After suffering a "Double Red Club" fiasco in the Premier League, Manchester United pressed Bedis to regain its glory in the Europa League. The first goal of the stadium, although Manchester United only added 4-1 icing on the cake, but the Dutch national team players were still excited to tears. Coach Tenghage once again hailed him as an unsung hero of Manchester United.

Wieghorst joined Burnley on loan during the January transfer window. He only scored one goal in the Carling Cup away game against Nottingham Forest. According to Opta, he has collected 22 shots at Old Trafford. He didn’t score any goals. This game was his 23rd shot and he finally scored. He immediately rushed to the corner flag and knelt down to celebrate. He was so excited that he almost screamed. Manchester United fans criticized Wieghorst for touching the sign "This is Anfield" when he left Liverpool. This goal at Old Trafford made him feel relieved.

Manchester United coach Vladimir Tenghage said after the game: "As a striker, he was very close to scoring goals many times before. Wieghorst has been helping his teammates create space and opportunities, and now he finally gets the goal he deserves. "

De Blau got Guardiola’s support in his recovery, but the Manchester City manager hinted that if he didn’t play his best, there would be no guarantee that he would get the starting position. De Braune recently missed two games due to injury, and resumed starting in last week’s game. Guardiola called his performance in the first half "passive", but after the intermission, the Belgian’s performance improved and scored a wonderful goal.

However, in the game against Newcastle last week, De Braune was somewhat out of step, which prompted the manager to tell him to "get back to basics" in this week’s training. With Manchester City’s away game against Crystal Palace on Saturday, Guardiola supported him: recovering from a slight decline.

Guardiola explained: De Braune is ready to play, just like other Manchester City players. On the first day of our arrival, everyone stayed late for training. At the same time, Gua Shuai also said: He reserved the possibility of rotating the lineup at Selhurst Park. I know him well and know how important he is. At the same time, there are ups and downs, just like Phil Forden and other players, they compete with other players. At a certain stage of the season, it is normal that one player may be better than another player and the other player may be worse. I hope the team can win this special game. Football is always so unpredictable. In these seven years, De Braune has always been himself. When he missed the game, he was either rested, tired or injured.

Guardiola said that the next week will be "decisive" for Manchester City, which will be their last Premier League game before the international match day, followed by the second leg of the Champions League 16 against Leipzig and the FA Cup quarter-final against Burnley. After announcing that De Braune was ready for these games, Guardiola insisted: The only focus of Manchester City is to go to London to challenge Crystal Palace.

"I will never give priority to the Champions League. We are fighting for the Premier League. The most important thing is the league. We have had a long week, so we need to have a good rest, rest for two days and try to play well. This has nothing to do with Leipzig. The strength of Crystal Palace deserves attention. They have many ace players in the frontcourt, and their games are unbelievable. We have to pay attention to a lot. The attack of Crystal Palace is incredible. They scored two goals through positioning. We must be careful. The players know this! "

Guardiola also talked about how Manchester City adapted to Harland’s tactics: "Find this balance in the right way, because when Harland starts running with strength, he tends to give him the ball because he is going to score!"! But there were several accidents in the game against Newcastle. I won’t rely on Harland alone. Our tactics are very rich! "

So for this news, fans, do you have anything to say? If you like this article, welcome to pay attention to Beta and chat with the stars and the ball game.

In the post-epidemic era of profound changes in business models and increasingly fierce competition, digital transformation is not only a strategic foresight, but also a necessary option for enterprise development. How to drive the excellent operation of enterprises with digitalization and realize the innovation of business model has become a bottleneck that human resource management urgently needs to break through.

