, I also think we need to use it carefully to ensure that we will not lose key human skills, such as reading and writing. AI can undoubtedly help human beings to improve production efficiency and quality of life, but it cannot completely replace human thinking and creativity.

People who are changing and want to change the world are all there. Tiger sniffing APP

Guardiola: Arsenal are in an incredible state, but we are still competing.

Live on March 12 th, Manchester City 1-0 Crystal Palace, Manchester City coach Guardiola accepted an interview with Sky Sports.

Guardiola: "My experience is that it is very difficult for us to come here every time. When we came here, I always had a feeling that we played well, but we also had to think about the tenacity of our opponents. We are always fighting because we want to score more goals. They have’ weapons’, Zaha is there, Orlis, Ezer, and they have incredible threats. They have calm and outstanding offensive players, which is a matter of patience. They will delay time, so we must rush them. "

"Everything makes me satisfied, and we missed some opportunities to fight back. It’s not easy. They have six players defending in the penalty area, Harland has two guards and Gundogan has one guard. It’s a matter of patience. They are very tight on Harland. Alvarez is very important and we need him. We need him in midfield. He has some chances. Gundogan is an excellent player. He won the penalty and Harland did the rest. "

"After Cancelo left, we only had Walker and Gomez as full-backs. We had four central defenders, and the defense was very solid. All four of them are outstanding players, so we defended well. Of course, Arsenal are in an incredible state. We are still competing, Arsenal scored 50 points before. It was a typical winter game, a difficult game. We were there all the time, and then we won. Now we have to do everything, next Tuesday and Saturday, hoping to spend one of the best nights we have ever experienced at home, and we can do it again. "

ChatGPT is hot out of the circle? Wait, the pig farm also has black technology.

Recently, ChatGPT has been popular. Before that, Wang Huiwen, the co-founder of Meituan, released the AI ? ? hero list, announced that he would pay for himself, and set up Beijing Lightyear Technology Co., Ltd. to confirm his entry. Later, there was an extreme dialogue between programmers from big factories and ChatGPT. From emotional consultation, project management to novel creation, ChatGPT was almost omnipotent and omnipotent (PS, Xiaobian was trembling with fear).

Behind the explosion of ChatGPT is everyone’s embarrassment and concern for the field of artificial intelligence. So is there any application of artificial intelligence technology in the field of pig breeding? How do they combine?

01

The Origin and Development of Artificial Intelligence Technology

Artificial intelligence technology is a branch of computer science. The original intention of its creation is that scientists hope that computers can imitate human intelligence, so that machines can handle complex things.

Artificial intelligence can be traced back to 1950, and Allen Matheson Turing put forward the famous "Turing Test" [which refers to asking questions to the testee through some devices (such as keyboards) when the testee is separated from the testee (a person and a machine). After many tests, if the machine makes the average participant make more than 30% misjudgment, then the machine has passed the test and is considered to have human intelligence.

In the same year, he published the paper "Computing Machine and Intelligence", and put forward and tried to answer the question "Can a machine think?". After the paper was published, it received extensive attention and discussion, and Turing was later called "the father of artificial intelligence".

In 1956, John McCarthy (computer scientist and cognitive scientist), an assistant professor in the Department of Mathematics at Dartmouth College, located in the small town of Hannos in the eastern United States, invited a group of big coffee scholars including Marvin Minsky (winner of Turing Prize in 1969) and Claude Shannon (founder of information theory) to hold an academic conference. The conference mainly discussed topics such as machine imitating human intelligence, including: how to program computers, neural networks, calculation scale theory, mechanical theory (referring to self-learning), randomness and creativity.

Dartmouth Conference has been held for more than two months. Although the participants did not reach an agreement, they agreed on a word for the discussion: Artificial Intelligence (AI). At this point, the word artificial intelligence began to appear in people’s field of vision, and 1956 was also called the first year of artificial intelligence. After that, the theoretical research and practical application in the field of artificial intelligence continued to break through (see the development history of AI for details).

(Image from Demeo Consulting Wang Wei)

Before ChatGPT, the last time artificial intelligence was widely concerned was in May 2017, when Alphago defeated Li Shishi, the world Go champion, by a score of 4: 1, and will face Ke Jie, a player from China, at the world internet conference in Wuzhen. You know, after Li’s defeat in artificial intelligence, Ke Jie made a statement in the media: Even if Alpha Dog beats Li Shishi, it can’t beat me.

