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There are many excellent niche games in today’s game market. They may not be advertised by big manufacturers, but they have unique gameplay and deep storylines. The following are some niche games I recommend for you. They all have unique features and charms. I hope you will like them.

1.《Celeste》

Chinese name: azure

Celeste is a platform game released by Canadian game developer Tommo. In the game, the player plays a girl named Madeline, who climbs a mountain and overcomes her inner fear. The game screen is simple and fresh, the music is beautiful, and the game is extremely difficult, which requires players to constantly challenge their limits.

2.《Papers, Please》

Chinese name: Please show me your certificate.

Papers, Please is a simulation game made by American game developer Lucas Pope. The player plays a border inspector to check the documents and information of passengers to prevent illegal entry. The game screen is simple and plain, and the music is dull, but the game plot is exciting and thought-provoking.

3.《Stardew Valley》

Chinese Name: Tale of Star Dew Valley

Stardew Valley is a simulated business game produced by American game developer ConcernedApe. The player plays a city resident, inherits an abandoned farm, and needs to manage the farm, grow crops, breed animals, collect resources, etc., and experience the fun of rural life. The game screen is exquisite, the music is soothing, and the game content is rich. It is a very suitable game to relax.

4.《Undertale》

Chinese name: undertale.

Undertale is a role-playing game created by American game developer Toby Fox. Players play a human trapped in the underground world and need to communicate with various monsters and choose different fighting methods. The cartoon of the game screen is lovely, and the music is cheerful and pleasant, but the game plot is profound and thought-provoking.

The above are some niche games that I recommend for you. They all have unique characteristics and charm, and are worth a try by players.

Live on May 21st, Beijing time, in the early morning of May 21st, in the 36th round of Serie A, AC Milan beat Sampdoria 5-1 at home. After the game, coach Pioli was interviewed.

Pioli said: "It’s good for us to have a game to play, because we have to get rid of the negative impact of the Champions League elimination. We scored a lot of goals in this game, which will only help us move forward in Serie A.. We still have two games to play this season, and then we will get the final result. Obviously, our performance in the Champions League group stage exceeded expectations, and we were eliminated in the group stage last year. On the other hand, our performance in the league failed to meet expectations.

"Our performance in the league was too unstable and we didn’t get many victories like this game. Next we will play against Juve, and we will try our best to prepare and remember that when we play beautiful football, we can do well. In the past two seasons, our journey has been extraordinary, far exceeding anyone’s expectations. We turned the balance sheet positive, helped a young team grow and won the league title, and also entered the semi-finals of the Champions League.

"It’s true that we represent Milan. We should be competitive in Italy and Europe. We have raised our standards, but some mistakes in Serie A this season have affected our position. I am proud of the decision made by the club, the board of directors and my players, because I know we are trying to improve ourselves. I believe we will learn more from this season than last season, because difficulties will help you become mature and understand things better.

"Gill is a strong player and the team has a solid foundation. The club has done a good job in renewing players’ contracts. We must also remember that there are no substitute players now, and everyone needs to contribute. I am proud of what we have been doing. The peak is beautiful and the trough is painful, but we know what we want to do and who we are, and we will continue to grow and make our fans happy. The team has had ups and downs this season, but the fans have always been positive. They have always stood by us and performed impeccably.

"I don’t know whether moral Kate Lare can stay in the team next season. We haven’t discussed the details yet. People forget too quickly how our young players struggled at the beginning, such as Tonali and Leo. Every player who comes to Milan needs time to realize what it means to play in such a stadium full of expectations and atmosphere. It takes time and patience, and we have both.

"My goal is to change this team."

Lei Feng, a good soldier of China People’s Liberation Army, is admired and loved by people all over the country for his selfless dedication and noble character. However, due to technical limitations, Lei Feng’s image data before his death is not complete, which makes many people have doubts and misunderstandings about his characters and deeds.

Now, with the continuous development and application of artificial intelligence technology, we have the possibility to repair the image of Lei Feng before his death, so that we can get to know this great man again.

Through AI technology, the image of Lei Feng before his death can be repaired and reconstructed, making his image more real and clear. This will not only help us better understand Lei Feng’s life and deeds, but also inspire more people to learn Lei Feng’s spirit and inherit Lei Feng’s patriotism and humanitarianism.

The process of restoring Lei Feng’s image before his death is not simple, and it needs a lot of data and algorithm support.

First of all, it is necessary to collect photos and video materials of Lei Feng before his death, and then analyze and reconstruct these materials through image processing and deep learning algorithms. Finally, a group of high-definition and authentic images of Lei Feng were obtained, which made people feel his image and deeds more truly.

