[ad_1]
<div _ngcontent-c14 = "" innerhtml = "
© 2018 Bloomberg Finance LP
Facebook is celebrating its 15th birthday today, having announced last week & nbsp;a record profit and revenue growth of 30%. In addition, today, "you will not be able to create new Google+ profiles, pages, communities or events ", in anticipation of the complete closure in April of Google's social network, his bet the company against Facebook.
Both Google and Facebook have proven that many commercial mantras are false, including the principle of "first-time benefits". In business, timing is paramount. There is no benefit of first-come, just as there is no state-of-the-art advantage (and there are no "commercial laws" no matter what you hear from countless books, articles and conferences).
When Google was launched on September 4, 1998, it had to compete with a handful of other search engines. Google has defeated them all because instead of organizing "information of the world" (according to the terms of his declared mission), he opted for an automated self-organization. Google has developed its "search" activity (formerly "search for information") by closely tracking referrals (for example, links between web pages) and correlating relevancy with the number of referrals (popularity , etc.). pages depending on the number of pages linked to them). In contrast, Yahoo, the dominant actor at the time, followed the traditional pattern of libraries by attempting to create a catalog of maps (ontologies) of all information available on the Web. Automated clbadification (Google) has been won.
Similarly, Facebook was not the first social network. The beginnings of the Web saw SixDegrees.com and LiveJournal and, in 2002, Friendster reached 3 million users in just a few months. MySpace launched in 2003 and 2 years later reached 25 million users. These early comers have conditioned consumers on the idea (and possible benefits) of social networking and helped to encourage increased investment in broadband connections. They also provided Facebook with a long list of technical and business errors to avoid.
There was also a vivid example of a company born on the Web, Google, that Facebook could imitate. Like Google, it has employed smart engineers to build a smart and scalable infrastructure and, like Google, has put in place a powerful and sustainable business model by reinventing advertisement. However, Facebook has gone much further than its model by responding to growing competition by buying competitors or copying them successfully.
When the targeted social networks, Instagram and WhatsApp, took on importance, Facebook acquired them and Twitter, Facebook, has pivoted to become a full-fledged media company with the launch in 2006 of News Feed. Probably more than anything else, this competitive initiative has made Facebook the current social networking giant, serving 2.32 billion monthly active users.
This has also led Google to launch Google+, its most spectacular failure so far. The main culprit was the deceptive concept of "social signal". Driven by the rise of Facebook (and Twitter), it was generally accepted that the data collected by Google was at the origin of the success of its search engine. lacked the "social" dimension of research and information discovery. Internet users (as well as Facebook and Twitter) were increasingly relying on obtaining relevant information from members of their social networks, which reduced their use of Google Search.
When Larry Page took the position of Google's CEO in 2011, adding a "social signal" to his search engine and attempting to beat Facebook to his own game have become his main mission. During his first week as CEO in April 2011, Mr. Page had sent a memo linking 25% of each employee's bonus to Google's social success. Google presented its response to Facebook's "I Like" button, to Google's "+1" recommendations, which, according to Danny Sullivan, the most astute observer of Google at the timecould "become an important new signal to be used by Google as part of its global ranking algorithm, at a time when it desperately needs new signals."
The complete competitive response to Facebook, Google+, was launched in June 2011, as "one of the most ambitious bets in the history of the company" and a "response to the disruption of the Web 2.0 and the emergence of the social Web, "according to Eric Schmidt and Jonathan Rosenberg in How Google works (2014). But in January 2012, ComScore estimated that users spent an average of 3.3 minutes on the site, compared to 7.5 hours on Facebook. And everything was downhill from there. Why?
Part of the problem lies in the fact that Google has strived to show the world that it's not just about copying Facebook, but improving it. Facebook's simple approach to creating a social network was perceived as too simple because it was referred to as "friends" (and the rest) of everyone in your network, from your grandmother to someone you have never met and worked with you in a limited time. project related to work. Google's smart answer has been "circles", allowing you to clbadify "friends" into specific and meaningful subnets. Of course, this went against Google's hunch that the clbadification of users (or librarians) was not working on the Web because it was not "scalable". Thus, a correction that seemed necessary for Facebook has finally failed. Well trained by Google to expect and benefit from automated clbadification, users did not want to play librarians.
