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Yao only scored 9 points in the fund game! The strongest surface 175 is not as good as Fang Shuo, and now even CBA can’t be played.

Thomas Jr., who was neglected in the NBA last season, was once reported to have joined the T1 League in Taiwan Province, China. However, due to a series of unreasonable demands put forward to the team (to stay in a five-star hotel, the food, clothing, housing and transportation of relatives and friends must also be paid by the team), he finally did not appear in the Baodao League. Thomas Jr., who is 34 years old, is far less competitive and physically functional than when he was a Celtic. In this Yao Fund Charity Tournament, Thomas Jr. is the absolute big name of the international star team, and his performance has really attracted everyone’s attention.

After the CBA has completely opened the home and away system, Thomas Jr., a star with a certain popularity, is indeed a potential target of CBA teams. However, given that he has no ball to play in the past season, his competitive state is still worrying, so this Yao Fund Charity Tournament may also be an important indicator for some CBA teams interested in signing him.

However, after the whole game, Thomas Jr. scored only 9 points, even worse than Fang Shuo (16 points). The offensive end relied too much on outside projection and was limited by his height. It was almost difficult for Thomas Jr. to score in the restricted area through breakthrough. Although Thomas Jr. won the full support of the fans at the game break or after the game, CBA is a stage that needs to speak with strength after all. If Thomas Jr. can only play the role of "selling tickets" like Jeremy Lin, I’m afraid most teams will flinch from him.

With the approaching of the new season, many CBA teams have signed their own foreign aid one after another, and only two teams, Kenya and Sichuan, have not yet confirmed their small foreign aid. Sichuan had previously been in contact with Gordon, who played for Beijing Control last season, so the only team that could sign Thomas Jr. was Kenya. However, at present, we don’t even know where to put the home court of the new season, and even the core players like Wu Guanxi and Zhao Lingzhou have given up. It is estimated that it is impossible for Kenya to spend a lot of money to sign Thomas Jr.

Of course, it is not ruled out that Thomas Jr. will sign other CBA teams as a third foreign aid later, but if he refuses to put down his posture, or comes to CBA to "collect and fight", he is bound to be a passer-by in CBA. In fact, in recent years, there have been many small foreign AIDS in CBA, such as Pierre Jackson and Feld, who have proved themselves in CBA.

Malanville, who played in Sichuan last season, Brandon Taylor, who played in Ningbo, and Brandon Jefferson, who played in Tianjin, although their strength was limited, they dared to play the game and were recognized by the fans. If little Thomas really wants to play in CBA, I hope he can keep a humble attitude. If he is a condescending and arrogant attitude, even if he was the strongest 175 on the surface, he is destined to be eliminated by CBA soon.

Hu Baosen personally supervised the Henan team and won the first victory at home.

Last night’s sailing stadium was happy. When the scoreboard was finally fixed at 1:0, Sarkozy and his coaching team were surrounded, and the fans at the scene left excited tears. At this moment, the Henan team waited for too long. Since the start of the tournament, the seven rounds of unbeatable haze have been swept away. Although the current Henan team is still mired in relegation, it has finally ushered in a glimmer of light.

In the 31st minute of the competition, the stands of the aviation body were dotted with stars, and the fans turned on the lights of their mobile phones to celebrate the 31st birthday of Henan Football. Among them was Hu Baosen, the boss of Jianye Group, who had been committed to Henan Football for 30 years.

In 1994, when Henan professional football was faced with a "life-and-death choice", Hu Baosen took over the Henan team with "rushing to the top and getting angry". Who knew that it was 30 years, and although he experienced too much bitterness and injustice in the middle, even though the "Jianye" used for 30 years was cut off by the "neutral name" of the Football Association, he still carried it down without hesitation, and invisibly Hu Baosen became a banner of Henan professional football.