Restoring the image of Lei Feng before his death is not only a technological innovation, but also a cultural inheritance and value transmission.

Through this AI technology, the history and culture of China can be better spread, and at the same time, more people can be encouraged to learn from Lei Feng’s spirit and inherit his patriotism and humanitarianism.

Lecture topic:When molecular design and experimental design have AI blessing, the new version of MaXFlow3.6.1 material will be released.

Lecture time:Thursday, March 16th, 2023, 15:00.

Speaker:Chuangteng Technology Lecturer

It takes only 2 seconds to obtain a stable 3D molecular structure?

The generation of three-dimensional conformation of molecules plays a key role in the design of small molecules in materials science, life science and other fields. Traditional methods usually need to predict the distance between atoms, the gradient of distance or the local structure such as twist angle, and then reconstruct its 3D conformation.

In MaXFlow3.6.1, the DMCG component will be launched soon. DMCG is a method to directly predict the atomic scale, that is, to directly generate the three-dimensional coordinates of molecules without considering the intermediate value. This method can adaptively combine bond and atomic information, and refine the generated conformational coordinates through continuous iteration. This method has achieved good performance on both GEOM-QM9 and GEOM-Drugs data sets.

MaXFlow3.6.1 is about to launch the online molecular 3D coordinate generation module DMCG. DMCG can directly predict the three-dimensional coordinates of each atom without providing intermediate values such as bond length and bond angle, and visualize the optimized three-dimensional structure. This method automatically extracts bond and atom information from molecular SMILES, and obtains the lowest energy conformation through iterative optimization. DMCG has achieved excellent performance on both GEOM-QM9 and GEOM-Drugs data sets, and its intrinsic properties such as band gap of the generated conformation are consistent with the real values. This method will provide an effective basis for subsequent property calculation and molecular simulation.

With it, the optimization of reaction conditions will no longer make you "bald"

In the process of preparing new materials, many reaction parameters are usually involved. In order to find the best preparation scheme and obtain the best yield, a lot of experimental verification is often needed, which brings a lot of workload to researchers and is very time-consuming and labor-intensive. How to optimize the experimental design scheme by means of AI, so that researchers can find the best scheme only through a limited number of experiments?

MaXFlow, a molecular simulation and artificial intelligence platform, integrates machine learning algorithm with experimental design (DOE), which helps researchers quickly lock the optimal interval and greatly reduces the number of verification experiments.

In MaXFlow3.6.1, EDBO component will be launched soon, which integrates Bayesian optimization algorithm. Bayesian optimization is a global optimization algorithm based on iterative response surface, which shows excellent performance in the tuning of machine learning model. In recent years, Bayesian optimization has also been applied to the chemical field. Using Bayesian optimization method in experimental design can effectively help optimize process parameters, thus realizing data-driven decision-making.

At this conference, you will also learn about MaXFlow’s rich model building functions.

[Text/Song] Recently, Lin Shi, Secretary General of Intelligent Networked Automobile of China-Europe Association, met with Ji Lianying, co-founder of Mu Niu Technology, at the first private board meeting, and presented a letter of appointment to Ji Lianying to hire him as an intelligent networked automobile expert of China-Europe Association. Subsequently, the two sides exchanged in-depth technical information, development strategy and direction of Muniu Technology.

Ji Lianying received his Ph.D. from Beijing Institute of Technology in 2009. He has worked in embedded systems, human perception technology, artificial intelligence algorithms and other research institutions such as China Academy of Sciences and National University of Singapore. He used to be the technical director of Wuxi Microsense Technology Co., Ltd., and developed the first full-body motion capture system in China. Before he founded Mu Niu, he worked in the University of Chinese Academy of Sciences. Muniu Technology was established in Kansas, USA in May 2015, and the Beijing R&D Center was also established in July. The name of Muniu Technology comes from Muniu Liuma —— The Muniu Liuma invented by Zhuge Liang and others in the Three Kingdoms period is the embryonic form of intelligent transportation. The Muniu team took this as an incentive, embraced the intelligent era and paid tribute to China’s intelligence and wisdom. Muniu Technology has a combination of Chinese and American genes, which has avoided the early exploration stage and directly started to exert its strength in the field of 77GHz. It has been at the forefront of technology from the beginning and has achieved fruitful results.

