Technology
Google brand story; From a small startup to ruling the web world
Proper noun: A search engine that popularized the company of the same name.
Preposition: For each; per.
Noun: A topology name.
Adverb: Beyond all others.
Preposition: For each; per.
Noun: A topology name.
Adverb: Beyond all others.
Preposition: For each; per.
Noun: A topology name.
Proper noun: A particular Internet company.
Proper noun: A search engine that popularized the company of the same name.
Proper noun: A particular Internet company.
Proper noun: A search engine that popularized the company of the same name.
Proper noun: A particular Internet company.
Proper noun: A search engine that popularized the company of the same name.
Proper noun: A particular Internet company.
Proper noun: A search engine that popularized the company of the same name.
Proper noun: A particular Internet company.
Proper noun: A search engine that popularized the company of the same name.
Google brand story; From a small startup to ruling the web world
The general public of the world cannot imagine removing Google services from their lives today. Regardless of the search engine or the Chrome browser, most of us set our programs on Google Calendar, and using Gmail, Google Drive, Google Docs, Google Maps, Google Photos, YouTube, and the like has become a daily habit for us.
Google’s role in shaping our relationship with the Internet world is undeniable. Many of this company’s products have known alternatives, But Google has designed its comprehensive and integrated ecosystem in such a way that we cannot easily abandon the use of all its applications and services.
This article was updated on the occasion of the anniversary of the establishment of Google on 14 September 1403.
But how dangerous will it be for technology companies to gain power at this level? Today’s opponents of Google are divided into several groups: some believe that Google is acting against the direction of freedom of expression by prioritizing certain search results. One group also argues that Google collects user data in a variety of ways that people are unaware of and that this data is not necessarily used in advertising.
For example, some activists of the de-Google movement say: “Spying on people at this level is not acceptable and should not be. “We need to control the technologies we interact with, not the other way around.”
But 26 years ago, before it came under the microscope of US antitrust cases and its empire was in danger of being disintegrated, the initial idea for founding the company was formed with a student project with the aim of facilitating people’s access to web information.
Back then, finding specific content on websites was more like exploring a disorganized library. Even the algorithms of the best search engines, such as Xcite and Altavista, often displayed scattered links in response to user queries that may or may not be related to the user’s search. In fact, finding what you were looking for was more like a game of chance. But Google changed everything.
Join us to review the story of the origin of the Google brand and its evolution.
Getting to know the founders of Google and the BackRub project
Larry Page and Sergey Brin met in the summer of 1995 at Stanford University’s doctoral student induction program, which included a tour around San Francisco. Both of them had just finished their master’s degree in computer science and were about to enter the doctoral degree with brilliant academic records.
Sergi Brin, who had a more social spirit, had volunteered to lead one of the student teams during the event. He had to show the university campus to the students and also lead the said recreational tour. Larry Page happened to be his bandmate and, contrary to expectations, their association during the camp was not pleasant for either of them.
According to Larry Page, Sergey Brin was too proud, while Sergey Brin considered Larry Page to be an unbearable person. They talked about urban infrastructure and social order for almost the entire camp and did not agree at any point.
Page later said in an interview: “We were arguing for a long time, Sergi had strong ideas and I think I was the same.” Sergiy Brin also confirmed his words and continued: “Both of us considered the other party hateful!” But the fact that we took time to discuss with each other showed that we also value thoughts.” They clearly complemented each other.
By the start of the first semester of their Ph.D., Page and Breen were no longer in contact and were working on their own projects and research. Page had learned from his father, a computer science professor at Michigan State, that a doctoral dissertation could determine the ultimate path of one’s academic career. When he approached his advisor, Terry Winograd, to decide on a thesis topic, he put more than 10 interesting ideas on his desk.
Larry Page had more than 10 different topics in mind for his thesis
However, Larry Page’s work did not start with researching the web search engine. Although Stanford graduates were getting rich founding Internet companies, Larry Page found the Web primarily interesting for its mathematical properties: each computer was a node, and each link on a Web page established a connection between nodes, something that a structure It showed classic graphics.
He says:
Computer scientists love graphs, and the World Wide Web could be the largest graph ever created.
Finally, with the consent of his mentor, Terry Winograd, Page began to examine the structure of web links. The point that disturbed his mind in the first stages of research was that although surfing the web from one page to another by following links was a simple and trivial task, few people paid attention to the reverse process, that is, the number of links behind each web page.
Larry Page in the BackRub project was looking for a way to count and determine the importance of each backlink on the web
Page thought that knowing which pages were linking to which pages would have many potential uses. This research led him to BackRub, a project focused on backlinks: perhaps if he could find a way to count and determine the importance of each backlink on the web, the web would become a more valuable place.
At that time, the web contained about 10 million documents with countless links between them. The computing resources of such a project were estimated far beyond student theses, and the dimensions and complexity of the project attracted the attention of Sergey Brin, who had worked on data mining articles and algorithm analysis during his PhD.
Sergey Brin joined the BackRub project and took over the mathematical side of the research, while Larry Page worked on link weighting and backlinks.
The weight of the links, in simple words, indicated that each link is from which source and with what degree of importance it targets another website. For example, the importance of the link that Intel’s website gave to IBM’s website was very different from the link that a teenager’s diary-blog gave to IBM’s website.
Sergey Brin handled the mathematical part of the research and Larry Page focused on link weighting
On the other hand, each link was placed in a different position and ranked according to the number of links on its home page. In other words, they counted not only the number of links on a page but also the links that were attached to each particular link. As the project progressed, its mathematical dimensions became more surprising and complex.
Sergey Brin says:
I loved data mining, which means analyzing huge amounts of data and finding patterns and trends. At the same time, Larry wanted to download the entire Internet, which contained the most interesting data possible for analysis.
Based on the results of their research, Page and Brin designed an algorithm called PageRank, which sent more popular sites to the top of the list and less important sites to the bottom of the list.
While investigating the work, they realized that the outputs of this model act somewhat similar to the search engine. In fact, BackRab was already a search engine that took a URL and provided a list of backlinks ranked by importance.
In addition, BackRub’s results outperformed those of other existing search engines such as AltaVista and Excite, which often listed irrelevant sites. By focusing on keywords, these search engines only looked at the text of the websites and ignored the most important factor, the ranking of the web pages.
Page and Brin developed the first search tool experimentally. This software only considered the headlines and page titles of the websites and then used the PageRank algorithm to rank and sort the websites. The results were significantly better than popular search engines.
Search engine development
At this point, Sergey Brin and Larry Page realized that they had taken a big step: the backrub engine not only performed well but also scaled as the Internet expanded. In other words, since the algorithm worked by analyzing links, the bigger the web, the more powerful the search engine.
For this reason, Page and Brin chose the name Googol (meaning the number one and 100 zeros in front of it) for their search engine, which was a symbol of processing the endless amount of information on the web. They published the first version of Google in August 1996 on the Stanford website with the domain google.stanford.edu, a year after they first met and got to know each other.
Page and Brin released the first version of Google for Stanford students with the domain google.stanford.edu
Its initial version was a success among a small group of Stanford users, and the two classmates quickly began improving the service to monitor the entire content of websites in addition to titles, while indexing more pages.
After Page’s room was filled, Brain’s room became their programming center and management office. Before long, the former BackRab was a legendary project in Stanford’s computer science department, consuming nearly half of the university’s network bandwidth. By the fall of 1996, it had gotten to the point where the search engine was regularly disconnecting Stanford’s Internet connection.
Larry Page later recalled:
We were lucky that there were so many forward-thinking people at Stanford who didn’t blame us too much for the resources we used.
The founding of Google: A Star rises
Page and Brin registered the google.com domain in September 1997. They knew that they could no longer rely on university resources to continue. In August 1998, one of the university advisors suggested that they meet Andy Bechtolsheim, the founder of Sun Microsystems. The meeting was held on the porch of this consultant’s house with a demonstration of the Google search engine.
Andy Bechtolsheim wrote a check for $100,000 to Google Inc. But the problem was that there was no company called Google yet. Page and Breen kept the check in their dorm room for several weeks while they went through the business registration process and opened new bank accounts for their business.
Andy Bechtolsheim, Google’s first investor
Google was officially registered on September 4, 1998, and according to the previous agreement, Larry Page became the CEO and Sergey Brin became the company’s president. The two defined the company’s mission in one phrase: “Organizing the world’s information and making it accessible and useful to all people.”
Google’s mission: “Organizing the world’s information and making it accessible and useful for everyone.”
Page and Breen moved their tools and equipment to the company’s first office, which was the garage of their friend Susan Wojitsky’s house in Menlo Park, and by the end of the year, they had hired six more software engineers to work with them. By the end of 1999, the number of Google employees reached 21 people, among whom the names of Salar Kamangar, Omid Kurdestani, Suzan Vejitsky, and Marisa Mir stand out.
While Google’s daily searches were growing exponentially, the development of the company’s infrastructure required more capital.
Google’s first office in the garage of Suzanne Wojitsky’s house
At the end of the first year of its establishment, it held its first fundraising round and received a total of one million dollars from three angel investors, Amazon CEO Jeff Bezos, Stanford University computer science professor David Cheriton, and Ram Shriram, one of the entrepreneurs of the technology world.
