爱上海419论坛,上海后花园论坛,阿拉爱上海龙凤1314

In the 37th round of Premier League, 6 matches were finished:Nottingham Forest 1-0 Arsenal, Bournemouth 0-1 Manchester United, Liverpool 1-1 Aston Villa, Tottenham 1-3 brentford, Fulham 2-2 Crystal Palace and Wolves 1-1 Everton.

With Arsenal losing to Nottingham Forest, Manchester City won the Premier League title ahead of schedule this season and achieved the great cause of three consecutive championships!Nottingham Forest also successfully relegated, with Everton, Leeds United and leicester city vying for the last relegation spot. There is still a glimmer of hope for Liverpool to fight for four aspects.

Nottingham Forest 1-0 Arsenal

In the 19th minute, Odegard made a mistake in passing the ball, and Gibbs White counterattacked and assisted Awoniyi to score a goal, 1-0!

In the end, Nottingham Forest beat Arsenal 1-0. Avonii was elected the best player of the game.

Nottingham Forest has only 18% possession rate, which is the lowest possession rate of the winning teams in the Premier League since the statistics were available in 2003/04.

This game made Manchester City win the championship ahead of schedule, becoming the second team in the history of the Premier League to complete three consecutive championships. The first team was Manchester United (twice).

Nottingham Forest has been relegated one round ahead of schedule, which means that all three newly promoted horses have been relegated this season, which is the fourth time in Premier League history after 2001/02, 2011/12 and 2017/18.

Bournemouth 0-1 Manchester United

In the 9th minute, Eriksson picked the restricted area, Senesi made a mistake, and casemiro barbed the goal, 0-1!

In the 84th minute, Ouattara went straight to plug, and Moore’s single-pole push was blocked by Degea.

In the end, Manchester United beat Bournemouth 1-0 away. Luke Shaw was voted the best player in the game.

Manchester United scored 22 goals away from home in the Premier League this season. Only in 2014/15 did the team score even less (21 goals).

Bournemouth has lost 70 goals in the Premier League this season, tying the record of losing goals in the top league in the history of the team (70 goals in the 2018/19 season).

Degea won the Golden Glove Award for the second time in his career with 17 clean sheets, the first time being in the 2017/18 season.

Liverpool 1-1 Aston Villa

In the 20th minute, konate put Watkins down in the restricted area, Villa got a penalty, and Watkins took the penalty and missed.

In the 27th minute, Douglas Lewis crosses from the right, and Jacob Ramsey outflanks the goal, 0-1!

In the 55th minute, Mince cleared the goal and Gakpo made up the shot to break the goal, but Fan Dike was offside first and the goal was invalid.

In the 89th minute, Salah made a cross from the right, and firmino, who came off the bench, grabbed the goal and scored 1-1!

This is the 25th time that Salah and firmino have scored in the Premier League together (Salah assisted firmino 12 times and firmino assisted Salah 13 times).

In the end, Liverpool drew 1-1 with Aston Villa.Firmino was elected as the player of the match, completing the farewell battle of Liverpool’s career at Anfield.

Tottenham 1-3 brentford

In the 8 th minute, Kulusevsky volleyed a free kick and Kane scored a long-range goal, 1-0!

In the 50 th minute, Visa scored the ball, and Mbeumo scored a goal on the right side of the restricted area, 1-1!

In the 62nd minute, Hickey went straight for the goal, and Mbeumo pushed the goal from a small angle, 1-2!

In the 88th minute, brentford steals in front of the restricted area in the frontcourt, and Mbeumo assists Visa to push and shoot the goal, 1-3!

In the end, brentford reversed Tottenham 3-1 away. Mbueumo was elected the best player of the game.

Brentford won the 14th Premier League victory this season, surpassing last season (13 wins), which was the most in the top league since the 1938/39 season (also 14 wins).

This season, Tottenham is the second team in the Premier League to score 60+ goals and concede 62 goals. The first time was Tottenham in 2007/08.

Fulham 2-2 Crystal Palace

In the 34th minute, Ezer counterattacked the ball, and Edward volleyed the goal, 0-1!

In stoppage time in the first half, harry wilson was knocked down by Mitchell in the penalty area, and mitrovic hit a penalty kick, 1-1!

In the 61st minute, William made a free kick from the right and mitrovic headed the goal, 2-1!

In the 83rd minute, Ward’s shot in the restricted area was tackled, and he immediately made up the shot and broke the goal, 2-2!

