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C Ronaldo complained to the coaching staff after losing the game.

C Ronaldo missed the opportunity

Cristiano ronaldo had a frustrating night after Riyadh was defeated by champion Vladimir Etihad 1-0. At the last moment of the game, Ronaldo missed the best opportunity of a perfect draw. Although Cristiano Ronaldo did not bring the winning tradition of Real Madrid to the Saudi League, he succeeded in bringing the bad temper of Real Madrid, Juventus and even Manchester United to Saudi Arabia, and once again became a castle for foreign fans to vomit wildly. .

C Ronaldo scored the second last point after the game, with only 4.4 points.

This is Ronaldo’s first defeat after joining the Saudi club. After the game, his score was only 4.4 points. Confucius, the penultimate player in the whole game, roared at his teammates.

Teammates comfort Ronaldo

Ronaldo, who is always too obsessed with goals, is furious. On the way to the end, he constantly complained to his teammates, kicked the water bottle on the sideline angrily, and even wanted to tear off the captain’s armband and throw it on the sideline. It is estimated that C Ronaldo restrained himself from throwing the captain’s armband when he noticed that the live camera was aimed at himself. Entering the player channel, the angry Cristiano Ronaldo even complained to the coaching staff.

The 38-year-old didn’t score in the last two games. When he rushed out of the stadium and down the player’s lane, he was obviously depressed when the final whistle sounded.

Ronaldo, who was unhappy after losing.

In a video that is now going viral on social media, the former Manchester United striker can be seen shaking his head in disappointment.

Although he was comforted by his teammates, Cristiano Ronaldo was obviously not satisfied with the result and continued to open his arms in frustration.

C Ronaldo kept shouting and complaining to his teammates.

When the captain of Riyadh Victory Team and his teammates slowly walked to the sideline, Cristiano Ronaldo quickened his pace and then lashed out at a pile of water bottles placed on the sideline.

After scoring eight goals in four appearances in February, all eyes were focused on Ronaldo, because there was a conflict between the two strong Saudi teams. But his efforts to integrate into the game failed to inspire his team to win.

Before the half-time, Cristiano Ronaldo had a chance to shoot and was saved by Etihad goalkeeper Marcelo Groche, but the Portuguese star was still offside.

Foreign fans put C Ronaldo and baby orangutans together.

Foreign fans mercilessly laughed at C Ronaldo, and foreign fans began to vomit Confucius’ anger crazily. This scene has been repeated countless times in Cristiano Ronaldo’s early career, and now it is repeated in Saudi Arabia, causing heated discussion. Just like C Ronaldo’s celebration, it seems to be his symbolic way to vent his anger. Many fans believe that Ronaldo’s indomitable spirit has made him what he is today. This is his true nature. But is it right to complain about your teammates when you lose? This is worth pondering. It is said that Riyadh spends 200 million euros a year to attract Ronaldo to join the Saudi alliance. The purpose is not to make Cristiano Ronaldo complain, but to hope that he can lead the team by going up one flight of stairs. What do you think?

Author | Rizel Scarlett

Translator | Bian An Editor | Wang Ziyu

Produced by | csdn (ID: csdnnews)

What programming language can continue to be popular 30 years after its birth?

If you can think of Python, congratulations, that’s right. In the October 2022 report, we found that Python is still the second most commonly used programming language on GitHub. Interestingly, the usage of Python increased by more than 22% year-on-year. In 2022, more than 4 million developers on GitHub were using it.

In this paper, we will introduce the history, characteristics and usage of Python in depth, and try to answer why the programming language conceived in the 1980s can continue to dominate the development. In addition, we will provide some useful tips and techniques for experienced Python developers.

What is Python?

Python is a high-level interpretable programming language, and its syntax is very simple, which makes it easy to read and very friendly to users and beginners. Python was originally built to satisfy the author Guido Van Rossum’s desire to design a simple and beautiful programming language. It was first released to the world in 1991.

Interestingly, this programming language, which originally wanted to express "beauty", chose the word Python as its name, which was related to a TV comedy "Monty Python’s Flying Circus in monty python" which was first broadcast in the 1970s in Britain.

Python language has been widely used in developers, data scientists, researchers and other fields since its birth. You may ask, where do you see that Python is simple and beautiful? Let’s make a comparison:

Usually, as an introductory example, every little white who studies programming will write this case:

Python

And if you use Java, you will have to write many more lines:

Java

Because Python is a universal language, it can be used in various applications, and its simplicity makes it an excellent language for automating tasks, building websites or software and analyzing data. Python has several other features that make it very popular among developers and engineers. These include:

Easy to read:

Python code uses English keywords instead of punctuation, and its line breaks help define code blocks. This means that you can easily understand the design purpose of the code by looking at the code;

Open source code:

You can download the source code, modify it, and use it at will;

Cross platform:

Some languages require you to modify the code to adapt to different platforms, but Python, as a cross-platform language, can run the same code on any operating system as long as it has a Python interpreter installed.