Andy Bechtolsheim, the founder of Sun Microsystems, was Google’s first investor
Many investors thought that the idea of a search engine startup would go nowhere, because the effort of technology companies was to keep users on their websites longer, and the search engine made people go from one website to another.
Google page in 1998
But the potential and early success of Google in the second round of fundraising attracted the attention of two famous venture capitalists: John Doerr of Kleiner Perkins and Michael Moritz of Sequoia Capital, after carefully examining Google, they decided to invest a total of $50 million in this fledgling startup. .
The interesting point is that before these investments, Larry Page and Sergey Brin had offered Excite to buy their startup for one million dollars, but Excite refused to pay more than 750,000 for Google, and thus the contract was canceled.
Google team in 1999 Palo Alto office
After raising capital, Google moved to its second office in Palo Alto, home to many famous Silicon Valley startups. In 2000, the Google team launched Google AdWords with the idea of Susan Wojitsky, which optimally changed the company’s revenue stream.
The AdWords service allowed companies to show their ads precisely to those who were looking for related products or services. This service was a revolutionary example in the world of online advertising and allowed Google to have a powerful money-making machine in addition to the search engine.
While the number of Google searches increased daily, with these changes, Google employees found a better mood and focused strongly on the path of progress.
At this time, John Doerr and Michael Koritz, the main investors of the company, according to their long-term experiences in the technology world, suggested to the founders of Google to hire a more experienced manager to lead their startup. Sergey Brin and Larry Page conducted complex interview sessions with several candidates but found none of them aligned with Google’s vision and long-term horizon.
In 2001, Eric Schmidt went to the interview meeting of the founders of Google with his hands full: he had detailed plans for developing Google internationally, diversifying products, sales, and accounting strategies, and managed to get on the Google board. A few months later, Page and Brin tapped him to become Google’s CEO, seeing Schmidt as the best fit for the company’s IPO event.
CEO Eric Schmidt’s tenure: Google’s explosive growth
Eric Schmidt was appointed CEO of Google in August 2001 and remained in this position for 10 years. The joint idea of Sergey Brin, Larry Page, and Eric Schmidt was to create a comprehensive ecosystem that would meet all the digital needs of users through Google.
In the product development department, Schmidt had Merissa Meyer by his side, who had previously managed web products with user interface changes and the introduction of Google Doodles. One of the first developments of Google in the search engine side was the addition of the image search section.
In 2002, Yahoo planned to buy Google for $3 billion
In 2002, Yahoo tried to buy Google for $3 billion, but Page and Brin rejected the offer; Because they believed that their startup has more value.
Google executives wanted this company to be a symbol of the endless power of innovation; For this reason, they adopted a policy that allowed Google employees to dedicate 20% of their working time to projects that interest them, even if it is outside the scope of their official duties. This policy led to the emergence of some of Google’s most popular products in the following years.
In 2003, the Google News division was launched, and the board of directors purchased a building complex in Mountain View, California, to provide a suitable space for the company’s operations until they employed a thousand employees.
Google Camp in Mountain View
This office, known today as “Google Plex”, expanded over time by purchasing the surrounding buildings and became the largest company camp in the world.
From Gmail to Chrome: The products that changed the web market forever
In 2004, the Gmail service created a storm in the world and raised the company’s position among users to a new level.
With 1 gigabyte of storage space, Gmail allowed users to quickly search for any email they had sent or received. In addition, this service provided users with new ways to automatically organize emails by topic. Many people thought that Gmail was Google’s April fool, but luckily it was not.
Gmail’s features far exceeded other free email services
In this era, Google’s revenue-generating strategies worked well, so that a few days before the initial offering of Google shares, stock market experts considered the company’s future to be very profitable.
Gmail in 2004
Finally, on August 19, 2004, Google’s IPO event took place at a price of $85 per share, bringing a fortune of about $1.7 billion to the company’s founders and early investors. In addition, the value of the company was estimated at 27 billion dollars.
Google IPO on Nasdaq with Eric Schmidt and Larry Page
The introduction of the Google Maps service in 2005 marked another success in Google’s career and became a background for the company’s research collaboration with NASA. Google Maps evolved over time and became one of the most valuable features of Google to facilitate people’s daily lives.
Google started working with NASA after the introduction of Google Maps
But no one expected the company’s next revolutionary product to impact the entire tech world.
In September 2008, Google introduced the Chrome browser to the world. Interestingly, Eric Schmidt was against Google’s entry into the web browser market from the beginning, and this product was developed at the insistence of Sundar Pichai, one of the company’s forward-looking executives who was supposed to play a key role in the company’s future.
To create Chrome, Google hired some of the original Firefox engineers and developed the browser first for Windows and then for other operating systems. The first version of Chrome came with a 40-page visual guide to show users how to work with the browser. In just 4 years, the popularity of Google’s browser surpassed Firefox and Internet Explorer.
Schmidt later said in an interview:
I told Larry Page and Sergey Brin that we shouldn’t think about browser or operating system development, we shouldn’t compete with Microsoft. They told me they were hiring people to improve Firefox, and six months later they showed me Chrome. To be honest, I was so excited to see the Chrome demo that I had no choice but to admit I was wrong.
At the same time, Google’s organizational culture was still at the center of attention. This company was known as one of the best working environments in the world by maintaining a creative work environment. In such an environment that was based on the freedom of creativity and innovation, Google could attract the best talents and encourage them to create new and efficient products.
Strategic purchases: Doubleclick, YouTube and Android
At a time when Google was improving the level of user experience by offering various products that often had better performance than competitors, it was also preparing the ground for building an inclusive ecosystem by buying leading startups.
For example, the company took the biggest step toward expanding its pervasive advertising empire across the Internet with its $3.1 billion purchase of DoubleClick, the company’s most expensive acquisition at the time. In 2006, Google also bought YouTube for 1.65 billion dollars to give its plans in the field of video content a more serious color.
Under the leadership of Salar Kamangar and then Susan Wojitsky, YouTube became one of Google’s most valuable assets and one of the best online video content platforms, used by millions of users every day.
One of the other decisive actions of Google is the purchase of the Android operating system for 50 million dollars in 2005, which was released in 2008 for the T-Mobile G1 phone known as the HTC Dream. Open source software and integration with the Google ecosystem and the highest levels of notification capabilities were the most important features of Android that made it the most popular mobile operating system in the world.
So far, there has been no news of Google’s serious presence in the smartphone market.
Founding of Alphabet and CEO Larry Page: Reorganizing the company
Between 2010 and 2014, Google was trying to create a new chapter in its history. Delving into fields beyond the search engine and web browser, the company had become a global innovation laboratory pursuing ideas ranging from driverless cars to projects in healthcare, renewable energy, and artificial intelligence.
In April 2011, Eric Schmidt resigned, saying that Google no longer needed the supervision of veteran executives like him, and Larry Page took his place. Larry Page and Sergey Brin realized a long time ago that they needed structural changes to better manage a company as big as Google and focus more on their ambitious projects. For this reason, in 2015, they made a bold decision.
They established a new holding company called Alphabet and brought Google and their other projects and companies under its umbrella. This move was not only a structural rearrangement but also reflected a profound philosophical change in Page and Breen’s approach. In this way, Google found a different position and at the same time in sync with a set of independent companies, each of which was looking for its specific and sometimes ambitious goals.
For example, the Google X division managed modern projects such as self-driving cars and smart cities. Meanwhile, Calico oversaw research related to increasing human lifespan and improving quality of life, and Verily focused on medical and biotechnology research.
In May 2011, Google reached a record of one billion visitors
Larry Page remained the CEO of Google until 2015, after which he took over the management of Alphabet. During his CEO tenure, Google experienced many ups and downs.
In May 2011, Google reached a record of one billion unique visitors. In the same year, “Chrome OS” was also introduced, which was mainly used in Chromebook laptops. These laptops were manufactured by Acer and Samsung and were first released to the general public in some retail stores, but in later years were made available to students and teachers in schools for educational purposes.
Google+ circles page
This period coincided with the introduction of one of Google’s famous and failed projects, namely Google Plus. The fact was that Google managers wanted to compete with Facebook by launching a social network, and in this regard, they replaced Google Plus with the Google Buzz microblogging service. Despite repeated redesigns, Google Plus never achieved success.
Google wanted to compete with Facebook by launching Google Plus
Another unfinished project of the company was Google Glass, whose experimental hardware was developed in the Google X and ATAP divisions. Despite the good idea and design, Google Glass needed technologies to process information that had not yet been developed at that time. In addition, some companies considered this product to be against their privacy and banned employees from using Google Glass.
July 2013, when Google announced the end of the Google Reader service, fans of this popular feed reader looked at this decision in disbelief. Shutting down Google Reader required courage, as we later saw in removing the headphone jack from iPhones. But this action made many Google users move to Twitter and search for daily news in tweets.
Finally, the purchase of DeepMind, an artificial intelligence laboratory based in London, was one of the most important steps taken by Google in this era, which later played a significant role in gaining the power of Google’s artificial intelligence department.