In the end, Fulham drew 2-2 with Crystal Palace. Mitrovic was voted the best player in the game.

Mitrovic has scored 14 goals in the Premier League this season, and Fulham is second only to Dempsey (17 goals in 2011/12) and Berbatov (15 goals in 2012/13).

Fulham scored 54 goals in the Premier League this season, a record for the team in the Premier League, and a single-season top league record since the 1967/68 season (56 goals).

Wolves 1-1 Everton

In the 34th minute, armand traore broke through the shot and was tackled. Huang Xican made up the shot and scored a goal, 1-0!

In the 99th minute, michael keane knocked horizontally on the right side of the restricted area, and Mina volleyed the goal, 1-1!

Mina scored in the 98th minute and 54th second, which was Everton’s latest Premier League goal since accurate timing statistics were available in the 2006/07 season.

In the end, Wolves drew 1-1 with Everton. Mina was elected the best player of the game.

# So how can the Premier League not love #

In the 37th round of the Premier League, Arsenal lost 0-1 to Nottingham Forest, sending Manchester City to win the Premier League championship three rounds ahead of schedule.

According to statistics, Arsenal have led the standings for a total of 248 days this season, setting a record for the longest time in the history of the top leagues in England.

In early April, Arsenal scored 72 points in 29 games after beating Leeds United 4-1, while Manchester City scored 64 points in 28 games, and Arsenal led by 8 points in one more game.

But then, Arsenal left Liverpool 2-2, West Ham 2-2, Southampton 3-3 at home and Manchester City 1-4 away, giving up the initiative directly. After that, Arsenal 3-1 Chelsea, 2-0 Newcastle away, 0-3 Brighton at home and 0-1 Nottingham Forest away, and lost 15 points in the last 8 rounds.

In contrast, Manchester City won 11 consecutive victories in the Premier League, reached the final in both the Champions League and the FA Cup, and reached the end in the case of three-line operations, which is expected to hit the triple crown.

It has been 19 years since Arsenal last won the Premier League title in 2003-04.

Pochettino has agreed that Chelsea will sign Inter goalkeeper Onana this summer, while Eduardo Mendi and kovacic will leave Stamford Bridge.

Pochettino has agreed to start coaching the Blues next season, and he is expected to fly from Spain to England next week to finalize the terms of the deal and outline his requirements for the position of head coach.

Chelsea and Inter Milan have started talks on Lu Kaku, and Lu Kaku will return to Stamford Bridge after a season on loan. Lu Kaku joined Chelsea for 97.5 million pounds two years ago, but he returned to Inter Milan on loan before the start of this season because his performance failed to meet expectations.

The Blues hope to continue to invest this summer. It has been determined that the goalkeeper’s situation is a key signing area, and at least one of Kepa and Mendi will leave this summer. Inter Milan’s Onana is Chelsea’s main target, and the Blues are willing to exchange kovacic for the goalkeeper. Kovacic’s contract expires in 2024, but Lu Kaku’s future is still uncertain.

According to reports, Chelsea had previously offered to exchange Ruben Chick, Chaloba or Mendi for Onana, but it failed. Kovacic is the latest candidate proposed by Chelsea, and it is reported that he is open to the transfer.

Onana, 27, joined Inter Milan from Ajax last summer. He played for Ajax for 214 times, and this season he played for Inter Milan for 38 times.

"

A new application test automation method, which can quickly evaluate the experience quality provided by the world’s popular mobile applications.

German technology company recently announced the introduction of enhanced functions for its Nemo device application test suite. The software solution adopts automation technology and artificial intelligence (AI), which gives a powerful boost to wireless service providers and application developers, and can help them quickly evaluate the real interaction between smartphone users and local mobile applications. It is German Technology that provides advanced design and verification solutions, aiming at accelerating innovation and creating a safe and interconnected world.

In the past few years, the number of users who use mobile applications to access digital content and participate in social media platforms and online games has increased significantly worldwide. Compared with the mobile web browser, the local mobile app can provide a tailor-made excellent experience; Therefore, the use of mobile applications has significantly promoted this growth.