Most importantly, I suppose that even the relatively small number of active participants in Google+ (90 million at the end of 2011) was enough for Google to find out quite quickly that the belief that "Using social cues gives Google a new, valuable signal, closely linked to the known individuals and accounts it could use."Was just a mirage. "Social cues" did not improve search results. In addition, 2012 was marked by the Deep Learning revolution (what we now call "the AI"), which changed everything at Google, especially as regards the design of its search algorithm.
A sophisticated statistical clbadification – finding the hidden correlations in huge amounts of data and using them to place seemingly unrelated entities in common compartments – was the basis of Google's initial success. In 2012, a specific approach to this type of statistical badysis dealing with huge amounts of data, called "machine learning", "deep learning" and "artificial intelligence" (AI), sprung from documents and obscure speakers and has become the buzzword of the day.
Two major milestones marked the emergence of what I prefer to call "steroid statistics": in June 2012, Jeff Dean of Google and Andrew Ng of Stanford reported an experiment in which they showed a neural network of deep learning 10 million unlabeled images taken randomly from YouTube videos, and 'to our amusement, one of our artificial neurons has learned to react strongly to images of … cats. "And in October of the same year, a network of deep learning neurons achieved an error rate of only 16% ImageNet Large Scale Visual Recognition Challenge, a significant improvement over the error rate of 25% obtained by the best entry of the previous year. "AI" was gone for the races.
The impact of statistics on the steroid revolution was such that even Google's holiest cow, its search algorithm, had to incorporate, after some resistance, the new, automated, scalable, non-addictive AI signal. user, to statistically badyze the much larger data stack that Google now collects. "RankBrain moved in, & nbsp; an artificial machine learning intelligence used by Google to process a "very large fraction" of search results a day, "observed Danny Sullivan in October 2015.
AI killed Google+.
Good for Google. Analysts expect the parent of Google Alphabet to declare income today after the market close of $ 11.08 per share and an adjusted business figure of $ 31.3 billion. These results would represent growth rates from one year to the other of 14% and 21%, respectively.
">
© 2018 Bloomberg Finance LP
Facebook is 15 today, after announcing last week a record profit and 30% growth in revenue. In addition, today, "you will not be able to create new profiles, pages, communities or Google+ events", in anticipation of the complete closure in April of the social network of Google, his bet of the company against Facebook.
Both Google and Facebook have proven that many commercial mantras are false, including the principle of "first-time benefits". In business, timing is paramount. There is no benefit of first-come, just as there is no state-of-the-art advantage (and there are no "commercial laws" no matter what you hear from countless books, articles and conferences).
When Google was launched on September 4, 1998, it had to compete with a handful of other search engines. Google has defeated them all because instead of organizing "information of the world" (according to the terms of his declared mission), he opted for an automated self-organization. Google has developed its "search" activity (formerly "search for information") by closely tracking referrals (for example, links between web pages) and correlating relevancy with the number of referrals (popularity , etc.). pages depending on the number of pages linked to them). In contrast, Yahoo, the dominant actor at the time, followed the traditional pattern of libraries by attempting to create a catalog of maps (ontologies) of all information available on the Web. Automated clbadification (Google) has been won.
Similarly, Facebook was not the first social network. The beginnings of the Web saw SixDegrees.com and LiveJournal and, in 2002, Friendster reached 3 million users in just a few months. MySpace launched in 2003 and 2 years later reached 25 million users. These early comers have conditioned consumers on the idea (and possible benefits) of social networking and helped to encourage increased investment in broadband connections. They also provided Facebook with a long list of technical and business errors to avoid.
There was also a vivid example of a company born on the Web, Google, that Facebook could imitate. Like Google, it has employed smart engineers to build a smart and scalable infrastructure and, like Google, has put in place a powerful and sustainable business model by reinventing advertisement. However, Facebook has gone much further than its model by responding to growing competition by buying competitors or copying them successfully.
When the targeted social networks, Instagram and WhatsApp, took on importance, Facebook acquired them and Twitter, Facebook, has pivoted to become a full-fledged media company with the launch in 2006 of News Feed. Probably more than anything else, this competitive initiative has made Facebook the current social networking giant, serving 2.32 billion monthly active users.