CEO Sundar Pichai’s era: the season of fighting with rivals
In 2015, together with the founding of Alphabet, Sundar Pichai, the company’s senior vice president under Eric Schmidt, replaced Larry Page as Google’s new CEO. Pichai, who joined Google in 2004, had proven his ability in leading the Google search bar, Google Gears, Google Pack, and Google Drive projects.
Pichai soon became one of the well-known faces of Google due to the idea of the Chrome browser and the management of the team that was responsible for the development of this software, and he became the deputy CEO of the company. He also played a significant role in the development of Android and the development of Google Apps.
One of the most important products that was introduced in the early days of Pichai’s CEO was Google Assistant. Google Assistant was introduced two years later than Amazon’s Alexa and 5 years after Apple’s Siri, But very soon it found its right place among users.
The wish of the founders of Google for the development of an inclusive and integrated ecosystem was realized during the management of Sundar Pichai
The strength of this virtual assistant was its synchronization with other products of the Google ecosystem, such as Google Home speakers, smart TVs, and most importantly, Android systems. Also, in 2016, Google announced the production of tensor processing units.
In October 2016, Google was at the forefront of the competition of flagship phones in the hardware sector with the introduction of Pixel phones, and two months later, the self-driving car project, which was considered one of the most successful projects of the Google X laboratory, was transferred to Waymo as an independent company after 6 years of testing. Guide the alphabet.
Sundar Pichai, unlike Eric Schmidt, was not afraid of competing with powerful technology companies, although now Google had also found a different face and no one considered it a new Silicon Valley player.
For example, Sundar Pichai had a special focus on the company’s cloud services, and despite long-standing competitors in this field such as Amazon and Microsoft, he invested heavily in building new data centers and developing cloud networks. With his efforts, Google Cloud became one of the top three cloud service providers in the world.
By introducing artificial intelligence tools and platforms in its cloud platform, Google was able to support corporate customers in various fields, including data analysis, machine learning, and process automation. During this period, the development and expansion of Nest smart home products also reached its peak. Although Google bought Nest in 2014, in recent years the integration of these products with the Google ecosystem has provided customers with an unparalleled user experience.
Some Google products, such as Google Translate, Google Lens, and Google Mate, found an undeniable role in people’s daily lives, and some projects, such as Google DeepMind projects, with every development and news, surprise the world beyond the technology world. Also, under the effective leadership of Sundar Pichai, Google has become one of the most powerful companies in the highly competitive market of generative artificial intelligence.
Google’s presence in the mobile market: from Nexus to Pixel
In the early 2010s, Google executives decided that they needed to enter the mobile market to improve the Android user experience and ensure timely updates for users.
At that time, Android was available as an open-source operating system to different manufacturers, and each company released its own version with desired changes and different user interfaces. But by producing Nexus phones, Google intended to provide users with a pure and integrated Android experience.
The first Nexus phone, named Nexus One, was introduced in January 2010 in collaboration with HTC. After that, Google introduced new Nexus models every year in partnership with one of the smartphone manufacturing companies:
- Nexus S: Samsung manufacturer, Android 2.1 Eclair operating system can be updated to Android 2.2 Froyo and Android 2.3 Gingerbread
- Galaxy Nexus: manufactured by Samsung, the operating system Android 4.0 Ice Cream Sandwich can be updated to Android 4.1 Jelly Bean
- Nexus 4: manufactured by LG, the Android 4.2 Jelly Bean operating system can be updated to Android 5.1
- Nexus 5: manufactured by LG, the Android 4.4 KitKat operating system can be updated to Android 6.0.1 Marshmallow
- Nexus 6: Motorola manufacturing company, Android 5 operating system before update to Android 7.1.1 Nougat
- Nexus 5X: manufactured by LG, operating system Android 6.0 Marshmallow updatable to Android 8.1.0 Oreo
- Nexus 6P: Huawei manufacturer, Android 6.0 Marshmallow operating system
The production of Nexus phones continued until 2015, but Google gradually realized that this series of phones, despite the loyal fans, could not compete well with other flagships in the market.
The production of the first series of Pixel phones began in 2016, and Google played the main role in the design and development of this series. The company optimized pure Android for Pixel phones to provide a smoother experience to the audience.
Since Google’s main goal was to compete with the flagships of Google and Samsung, it used better hardware and especially improved cameras in these products, which consequently raised their prices higher than the Nexus series. Also, the peak of Android integration with Google platforms was also seen in these phones.
However, since 2019, Google has tried to gain popularity among mid-range phone users by adding the Pixel series to its product series. Also, in 2023, the first Pixel Fold was introduced to compete with foldable phones of competing brands.
Google and artificial intelligence
Google was aware of the power of algorithms and machine learning from the beginning of its activities, and one of the most important areas in which it continuously invested was artificial intelligence.
As we said, in 2014, Google bought DeepMind Lab, which had advanced research in the field of artificial intelligence. Among the achievements of this laboratory, we can mention Alphago and AlphaFold projects.
Demis Hessabis, co-founder of Deepmind
Researchers at the AlphaGo project developed neural network models specifically for video games and game boards, and in 2016 AlphaGo beat the world champion Go player in a competition. Alphafold also made a significant contribution to the pharmaceutical industry by accurately predicting the three-dimensional structure of proteins using a deep learning system.
On the other hand, Google had opened a special account on the development of neural processing units. TPUs, or tensor processing units, were custom-designed silicon chips developed specifically for machine learning and optimized for TensorFlow. According to Google, TPUs train and run AI models much faster than traditional chips.
In 2019, Google used Bert algorithms in its search engine, which understood the meaning of words in the text instead of understanding words separately. According to Google, Bert greatly improved the responsiveness of the search engine, because users could ask Google their questions naturally instead of listing their desired keywords.
In 2023, Google finally made Bard’s generative artificial intelligence system available to users, which was based on the large conversational language model LaMDA. Google Bard was integrated into many everyday Google services such as Drive, Maps, Docs, Gmail, and YouTube.
With the increasing popularity of ChatGPT, in May 2023, Google introduced the next generation of its artificial intelligence language model called PaLM 2, which had more capabilities in the field of understanding different languages and the power of reasoning and coding. Google Jumnai based on this model was developed and replaced Bard.
Getty Images
Google’s noticeable speed and effort in the field of productive artificial intelligence can be considered one of the most obvious competitive manifestations of this company to obtain a greater share of various technology markets. After Microsoft’s huge investment in the startup OpenAI, Google also invested 500 million dollars in the startup Entropic.
The challenges of Google Jamnai photo production caused Sundar Pichai to invite Sergey Brin and Larry Page to have a closer relationship with this company by declaring an emergency (code red). Following this event, Sergey Brin officially confirmed his return to Google.
Also, in 2024, Google showed its readiness to compete with Apple by completely redesigning Android and took great steps towards local processing of artificial intelligence features in phones, such as Circle to Search.
Google Antitrust Cases: Growing Challenges
The flow of legal cases and complaints related to Google’s monopoly started in 2010; That is when the European Union Commission started a wide-ranging investigation into the anti-competitive behavior of this company. At that time, one of the main accusations was that Google placed its products and services above competitors in the search results, thereby marginalizing other companies.
This investigation became one of the longest and most complex antitrust cases in the history of technology, and finally, in 2017, the European Union sentenced Google to pay a heavy fine of 2.4 billion euros for prioritizing its shopping services (Google Shopping). .
A year later, the European Union condemned Google to pay a fine of 4.34 billion euros; But this time because of the Android operating system. Now Google was accused of encouraging mobile phone manufacturers to install their own apps (such as Google Maps, Gmail, and Play Store) and thus keeping competitors out of the market.
Read more: Amazon brand story; A store for everything
In this case, Microsoft, Nokia, and Oracle were influential in the final verdict and condemnation of Google by participating in the research group called FairSearch. In 2019, Google was fined another 1.5 billion euros by the European Commission. Google Adsense service was the main focus of these accusations.
Judge Amit Mehta in the Google monopoly case
After this case, it was the turn of the US Department of Justice to file a new and detailed complaint regarding Google’s monopolistic actions in the search engine and advertising market. In this lawsuit, more than 30 US states were on the opposite side of Google and sided with the judiciary.
In response to the accusations of the United States Department of Justice, Google announced that the online search and advertising market is a competitive market and different companies operate in this market. According to Google, users choose the company’s products and services because of their high quality, and this does not indicate exclusivity.
But in August 2024, Google finally lost its biggest antitrust case and was convicted by a Colombian court that it illegally monopolized the search market.
The Department of Justice and US prosecutors say that Google pays billions of dollars annually to mobile phone manufacturers such as Apple and Samsung to install the company’s search engine as the default application on their products in order to maintain its 95% share of mobile searches.
The consequences of this ruling can be very heavy for Google, while Google still has several other antitrust cases pending.
On the eve of the 26th year of Google’s establishment, this company with a market value of 2.02 trillion dollars is known as the fourth most valuable company in the world.
However, Google has never faced such serious challenges. Will it break up as US government and judicial officials say? Will the emergence of new artificial intelligence search systems such as SearchGPT diminish the popularity of Google’s search engine? How do you see the future of it?
How to solve the problem of slow charging of the Android phone?