Matti Passoja, the head of Nemo wireless solution of De Technology, said: "Service providers and mobile application developers want to know the real experience of end users when they access OTT applications with smartphones connected to cellular networks, and they need a reliable way to verify it. It is DeTech that has created an automated application testing method based on its unique software and hardware technology platform. This method uses real applications, and can accurately understand network performance even in extremely complex and changeable situations. "

It is DeTech that makes full use of artificial intelligence, machine learning (ML) and automation technology, and uses the data captured by local mobile applications (instead of the simulated data flow) to create a brand-new device testing application method. This method can evaluate the interaction between end users and their mobile applications more accurately. The new application test automation method can help wireless service providers quickly optimize the performance of 5G network, and at the same time provide better quality of experience (QoE) for smartphone users. Users can enjoy the world’s most widely used OTT services and social media applications, such as Facebook Messenger, Microsoft Teams, Snapchat, TikTok and Zoom.

The new automatic test application method is one of the three supplementary test methods provided in Nemo device application test suite of German Science and Technology. According to the type of mobile application and key performance indicators (KPIs), the test method can be used with a Nemo field test solution. Nemo test suite users can obtain comprehensive, real and flexible 5G network performance verification and end-user QoE evaluation.

It is a Nemo testing tool of German Science and Technology, which can capture real measurement data in the field and use it for real-time analysis or post-processing analysis. These test tools include Nemo Outdoor 5G NR drive test solution, Nemo Backpack Pro 5G indoor benchmark test solution and Nemo network benchmark test solution.

Generative AI is getting more and more popular. Is this really a good business?

Recently, AI painting is on fire.

By inputting some words, AI can generate an image that matches the words in a few seconds. These images are wild, and some are even bizarre. For example, people have extra fingers on their hands, and their fingers bend unnaturally. Even, AI can generate some meaningless billboards and alphabets that humans have never seen before.

Although AI painting is outrageous, it has set off a wave of science and technology: the spring of generative AI has come.

David Beisel, a venture capitalist at NextView Ventures, said that in the past three months, the word "generative AI" once became a hot word. Moreover, the generative AI technology has developed rapidly and the market enthusiasm is so high that many people even quit their jobs to start a business in this field.

There is no doubt that AI has been in a prosperous stage in the past five years or so, but most of these past advances have to do with understanding the existing data-for example, the AI model has been able to quickly and efficiently identify whether there are only cats in your mobile phone photos. However, the generative AI model generates something completely new that has never been seen before. In other words, generative AI is not just about analyzing existing data, but creating.

Boris Dayma, founder of Craiyon generative AI, believes that "generative AI is not only creating old images, but also creating many new things, which are completely different from what we have seen before."

Sequoia Capital also said in a blog post on its website: "Generative AI has the potential to create trillions of dollars in economic value." Sequoia Capital predicts that generative AI may change all industries that require human beings to create original works, from games to advertising to the legal profession. It is worth mentioning that Sequoia Capital also pointed out in its blog post that this message was partly written by GPT-3 (GPT-3 is a generative AI capable of generating text).

Working principle of generative AI

In the past, deep learning technology was widely used to train the model on large data sets. When the program understands the relationships in these data, the model can be applied to actual scenes, such as identifying whether there is a dog in a picture or translating text, and so on.

The working principle of the image generator is to reverse this process. For example, instead of translating English into French, it translates English phrases into images. Specifically, it usually has two main parts, one is to process initial phrases, and the other is to convert data into images.

At first, generative AI was based on a method called GAN, that is, the generative adversarial network. In essence, this method is to make two artificial intelligence models compete with each other to better create images that meet the target.

At present, generative AI is usually based on Transformer, such as image generator DALL-E and so on. DALL-E was first created by OpenAI in 2021, and in 2022, OpenAI released DALL-E 2.

Christian Cantrell, a developer who focuses on generative AI, said: "With DALL-E 2, we can really cross uncanny valley." (The Valley of Terror theory is a hypothesis about human perception of robots and non-human objects. It was put forward by Japanese robot expert Masahiro Mori in 1970. )

Another commonly used AI-based image generator is Craiyon (formerly known as DALL-E Mini), where users can enter phrases in the browser and see the illustrations it generates within a few minutes.

According to Dayma, since its launch in July 2021, Craiyon has produced about 10 million unprecedented pictures every day, which adds up to 1 billion. Earlier this year, the use of Crayon soared, and Dayma also took Crayon as its full-time job. In addition, Dayma has created a Twitter account to post the weirdest and most creative pictures generated by Craiyon. For example, ketchup comes out of the tap on the Italian sink.

In addition, Stable Diffusion has also received wide attention. The project was released in August this year and has been open source on GitHub. Developers can run the project on computers, not just in the cloud or through programming interfaces. For example, Stable Diffusion can be integrated into Adobe Photoshop by plug-in, allowing users to generate backgrounds and other parts of images, and use layers and other Photoshop tools to operate in applications.