With the accelerating iteration of digital technology and the emergence of new formats of digital economy, the digital transformation of enterprises is not a simple matter. Digitalization should start from the whole enterprise level and jump out of the whole functional department, so that human resource managers are no longer just a supporting role, but a leader or promoter who can promote the digital transformation and business development of enterprises. Through redefining the organizational ecology, reconstructing the relationship between organizations and individuals, building an ecological circle that runs through employees, enterprises, customers and suppliers, and empowering the overall business development of enterprises. CDP Group’s human resource management system has mature landing scenarios in recruitment, attendance and personnel affairs, such as resume analysis, intelligent question-and-answer robot, intelligent scheduling, intelligent terminal, etc., unified management of positions, opening up various recruitment channels, one-stop posting of positions, receiving resumes, flexible attendance rules, multiple punching modes, holiday quota and approval, attendance report and salary integration, and online submission of personal information, family members, educational background and work experience. An integrated system makes it easier for business processes to form a closed loop. Free HR from daily delivery affairs, and devote more energy to the design of HR service products and the iteration and optimization of middle and back-office processes.

The digital transformation of enterprises is a comprehensive strategic transformation, which aims to realize the automation, cooperation and intelligence of all links inside and outside the organization through digital technology and improve the productivity, efficiency and competitiveness of enterprises. However, digital transformation is not a simple task, it needs the wise decision of leaders, organizational cultural changes, talent cultivation and technical support. CDP Group has continuously accelerated the digitalization of customers and the automation of human resource processes through its own platform mechanism, promoted organizational change, effectively improved the efficiency and benefit of enterprises, and even helped enterprises realize their ultimate value. For example, in Senma, the change of business makes the remote management of sales terminal clerk face great challenges in terms of cost control and efficiency compliance. Under the original management mode, how to support the new business form and at the same time support the strategic goal of the enterprise facing the future has become an urgent problem for Senma. CDP Group helped Senma to realize digital transformation through human resource management system, and got rid of the previous dilemma of lagging information flow across regions and multi-stores and manual offline operation, which greatly reduced the cost of the second investment in enterprise informatization and improved management efficiency. It has achieved the transformation goal of accurate data, clear process, smooth information, legal compliance, intelligence and convenience. CDP Group has helped Senma achieve efficiency improvement, rapid development of talents and data-driven decision-making through digitalization of human resources.

At present, China is accelerating innovation and making continuous breakthroughs in the new generation of information technology fields such as 5G, artificial intelligence, blockchain, cloud computing, big data and edge computing, and reshaping the new production mode, service mode and organizational form of the industry. Enterprises should actively embrace digitalization in order to better promote the development of enterprises from informationization to digitalization and intelligence, and promote the digitalization and agility of organizations.

At present, the AI technology represented by ChatGPT is exploding on the Internet. As a natural language processing tool driven by artificial intelligence technology, it can not only conduct dialogues by learning and understanding human language, but also chat and interact according to the context, and also write copywriting, code, answer questions and automatically search for answers.

Based on artificial intelligence technology, service robots match users’ needs, deeply integrate in some specific scenarios, and solve customers’ problems conveniently and quickly. They are widely used in government affairs, taxation, public security, banks, hospitals and other fields. When OpenAI announced the opening of the APIs of ChatGPT and Whisper models, what kind of sparks will the service robots meet with ChatGPT’s "technology giant"?

# Headline Creation Challenge ## One knowledge point every day ## 10 trillion parameters, can you pile up a general artificial intelligence? #

Although the current large-scale language models, such as GPT-3 and GPT-4, have more than 10 trillion parameters, these models still cannot be regarded as the realization of General Artificial Intelligence (AGI).

General artificial intelligence refers to an artificial intelligence system that can carry out various intelligent activities like human beings. It has the ability of self-learning and adaptation, and can cope with various situations and tasks. Although the current large-scale language models can perform well in some tasks, they are still only in the category of "Narrow AI".

In addition, general artificial intelligence needs to have more abilities, such as perception, exploration, understanding and emotion, which are still not realized by simple parameter stacking. Therefore, to achieve real universal artificial intelligence, we need to innovate and make progress in algorithms, hardware and software.