One of the worst things that we notice when working with a smartphone is the slowing down of the charging process. Samsung phones, Xiaomi phones, Huawei phones, OnePlus phones, and any other Android device can face slow charging problems for various reasons.
If your phone is charging slowly and you want to know how to protect your phone battery, you can check some things to fix the problem before going to the repairmen. In addition to common cases such as battery failure, phone software not being updated, and deleting unused programs, there are solutions that can be used to improve charging speed.
-
Checking the health of the charging cable
-
Check the charger
-
Checking the charging port of the phone
-
Using a weak power source
-
Overheating of the phone while charging
-
Not using the phone while connected to the charger
-
Disabling fast charging
-
Checking the fast charging capability of Samsung phones
-
Checking the fast charging capability of other Android phones
Checking the health of the charging cable
Experience shows that in many cases, the reason for the slow charging of the Android phone is a faulty cable; Especially when you have used the charging cable for a long time.
In response to the question of how to keep the mobile battery healthy, one of the solutions will definitely be to use a standard cable. During the use of the charging cable, various damages can reduce its charge transmission power; As a result, it does not charge your Android phone at a high speed like in the first days. Therefore, before doing anything, check the cable carefully and preferably use another healthy cable to charge the device to determine whether the problem is with the cable or not.
Of course, calibrating your phone’s battery is another method that helps you return your device’s battery performance to its original state.
In the Zomit products section, the prices of charging cables of different brands are presented along with their detailed technical specifications so that you can choose the best option when buying.
Check the charger
Everything we said about the health of the cable also applies to the phone charger. This accessory can face problems during use due to various reasons such as impact, long-term use, power fluctuations, and initial manufacturing quality, and cannot transfer the charge to the phone like in the first days.
Now smartphone manufacturers have removed the charger in many of their models, and for this reason, it becomes more important to pay attention to the chargers we have. Sometimes using old chargers to charge new phones is the main reason for slow charging speed; Because they do not have enough output power to take advantage of advantages such as fast charging. On the other hand, some people buy these products due to the low price of chargers of some brands; But it is recommended to buy a better quality charger by paying more money.
To protect the Samsung phone battery, the best solution is definitely to use original chargers made by this company.
Note that if you do not use the original charger of the device, use authentic and high-quality alternative samples such as Samsung charger, Anker charger, or other brands to charge your phone and match its voltage with the voltage supported by the device. For example, if your phone supports 33W charging, it is recommended to use a 33W charger. The best charger article will help you choose the best charger model.
How to solve the problem of slow charging of the Android phone?
Checking the charging port of the phone
Maybe the slow charging of the phone is related to its port; In fact, the dirtiness of the charging port is one of the most common causes of the aforementioned problem. Check the charging port of the device carefully and clean it with compressed air or a small soft brush. Accumulation of dust and other particles on the copper lines of the charging port can prevent the correct connection of the charger socket to it and also prevent the correct transfer of electricity, and this can lead to a decrease in charging speed.
In some cases, you will notice that the charging port is a little loose after connecting the cable to the phone; In this scenario, it is possible that one of the pins of the charging port is loose. Unfortunately, there is not much you can do in the mentioned conditions and you have to go to authorized mobile repair centers.
Using a weak power source
Using the USB port of a laptop or computer and other electronic devices can be another reason for slow phone charging; Because in many cases, these ports have a weak power output that is lower than the input power of the phone, and as a result, the charging speed decreases.
In this situation, check your smartphone by connecting it to the main charger and power outlet to determine whether the problem is from a weak power source or not. In some cases, the defective wiring of the building can also cause the failure of electrical outlets, which can be ensured by connecting another electrical device to the desired outlet.
Overheating of the phone while charging
Do you know that the hotter your smartphone gets, the slower its charging speed? This feature is actually one of the device’s solutions to protect internal parts from failure; When the internal temperature exceeds the limit, it will reduce the charging speed, and this feature is one of the ways to take care of the battery of Samsung and other brands. In other words, the cooler your device stays, the faster it will charge, and this is why many fast wireless chargers are equipped with an internal fan.
If you want your Android phone to charge faster, remove the protective case and place it in a cool place (for example, next to a window out of direct sunlight).
Not using the phone while connected to the charger
If you cannot stay away from your Android phone even for a moment and you use it continuously during the day, the device will not have a chance to rest while charging. Using the phone while connected to electricity can lead to an increase in the consumption of hardware resources and, as a result, an increase in battery consumption, and these processes together reduce the device’s charging speed. So simply give yourself and the device some rest while charging your phone and don’t use it.
Using the phone while connected to the charger will generate more heat, and this factor will reduce the charging speed and even damage the battery in the long run.
Disabling fast charging
Some Android phones, including various models of Samsung phones, have provided the possibility of deactivating fast charging, and in other words, the reason for the slow charging of your Android phone can be related to the deactivation of this feature. In the following, we explain the method of checking the activation of fast charging. If you need to, you can also visit the article Does fast charging ruin the battery because you will get complete information about fast charging technology and its possible damages.
Checking the fast charging capability of Samsung phones
Enter the settings of your Samsung phone and then go to Battery > Charging settings. On this page, you will see the Fast Charging option, if it is active, the device will be charged at maximum power, and if the feature is off, the phone will be charged at a slow speed.
How to solve the problem of slow charging of the Android phone?
Checking the fast charging capability of other Android phones
If you are using a non-Samsung Android phone, go to the settings menu and type Fast Charge in the search section. If your device has the ability to enable and disable fast charging, this option will be displayed and you can turn it on or off.
You may ask how to take care of the phone’s battery when using fast charging, and the answer is that it is suggested to disable the fast charging feature as often as possible. In fact, by doing this, you allow the battery of the device to be charged at a normal speed without applying too much pressure, which can help improve its temperature and life.
In the article on how to change the charge symbol of Samsung phones, a simple method to change the graphic appearance of the charge indicator in Galaxy phones is explained, which we suggest you read if you wish.
The new version of Copilot was unveiled; Microsoft artificial intelligence
Today, Microsoft unveiled extensive changes to the Kopilot smart assistant. By adding audio and visual capabilities, Copilot will become a more personal AI assistant. Copilot’s new features include a special mode for reading news headlines, the ability to view the content of your screen, and an audio feature for more natural interaction.
Copilot’s smart assistant is undergoing a major redesign across mobile, web, and dedicated Windows platforms to improve its user experience with a card-based approach and more closely resemble Inflection AI’s Pi personal AI assistant.
Earlier this year, Microsoft hired a number of Inflection AI experts, including Mustafa Suleiman, co-founder of Google DeepMind and current CEO of Microsoft’s AI division. This is Suleiman’s first major impact at CoPilot after taking over the leadership role of Microsoft’s AI division.
The user interface of Copilot has undergone a significant evolution compared to the previous versions of Microsoft and has a completely different look. This user interface elevates the user experience to a higher level with a warmer and more attractive design, especially on the personalized Copilot Discover screen.
Unlike simple text prompts in chatbots, Copilot Discover provides useful and relevant information to the user. Microsoft says it’s fully personalizing Copilot’s home page based on a user’s conversation history, and over time will enrich the page with useful searches, tips, and related information.
Earlier this year, Microsoft handed over the version for regular users to Tim Sulaiman to do more experiments in the field of personalization and creating personality traits for this smart assistant. “What we’ve learned from the Pi team and the professionals who have joined us from Inflection AI is that they always pay close attention to the details of our customers’ needs,” Yusuf Mehdi, executive vice president and senior director of consumer marketing at Microsoft, said in an interview with The Verge. “The way they listened and what they learned from the long conversations in this research has undoubtedly influenced what we’ve done.”
In addition to improving Kopilot’s appearance, Microsoft has taken great strides by adding ChatGPT-like voice capabilities. Now users can chat with Kopilot’s AI assistant, ask questions, and even interrupt the conversation like a normal conversation with friends or colleagues. Copilot currently offers four different audio options.
Microsoft
Copilot Vision is the second big change that allows Microsoft’s AI assistant to see what you’re looking at on a web page. You can ask it questions about text, images, and page content, and get natural answers combined with Copilot’s new audio features. For example, when shopping online, you can use Copilot Vision to receive product suggestions and let it search for a variety of options for you.
Microsoft
The use of Copilot Vision is completely optional, and Microsoft emphasizes that no content is stored or used to train models. Copilot Vision isn’t available on all websites yet, as Microsoft has put restrictions on the types of websites that the feature works with. “We start with a limited list of popular websites to ensure the experience is safe and secure for all users,” says the Copilot team.
According to The Verge, Microsoft has clearly outlined a long-term vision for new audio and visual features in the Copilot smart assistant. In one hands-on demonstration, Copilot Vision was used to analyze images of old handwritten food recipes. Copilot Vision is able to recognize the type of food and estimate its approximate cooking time. Microsoft also showed off a similar experience for Xbox games earlier this year, showing how Copilot can help users navigate games like Minecraft.
The next stage of Copilot development includes a new feature called Copilot Daily. This feature provides audio summaries of news and weather as if read by a professional news anchor. This summary is designed as a short clip that users can listen to in the morning.
Microsoft
The content of Copilot Daily is obtained only from reliable and authorized news and weather sources. Microsoft is initially working with news agencies Reuters, Axel Springer and Hearst, and the Financial Times, with plans to add more news sources in the future.