Cantrell, the developer of the plug-in, said, "I want to meet these creative professionals, so that they can introduce artificial intelligence into their creative work, instead of destroying their work."

It is understood that Cantrell has worked for Adobe for 20 years. After leaving in 2022, Cantrell focused on the direction of generative AI. Cantrell said that Stable Diffusion has been downloaded tens of thousands of times, and artists told him that they used this plug-in in many unexpected places, such as making Godzilla animation or creating pictures of Spider-Man.

Start-up companies get together

Some investors regard generative AI as a potentially transformative change, just like the early development of smart phones or the Internet. This kind of transformation has greatly expanded the potential market of this technology.

"Before that, artificial intelligence was not unprecedented. Before 2007, we were not without mobile devices, "said Beisel, a seed investor." But at this moment, everything came together. The final consumer can experience and see something different from before. "

Cantrell believes that machine learning is similar to a more basic technology: database. "Machine learning is a bit like a database, which opens up a whole new world for network applications. All the applications we have used in our life are built on the database. But no one cares about how the database works. People only know how to use it. "

Michael Dempsey, managing partner of Compound VC, said that in the past, it was "very rare" for laboratory technology to enter the mainstream, but at present, generative AI has attracted wide attention of venture capitalists. Nevertheless, he warned that the current generative AI may be in the "curious stage" near the peak of the hype cycle, and the companies established at this stage may fail because they don’t focus on the specific uses that enterprises or consumers are willing to pay for.

Others in the industry believe that startups that can apply new technologies such as generative AI today may challenge technology giants such as Google, Meta and Microsoft in the future.

At present, many companies applying generative AI technology have already received large amount of financing, and their valuations have also risen. For example, earlier this year, Hugging Face was valued at $2 billion after receiving investments including Lux Capital and Sequoia Capital; OpenAI has also received more than $1 billion from Microsoft and Khosla Ventures.

In addition, according to Forbes, Stability AI, the developer of Stable Diffusion, is negotiating with investment institutions to raise up to $1 billion in venture capital.

Cloud vendors and chip vendors will benefit.

Besides start-ups, cloud service providers such as Amazon, Microsoft and Google can also benefit from it, because generative AI may require a huge amount of computation.

Meta and Google have also taken action and started recruiting talents. In September of this year, Meta released an artificial intelligence application called "Make-A-Video", which can generate videos, which makes the generative AI technology a step further.

"This is a great progress," Zuckerberg, CEO of Meta, posted on his Facebook page. "It is much more difficult to generate videos than photos, because besides correctly generating each pixel, the system must also predict how they will change over time."

Recently, Google matched with Meta and released a program code called Phenaki, which can also convert text into video and generate several minutes of footage.

This craze may also boost chip manufacturers such as Nvidia, AMD and Intel, because the advanced graphics processors produced by these companies are ideal for training and deploying artificial intelligence models.

At a recent meeting, Huang Renxun, CEO of Nvidia, emphasized that generative AI is the key use of the company’s latest chip, and he said that this kind of program may "revolutionize communication" soon.

At present, there are not many uses of generative AI that can generate commercial benefits. Many exciting breakthroughs today come from free or low-cost experiments. For example, some writers have tried to use image generator to generate images for articles. An example of Nvidia is to use a model to generate new 3D images, including people, animals, vehicles or furniture, which can be filled into the virtual game world.

Ethical issues can not be ignored.

While generating AI excites the industry, the ethical issues it brings are also worthy of attention.

The first is employment. Compared with professional illustrators, generative AI is obviously cheaper. Therefore, generative AI is likely to rob artists, video producers and other people engaged in creative work of their "rice bowls".

In addition, there are complex problems in originality and ownership of the content created by generative AI.

Generated AI is trained on a large number of images. Therefore, it is still controversial whether the creator of the original image has copyright requirements for the generated new image.

Some time ago, an artist won an art competition in Colorado, and his winning image was created by a generative AI named MidJourney. After winning, the artist said in an interview that he selected one image from hundreds of images generated by himself and post-processed it in Photoshop.

It is worth mentioning that some images generated by Stable Diffusion are watermarked, which indicates that some of the original data sets are copyrighted. Previously, Getty Images (a picture trading company based in Seattle, USA) announced that it was forbidden for users to upload generated AI pictures to its picture library, because the company was worried that there might be some copyright problems in such pictures. .