Ji Lianying said at the meeting: "The core founding teams of the company all graduated from the Institute of Radar Technology of Beijing Institute of Technology and have more than ten years of research and project experience in radar. The company has been focusing on the research and development of millimeter-wave radar, and has profound technology and research and development strength in broadband antenna, MIMO and signal processing, and is at the leading level in the industry. Has more than ten patents. "

Ji Lianying said: "In the radar market, the passenger car market is the largest, but this market is basically monopolized by international manufacturers. In the field of commercial vehicles, foreign manufacturers disdain to do it, which is a very big blue ocean for domestic manufacturers. In the field of autonomous driving, the demand for driverless technology is relatively high. "

Lin Shi, secretary-general of China-Europe Association Intelligent Networked Automobile, pointed out that as a startup company, Muniu Technology has faster and stronger execution compared with large companies, so it may be faster than large companies in the innovation and creation of the same new technology. The popularization of ADAS to low-end cars requires higher cost performance and more practical technical support. China has both the largest manufacturer of low-end cars and a highly innovative enterprise like Muniu Technology, which is the weight to participate in the global automobile market competition.

Lin Shi, Secretary-General of China-Europe Association Intelligent Networked Automobile, is looking forward to the future development of Muniu Technology. He hopes that Muniu Technology will "escort" China’s new energy automobile industry by relying on the "hard power" of its own enterprises in the intelligent era.

Since ChatGPT swept the world, companies have opened their wallets to explore this technology, and the field of artificial intelligence has set off a new wave of enthusiasm. It has also attracted people’s attention to GPT-3 of OpenAI, which is a large language model (LLM) behind phenomenal ChatGPT, and it provides similar human responses to queries.

However, the hardware for training code (mainly NVIDIA GPU) is in short supply and expensive, or only companies with strong financial resources can use it. However, Pittsburgh Supercomputing Center hopes to provide researchers with free access to the world’s largest chip to run the Transformers model. Microsoft has applied GPT-3 to AI technology in Bing search engine.

The Supercomputing Center (PSC) of Carnegie Mellon University and Pittsburgh University is launching a new round of access to the CS-2 system of Cerebras, which is widely used to train large-scale language models. CS-2 is the AI accelerator in the Neocortex supercomputing system of PSC.

CS-2 has a wafer-scale engine chip of Cerebras, which is considered to be the largest chip in the world with 850,000 cores. The chip is used in artificial intelligence (AI) and traditional supercomputing (such as the decarbonization project used in the National Energy Technology Laboratory), which provides more accurate results through logical calculation.

PSC welcomes high-performance computing projects mainly related to artificial intelligence and machine learning workload, but it is not popular with traditional high-performance computing applications. The project encourages applications to adopt AI algorithm to run traditional HPC workloads. These proposals must be non-patented and can only come from American research institutions or non-profit organizations.

In addition to GPT-3, CS-2 system also supports the popular BERT Transformers model.

Andrew Feldman, CEO of Cerebras Systems, said: "There is a lot of discussion about large language models and very large language models. However, after a given scale (for example, 13 billion parameters), the number of organizations that actually train a language model from scratch is very small. Because you need to solve a lot of hardware problems first. "

Generally, running the Transformers model requires a lot of data, data science knowledge and deep machine learning expertise. Training data takes several weeks, and hardware options include GPU and TPU(GPU is used by Microsoft for Bing and AI, while TPU is used by Google for Bard chat bots).

Neocortex of PSC has been used to study artificial intelligence in the fields of biotechnology, cosmic vision map and health science. The system is also used to study the method of deploying AI on the new memory model deployed in CS-2.

Cerebras’ WSE-2 chip in CS-2 contains 2.6 trillion transistors, and all related AI hardware is concentrated in a chip size. The system has 40GB SRAM on-chip memory, 20 PB bandwidth per second and 12 100Gigabit Ethernet ports. CS-2 is connected to HPE’s SuperdomeFlex system, which has 32 Intel XeonPlatinum 8280L chips, each with 28 cores, and the running frequency is as high as 4GHz.

In contrast, NVIDIA GPUs are usually distributed on many systems. Nvidia’s GPU relies on CUDA parallel programming toolkit, which is widely used to study artificial intelligence. Feldman: "I think we have a great chance to replace GPU and TPU and do it in a more effective way-achieve better goals with fewer mistakes."

The demand for ChatGPT has overwhelmed the OpenAI system, so the demand for AI computing will be overwhelming in the future.