Copilot is able to answer more complex questions thanks to advanced OpenAI models. The new Think Deeper feature allows CoPilot to spend more time processing complex questions and provide step-by-step and more detailed answers. This feature will be very useful, especially for comparing two different options.
The Think Deeper feature is still in the early stages of development and Microsoft has it in Copilot Labs. These labs are a space to evaluate new features that Microsoft develops.
The Copilot Vision feature will also initially be part of Copilot Labs, where users can share their thoughts on new experiences. Microsoft is taking a more cautious approach to Copilot Vision after the recall was criticized for security and privacy issues.
From today, the new Copilot will be available to users. The new Copilot can be accessed through the iOS and Android mobile apps, the copilot.microsoft.com website, and the Copilot Windows app.
Initially, the Copilot Voice feature will only be available in English in Australia, Canada, New Zealand, the United Kingdom, and the United States. However, there are plans to expand this feature to more regions and languages in the future. The Copilot Daily feature will initially be limited to the US and the UK, and the Copilot Vision feature will initially be available to a limited number of Copilot Pro subscribers in the US.
Noun: Neutral
Adjective: (gender).
Conjunction: the sound sequence /ɛn/.
onAdjective: In the state of being active, functioning or operate.
Adjective: happen; ; being or due to be put into action.
Adjective: Fitted; covering or being worn.
Adjective: Acceptable, appropriate.
Adjective: Possible; capable of being successfully carried out.
Adjective: destined; involved, doomed.
Adjective: Having reached a base as a runner and being positioned there, awaiting further action from a subsequent batter.
Adjective: Within the half of the field on the same side as the batsman’s legs; the left side for a right-handed batsman.
Adjective: Of a ball, being the next in sequence to be potted, according to the rules of the game.
Adjective: Acting in character.
Adjective: Performative or funny in a wearying manner.
Adjective: menstruating.
Adverb: To an operate state.
Adverb: So as to cover or be fitted.
Adverb: Along, forwards (continuing an action).
Adverb: In continuation, at length.
Adverb: See also ‘odds-on’.
Preposition: Positioned at the upper surface of, touching from above.
Preposition: Positioned at or resting against the outer surface of; attached to.
Preposition: covering.
Preposition: At or in (a certain region or location).
Preposition: Near; adjacent to; alongside; just off.
Preposition: support by (the specified part of itself).
Preposition: Aboard (a mode of transport, especially public transport, or transport that one sits astride or uses while standing).
Preposition: At the date or day of.
Preposition: At a given time after the start of something; at.
Preposition: deal with the subject of; about; concerning.
Preposition: In the possession of.
Preposition: Because of; due to; upon the basis of (something not yet confirmed as true).
Preposition: At the time of (and often because of).
Preposition: Arrived or coming into the presence of.
Preposition: Toward; for; .
Preposition: Engaged in or occupied with (an action or activity).
Preposition: Regularly taking (a drug).
Preposition: Under the influence of (a drug, or something that is causing drug-like effects).
Preposition: In addition to; besides; indicating multiplication or succession in a series.
Preposition: Serving as a member of.
Preposition: By virtue of; with the pledge of.
Preposition: To the account or detriment of; denoting imprecation or invocation, or coming to, falling, or resting upon.
Preposition: Against; in opposition to.
Preposition: According to, from the standpoint of; expressing what must follow, whether accepted or not, if a given premise or system is assumed true.
Preposition: In a position of being able to pot (a given ball).
Preposition: Having as identical domain and codomain.
Preposition: Having <math>V^n</math> as domain and V as codomain, for the specified set V and some integer n.
Preposition: generate by.
Preposition: of.
Preposition: At the peril of, or for the safety of.
Verb: To switch on.
Noun: In the Japanese language, a pronunciation, or reading, of a kanji character that was originally based on the character’s pronunciation in Chinese, contrasted with kun.
Adjective: In the state of being active, functioning or operate.
Adjective: happen; ; being or due to be put into action.
Adjective: Fitted; covering or being worn.
Adjective: Acceptable, appropriate.
Adjective: Possible; capable of being successfully carried out.
Adjective: destined; involved, doomed.
Adjective: Having reached a base as a runner and being positioned there, awaiting further action from a subsequent batter.
Adjective: Within the half of the field on the same side as the batsman’s legs; the left side for a right-handed batsman.
Adjective: Of a ball, being the next in sequence to be potted, according to the rules of the game.
Adjective: Acting in character.
Adjective: Performative or funny in a wearying manner.
Adjective: menstruating.
Adverb: To an operate state.
Adverb: So as to cover or be fitted.
Adverb: Along, forwards (continuing an action).
Adverb: In continuation, at length.
Adverb: See also ‘odds-on’.
Preposition: Positioned at the upper surface of, touching from above.
Preposition: Positioned at or resting against the outer surface of; attached to.
Preposition: covering.
Preposition: At or in (a certain region or location).
Preposition: Near; adjacent to; alongside; just off.
Preposition: support by (the specified part of itself).
Preposition: Aboard (a mode of transport, especially public transport, or transport that one sits astride or uses while standing).
Preposition: At the date or day of.
Preposition: At a given time after the start of something; at.
Preposition: deal with the subject of; about; concerning.
Preposition: In the possession of.
Preposition: Because of; due to; upon the basis of (something not yet confirmed as true).
Preposition: At the time of (and often because of).
Preposition: Arrived or coming into the presence of.
Preposition: Toward; for; .
Preposition: Engaged in or occupied with (an action or activity).
Preposition: Regularly taking (a drug).
Preposition: Under the influence of (a drug, or something that is causing drug-like effects).
Preposition: In addition to; besides; indicating multiplication or succession in a series.
Preposition: Serving as a member of.
Preposition: By virtue of; with the pledge of.
Preposition: To the account or detriment of; denoting imprecation or invocation, or coming to, falling, or resting upon.
Preposition: Against; in opposition to.
Preposition: According to, from the standpoint of; expressing what must follow, whether accepted or not, if a given premise or system is assumed true.
Preposition: In a position of being able to pot (a given ball).
Preposition: Having as identical domain and codomain.
Preposition: Having <math>V^n</math> as domain and V as codomain, for the specified set V and some integer n.
Preposition: generate by.
Preposition: of.
Preposition: At the peril of, or for the safety of.
Verb: To switch on.
Noun: In the Japanese language, a pronunciation, or reading, of a kanji character that was originally based on the character’s pronunciation in Chinese, contrasted with kun.
Proper noun: The earth-dragon of Delphi, represented as a serpent, killed by Apollo.
Noun: Any member of the comedy troupe Monty Python: Graham Chapman, John Cleese, Terry Gilliam, Eric Idle, Terry Jones or Michael Palin.
Proper noun: The earth-dragon of Delphi, represented as a serpent, killed by Apollo.
Noun: Any member of the comedy troupe Monty Python: Graham Chapman, John Cleese, Terry Gilliam, Eric Idle, Terry Jones or Michael Palin.
Proper noun: The earth-dragon of Delphi, represented as a serpent, killed by Apollo.
Noun: Any member of the comedy troupe Monty Python: Graham Chapman, John Cleese, Terry Gilliam, Eric Idle, Terry Jones or Michael Palin.
Noun: normal
Noun: Neutral
Adjective: (gender).
Conjunction: the sound sequence /ɛn/.
Everything about Python; A programming language for everyone
Python is one of the most popular programming languages in the world, and most people who want to take the first steps in programming choose Python; Because It is very close to the English language and removes most of the fear and hesitation of beginners in the early stages; So that learning programming language seems possible for them.
According to the latest Stack Overflow survey of 2022, Python is the third most popular language among people who want to learn programming language and the fourth most popular language among developers.
It is also a versatile language used in a variety of fields including artificial intelligence, machine learning, data science, and web development, easily making it to the list of top-grossing programming languages of 2023.
If you are curious about Python and want to make sure that it is exactly the language you need before starting to learn the programming language, follow this article.
-
The story of the birth of Python
-
Zen Python
-
How does Python work?
-
Reasons for Python’s popularity
-
Python frameworks
-
1. Django
-
2. Flask
-
3. Bottle
-
4. CherryPy
-
5. Web-to-Py (Web2Py)
-
Python libraries
-
1. TensorFlow
-
2. Scikit-Learn
-
3. Numpy
-
4. Keras
-
5. PyTorch
-
What projects can be developed with Python?
-
What companies use Python?
-
Install Python
-
How long does it take to learn Python?
-
Where to start to learn Python?
-
Python alternative languages
-
Weaknesses of Python
-
The Future of Python
The story of the birth of Python
The Python programming language was born in December 1989 during the Christmas holidays in Amsterdam, Holland. Guido van Rossum, a Dutch programmer then working at Centrum Wiskunde & Informatica, a mathematical and computer science research institute, decided for fun while spending the Christmas holidays on a new programming language that had been around for a long time. He wanted to write a commentary based on ABC.