With the improvement of image generation software, generative AI may also deceive users, make them believe false information, or display images or videos of events that never happened.

In addition, developers must also deal with the possibility that models trained on a large amount of data may have biases related to gender, race or culture contained in the data, which may cause the models to show such biases in their outputs.

Original link:

Source: AI Frontline, author: Kif Leswing. If there is any infringement, please contact to delete it.

People don’t seem to care much about the future world described in the sci-fi movie The Matrix, but a recent news released on the Meta platform has made people curious about the future world. According to Forbes, a virtual community named Game Free is building a virtual world-"Metauniverse". It has been established for more than ten years, but it is relatively simple compared with the world in the Matrix. What is the magic of meta-universe? Has it become a reality now?

I. Future Society
The idea of "Metauniverse", first put forward by Meta Company, is an expression way to turn people’s vision of the future society into reality. In the setting of X-Men, Professor X has special devices and abilities in real life, and can breathe and move freely, but he can’t turn his control into a real society. The reality is not infinitely close, but gradually close to the ideal society. That is to say, the "infinite approach" pursued by the X-Men is not realistic in real life: it is impossible to turn one person into another; Unable to control human behavior; Unable to control the direction of people’s actions in reality … eventually led to the X-Men being abandoned by the world. If the X-Men movies are sorted out, it is found that the movies have a clear vision for the future society, then the meta-universe will be closer to the real state in reality: on the one hand, the meta-universe, as a virtual space, can be infinitely connected to the real world; On the other hand, Metauniverse will become the key "cornerstone" for building the infrastructure of human society … So what will human society become in the future?

Second, intelligent hardware
The universe is not only a game world, but also a technology. In MetaUniverse, through various virtual carriers such as games and videos, MetaUniverse players can be immersed in it, which is not only a space for games and entertainment, but also an interactive space for knowledge, skills and contacts. There is a kind of meta-universe in a special sense, which is a "virtual life" mode in which the virtual world and the real world merge, influence, blend, promote and expand with each other. It is a place where people can exchange and interact with each other, acquire knowledge and skills and cultivate friendship in this virtual world. For users, Metauniverse makes itself a "human" character-this is the experience they need in games and the real world. For hardware equipment manufacturers, it is the performance of the product itself besides ensuring entertainment, interaction and other functions.

Third, artificial intelligence
As the core of scientific and technological innovation, artificial intelligence will gradually get more applications in the meta-universe. With the help of human beings, artificial intelligence has developed from relying on single software and single function in the past to the present artificial intelligence. In the future, artificial intelligence will be more dependent on computing power. For example, driverless cars are an attempt to realize barrier-free travel in the meta-universe. Starting from the progress in the field of driverless cars, this paper explores the possible forms that driverless cars may appear in the meta-universe, hoping to provide more exploration space for the meta-universe. It is foreseeable that artificial intelligence will play an important role in the meta-universe in the future.

IV. Conclusion.
With the rise of meta-universe, virtual world has been given more and deeper meanings, and the application of science and technology by human beings has changed from passive acceptance to active creation. At the same time, the lifestyle and experience provided by the virtual world in the meta-universe have greatly enriched human thinking and feelings, and made people interested in a new thing. However, with the development and innovation of technology, this trend will gradually become stable. But we believe that technology is always a double-edged sword. It can bring convenience and benefits to human beings, but it may also bring harm to human beings. Like the future world described in science fiction movies, human beings are sleeping in a dormant warehouse made of machines, and their brains are linked to the meta-universe world, so they live falsely.

From scientist to entrepreneur, Yu Kai is not the first person to "run away" in the field of artificial intelligence.

Despite the previous achievements in scientific research, joining in entrepreneurship means facing the reality of bone feeling.

In March 2015, Yu Kai said in an interview: "If a business can get the resources it deserves to do what it wants, then choose to start a business; If you join a big platform and have more resources to do one thing, then join a big platform. " Sure enough, three months after that, he left Baidu and founded Horizon.

From the initial "no one pays the bill" to October this year, Horizon successfully won the investment of 2.4 billion euros from Volkswagen, setting the largest single investment record for Volkswagen in the past 40 years, and establishing a joint venture company with audi ag’s software company. The transformation of Yu Kai’s identity can be described as unsuccessful.