2023 is the third year of Henan team’s share reform. Although the shares held by Jianye are decreasing, Lao Hu’s love for football has not diminished. Just as the team was in a precarious situation, Hu Baosen once again came to the stadium to watch the battle. The players on the field seemed to be injected with a needle of "stimulant". Even Ke Zhao and Li Songyi, who were rough in previous games, were like a different person, fighting actively and bloody, and performed well at both ends of the attack and defense. Wang Shangyuan, the captain of the team, was injured in the 27th minute, which cast a shadow over the game. However, at this time, Ke Zhao and Covic stood out, and it was their tacit understanding of "connection" that scored the winning goal for the team and helped the Henan team win the first game in 2023.

Although it won the first victory in the league, this victory is not enough to get the team out of the quagmire. At present, the team has 7 points, only 1 point higher than the relegation circle. The future situation is still grim. The next round of the team will go to Shanghai to challenge the current "leading" Shanghai Shanghai team, but the alarm in Henan has not been lifted, and the front line is weak, the lineup is not complete and the camp is full of injuries. This is a cruel reality faced by the team and an urgent problem to be solved.

No matter how bumpy the road ahead is, we must go on without hesitation. Hu Baosen’s performance in the air also gave the fans a "reassurance" and quelled the "rumor" that the Henan team might quit at the end of the year. As long as Lao Hu is there, Henan professional football is there. This is a spirit, a belief and a trust.

I wish Henan football better and better!

The annual best women’s volleyball team in the Champions League will be judged to see who can become the top seven in volleyball today.

The 2022/2023 Women’s Volleyball Champions League is coming to an end. At present, there is only one final game left. The only suspense is who will win the Champions League Gold Cup, Isachibashi or Wakif Bank.

In order to create momentum for the Champions League, the European Volleyball Federation began to organize the selection of the best women’s volleyball team in the Champions League in 2022/2023. Let’s take a look at which players are the top players in the Champions League this season, who will be elected as the top seven women’s volleyball teams today, and see if there is your favorite star on the list.

The Turkish team has become the big winner of the women’s volleyball Champions League this season. They have successfully encircled the Italian team. Coneri Yano was blocked from the semi-finals by Fenerbahce. Although Novara reached the semi-finals, she still fell to the semi-finals. In this way, the Turkish women’s volleyball team is definitely the big winner of the best lineup.

There are four candidates for the best setter. They are Ogennovich, the "Bitter Melon Sister" of Isachi Bashi, Ozbaye of Wakif Bank, Mariks of Fenerbahce and Wowosh of Yano, Coneri.

These four people are all big cows in the field of second setters, among which "Bitter Melon Sister" and Wowosh are even more cattle. They have won the best second setters in the Champions League before. Up to now, the voting situation is: Vowalsh won 56.5%, Ozbaye 32.7%, Makelis 8.1%, and "Bitter Melon Sister" Ogennovich 2.7%.

Yano, Coneri, where Vowalsh is located, did not enter the semi-finals, but Vowalsh temporarily ranked first in the voting, showing her popularity. Isachi Bashi entered the final of the Champions League, but its main setter, Ojeninovic, came last in the voting. Perhaps she is really old at the age of 39.

The best candidates are also four: Karakurt of Novara, Egnu of Wakif Bank, Vargas of Fenerbahce and Boskovich of Ithachi.

If it is a few years ago, there is still some debate about who is the first in the world today, but now, there seems to be no suspense, and Boskovich is the only one in the world. In the past, Egnu was able to wrestle with Boskovich, but now, Boskovich is ahead of Egnu in stability, skill, strength, self-control and self-motivation.

As for Karakurt and Vargas, Karakurt is particularly emotional and unstable, so he can’t be the core of the team. Although Vargas can’t compete with Boskovich at present, her rising space is not small, and she is definitely more promising than Karakurt.

The current voting situation reflects the above analysis, with Boskovich winning 50.2%, Vargas 39.3%, Egnu 9.4% and Karakurt 1.2%.

1, who is the first attack?. The four candidates selected as the first main attack are Gaby of Wakif Bank, Wolongkova of Ithachi Bashi, Carcasses of Novara and Kotikova of Lekane Warero. In terms of fame and fighting capacity, Gaby, a small steel gun, and Wolongkova, a heavy gun, are undoubtedly the biggest, while Carcasses, 37, and Kotikova, 24, are much worse, and their teams are also slightly worse, so Gaby and Wolongkova are the most competitive.