ABC is a high-level, general-purpose programming language similar to BASIC and Pascal that was developed at the institute where Rossum worked. The purpose of creating ABC was to teach programming and prototyping, and because it was high-level (that is, it was similar to human language), it was easily read in English, and it was the best solution for teaching loops, logic, and data to beginners. Van Rossum had worked on the ABC project for several years and implemented many of its features in Python. The reason for choosing the name Python for this new language was his interest in the comedy series ” Monty Python Bird Circus “.
Khidou wanted the development of the application to be possible simply and without worrying about hardware, memory management, and such complications; So he thought of inventing his own programming language, inspired his ideas from ABC, and reducing the project time from three years to a three-month project; And that’s how Python was born.
Python’s name is taken from the Monty Python comedy series
In February 1991, van Rossum published Python code on alt. sources. alt. sources was like a forum where people shared their source codes and it can be considered one of the first platforms that helped the development of open-source projects.
Python is a high-level interpreter language; This means that it is closer to human language, so it is easier for beginners to learn, but to be comprehensible to a computer, it needs software to directly implement the instructions. In fact, the Python language was founded on the principle of making programming understandable to everyone, and van Rossum adhered to this principle throughout his career.
Python was founded on the principle of making programming understandable to everyone
At first, Khedo didn’t have much hope for Python’s popularity. Before the globalization of the Internet, it was difficult to convince people to use a new programming language, and in the 1980s, Khedo had to travel and distribute magnetic tapes to people for years to introduce and promote ABC. ABC at that time could not make room between the programmers; For this reason, Khido did not have any special expectations from Python; Although the introduction of Python, which in those days was enough to download from newsgroups known as Usenet, was much easier than door-to-door distribution of magnetic tapes.
Khedo van Rossum speaking at the 2018 Python Language Conference
But in 1995, a company called Zope was founded, specializing in the production of ad engines for the Internet. Zope created dynamic web pages written in Python, thus popularizing Python in its early days. Zope is run by a team of Python developers, joined by Van Rossum in 2000.
It was around this time that Van Rossum was nicknamed the “benevolent dictator for life” because he was the creator of this language and controlled its development stages. This nickname was later given to the leaders of text game projects who were the founders of the project themselves and had the final say in discussions and disagreements.
Released in October 2000, Python 2 quickly became popular in the systems industry as programmers were able to find creative ways to automate their processes. During this period, web development also experienced significant growth, and frameworks such as Jinja, Flask, and Django emerged, and large communities were immediately created for these frameworks.
In 2001, the Python Software Foundation was founded, an American non-profit organization dedicated entirely to the Python language. This foundation is also responsible for organizing the Python conference, which is held in 40 countries.
By 2010, Python-based frameworks were among the top ten, although the number of dynamic website competitors was increasing day by day so the 2000s can be called the peak years of Python. According to the TIOBE site ranking, in 2000, Python was the 20th most used language; By 2005, it climbed to the 6th place, and in April 2023, it finally reached the position of the copy. This website has selected Python as the “Programming Language of the Year” in 2007, 2010, 2018, 2020 and 2021.
The TIOBE site chose Python as the “Programming Language of the Year” five times
In 2005, Van Rossum joined Google and worked on Google App Engine, which ran Python applications in the cloud. With Van Rossum joining Google, Python’s bright future was guaranteed.
Python 3 was released in December 2008 and caused a lot of trouble for developers because it was not compatible with Python 2. Some developers preferred to work with Python 2 and others with Python 3.
Although Python quickly became popular among tech startups, it didn’t catch on among large companies for a long time. Until the late 2000s, MIT student Drew Houston, after leaving his flash drive at home, thought of creating a space for file sharing, and in 2007, he released the Dropbox software for this purpose. Dropbox was written in Python and within a year it reached three million users and attracted the attention of large companies. Since Dropbox was written in Python 2, van Rossum joined the team in 2013 to port the program to Python 3. Van Rossum worked with Dropbox until his retirement.
It was October 2019 when Van Rossum officially announced his retirement and stepped down from the position of “the eternal benevolent dictator”. After Van Rossum’s retirement, the core Python developers formed a steering council to decide on future changes to Python, and Van Rossum is a member of this council.
Python has become so big and popular these days that more people are deciding on it. In November 2020 Van Rossum announced that retirement was boring for him and joined Microsoft’s developer division as a “Distinguished Engineer” given to the company’s most outstanding engineers. In a tweet, he promised to make Python better for all platforms, not just Windows.
Zen Python
Tim Peters, one of the main developers of Python, wrote a set of programming principles in 1999, known as the “Zen of Python”. Python developers and programmers are still trying to adhere to these principles. To view these principles in the Python interpreter, just enter the “import this” code to display this list:
- Beautiful is better than ugly.
- Explicit expression is better than implied.
- Simple is better than complicated.
- Complex is better than complicated.
- Straight and smooth is better than nested.
- Scattered is better than dense.
- Readability is important.
- Special cases are not special enough to break the rules.
- Although the feasibility is more pure.
- Errors should never be dismissed in silence.
- Unless they are explicitly silenced.
- When faced with ambiguity, avoid the temptation to guess.
- There should be one (and preferably only one) clear way of doing things.
- Although this method may not seem obvious at first unless you are Dutch.
- Now is better than ever.
- Although “never” is often better than “right now”.
- If its implementation is hard to describe, it’s a bad idea.
- If the implementation is easy to describe, it might be a good idea.
- Namespaces are a great idea, let’s use them more!
How does Python work?
When you write a program in C or C++, you must compile it; This means that you have to convert the code that is understandable for humans into a code that is understandable for computers. Machine code is actually low-level instructions that can be directly executed by the CPU. After the compilation process is completed successfully, your code will produce an executable file. Running this code will execute all the instructions you wrote step by step.
But Python is generally an interpreted language and not a compiled language, although compilation is one of the stages of the coding process with Python. Python code in the file py. It is written, first, it is compiled as bytecode and then in pic format. or pyo. is saved.
In fact, instead of being translated into machine code like C++, Python code is translated into bytecode. Bytecode is a set of low-level instructions that can be executed by an interpreter. On most computers, the Python interpreter is installed in the path usr/local/bin/python3.11/. Instead of executing instructions on the CPU, bytecode executes them on the virtual machine.
One of the advantages of interpreted languages like Python is that they are independent of the operating system; This means that as long as the Python bytecode and the virtual machine are of the same version, this code can be run on any platform, including Windows or MacOS.
Reasons for Python’s popularity
Think of the day when every user can program their own computer. We look to a future where every computer user will be able to “lift the hood” and improve the applications inside the computer. We believe this will fundamentally change the nature of software and software development.
These sentences were the proposal that the “Computer Programming for Everyone” project used to introduce itself. Van Rossum started this project to encourage people to program and he believed that the programming language should be so simple and understandable that every computer user can learn it easily.
Although Python language is slower than C and Java and is not suitable for designing applications that require high speed to run, such as heavy games, it has many advantages that have made it one of the most popular programming languages; including:
1. Easy to learn and use
Learning and using the Python language is very easy for beginners because it has a simple structure, readable codes, and commands very close to the English language, and compared to other languages, it requires writing much fewer lines of code to execute tasks.
A comic about how easy Python is
2. A big and supportive Python community
Python was created more than 30 years ago, and since then the community of Python programmers has grown enough to support any developer at any level, whether a beginner or a professional. To learn Python, there are many free educational resources and videos in this forum and all over the Internet, and for this reason, people who choose this language to learn will not have to worry about the lack of resources.
3. The support of big sponsors
Programming languages grow faster with the support of large companies. Facebook supports PHP, Oracle supports Java, and Microsoft supports Visual Basic and C#. Python language is also supported by Facebook, Amazon web services and especially Google. Since 2006, Google has chosen Python to develop many of its applications and platforms.
4. Hundreds of Python libraries and frameworks
Due to its large sponsors and active community, Python has a variety of unique libraries that save programmers time. There are many cloud multimedia services that support Python developers on different platforms through library tools.
5. Versatility, efficiency, reliability and speed
Python language can be used in various environments including mobile and desktop applications, web development, and hardware programming. Python’s versatility has made it the first choice of many programmers in various fields. Although the execution speed of programs written in Python is slightly lower than that of compiled languages such as C, developing an application in Python takes much less time and takes up less space in memory.
6. Big data, machine learning, and cloud computing
After R, Python is the most popular programming language in the field of data science and analysis, because it is a very understandable language for many researchers who do not have a programming background. A large amount of data processing in companies is done only with Python. Most of the research and development projects are also done with the Python language, because Python has many uses, including the ease of analyzing and organizing usable data. Meanwhile, hundreds of Python libraries are used in thousands of machine-learning projects every day. Realizing the importance of Python, the hiring of Python programmers with mastery of data science principles has also increased a lot.
7. The flexibility of the Python language
Python is so flexible that it allows the developer to try a different project each time. Python does not limit developers to the development of specific applications and leaves them free to create any desired application. Also, migrating from JavaScript to Python is very easy for people who want to go from front-end to back-end, even though the two languages are different.
8. Using Python in universities
Due to the use of Python in the field of artificial intelligence, deep learning, and data science, today this language is used to teach programming in schools and universities.
9. Automation capability
The many tools and modules that Python provides to the developer make the process of automating repetitive and boring tasks very easy and save time. Meanwhile, the number of lines of Python code for automation tool development is so small that it surprises the programmer.