Before becoming the founder of Horizon, Yu Kai’s label was the top international scholar in the field of machine learning and the main promoter of deep learning technology in China. His published papers were cited more than 20,000 times, and he won the silver award for the best paper in ICML-2013 International Machine Learning Conference. He himself also served as the domain chairman of ICML and NIPS, two major conferences of machine learning.

Yu Kai’s achievements in the academic field go far beyond this.

NEC Research Institute of the United States was once one of the major centers of international machine learning research. During his tenure, Yu Kai established a highly prestigious technology research and development team in Silicon Valley. This team is one of the earliest and most active teams in the field of deep learning in the world. A series of technologies led and developed by him have pushed image object recognition to a new level worldwide, and won many international famous awards.

After joining Baidu in 2012, the voice technology team, deep learning technology team and image technology team led by Yu Kai won the "Baidu’s highest award" three times in succession, creating records of various technical and business teams within Baidu.

In the eyes of outsiders, Yu Kai at that time, both academically and professionally, was smooth sailing.

But at this time, he chose to start a business.

Yu Kai’s reason is straightforward: "In the past three years, what I have done at Baidu is to promote artificial intelligence in the cloud. But I think there will be a bigger trend in the next few years that I have to do: from artificial intelligence in the cloud to artificial intelligence around everyone. "

Therefore, Yu Kai, who has always believed in "doing things is the most important thing", founded Beijing Horizon Information Technology Co., Ltd. in July 2015, focusing on edge computing in the field of artificial intelligence.

From the moment the company was founded, in his own words: First of all, I will forget that I am a scientist more and more.

To be a scientist, you can put the mainexperienceDo research and write papers, but as an entrepreneur, you should focus more on business and customer needs.

Yu Kai has always wanted to grasp some "truth" things in this process, for example, things that can really create long-term value. With this idea in mind, at the beginning of Horizon’s establishment, he played the slogan of "making brains for machines", and avoided the edge of the field giants, took the edge computing route, and insisted on making AI chips.

It was really hard at first.

When recalling the initial stage of starting a business and determining the development direction, Yu Kai mentioned: At that time, we were predicting a far future, a future that might take 20 years as its dimension. From computers to smart phones, and beyond, what is a bigger computing platform than these? At that time, they were sure,beRobot computing platform. AI chip is the indispensable key to realize this calculation.

Now that we hear about AI chips, it’s needless to say its importance. But when Horizon was founded, not every investor could understand the "blueprint" in Yu Kai’s eyes. As a direct result, the horizon was once unsustainable. Until smart cars become "robots"calculate"The first and biggest landing scene at present, everyone began to understand that Yu Kai had bet on it.

In 2020, smart cars ushered in an outbreak period. As a result, there is a global "lack of core" in the automotive industry.question.

A chip with excellent computing power, like a smart brain, can accurately control the behavior of the vehicle. A series of functions, such as environmental awareness, route planning, driving assistance and so on, advertised by smart cars all need to rely on chips to be realized.

This is also consistent with what Yu Kai has always wanted to do. He has always believed that the real significance of artificial intelligence is not to survive and develop as the opposite of human life, but to support people’s decision-making and enhance their ability. Once the smart car scene is broken down, this ability will definitely spill over to others.floatApplication scenario of robot.

In August 2019, Horizon announced the mass production of China’s first car-class AI chip "Journey 2";

In September 2020, Horizon officially launched the AI chip "Journey 3";

In July, 2021, Horizon released "Journey 5", a high-performance and large-computing, full-scene intelligent central computing chip for the whole vehicle.

……

Yu Kai once said, "The course of a scientist’s entrepreneurship is not based on business opportunities,FromStart in the future. "

This cooperation between Horizon and Volkswagen may be the next future in Yu Kai’s plan.

Analysis of industrial chain, market demand potential and enterprise layout of domestic smart speaker industry in 2022 [Figure]

Smart speaker, the product of a speaker upgrade, is a tool for home consumers to surf the Internet by voice, such as ordering songs, shopping online, or knowing the weather forecast. It can also control smart home devices, such as opening curtains, setting the refrigerator temperature, warming up the water heater in advance, etc.

Basic functions of intelligent speakers

Source: Collation of Common Research Network.

Intelligent speaker industry chain includes traditional acoustic-related OEM/ODM suppliers, chip suppliers, voice technology service providers, content providers and channels.

Intelligent speaker industry chain

Source: Collation of Common Research Network.