Before the start of the competition, Ke Jie had high hopes and was once regarded as "the last hope of mankind". However, the reality is cruel. Alphago(Master) beat Ke Jie, a talented teenager in China, with a score of 3: 0.

After the on-site interview, Ke Jie once choked:Playing chess with AlphaGo is too painful, AlphaGo is too calm, it is too perfect, and I can’t see any hope of victory.. So why is "artificial intelligence" technology so powerful?

02

Analysis of artificial intelligence technology

Artificial intelligence mainly includes five core technologies, namely computer vision, machine learning, natural language processing, robotics and biometrics.

Computer vision is a science that studies how to make machines "see", which means that cameras and computers are used to identify, track and measure targets instead of human eyes, and further graphic processing is carried out, so that computers can be processed into images that are more suitable for human eyes to observe or send to instruments for detection.

Machine learning is the core of artificial intelligence technology, which enables intelligent machines to simulate human behavior independently with the support of algorithm complexity theory, convex analysis, statistics and other disciplines. Machine learning refers to how to improve the performance of specific algorithms in empirical learning, that is to say, machine learning is based on massive data or past experience to optimize the performance standards of computer programs.

To put it simply, this process is similar to personal self-reflection, which is to review past experiences and then adjust the optimization behavior so as to do better next time. But different from personal reflection, personal reflection has limited sources of experience, while machine learning is based on a huge database given by developers, with wider sources of experience and data and more timely feedback based on goals.

Natural Language Processing (NLP) is a variety of theories and methods to study how to achieve effective communication between people and computers in natural language. Natural language processing is a science integrating linguistics, computer science and mathematics, which can be mainly applied to machine translation, public opinion monitoring, automatic summarization, viewpoint extraction, text classification, question answering and so on.

Robot refers to performing tasks such as working or moving through programming and automatic control. Robots have the basic characteristics of perception, decision-making, execution, etc., which can assist or even replace human beings to complete dangerous, heavy and complicated work and improve work efficiency and quality. At present, sweeping robots have entered the daily life of the public.

Biometric technology is closely combined with high-tech means such as optics, acoustics, biosensors and biostatistics through computers, and uses the inherent physiological characteristics (such as fingerprints, faces, irises, etc.) and behavioral characteristics (such as handwriting, voice, gait, etc.) of human bodies/creatures to identify their identities, such as "face recognition" and "pig face recognition".

Therefore, artificial intelligence can be understood as imitating human information input (images, words, sounds, etc.), information processing (based on the correct thinking model in the past) and then action execution, and constantly strengthening various abilities in the process to achieve the set goals and continue to improve. The core of artificial intelligence lies in deep learning, that is, continuous feedback and continuous optimization based on strategy.

The mechanism of deep learning is similar to the deliberate practice learning method proposed by Florida psychologist Anders Millard J. Erickson. Anders pointed out that the key factor to distinguish a person’s mediocrity and Excellence in the professional field is the degree of deliberate practice. The longer the deliberate practice, the higher the professional level. Deliberate exercises mainly include four elements:Clear goals, staying away from the comfort zone, concentration and timely feedback.. Different from human deliberate practice, the deliberate practice process of the machine has no emotion, so it is more efficient to execute.

Just a few months after Alphago(Master) defeated Ke Jie, in October of 17, DeepMind team published a new paper in Nature magazine, and launched a new generation of product AlphaGo( Zero). The paper points out that Alphago(Zero) reached the level of Alphago(Master) in only 21 days, and when Alphago(Zero) played the 40th day, it had already defeated all previous programs and won the world Go championship.

Afterwards, the industry put forward three cores for Alphago to quickly reach the top level in the world: first, it adopted a learning algorithm combining machine learning and neuroscience; Second, in Google’s powerful cloud computing system, more than 30 million steps of professional chess player’s chess manual have been learned through a large amount of data analysis; Third, throughThe ever-increasing self-gameFind a better idea than the basic chess manual. Artificial intelligence technology is created by human beings, and the achievements in some aspects are far beyond human beings, which may also be worth thinking and learning.