10. Python is the language of startups
Ease of use, fast development, and low costs make Python a good choice for small startups with limited budgets. With the significant increase in the popularity of social media and the explosion of data in this platform, many startups active in the field of data analysis go to the Python language.
Python frameworks
Python frameworks are a collection of modules and packages that help developers speed up development. These frameworks automate common processes and implementations and save time, allowing the developer to focus only on the application logic and leave the implementation of these common processes to the framework.
Python frameworks are generally divided into two categories:
- A micro-framework that is easy and convenient to use and suitable for developing small and medium-sized applications.
- The full-stack framework, which has a more complex nature, provides the user with more extensive libraries, has the ability to manage data, and is used for the development of various applications.
Developers need access to the frameworks of this language to build applications with Python. Here we introduce 5 examples of the best and most popular Python frameworks:
1. Django
Large companies use the Django framework to save time and write less code in developing web applications. Django is a full-stack framework and is very popular because it is free and open-source. In fact, Django is so popular that if you go to a Python developer, wake him up, and ask him at gunpoint to design an app for you, you have no doubt that he will automatically switch to Django.
This framework includes all the necessary features by default, but its main feature is the emphasis on the principle of “avoid duplicate work”. Developers save time in the development of their projects with the help of Object-Relational Mapping, which is available in the Django framework.
Large companies and organizations that use the Django framework to build applications include NASA, Instagram, YouTube, and The Washington Post.
2 . Flask
Flask falls under the category of microframeworks, which means it focuses on the bare minimum and leaves the rest to the developer. The Flask framework is a very suitable choice for people who know exactly what they want and want to have their hands open in designing web applications. This framework is also a good choice for emergency projects, medium to large scale. In cases where Django does not meet your needs in the development of web projects, you can go to Flask.
Famous brands that use Flask include Netflix, Lyft, Airbnb, Reddit, and Mailgun.
3. Bottle
If you think that Flask doesn’t open your hands enough to design the application you want, go to Battle. Battle framework is a good choice for developing very small applications (for example, less than 500 lines of code) that do not require special features. Since Battle is a microframework, it only depends on the Python standard library.
Of course, keep this point in mind that in practice, using the Battle framework may interfere with your work; If you need to add a special feature to the application in the middle of the project, you will be in trouble, because Battle puts all the code in a single file. The battle framework is not suitable for developing large applications.
4. CherryPy
CherryPy is an open-source microframework for Python. Its minimal design is suitable for building web applications that can run on various platforms, including Windows, MacOS, Linux, and any other operating system that supports Python.
Cherry Pie is a good option for startups because it has few restrictions. This framework uses any type of technology for formatting, data access, etc., and it easily handles sessions, statistics, cookies, file uploads, and so on. The CherryPy community supports both beginners and professional developers.
5. Web-to-Py (Web2Py)
Web2Py is a full-stack framework and is a good choice for developers and data scientists due to its data management capabilities. This framework is mostly used for projects related to data collection and analysis.
Python libraries
The main difference between a framework and a library is their “complexity”, which is less in libraries. A library is a set of packages that implement certain operations, while a framework contains the architecture of an application.
When the developer calls a method from the library, the control of the development process is in his own hands; But in the case of frameworks, the control of the process is in the hands of the framework, not the developer. Frameworks are more commonly used than libraries because they are more flexible and provide tools for the user to extend their features. Next, we will introduce 5 popular Python libraries
1. TensorFlow
TensorFlow is an open-source library suitable for projects related to neural networks, computational graphs, and applications focused on machine learning. This library was created by Google in collaboration with the Brain Team deep learning artificial intelligence research team; For this reason, this library is present in almost all Google applications for machine learning.
2. Scikit-Learn
The PsycheLearn library is for Python applications focused on machine learning and is ideal for validating supervised models on unseen data. Scikit-Learn also provides an efficient approach for clustering, factor analysis, and principal component analysis for unsupervised neural networks and is a good choice in the field of image processing, such as feature extraction from images and texts.
3. Numpy
Numpy is a library that other libraries such as TensorFlow use as their internal library to perform several operations. Since Python deals with applications in the data domain, Numpy helps developers a lot with its complex capabilities.
The main advantages are interactive features and ease of use. This library greatly simplifies complex mathematical implementations. If you are thinking of doing a project in the field of data science and machine learning, using the Numpy library will help you a lot.
4. Keras
Keras is a machine learning library in Python and provides a smooth mechanism for developing neural networks. Cress also offers best-in-class applications for model compilation, data set processing, graph visualization, and more.
This library is used in the development of backend applications based on Python. For example, Uber, Netflix, and Instacart use this library. In addition, startups with machine learning at the core of their product design have a special look at this library.
5. PyTorch
PyTorch is one of the largest machine learning libraries that allows developers to perform tensor calculations and performs well in the field of neural networks. If you are interested in natural language processing (NLP), the PyTorch library is a good choice for your projects.
Facebook developed this library in its artificial intelligence research group, and Uber uses it in the backend of its “Pyro” programming software. Since its inception, PieTorch has grown in popularity and attracted the attention of an increasing number of machine learning developers.
What projects can be developed with Python?
Learning the basics of Python is one thing, but what to do with this skill is another story and may become a challenge for some. Here we introduce 15 interesting and practical projects that can be developed with Python, which are good options to start with:
1. Organize files in the system
Python can be easily used to automatically organize files on the system. Operations such as renaming, copying, and moving hundreds of files can be done by writing a piece of Python code in a few seconds. For example, beets, a free and open-source software for organizing music files, uses Python and allows the user to manipulate the codes and even write the desired plug-in.
2. Listing
Using Python, you can save a list of your favorite websites on the Python command line instead of bookmarking them and moving them from one browser to another. For example, Buku bookmark management is written in Python 3 and besides managing the list of favorite websites, it has the possibility of automatic tagging, fixing broken links and searching in the database, and even locking and encrypting your lists.
This app is an open-source project and if you have an idea and don’t know what to do with it, you can add it as a new feature to this project so that other users can use it.
3. Creating a resume on a static website
Written in Python, Pelican is designed for building static websites and is a great choice for creating a clean yet interactive resume. In Pelican, you can access Python codes and modify them as much as you want.
4. Building dynamic websites
Python web frameworks such as Django and Flask will help you a lot to build dynamic websites with many features. For example, Instagram uses Django and Pinterest uses Flask, and both have the ability to manage high-resolution images, complex user interactions, and responsive web design elements, and use Python in their backend.
5. Data visualization
Python libraries provide a large set of data visualization tools to make it easier to examine data using graphs and maps. With the Python-based visualization library Seaborn and Matplotlib, you can easily display your data as graphs and maps, and use libraries like Bokeh to add more interactivity.
6. Construction of neural network
Companies like Uber use neural networks to communicate between passengers and drivers and even improve the quality of food and restaurant offers. Python language is at the center of these activities. According to Uber, the Pytorch deep learning library is the mainstay of the company’s algorithm development.
Python provides libraries such as Tensorflow and Cress for deep learning projects. By learning Python and using these libraries to build neural networks, you will gain a skill that will be useful in various projects for years to come.
7. Building a recommender engine
Another popular use of machine learning is the recommender engine. Python libraries such as NumPy and Scikit-Learn provide the user with a large set of diverse tools to create a platform for product offerings, for example, in online stores. For example, with the help of this data science stack and its combination with big data frameworks such as Apache Hadoop, Spotify, and Netflix can analyze data and suggest their favorite music and movies to users.
8. Analysis of user feedback
User sentiment analysis helps businesses make important decisions, and Python’s data science stack, its natural language toolbox (nltk), combined with simple, supervised learning algorithms can quickly identify comments, tweets, or any kind of feedback from Check the user side.
9. Collecting data from websites
Of course, many of these projects mentioned so far are not possible without data collection. With the help of Python and libraries and frameworks like Selenium , ScraPy and BeautifulSoup, you can easily extract information from different websites. Additionally, Python easily integrates with existing APIs, helping to pull structured data from websites quickly and efficiently.
10. Making mobile applications
More than 45% of the world’s population uses a smartphone, and for this reason, the mobile application market is always hot. With the help of the Kivy Python framework, you can develop applications that can be run on different operating systems. For example, Dropbox has used Python to build its mobile application, which runs without any problems on Windows, Mac OS, and even some Linux distributions.
11. Cryptocurrency exchange
With the help of Python, you can create a cryptocurrency trading robot that is active all the time and operates independently of the user. It is also possible to predict the best time to buy and sell cryptocurrency by combining machine learning algorithms in this bot. Even if you are not interested in buying and selling cryptocurrency yourself, your bot can have a high price in the market.
12. Making bots for social networks
With the help of Python, bots can be made to take over a large amount of your online activities on social networks. You can connect directly to social networking services with the help of libraries like Tweepy and InstaPy, or write a bot code and connect it to an API, just like the ones offered by YouTube Reddit, or Discord.
13. Creating a chatbot
These days, with the advent of ChatGPT and Bing Chat, the chatbot market is hot! Python makes it possible to build complex chatbots by integrating nltk with machine learning libraries. You can even add sound to your chatbot using the PyAudio and SpeechRecognition libraries and add speech-to-text functionality.