At present, Gaby is far ahead with 78.7%, Wolongkova is second with 16.9%, Carcasses is 2.3%, and Kotikova is 2.1%. It seems that the eyes of fans are quite professional.

2. The two new talents are the most popular in the second main attack selection.. The four candidates shortlisted for the second main attack are Xiaocaiwa and Cristina of Fenerbahce, and the other two are Calander of Reshuff, Poland, and Serra of Milan women’s volleyball team.

To tell the truth, the candidate for the second main attack is a bit weird. Xiaocaiwa and Christina were selected in an upright way. They are too brilliant this season, but they are quite aggressive at a young age. The biggest controversy is Serra, the main attack of Milan women’s volleyball team is useless at present. She is only ranked 64th in the Champions League attack list, with a poor attack score of 45 points. Is she here to be funny? The current vote rate also confirms Sierra’s unbearable situation.

Xiaocaiwa ranked first with 64.9% of the votes, followed by Christina with 30.6%, Serra with only 3%, and Calander with only 1.5%. It seems that the two teenagers are promising, especially Xiaocaiwa.

The four candidates selected for the Best Freeman are normal. They all come from the top four teams, namely, Aika of Wakif Bank, Akiz of Ithachi Bashi, Fersino of Novara and Og of Fenerbahce.

The strength of these four people is equal to that of Zhong Bo, which reflects that they are anxious to win votes. At present, Og won 43.1% of the votes, Aika 29.5%, Akiz 19.2%, and Felsino 8.25 ranked last. To be honest, it is really hard to draw a conclusion about who can laugh at the end.

The best secondary attack is to select blocking machines. Blocking ability is an important reference, and of course, fame is also a plus item that cannot be ignored.

1, the best first attack Gunes war teammate Og Bo Gu.. The four candidates for the best first attack are Gunes and Og Bo Gu of Wakif Bank, and the other two are Jack of Isachi Bashi and Stevanovic of Milan Women’s Volleyball Team.

Talking about the situation of these four candidates, Gunes and Og Bo Gu are naturally the most promising candidates. Gunes is super in strength and popularity. Og Bo Gu is very "chicken blood" this season. Jack has done well but is not well-known. Only Stevanovic is simply here to play soy sauce, or to make up the numbers. Her blocking in the Champions League is only 9 points.

At present, Gunes has 44.1% of the votes, Og Bo Gu 42.9%, Stevanovic 8.1% and Jack only 4.9%.

2. The most popular candidates for the best second attack are Ida and Danesi.. The best second-in-command competitors are Fenerbahce’s old second-in-command Aida, Novara’s Danesi, Kone’s De cruyff and Lecanevorero’s Keqiulina. Looking at the blocking data alone, Danesi is the best, with an average blocking score of 0.91 and Ada only 0.48, but the selection seems to be more about popularity. At present, the election situation is: Ada is the first, with 55.7% of the votes, Danesi is the second, with 31.4% of the votes, De cruyff is 10.2%, and Ke Qiu Lina is 2.8%, which is very favorable for Ada.

The Women’s Volleyball Champions League is the world’s top event at the level of volleyball clubs. There are many stars and giants, and the game is beautiful and fierce. Who will be the best team in this Champions League? Let’s wait and see!

The Best Goalkeeper in IFFHS History: Buffon Cassie, Neuer’s top three, Van der Sar’s fifth and Lori’s 13th.

Live on March 10th, the ranking of the best coaches in the history of the International Federation of Football History and Statistics (IFFHS) was scored according to the ranking of the best coaches in IFFHS every year from 1987 to 2022, with the first place getting 20 points every year, the 20th place getting 1 point every year, and no points except the 20th place.

Among them, the best goalkeepers in all continents are Buffon (UEFA, Italy), Daiyaya (AFC, Saudi Arabia), chilavert (South American Football Association, Paraguay), Enyema (non-FIFA, Nigeria), navas (Central and North America and Caribbean Football Association, Costa Rica) and Bosnic (Oceania Football Association, Australia).