03

Application of artificial intelligence technology in pig farm

The combination of artificial intelligence technology and agriculture can be traced back to March 2015. Li Keqiang, then Premier of the State Council, put forward the action plan of "internet plus" for the first time in his government work report; In July of the same year, the State Council issued the Action Plan on Actively Promoting the internet plus (hereinafter referred to as the Action Plan).

The Action Plan clearly puts forward to actively promote the modern agriculture in internet plus, and points out that it is necessary to establish standardized scale livestock and poultry breeding bases and aquatic healthy breeding demonstration bases,Promote the popularization and interconnection of intelligent devices such as accurate feed delivery, automatic disease diagnosis and automatic waste recycling.. The release of Action Plan opened the historical curtain of agriculture in internet plus.

After that, AI technology, like other emerging Internet technologies, was gradually applied to the practice of agricultural industry. On the one hand, new cutting-edge technology, on the other hand, traditional agriculture, how do they combine? What kind of sparks will break out?

Scenario 1: Pig farm monitoring and pig inventory

Since the outbreak of African swine fever in 2018, biosafety has been crucial for aquaculture enterprises. Under the traditional breeding mode, people and things inside and outside the pig farm are complicated, and materials, vehicles, birds and animals come in and out frequently. It is extremely difficult and time-consuming to achieve effective supervision. For example, in the process of dissecting dead pigs, improper wearing of protective clothing by operators may cause the spread of diseases in pig farms. It is difficult to pass the manual on-site review, and it is impossible to supervise all the time. By using technologies such as artificial intelligence and Internet of Things, employees’ misconduct can be identified and early warning signals can be conveyed to managers in time, which can effectively avoid the risk of disease spread.

In addition, artificial intelligence technology can also be used to count and estimate the number of pigs. In the traditional breeding process, pig dealers need to go to the pigsty for on-site counting and weighing in the pig selling process. By using the camera above the pig farm combined with artificial intelligence technology, the pigs in the pen can be counted in real time, so as to achieve the effect of remote pig watching and real-time weight estimation.

The AI patrol and early warning interface of "Pig Xiao Zhi" of rural credit cooperatives.

Scheme of intelligent pig farm with integrated rural credit, mathematics and intelligence for message or private message consultation

Scene 2: Intelligent dung cleaning robot and inspection robot

Pig farm is a model of large-scale farming. Large-scale farming and high manure output are difficult problems that plague the operation of enterprises. In traditional farming mode, manual cleaning is usually needed, and the labor input cost is high in the process of manual cleaning. Some pig farms use water to clean manure, which consumes a lot of water, and at the same time, it is easy to cause high humidity in pig houses and cause health problems of pigs. By using artificial intelligence technology to develop a dung sweeping robot, it can effectively solve the problems of difficult cleaning, reducing water consumption and saving costs.

Similarly, robots developed by combining intelligent speech recognition and visual recognition technologies can cruise around the pigsty all day, find abnormal pigs (such as fever and shivering) in the pigsty in time, prevent and control diseases in advance, and effectively resolve the risk of disease infection.

Mu Yuan inspection robot

The above are only typical application scenarios of artificial intelligence technology in pig farms. With the expansion of business scale and the improvement of cost control and biosafety requirements of enterprises, the combination of artificial intelligence technology and pig breeding is becoming closer and closer.

04

tag

At last year’s Deep Bay Meeting, in view of the application of intelligence in pig farms, Qin Yinglin, chairman of Mu Yuan Co., pointed out: "It takes three years for us to train an excellent employee, and many employees are unqualified for three years, which takes five or even ten years. But we want to make a machine in the assembly line, and gather all our wisdom of raising pigs. We are producing this very quickly now, and producing thousands of units a day is equivalent to producing the corresponding number of laborers. "

It can be seen that artificial intelligence technology has been applied on a large scale in the farms of some enterprises. With the continuous development and mature application of technology, it is certain that "unmanned pig farms" and "unmanned farms" will eventually come true.

References:

Talking about the development of AI from ChatGPT, consulting with Deme.

Nature is heavy: human beings have misunderstood the dopamine mechanism in the brain! ? Top Edition AlphaGo Enlightens Brain Science, Quantum Bit

Qin Yinglin’s Sharing in Deep Bay Meeting, Wandou Agricultural Science.