Artificial intelligence (AI) means that machines simulate human intelligent behavior by means of learning, reasoning and automation technology. The rise of AI industry originated from the field of computer science, and began to develop since 1950s, but the period of real rapid development was in recent years, especially after 2010. This paper will make a deep analysis of the AI industry from the perspectives of the development history of the AI industry, the upstream and downstream interpretation of the industrial chain, the analysis of key companies and people, and the analysis of industry hotspots.

First, the development process of AI industry

Since 1950, the AI industry has started research and experiments for decades, but it didn’t really enter the outbreak period until after 2010. In 2010, Watson of IBM was in Jeopardy! Beating two famous players in the game attracted global attention. Since then, AlphaGo has defeated the top players in the Go game, which proves the powerful ability of AI technology. In 2017, AlphaGo Zero developed by Google’s DeepMind company defeated the previous AlphaGo, showing a higher level of intelligence. In addition, with the progress of hardware technology, the application of AI industry has become more and more extensive, such as face recognition, autonomous driving, smart home and other fields, which has brought the development of AI industry into a new stage.

Second, the upstream and downstream interpretation of the industrial chain

The industrial chain of AI industry can be divided into three parts: hardware, algorithm and application. In terms of hardware, it mainly includes chips, sensors, servers and other equipment. The algorithm part is the core of AI technology, mainly including machine learning, deep learning, natural language processing and other technologies. The application part is the landing application of AI technology, involving artificial intelligence medical care, smart home, autonomous driving, smart city and other fields.

In the upstream of the industrial chain, chip manufacturers are an important part of the AI industry. At present, the world’s major AI chip manufacturers include Intel, NVIDIA, AMD, Broadcom and other companies. The chip products of these companies can be used in cloud computing, Internet of Things and other scenarios. In the middle reaches, AI algorithm companies are key players, such as Baidu, Google, IBM, Microsoft and other companies have their own AI algorithm research teams. In addition, there are some AI companies that focus on a certain field, such as artificial intelligence medical companies. Downstream, AI application companies are the main components of the AI industry chain, including artificial intelligence medical care, smart home, autonomous driving and other companies. These companies have applied AI technology to actual scenes, which has brought great commercial value.

Third, the analysis of key companies and people

In the AI industry, some key companies and figures have attracted much attention. Among them, Google and Facebook are considered as leading companies in the AI field. Google has strong strength in artificial intelligence research. Through its AI subsidiary DeepMind, Google has made many achievements in the fields of AlphaGo and AlphaZero. Facebook, on the other hand, has shown great strength in the fields of face recognition and speech recognition. By acquiring companies such as Face.com and Wit.ai, Facebook has made many attempts in the field of AI.

In addition, Andrew Ng is considered as one of the important figures in the field of artificial intelligence. He was the leader of Google’s artificial intelligence team and played an important role in some AI projects of Google. Later, he joined Baidu and founded Baidu’s Artificial Intelligence Research Institute, transforming Baidu from a traditional search engine company into an AI company.

Fourth, analysis of industry hotspots

The hot issues in the AI industry mainly involve technology, safety and ethics. In terms of technology, the development of artificial intelligence still faces some challenges, such as how to improve the efficiency of machine learning and how to deal with the problem of data scale. In terms of security, the black box problem of AI has always been concerned, that is, the decision-making process of AI model is opaque and difficult to explain. Ethical issues are also an important topic in the AI industry, such as how to ensure that the development of artificial intelligence is in line with the interests of mankind, how to avoid the negative impact of AI on society, and so on.

In addition, autonomous driving is also an important hot spot in the AI industry. Autopilot technology has a wide application prospect in automobile, logistics and other fields. However, the realization of autonomous driving technology still faces many technical challenges, such as how to deal with complex traffic environment and how to ensure the safety of vehicles.

In short, with the continuous development of AI technology, the prospect of artificial intelligence industry is very broad. At the same time, the development of AI technology also needs the joint efforts of society to ensure that the application of AI is in line with the interests of mankind and avoid negative impacts on society.

Mohamed Salah missed a penalty for OPE against Bournemouth at noon on Saturday.

VAR awarded Liverpool handball

Salah broke the reds’ first goal of the season.

Klopp lost to relegation fighter Bournemouth.

What happened? Liverpool were awarded a penalty for Adam Smith’s handball, which gave them a chance to equalize the score against Bournemouth. Salah stood up for Liverpool’s first penalty of the season and uncharacteristically missed the ball!

The bigger picture: Liverpool hope to take advantage of last week’s 7-0 victory over Manchester United on the South Coast. Philip Bill scored the only goal of the game, and the Red Army fell behind. They thought they had a chance to return to the game before Salah missed the penalty.