In 2019, China’s smart speaker market experienced explosive development, with the shipment of smart speakers reaching 45.89 million units, up by 109.7% year-on-year. In 2020, affected by the Covid-19 pandemic, the sales volume of smart speakers reached 36.76 million units, with a cumulative decrease of 8.6%. In 2021, the market shipment of smart speakers contracted by 2.50% year-on-year, dropping slightly to 35.841 million units.

2018-2021 China Smart Speaker Market Shipment Trend

Source: Collation of Common Research Network.

In 2021, China’s smart speaker market was 7.885 billion yuan, up by 14.99% year-on-year. With the continuous integration and improvement of intelligent speaker artificial intelligence technology, the potential of smart speaker consumption market in China will be released in the future, and the industry is expected to usher in rapid growth.

2018-2021 China Smart Speaker Market Scale Trend

Source: Collation of Common Research Network.

At present, the main functions of smart speakers in China are voice interaction, content service and home control. Voice interaction is a voice interaction technology based on voice recognition and semantic understanding, which provides a more natural man-machine interaction mode. Content service and life service are streaming media resources such as high-quality music and audiobooks, and third-party service resources such as take-out and taxi service. Home control is connected to the cloud through networking, becoming a home control center and interconnected with other smart home products. With the development of voice interaction technology, smart speaker products can not only provide content entertainment services and life services, but also connect to smart homes, realize scene intelligent control, and become the control center of smart homes. In the future, the Internet of Things will take voice as its population, resulting in a new business model.

Domestic layout smart speaker manufacturers can be divided into five categories.

Source: Collation of Common Research Network.

What is the market prospect of smart speaker industry? The 2023-2029 China Smart Speaker Market Survey and Investment Strategy Report published by Gongwang has analyzed in detail the relevant definitions of smart speaker industry, the global smart speaker industry market development status, the development environment of smart speaker industry in China, the operation of smart speaker industry in China, the monitoring of the operation data of smart speaker industry in China, the market structure of smart speaker in China, the demand characteristics and trends of smart speaker industry in China, China smart speaker industry regional market situation, China smart speaker industry competition, China smart speaker industry development prospect analysis and forecast, China smart speaker industry development strategy and investment suggestions, etc., to help enterprises and investors understand the smart speaker industry market investment value. If you want to have a systematic understanding of the smart speaker industry or invest in the smart speaker industry, this report is your indispensable and important tool.

Recently, Yan Ning, a famous structural biologist, announced that he would resign from Princeton University and set up the Academy of Medical Sciences in Shenzhen. In response to the latest research that she will focus on when she returns to China, she said that the discovery of structural biology is of great significance to the pharmaceutical industry, including the research on the interaction between drugs and hormones, which has more implications for drug development and disease treatment.

Yan Ning said, for example, that through the method of structural biology, scientists saw for the first time that two commonly used drugs used protein as a "scaffold", which directly "side by side" affected the normal function of protein.

Technological change promotes the development of structural biology.

Protein, as the scaffold and main substance of human tissues and organs, plays an important role in human life activities. In the cell, a large number of protein elements form the molecular machines, which performs important molecular processes in the cell through the interaction of protein, including the cell’s response to the external environment and the internal environment, and also forms a signal transduction network system with the interaction of protein as a link.

Structure By studying the three-dimensional structure, dynamic process and biological function of biological macromolecules, biology can provide more details of protein interaction and real-time dynamic process, thus helping scientists to understand molecular mechanism and explore the pathogenesis of diseases related to macromolecular dysfunction.

The development of biology not only contributes to the discovery of drugs, but also affects the research fields of life sciences including biochemistry, cell biology, genetic development, neurobiology, microbiology and pathopharmacology.

The development of science and technology has been promoting the progress of structural biology. In 2017, the Nobel Prize in Chemistry was awarded to cryoelectron microscopy, which can greatly improve the efficiency of analyzing the atomic resolution three-dimensional structure of large protein complexes; Moreover, researchers can freeze biomolecules in motion and visualize their motion process.

This breakthrough has brought a perfect storm to the field of structural biology. In recent years, important breakthroughs have been made in the field of life sciences. The work of China scientists such as Cheng Yifan, Shi Yigong, Yang Maojun and Liu Zhengfeng has also benefited from this technology. They have analyzed the important complex structure of atomic resolution. In addition, the enzyme that produces the protein that leads to Alzheimer’s syndrome was analyzed by cryomicroscope.