Guiding Opinions on Actively Promoting "internet plus" Action, the State Council

Brief introduction of Artificial Intelligence (AI)

The development history of Artificial Intelligence (AI) can be traced back to 1950s. The following are the main stages of the development history of AI:

  1. Logical reasoning and problem solving (1950s-early 1960s): The early AI system was based on symbolic logic, and solved problems through logical reasoning of facts and rules. However, this method has limitations, and it is difficult to deal with a large number of uncertain and fuzzy information.
  2. Machine learning and pattern recognition (1960s-1980s): The research of AI began to turn to machine learning and pattern recognition. Machine learning is a method to learn and optimize algorithms by training data, while pattern recognition is a method to realize intelligence by identifying and classifying patterns. These methods have been widely used in image recognition, speech recognition and natural language processing.
  3. Expert system and knowledge representation (1980s-1990s): AI research began to pay attention to expert system and knowledge representation. Expert system is an intelligent system based on expert knowledge and inference rules, which can simulate the decision-making process of human experts. Knowledge representation is a method to organize knowledge and information into a form that can be processed by computer, and it is an important foundation to realize AI.
  4. Statistical learning and deep learning (1990s-2010s): With the continuous development of computer hardware and algorithms, AI research began to pay attention to statistical learning and deep learning. Statistical learning is a machine learning method based on statistical model and data analysis, which can handle a large number of data and complex nonlinear relationships. Deep learning is a machine learning method based on neural network, which can handle more complex and high-dimensional data.
  5. Self-learning and multi-modal AI(2010 to present): AI system is gradually realizing the ability of self-learning and self-optimization, and can continuously improve its own model and algorithm according to feedback and data. Multi-modal AI is an AI technology that can handle a variety of data types and perceptual information, including images, voices, texts, etc., and can realize more comprehensive and intelligent human-computer interaction.

Important events:

  • In 1956, the concept of artificial intelligence was put forward at Dartmouth Conference, which marked the birth of AI.
  • In 1962, Arthur Samuel developed a self-learning program, which was an early application of machine learning.
  • In 1969, Marvin Minsky and Seymour Papert published Perceptrons, which revealed the limitations of single-layer neural networks and promoted the development of neural networks.
  • In 1975, John Holland developed genetic algorithm, which is an optimization algorithm that imitates the process of biological evolution.
  • In 1981, Japan launched the first commercial robot WABOT-1.
  • In 1997, IBM’s deep blue supercomputer defeated Kasparov, the world champion of chess, indicating that computers can surpass human intelligence in some fields.
  • In 2011, IBM’s Watson artificial intelligence system defeated human players in the program "Dangerous Edge".
  • In 2016, AlphaGo defeated Li Shishi, the world champion in the Go competition, marking an important step in the application of artificial intelligence in complex games.
  • In 2018, the GPT-2 model developed by OpenAI made a major breakthrough in the field of natural language processing, which can generate high-quality natural language texts.

The latest development trend:

  1. Self-learning: AI system is gradually realizing the ability of self-learning and self-optimization, and can continuously improve its own model and algorithm according to feedback and data.
  2. Deep learning: Deep learning is a machine learning method based on neural network, which can handle a large number of data and complex nonlinear relationships, and is one of the main trends of current AI development.
  3. Artificial intelligence chip: Artificial intelligence chip is a chip specially designed for AI application, which can realize efficient calculation and data processing and is an important technical support for AI popularization and application.
  4. Multi-modal AI: Multi-modal AI is an AI technology that can handle a variety of data types and perceptual information, including images, voices, texts, etc., and can realize more comprehensive and intelligent human-computer interaction.
  5. AI and Internet of Things: The combination of AI and Internet of Things can realize more intelligent and efficient automatic production and management, including intelligent energy, intelligent transportation, smart home and other fields.
  6. AI Ethics and Law: With the continuous development and application of AI technology, AI ethics and legal issues have attracted more and more attention, including privacy protection, data security, and responsibility distribution.

In short, the development trend of AI technology is diverse, involving algorithms, chips, data and applications. In the future, AI technology will continue to develop and apply in depth, bringing more convenience and innovation to mankind.