It is extensible:

Python code can be written in other languages (such as C++), and users can add low-level modules in Python interpreters to customize and optimize their tools.

Has a powerful standard library:

This library can be accessed by anyone, which means that users don’t have to write code for each function, but access the built-in modules to help solve problems in daily programming.

What is Python usually used for?

Python can be used for almost anything, from network and software development to machine learning and artificial intelligence (AI). Let’s look at one of the most common use cases.

If you run it, you will see some jokes, which Python engineers usually use to laugh when they are bored.

Anyway, let’s introduce the current situation of Python from some fields:

1.Web and software development field

Python is a popular language for Web and software development, because you can create complex multi-protocol applications on the basis of ensuring concise and readable code. In fact, some of the most popular applications are built in Python. In addition, Python’s open source community provides developers with a lot of reusable code, frameworks and support. Django, for example, is one of the most commonly used Python frameworks designed by a group of experienced developers, aiming to help others develop applications efficiently and solve some common problems that may hinder them from advancing the project.

2. Task automation

An important advantage of using Python is that it can automatically perform some streamlined or repetitive tasks. With Python, you can learn how to automate anything by using built-in modules or pre-written code from its robust library. Or you can write your own custom scripts to perform specific operations. For example, you can easily send an email automatically using the "smtplib" module or copy a file using the "shutil" module. Python also has a set of robust test frameworks, which makes it an excellent language for test automation. Frameworks like Pytest, Behave and Robot allow developers to write simple and effective tests to ensure the quality of their construction.

3. Machine learning and big data

Here is an interesting fact: Python is the preferred language for data science and research. Because its syntax is easy to understand and adaptable, people with little development experience can easily learn Python and use it to manipulate data for research, reporting, prediction or regression analysis. Collecting and analyzing data is a time-consuming task for data scientists. Python, as one of the main languages for training machine learning (ML) models, can analyze and identify the features in these model data through specific algorithms, so as to make predictions or decisions based on these data. It can also be continuously optimized and adjusted based on previous data sets to cope with new variables. Data scientists and developers who train ML models often use some libraries, such as NumPy, Pandas and Matplotlib, to complete automatic data cleaning, transformation and visualization.

4. Financial or financial analysis

Similar to how Python helps data scientists deal with large data sets, Python is widely used in the financial industry to quickly perform complex calculations. The stock market will produce a lot of data, Python can be used to import data about stock prices, and identify trading opportunities through algorithm generation strategies. The language can also be used for portfolio optimization, risk management, financial modeling and visualization, cryptocurrency analysis and even fraud detection.

5. Artificial intelligence

Python can also be used in some of the most complex artificial intelligence (AI) technologies, and it is actually one of the preferred languages for AI. Python’s concise and readable code allows developers to create consistent and reliable systems. Its huge library provides many frameworks like PyBrain, which provides developers with powerful algorithms for machine learning tasks. In addition, the visualization function of Python can help transform these large data sets of AI or ML into understandable graphs or reports. Interestingly, OpenAI, an artificial intelligence research laboratory, uses Python framework Pytorch as their standard framework for deep learning and is used to train its artificial intelligence system.

Why is Python so popular?

Apart from relatively simple learning, there are other reasons why Python continues to be popular. Including:

High production efficiency:

Compared with other more complex programming languages such as C++, Python’s syntax allows users to do more things in less time and reduces the time and effort to write the same line of code.

It has a broad and supportive user community:

Even the best developers will encounter problems, and the user community has become a valuable resource gathering place. Python has a huge community that provides documentation, tutorials, tips and tricks to master the language. For example, the Python community on GitHub provides everything from the latest version of the language to Bug reports and update instructions.

Education recognized:

Python has become the preferred programming language in education, and some students even met Python in primary school. Believe it or not, there are some children’s picture books specially written for Python. Although students majoring in computer science are often taught Python, its use has already gone beyond a single discipline and extended to other fields of STEM and academic research. For example, Python can be used to solve differential equations, perform statistical analysis, simulate and track particle diffusion, and so on.

It has a high enterprise demand:

Because of its wide applicability in development and data analysis, learning and understanding Python is generally considered as a necessary skill for job seekers. According to the situation of well-known recruitment agencies, Python language is the third programming language for global recruiters in 2022.

