标签： 新上海sh419

Tottenham’s 3-goal striker joined Real Madrid, and Ancelotti personally named him, rejecting Mbappé for the reunion of mentoring.

This season’s Real Madrid failed to achieve the desired results, and Benzema failed to continue the excellent performance of last season. Although Real Madrid will still renew the contract with Benzema, it may even let Benzema end his career at Real Madrid. However, Real Madrid still have to prepare for Benzema’s decline. They can’t put all the pressure on a 35-year-old veteran, even if the veteran’s name is Benzema. Therefore, Real Madrid has also started the plan to find a successor, but the plan is not going so smoothly.

At present, there are many excellent center players in the world football, from Lu Kaku and lautaro of Inter Milan to Osman of Naples, Harland of Manchester City and Kane of Tottenham Hotspur, all of them are hot players in the transfer market. However, judging from the current news, except Harland, all these players are disdained by Real Madrid, including Kane. Of course, Kane is too old, and his 30-year-old age will make him unable to guarantee his state in the next few seasons. Real Madrid is not willing to take such risks, while Osmain is because of his injury.

Harland and Mbappé were the best targets for Real Madrid, but the relationship between Mbappé and Real Madrid broke down because of the transfer failure last season, and it was difficult for Harland to succeed when he was at home in Manchester City. Therefore, although Real Madrid has enough transfer fee budget and its players are attractive enough, it is still very difficult to get a top center to join in the summer transfer period. And it should be noted that it is difficult for both Benzema and the top center they want to accept the arrangement of substitutes.

Since it is impossible to get a top center, Real Madrid will change its signing strategy and focus on other strikers. Rishalison from Tottenham has become one of their choice targets. The Brazilian striker, who just joined Tottenham this season, is not happy in Tottenham. He scored only three goals for the team in 33 games, which completely failed to play his own value, which also made his worth decline. If Real Madrid wants to find Benzema’s successor, Rishalisson is definitely not the right candidate. If it is just to find a substitute player, it may be considered.

The reason why Rishalison’s name will appear in Real Madrid’s selection list is because of Ancelotti’s relationship. They once cooperated at Everton, and Rishalison played very well, so it is possible to reunite this time. However, it is still very difficult to join a top team like Real Madrid with its past signing strategy and Rishalisson’s performance on the court. If Real Madrid really want to make signings, they can find a more suitable target.

4-0 counterattack, China bombarded 103-0 and 77-0 after 00, and Sijiahui started 4-1 strongly.

In the early morning of April 23rd, Beijing time, the 2023 Snooker World Championships continued. In the second round of a focus match, China’s 20-year-old Si Jiahui took a 4-0 lead over the opponent in the first stage with veteran Robert Milkins, and after a 4-0 counterattack. In the first round, Si Jiahui beat the world champion "Magic" Sean Murphy 10-9 to advance strongly.

The World Snooker Championship is the most important annual snooker event. The 20-year-old Si Jiahui won through two qualifying rounds. Get the chance to participate in the World Championships in Crucible. And his opponent in the first round of the World Championships is very strong. He is Murphy, the first World Championship champion after 1980s, and he just won the player championship and runner-up in the Tour Championship not long ago.

In the face of powerful Murphy, Si Jiahui played a very domineering performance. His opponent in the first round is Murphy, who is in a hot state this season and won the "Magic" not long ago.

In this campaign, in the first four games, Si Jiahui fell behind 0-2 and 1-3. In the fifth game, the counterattack mode was started, and 77-2 pulled back a game. In the sixth game, the two men started a tug-of-war. In the stalemate game, Si Jiahui got a hand several times and pulled another game at 109-60. The score was tied at 3-3, and both sides returned to the same starting line.

In the seventh game, Si Jiahui scored 50 points in a single shot, won another game 86-34 and overtook the score 4-3. In the eighth game, although Murphy played very tenaciously, Si Jiahui’s state was still excellent. He scored 53 points in a single shot, 81-40 and then went to the next city, and the score came to 5-3.

In the ninth game, after losing four games in a row, Murphy finally stopped the decline. He pulled back a game through piecemeal, 65-19, and the score was 4-5. At the end of the first half, Si Jiahui was one game ahead. In the second half, Si Jiahui continued to make a strong effort. After the fifteenth game, he won three match points 9-6.

In desperation, Murphy launched a strong counterattack to save three match points and chase the score to 9-9. In the deciding game, Si Jiahui didn’t drop the chain, 56 points in a single shot sealed the victory, and the total score was 10-9. In the second round, facing veteran Milkins, when Si Jiahui started 0-1 behind, he made a 4-0 counterattack and 4-1 overtook the score.

Infrastructure for training AI to solve common problems

In order to train artificial intelligence models that can solve common problems, infrastructure is needed to provide support. These infrastructures are usually composed of hardware, software and tools to improve the efficiency and accuracy of model training. This article will introduce the infrastructure for training AI to solve common problems.

I. Hardware infrastructure

When training artificial intelligence models, it is usually necessary to use high-performance computing hardware to provide support. The following are several common hardware infrastructures:

  1. CPU: The central processing unit (CPU) is a general-purpose computing hardware, which can be used to run various types of software, including artificial intelligence models. Although the performance of CPU is relatively low, it is still useful in training small models or debugging.

  2. GPU: A graphics processor is a special computing hardware, which is usually used to process images and videos. Because of its highly parallel structure, GPU can provide higher computing performance than CPU when training artificial intelligence models, so it is widely used.

  3. TPU: Tensor processor is a kind of hardware specially used for artificial intelligence computing, developed by Google. The performance of TPU is higher than that of GPU, and it is suitable for large-scale artificial intelligence model training and reasoning.

Second, the software infrastructure

In addition to hardware infrastructure, some software tools are needed to support the training of artificial intelligence model. The following are some common software infrastructures:

  1. Operating system: Artificial intelligence models usually need to run on an operating system, such as Linux, Windows or macOS.

  2. Development environment: Development environment usually includes programming language, editor and integrated development environment (IDE) for writing and testing artificial intelligence models. Common development environments include Python, TensorFlow, PyTorch and Jupyter Notebook.

  3. Frames and libraries: Frames and libraries provide some common artificial intelligence model algorithms and data processing tools, making model development and training more convenient. Common frameworks and libraries include TensorFlow, PyTorch, Keras and Scikit-Learn.

Third, the tool infrastructure

In addition to the hardware and software infrastructure, some tools are needed to support the training of artificial intelligence models. The following are several common tool infrastructures:

Dataset tool: Dataset tool is used to process and prepare training datasets, such as data cleaning, preprocessing, format conversion, etc. Common data set tools include Pandas, NumPy and SciPy.

2 Visualization tools: Visualization tools are used to visualize the training process and results to help users better understand the performance and behavior of the model. Common visualization tools include Matplotlib, Seaborn and Plotly.

Automatic parameter tuning tool: The automatic parameter tuning tool is used to optimize the parameters of the model to improve the performance and accuracy of the model. Common automatic parameter tuning tools include Optuna, Hyperopt and GridSearchCV.

In short, training artificial intelligence models to solve common problems requires the use of a variety of infrastructures, including hardware, software and tools. These infrastructures are designed to improve the efficiency and accuracy of model training, so that the model can better solve various practical problems. In practical application, users need to choose the appropriate infrastructure according to specific requirements and data characteristics, and design and implement it accordingly.