However, to achieve real universal artificial intelligence, we need to innovate and make progress in the following aspects:

1. Algorithm: Although the current large-scale language models can perform well in some tasks, they are still only in the category of "narrow artificial intelligence". Therefore, we need to research and develop more general artificial intelligence algorithms, such as reinforcement learning, meta-learning and transfer learning.
2. Hardware: In order to realize general artificial intelligence, a lot of computing resources are needed to support the operation of artificial intelligence system. Therefore, it is necessary to research and develop more efficient and intelligent computing hardware, such as quantum computers and neuron chips.
3. Software: To realize general artificial intelligence, we need to develop a more perfect software system, including autonomous learning and adaptability, emotion and consciousness. This requires us to deeply study the essence and mechanism of human intelligence and apply it to artificial intelligence systems.
4. Human-computer interaction: To realize general artificial intelligence, we need to research and develop more natural and efficient human-computer interaction methods, including voice, images, gestures and other forms. This requires us to conduct in-depth research on human interaction patterns and habits and apply them to artificial intelligence systems.

To sum up, the realization of real universal artificial intelligence needs innovation and progress in algorithms, hardware, software and human-computer interaction. Although the current large-scale language model parameters have reached 10 trillion, they still cannot be regarded as the realization of general artificial intelligence. We need to make continuous efforts and exploration to realize the real general artificial intelligence.

ChatGPT

With the acceleration of urbanization and the popularity of automobiles, traffic congestion has become a problem in many cities. Because of the difference of traffic signal control mechanism, navigation software sometimes leads drivers to crowded sections, which slows down the travel speed and affects the road traffic flow. In recent years, more and more navigation software began to try to predict the change of traffic lights through intelligent technology, so that drivers can travel more efficiently. So, how does the navigation know that the red light is about to turn green? This involves black technology such as machine learning and Internet of Things technology, which will be introduced in detail below.

First, the traffic light control mechanism

Before introducing the change mechanism of navigation forecasting traffic lights, let’s first understand the principle of traffic light control. Signal light control mainly adopts timing control and induction control.

Timing control: the signal light changes according to the preset time, for example, the parking red light is on for 3 minutes and the green light is on for 1 minute. This method is mainly suitable for areas with small human flow, such as night or remote areas.

Induction control: the signal lamp responds to the traffic flow on the road through the induction equipment, and dynamically adjusts the time of light color change. For example, when it is detected that the traffic volume increases and there is accumulation at the same time, the signal lamp will adjust the color change time according to the situation to give priority to ensuring the smooth flow of traffic.

Second, how does navigation predict the change of signal lights?

Based on the different control mechanisms of traffic lights, navigation software can use different technologies to predict the changes of traffic lights.

1. Timing prediction

For the signal lamp with timing control, navigation can calculate the period and time of signal lamp change by recording historical data, and compare it with the current time, thus predicting the time of signal lamp change. This method is simple and reliable, and is suitable for areas with small human flow. However, because this method can’t consider external factors such as traffic flow changes on roads, the accuracy is low for urban areas with traffic congestion.

2. Sensor prediction

For traffic lights controlled by inductive devices, navigation software can obtain real-time traffic flow data through the Internet of Things technology, so as to predict the changes of traffic lights. This method needs to cooperate with the sensor equipment on the road, and establish a data model by collecting data such as traffic flow and speed, so as to accurately predict the changing time of traffic lights. For example, Google tried this method in its own map, and established a global traffic information database by collecting users’ location data and traffic condition data, thus providing real-time congestion information on a global scale.

3. Artificial intelligence prediction

In addition to sensor prediction, machine learning can also be applied to signal light change prediction. Navigation software can build a model to predict the change of traffic lights by collecting users’ position, speed and various data used for road features, such as historical traffic volume, rush hour travel time, weather, etc., and then using machine learning algorithms to analyze these data. Using artificial intelligence technology to predict traffic lights can predict the changing time of traffic lights more accurately, and at the same time, take road traffic conditions into consideration to enhance the stability and accuracy of prediction.

III. Summary of the article

With the continuous development of Internet of Things technology and artificial intelligence, the ability of navigation software to predict the change of traffic lights will become stronger and stronger. To sum up, navigation can predict the change of traffic lights by recording historical data, sensor prediction and artificial intelligence prediction. However, at present, the accuracy of navigation software to predict the change of traffic lights still needs to be improved, and more accurate data collection and more efficient algorithms are needed to strengthen the prediction model. The technology of predicting the change of traffic lights can better realize the intelligence of urban traffic and provide drivers with a more convenient and efficient travel experience.