Python is everywhere, and it has been widely used to build a large number of technologies, websites and even systems that most people encounter every day. The technology it provides, from your favorite video streaming service to machine learning algorithms, even helps you to conduct cryptocurrency transactions. To give a broader example, NASA is also using Python to analyze the data of the complex James Webb space telescope, which makes it one of the few programming languages used in projects outside the world.

Recently, SaaS giant Salesforce announced the launch of a $250 million fund, which is by far the largest AIGC venture capital fund.

In this regard, CEO Clara Shih said that the fund will focus on "cultivating the next generation of artificial intelligence startups".

Some analysts also said that although the generative AI like ChatGPT itself amazed the public. However, their greatest role in the enterprise lies in their combination with the company’s business, which is obviously the goal of Salesforce.

However, judging from today’s stock price performance, the heavy AI did not make this old SaaS manufacturer dead.

250 million US dollars, which has exceeded the net profit of last year.

Different from VC’s pursuit of high returns, as a typical CVC, Salesforce chose to set up the fund at this time more likely because of industry competition and stock price considerations.

We saw that the foundation of the fund was announced at its annual conference TrailblazerDX. At that time, the company announced three major initiatives in generating artificial intelligence:

First, Salesforce is integrating generative artificial intelligence into customer relationship management products under Einstein GPT. These new features are designed to combine the data in Salesforce with a series of generative AI engines (including engines from OpenAI and Cohere), so that customers can seize the initiative in making marketing emails, writing supporting articles and even making computer code.

Second, Salesforce announced its cooperation with OpenAI, which makes ChatGPT available directly from Slack. This function is currently in the testing stage and will be launched on a large scale later this year.

Third, Salesforce Ventures is launching a $250 million investment fund to support generative AI startups.

There are several backgrounds that have to be mentioned behind these three measures.

First of all, on the eve of releasing its new AI product, Salesforce released a survey result, which showed that although some IT leaders expressed concern about AI, most people thought it could help them better support customers and improve data insight. Even 67% of the respondents said that they would give priority to this technology in the next 18 months, and one-third of the respondents thought it would be their top priority.

At the same time, Salesforce believes that it has identified several areas where artificial intelligence is reshaping the sales pattern: artificial intelligence insight of sales, natural language chat robots for service requests, targeted marketing content and personalized e-commerce experience.

Secondly, at the end of last year, after OpenAI’s ChatGPT broadened the imagination of the technology industry, many large companies rushed to announce the function of using artificial intelligence to generate content. Last month alone, Microsoft integrated OpenAI technology into Bing, Google announced the launch of ChatGPT competitor Bard, Meta released one of its large language models under the open source license, and Snapchat launched a social generation tool.

In addition, Microsoft recently launched Dynamic 365 Copilot, a functional assistant tool for customer relationship management (CRM) and enterprise resource planning (ERP) based on artificial intelligence, which directly extended its hand to the territory of traditional enterprise software platforms such as Zoho, Salesforce and IBM.

A consensus in the field of science and technology is that it is often fatal to miss the first advantage of technology, so we have seen Salesforce’s heavy investment in AI.

More importantly, the deployment of AI and the launch of Slack’s new ChatGPT application are at a critical moment when the board members of Salesforce are replaced, and investors have been pushing for new changes. Even at the beginning of this year, the company cut 10% of its employees.

As we all know, affected by the macro-environment, the market value of American SaaS companies suffered a decline in different degrees in 2022, and Salesforce was not spared. Salesforce is also under pressure from investors. Using the white-hot trend of generating artificial intelligence can help companies resist concerns about their growth prospects.

It is worth mentioning that at the beginning of this month, Salesforce released the latest financial report data. According to the financial report, the revenue of Salesforce in fiscal year 2023 was $31.4 billion, an increase of 18% year-on-year. However, the income growth rate has slowed down this fiscal year. Its revenue in the fourth quarter of fiscal year 2023 was $8.4 billion, a year-on-year increase of 14%, which was lower than the annual growth rate.

In terms of profit, salesforce’s operating profit in fiscal year 2023 was $1 billion, compared with $500 million in the previous fiscal year, which was significantly improved this fiscal year. This fiscal year, the company’s net profit was $200 million, compared with $1.4 billion in the same period of the previous fiscal year, and the net profit in the latest fiscal year decreased by 86%.

It can be seen that the scale of the AIGC fund has exceeded the net profit of Salesforce last year, which can be seen from the investment.

According to public data, Wall Street analysts agreed that earnings per share (EPS) in the fourth quarter was $1.36. However, the company reported earnings per share of $1.68, far exceeding expectations. In addition, the average income of analysts is estimated to be about $8 billion, while the company’s revenue in the fourth quarter was $8.4 billion.