14. Connecting to the Internet of Things
With tools like Arduino and Raspberry Pi, you can build robots, home appliances, and small devices that connect to the Internet of Things and use the Python language. For example, MicroPython is an open-source project that greatly simplifies programming for microcontrollers. You can even set up your own firewall or irrigation system using Python.
15. Use of other languages
Sometimes the project you have in mind cannot be completely written in Python. In this situation, it is not necessary to abandon Python completely and go for other languages; Rather, the flexibility of Python allows you to use their capabilities in your Python project with the help of special Python modules (extension modules) wherever you need to use another language such as C or C++.
What companies use Python?
Many technology companies and large and successful organizations in the world use Python language for their website backend development or data analysis. Here we get to know some of them:
Instagram , the largest photo sharing application in the world with more than 2 billion daily active users, uses the Django framework, which is written in Python, for its backend, and the reason for this is the simplicity and popularity of Python.
Google is the most used search engine in the world with a 93% share of the market. Google has been a fan of Python since the beginning, and its founders decided to “use Python wherever possible and C++ wherever necessary .” The ease of using Python is enough that Google’s first web crawler, which was written in Java, was later rewritten in Python to make it easier to use.
Spotify
Spotify, a music and podcast streaming platform, was launched in 2008 and has more than 450 million active users today. While Spotify’s website uses WordPress, its application is built with Python. 80% of Spotify services are based on Python and the rest are based on other languages such as Java, C, and C++. Spotify also uses Python for data analysis and backend services.
Netflix
With more than 200 million members, Netflix is the largest Internet television network in the world. Like Spotify, Netflix uses Python for data analysis. Additionally, it allows its software engineers to code in whatever language they are most comfortable with, and most Netflix programmers have preferred Python. According to Netflix engineers, Python’s standard library, its highly active and growing community, and the wide variety of available libraries make it possible for developers to solve any problem.
The Reddit website has more than 400 million monthly active users and is the 10th most visited website in the world in 2023. Reddit originally used Lisp but was rewritten in Python six months after launch. The reason for this change was Python’s access to more diverse libraries and its flexibility in terms of development. When Reddit hires programmers, they tell them that everything they write must be in Python so that it’s easier to read and it’s easy to understand if the code they wrote is good or bad.
Python language has many fans among large companies and organizations. Other examples of prominent companies using Python include Facebook, NASA, Quora, Pinterest, YouTube, Dropbox, Amazon, Uber, Lyft, CIA, PayPal, Nokia, and IBM.
Install Python
Python can be installed on Windows, Linux, MacOS, and certain platforms such as Android, iOS, Solaris IBM AS/400, etc. and there are different ways to install it. But before installing, you should know that Python has two versions, 2 and 3. Version 2 was popular in the 2000s, but now the best version to use is version 3; Because the language and libraries are only updated in the third version.
The easiest way to install the latest version of Python is to download it from the official site itself. Just be careful when installing, check the “Add Python 3. x to PATH” option so that after installation you can install coding and Python packages through the cmd environment. In the Windows environment, you can also download and install Python through the Microsoft Store, which is very easy.
-
Introductory training of Python programming language
-
What tools and software will we need to start programming?
Most Linux distributions also come with Python by default, and you may need to update it to the latest version. To install Python in Linux, you can do it through the package manager, and if it is not possible, through the source codes.
The easiest way to add functionality to pure Python, especially for data scientists, is to download it from the Anaconda site. The package you download from this site includes pure Python, essential libraries for scientists, and machine learning (such as name, say, and pandas), as well as two coding tools, Spyder and Jupyter Notebook. Installing this package is very easy and you only need to select your operating system and click on download.
How long does it take to learn Python?
If you have no background in Python and want to start learning it from scratch, it usually takes three to six months to learn it; However, it takes several years to become an expert in this language.
If you have a background in the Java programming language and want to learn Python as a second language, it only takes a day or two to familiarize yourself with the Python environment and write your first “hello world” code. If you use interactive platforms like Educative or CodeCademy or freeCodeCamp, you can write very simple programs in Python in a few minutes.
On the other hand, if you plan to use Python in data science (for example, for data analysis or machine learning), it takes less time to learn, because for data science you only need a specific use of the language and an understanding Its basic principles do not take more than one to two months. According to 365datascience statistics, if you devote 5 hours of your time a day to learning Python, you can learn the fundamental principles required for data science analysis in Python within a month.
Fortunately, in order to be hired as a Python programmer, you don’t need full expertise in this field, and just learning Python, debugging, and familiarity with software development tools such as Git is enough; You will gain expertise along the way.
Where to start to learn Python?
The best way to learn Python or any other programming language is to practice coding on a daily basis. Of course, that’s easy to say, because as soon as you start coding, you’re faced with big challenges, and all you have to do is drop a semicolon somewhere and you’ll get a whole bunch of error messages. That’s why you will need a guide to learn Python.
Although you’ll get the best guidance from face-to-face interactions with people familiar with Python, there are other ways to learn the language. For example, you can use free websites like w3school or geeksforgeeks or freecodecamp or online courses like The Complete Python Pro Bootcamp on the Udemy website and when you get a good understanding of this language, go to read a book like Automate the Boring Stuff with Python for a deeper knowledge of Get Python. Of course, reading a book is not an easy way to learn a programming language, and you can use online courses based on these books.
On the other hand, you can advance learning Python by running a project; For example, a project related to automation, building a web application, or even a machine learning model.
These days, learning Python with mobile applications has also become popular; Programs like SoloLearn or Datacamp provide you with a simple way to learn programming languages and use an environment to run codes; However, you may need to get help from other guides as well.
Python alternative languages
The most famous alternative programming language to Python is called Ruby, which is structurally so similar to Python that it is difficult to learn them one after the other; It’s like trying to learn Spanish and Portuguese at the same time.
Another alternative language in the web domain is full-stack JavaScript. Python and JavaScript are not very similar, but they can be used for similar purposes.
Weaknesses of Python
Python is often accused of being “slow” because of its high-level and interpretive nature; Because the interpreter has to do the extra work of translating the bytecode into something machine executable. Simply put, if you can speak to someone in your native language, the conversation will go faster than if you had the help of a translator to translate your language into a language that the other person can understand.
Python is often accused of being “slow”.
Python also takes more time to run than low-level and compiled languages like Java or Rust because it has to be converted into a language that can be understood by the computer. As a result, Python is not often used in cases where execution speed is extremely important, such as building distributed database systems or developing heavy games.
On the other hand, the efficiency of Python in terms of using memory and storage space is less than that of compiled languages; As a result, mobile applications written in Python consume a lot of RAM and battery.
Another weakness of Python is its variety of different versions, which can be confusing for those who are planning to start programming for the first time.
Regarding Python, the concern of scalability is sometimes raised; However, this problem can be solved to some extent with alternative Python implementations such as PyPy.
The Future of Python
From its humble beginnings as a small Christmas project, Python has taken a long and bumpy journey to become one of the most popular programming languages in the world. Many of the key principles that led to the birth of Python, including simplicity and ease of understanding, still hold true for the language and will define its future development path.
Although Python is becoming more and more popular and has virtually taken over the field of data science, there are some challenges in its way. For example, Python’s presence in smartphones, which are more common these days than PCs, or multi-core processors, is minimal.
Python has taken over the field of data science, But its presence in smartphones is weak
The main reason for Python’s popularity is its use in machine learning; But it doesn’t have much to say in the field of mobile or web application development, because it is slow. Python creator Van Rasmus, who now works at Microsoft, admits that Python-based applications consume a lot of RAM and battery. He is improving the performance of Python and believes that it is possible to double the efficiency of Python in the future.
In addition, due to being “sticky”, Python has acquired a wider range of users, and programmers push the boundaries of this language every day with the power of their creativity and innovation. Many people think that Python is only used in the backend, but the capabilities of this language are much more than these words.
In the words of Python’s creator, Guido van Rossum, “Python is a test to determine how much freedom programmers need.” If it exceeds its limit, no one can read another person’s code. If it falls below its limit, the ability to express ideas will be jeopardized.
The wonderful world of ultrasound
How to solve the problem of slow charging of the Android phone?
Why does Everest get higher every year?
The new version of Copilot was unveiled; Microsoft artificial intelligence
Dark matter and ordinary matter can interact without gravity!
Why is the loneliness epidemic so hard to cure?
Google brand story; From a small startup to ruling the web world
How to hide a file or directory in Linux?
How does loneliness affect the brain and body?
Everything we expect from the iPhone 16 unveiling ceremony
-
Technology1 year agoWho has checked our Whatsapp profile viewed my Whatsapp August 2023
-
Technology1 year ago
Second WhatsApp , how to install and download dual WhatsApp August 2023
-
Technology1 year ago
How to use ChatGPT on Android and iOS
-
AI2 years ago
Uber replaces human drivers with robots
-
Technology1 year ago
The best Android tablets 2023, buying guide
-
Technology1 year ago
The best photography cameras 2023, buying guide and price
-
Humans2 years ago
Cell Rover analyzes the inside of cells without destroying them
-
Technology1 year ago
How to prevent automatic download of applications on Samsung phones