In August, 2015, Shi Yigong’s research team published an article in Nature, reporting the three-dimensional electron microscope structure of human γ -secretase with a resolution of 3.4 angstrom, and studying the function of the pathogenic mutant of γ -secretase based on the structure analysis, which provided an important foundation for understanding the working mechanism of γ -secretase and the pathogenesis of Alzheimer’s disease.

In February, 2020, after the outbreak of COVID-19, the research team of West Lake University successfully analyzed the full-length structure of novel coronavirus receptor ACE2 for the first time by using cryo-electron microscopy, which helped the research and development of drugs in COVID-19.

What does AI predict protein folding change?

With the help of artificial intelligence technology, DeepMind, a subsidiary of Google, recently announced 220 million kinds of protein structures predicted by AlphaFold software, which shocked the field of structural biology, because it indicates that artificial intelligence enterprises have begun to "truly hand over the power of Al to scientists all over the world".

Scientists compare the significance of this disruptive breakthrough with the human genome project. In the 1990s, when the Human Genome Project began to take shape, scientists realized that it was not enough to master the base arrangement of genes, but also to know the protein, the product of genes.

Shi Yigong, academician of China Academy of Sciences, structural biologist and president of West Lake University, commented on AlphaFold’s work: "Its accurate prediction of protein structure is the greatest contribution of artificial intelligence to the scientific field, and it is also one of the most important scientific breakthroughs made by mankind in the 21st century."

Shi Yigong once told China Business News: "AlphaFold represents the world’s leading artificial intelligence protein organization prediction system." At the same time, he said, China’s high-tech enterprises are catching up, expecting to bring surprises to the world in the near future.

He also said that the improvement of the accuracy of protein structure prediction will greatly benefit the pharmaceutical industry. "Artificial intelligence prediction of protein structure provides an important foundation for drug design and optimization. The structure of drug target proteins combined with all small molecule drugs can almost be wiped out by AlphaFold. " Shi Yigong said.

In the opinion of some scientists, although AlphaFold’s work is shocking, the accuracy of drug research and development prediction is not enough. Professor Liu Zhijie, executive director of iHuman Institute, Shanghai University of Science and Technology, told the First Financial Reporter: "It has been a long time to predict the protein structure. Now the accuracy of the prediction is definitely getting higher and higher, but it still hasn’t reached the precision of crystal structure."

Liu Zhijie First Financial News told the reporter that the crystal structure is the most accurate, and now artificial intelligence can predict the protein folding with the accuracy of electron microscope and nuclear magnetic resonance. In addition, because there are thousands of structures in protein, the difficulty of analysis is different. "If some protein sequences are similar to the known structure of artificial intelligence, it is easier to predict." Liu Zhijie said.

However, he still believes that with the continuous improvement of the prediction accuracy of protein folding, it will play a more important role in the field of life sciences in the future. "If the current prediction can reach the accuracy of electron microscope, some drugs can already be designed. Drug design is the biggest application field of artificial intelligence protein folding prediction." Said to Liu Zhijie First Financial Reporter.

Others think that with the development of artificial intelligence, there may not be so many structural biologists in the future. "Many researchers who do structural biology are actually more like technical service personnel. The more people there are, the more structures that can be analyzed. Therefore, in essence, a large part of their work depends on manpower. Now with AI, it is true that a large number of people who do structural biology have changed careers." A virus researcher told the First Financial News reporter.

However, for top structural biologists such as Shi Yigong, technology is only a powerful support for the "top brain", which can help them realize more ideas. "Every conscientious biologist should know how to make good use of the structural prediction of artificial intelligence." Shi Yigong said.

Professor Michael Levitt, winner of the Nobel Prize in Chemistry in 2013, told China Business News: "I think many structural biologists are not only doing structural research, but also doing a lot of work on protein function and drug research and development, just like Professor Yan Ning. Artificial intelligence only liberates a part of traditional manpower, but the progress of science still needs to rely on the smartest human brain. I’m afraid that artificial intelligence alone will not work. "

In recent years, a number of AI pharmaceutical companies have also been born in China. In this regard, Ewing Nan, academician of Chinese Academy of Sciences and president of Beijing Institute of Scientific Intelligence, pointed out to the First Financial Reporter: "The emergence of AI for Science research paradigm is an important historical opportunity for scientific and technological innovation, which not only expands the capability boundary of data-driven and physical model-driven models, but also is expected to promote the organic combination of the two, provide theoretical basis for further solving practical problems, and greatly narrow the distance between scientific research and practical application."