But despite the amazing revenue growth of Salesforce in recent years, it is expected to achieve the goal of reaching $50 billion in sales in fiscal year 2026. But its share price trend has been developing in the opposite direction. Since December 2020, the company’s share price has plummeted by nearly 30%.

It is not difficult to see that Salesforce is eager for the growth prospects of its performance.

The first four companies to be selected.

Back to Salesforce, the new fund itself. Although the fund is the largest fund of Salesforce Ventures, it is not the first dedicated AI fund. As early as 2017, it raised $50 million for the artificial intelligence innovation fund to support its Einstein artificial intelligence toolset.

According to PitchBook, Salesforce Ventures has participated in 140 venture capital transactions of artificial intelligence and machine learning startups, accounting for about 19% of its total investment so far.

John Somorjai, executive vice president of Salesforce enterprise development and Salesforce Ventures, said: "for more than ten years, Salesforce Ventures has been investing in high-potential enterprise technology business, and these initial investments of the fund to generate artificial intelligence companies are fully in line with this strategy."

In fact, in the past decade, Salesforce Ventures has raised more than a dozen funds, ranging in size from $50 million to $125 million, and has also launched a series of vertically specific investment funds, including funds targeting specific regions such as Japan or Canada.

But before, Salesforce Ventures usually invested in enterprise cloud startups. After all, such investments may become more important for this software company because of the restrictions on large-scale acquisitions. For example, it has invested in star companies such as Zoom and DocuSign, and invested heavily in Snowflake IPO.

It is precisely because of its huge transaction scale and strategic value that Salesforce Ventures has always been regarded as the king of SaaS unicorns. At the same time, some people think that it may continue this myth in the AI field.

It is reported that the fund has invested in four start-up companies: You.com, a upstart search engine, just launched the generation of artificial intelligence a few months ago; Anthropic, an AI startup founded by former employees of OpenAI and highly sought after by VC, developed ChatGPT；; Cohere, a natural language processing (NLP) startup that recently cooperated with Google; And a secret startup called Hearth.AI

Specifically, Richard Socher, the founder of You.com, is the former chief scientist of Salesforce. The company was founded in 2020, and launched the AI chat function YouChat in search engines before Google and Microsoft at the end of last year. In terms of financing, at the end of 2021, You.com completed a $20 million seed round of financing led by Marc Benioff, CEO of Salesforce, and then completed a $25 million series of financing in the middle of last year.

Anthropic was founded in January, 2021. The latest report shows that shortly after accepting hundreds of millions of dollars from Google, it recently completed a new round of financing of 300 million dollars. After this financing, the value of Anthropic reached 4.1 billion dollars. Earlier, Anthropic raised $704 million through Series A and Series B financing in 2022.

Similarly, Cohere was founded in 2019, mainly providing access to large-scale language models and natural language processing (NLP) tools through APIs. Cohere has raised $170 million so far, including $125 million in Series B financing last year and $40 million in Series A financing in 2021. Earlier this year, it was reported in Reuters that Cohere was in talks to raise hundreds of millions of dollars in a round of financing, and the valuation of this startup may exceed 6 billion dollars after the completion of financing.

As for Hearth.AI, it should have been established in May, 2022. Except that it is the next generation management system (CRM) shown on its official website, we have not found any more public information. (Text/Zhang Xue, source/investment network)

AI painting is getting closer and closer to everyone’s life, and the most direct manifestation is the "AI painting" filter in Tik Tok, which has recently caught fire on the Internet. It takes only a few seconds to upload your own photos, and the filter can automatically convert them into the corresponding secondary animation style.

Some renderings generated after the picture can be seen that although this AI painting filter can’t accurately restore the movements, costumes or facial features of characters, but the overall effect is quite good-the details of human body proportion, facial features and costume modeling are still very accurate, the colors are beautiful, and the depiction of light and shadow is also in place.

Different types of photos, found this. AI painting filter works best when dealing with a single photo. If there are multiple people overlapping or closely fitting in the uploaded picture, AI doesn’t seem to be able to identify them accurately. For the props held by cats, glasses or characters, this AI filter will directly choose "ignore"; There will even be problems such as gender mistakes and the collapse of painting style.

The problem did not cause dissatisfaction. On the contrary, many users shared their original pictures and the renderings of the cow’s head and the horse’s mouth, which attracted extensive onlookers from netizens. The contrast caused by the defects of AI program is unbearable, and everyone has said that this should not be called "artificial intelligence painting" but "artificial mentally retarded painting".

In addition to getting closer and closer to people’s work and lifeSome AI painting tools we are familiar with have also made great progress and improvement in performance.