Here are the top 50 best goalkeepers in IFFHS history:

1. Buffon (Italy)

2. casillas (Spain)

3. Neuer (German)

4. Cech (Czech Republic)

5. Van der Sar (Netherlands)

6. Schmeichel (Denmark)

7. Kahn (Germany)

8. courtois (Belgium)

9. chilavert (Paraguay)

10. Zeng Jia (Italy)

11. zubizarreta (Spain)

12. Taffarel (Brazil)

13. Lori (France)

14. Predholm (Belgium)

15. fabien barthez (France)

15. oblak (Slovenian)

17. David Seaman (England)

18. Valdez (Spain)

19. Dida (Brazil)

20. Bai Ya (Portugal)

21. navas (Costa Rica)

22. pagliuca (Italy)

23. TOLEDO (Italy)

24. Lehmann (Germany)

25. Ter stegen (Germany)

25. allison (Brazil)

Cesar (Brazil)

28. Degea (Spain)

29. illgner (Germany)

29. van breukelen (Netherlands)

31. roberto abbondanzieri (Argentina)

32. goicochea (Argentina)

33. kopke (Germany)

Campos (Mexico)

34. Peter Hilton (England)

36. Ravilly (Sweden)

37. Dasayev (Russia)

38. peruzzi (Italy)

38. Southall (Wales)

40. Reina (Spain)

41. Cheney (Brazil)

42. canizares (Spain)

42. Bravo (Chile)

44. pfaff (Belgium)

44. Handanovic (Slovenia)

46. Duddeck (Poland)

47. Akinfeev (Russia)

48. Cordoba (Colombia)

Bernard Rama (France)

48. ochoa (Mexico)

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

Parisians left to contemplate familiar failure

Paris Saint-Germain were convinced that persuading Kylian Mbappe to stay would finally deliver them Champions League glory, but the failure to build a strong enough team around the France superstar has contributed to another early European exit.

A 2-0 loss to Bayern Munich in Germany saw the Qatar-owned club lose their last-16 tie 3-0 on aggregate, falling in the first knockout round for the fifth time in seven years.

There were celebrations last May when Mbappe agreed a new three-year contract to stay with Lionel Messi and Neymar in the French capital rather than join Real Madrid.

The appointments of super scout Luis Campos as head of recruitment and Christophe Galtier as coach to replace Mauricio Pochettino were supposed to be followed by the building of an exciting new team.

“It is not about the construction of the squad. It is just the story of the season,” said Galtier. “We were missing important players. The squad, over the two legs, was seriously weakened.”

He had a point, with Mbappe only able to make a cameo appearance off the bench after a thigh injury as PSG lost 1-0 in the first leg.

Neymar is missing with an ankle injury, while Presnel Kimpembe is out and fellow defenders Marquinhos and Nordi Mukiele both came off during yesterday’s game.

“It has been a very busy season. Players’ bodies have been asked to do a lot,” Galtier said.

“There was the World Cup, and obviously when you get to the last 16 it is good to have everyone available.”

PSG placed their hope in Mbappe and Messi turning the tie around in Munich, but the Argentine World Cup winner had little impact while the 24-year-old Mbappe saw just 32 touches of the ball.

“As I said in my first Champions League press conference this season, we were going to do our maximum. The truth is this is our maximum,” admitted Mbappe, whose own future will now again become the subject of increasing speculation

Masters: Invite sent to US golfer Scott Stallings’ namesake

US golfer Scott Stallings was handed a shock after discovering his Masters invitation had been sent to another person of the same name.

The 37-year-old tweeted he had been “checking the mailbox five times a day” for his invitation before receiving a direct message from another Scott Stallings.

The three-time PGA Tour winner posted the message from his namesake, which included: “I’m 100% sure this is NOT for me. I play but wow! Nowhere near your level.”

The message began: “Hi Scott. My name is Scott Stallings as well and I’m from GA (Georgia). My wife’s name is Jennifer too!!

“I received a FedEx today from the Masters inviting me to play in the Master’s Tournament April 6-9, 2023.

“It’s a very nice package complete with everything needed to attend. I think we have some confusion because of our names, our wife’s names and geographical location.”

He then attached a picture of the invitation adding: “I’m really not kidding I promise.”