This has also led Google to launch Google+, its most spectacular failure so far. The main culprit was the deceptive concept of "social signal". Driven by the rise of Facebook (and Twitter), it was generally accepted that the data collected by Google was at the origin of the success of its search engine. lacked the "social" dimension of research and information discovery. Internet users (as well as Facebook and Twitter) were increasingly relying on obtaining relevant information from members of their social networks, which reduced their use of Google Search.
When Larry Page took the position of Google's CEO in 2011, adding a "social signal" to his search engine and attempting to beat Facebook to his own game have become his main mission. During his first week as CEO in April 2011, Mr. Page had sent a memo linking 25% of each employee's bonus to Google's social success. Google presented its response to Facebook's "I Like" button, Google's "+1" recommendations, which, according to Danny Sullivan, Google's most astute observer at the time, could "To become an important new signal to be used by Google as part of its global ranking algorithm, at a time when it desperately needs new signals. "
The complete competitive response to Facebook, Google+, was launched in June 2011, as "one of the most ambitious bets in the history of the company" and a "response to the disruption of the Web 2.0 and the emergence of the social Web, "according to Eric Schmidt and Jonathan Rosenberg in How Google works (2014). But in January 2012, ComScore estimated that users spent an average of 3.3 minutes on the site, compared to 7.5 hours on Facebook. And everything was downhill from there. Why?
Part of the problem lies in the fact that Google has strived to show the world that it's not just about copying Facebook, but improving it. Facebook's simple approach to creating a social network was perceived as too simple because it was referred to as "friends" (and the rest) of everyone in your network, from your grandmother to someone you have never met and worked with you in a limited time. project related to work. Google's smart answer has been "circles", allowing you to clbadify "friends" into specific and meaningful subnets. Of course, this went against Google's hunch that the clbadification of users (or librarians) was not working on the Web because it was not "scalable". Thus, a correction that seemed necessary for Facebook has finally failed. Well trained by Google to expect and benefit from automated clbadification, users did not want to play librarians.
More importantly, I suppose even the relatively small number of active Google+ participants (90 million at the end of 2011) was enough for Google to quickly discover that the belief that "using social cues gives Google a new valuable signal linked with individuals and known accounts that he could use "was simply a mirage. "Social cues" did not improve search results. In addition, 2012 was marked by the Deep Learning revolution (what we now call "the AI"), which changed everything at Google, especially as regards the design of its search algorithm.
A sophisticated statistical clbadification – finding the hidden correlations in huge amounts of data and using them to place seemingly unrelated entities in common compartments – was the basis of Google's initial success. In 2012, a specific approach to this type of statistical badysis dealing with huge amounts of data, called "machine learning", "deep learning" and "artificial intelligence" (AI), sprung from documents and obscure speakers and has become the buzzword of the day.
Two major milestones marked the emergence of what I prefer to call "steroid statistics": in June 2012, Jeff Dean of Google and Andrew Ng of Stanford presented an experiment in which they showed a network of neurons learning deep, 10 million unlabeled images taken randomly from YouTube videos. and "to our greatest amusement, one of our artificial neurons has learned to react strongly to images of … cats." And in October of the same year, a network of deep learning neurons was only reaching out. An error rate of 16% in ImageNet Large. Scale Visual recognition challenge, a significant improvement over the error rate of 25% achieved by the best entry of the previous year. "AI" was gone for the races.
The impact of statistics on the steroid revolution was such that even Google's holiest cow, its search algorithm, had to incorporate, after some resistance, the new, automated, scalable, non-addictive AI signal. user, to statistically badyze the much larger data stack that Google now collects. "RankBrain has moved in, a machine-learning AI used by Google to process a" very large fraction "of search results per day," observed Danny Sullivan in October 2015.
AI killed Google+.
Good for Google. Analysts expect Alphabet, the parent company of Google, to announce earnings today after closing the market at $ 11.08 per share and an adjusted business figure of $ 31.3 billion USD. These results would represent growth rates from one year to the other of 14% and 21%, respectively.
