Trillions of questions, no easy answers

trillions of questions no easy answers

Trillions of questions, no easy answers

This text presents some highlights from the Google home movie published on YouTube on October the 16th, 2020 with the same name of this text title: “Trillions of questions, no easy answers”

You can watch the Google home movie in the following YouTube link:

https://www.youtube.com/watch?v=tFq6Q_muwG0

There is interesting information in this home movie for digital marketing and SEO professionals. This home movie can also be interesting to people that have curiosity in how the Google search algorithm works.

Following the highlights:

Google mission is to organize the world’s information and make it universally accessible and useful.

Google crawls, storages, indexes and ranks all the world wide web information permanently. This information is storaged in several big data centers all over the world.

Google search is a never ending project. It has been, it is, and it will always be a long and never ending journey.

40% of European websites launched during 2019 were spam.

15% of daily queries are new for Google.

Google makes an average of 6 daily changes to the search algorithm. These 6 daily changes are the result of near 200 search projects. The ratio of projects launched versus projects executed is 6/200 or only 3% of all the search projects are launched.

Each search project goes through the following phases: idea creation, team building, experiment, measurement, data analysis, prove, launch committee presentation and reject or launch status.

Search projects are presented to the launch committee by a third party analyst, and never by the project team member.

There are thousands of independents search quality content evaluators or raters that are permanently using the search algorithm to rate content quality all over the world. These evaluators use the Google Search Quality Raters Guidelines to classified the content as high, medium or low quality.

Quality content is a very important variable in the search results. However, other variables are also important, such as freshness, relevance and performance.

Author EAT is also measured by the independent evaluators. Author expertise, authority and trust are important for the quality of the content.

The launch committee recently approved the DeepRank project, which is one of the most important machine learning and artificial intelligence search projects launched by Google. This project will help the algorithm to understand text.

The following Google engineers and scientists participated in the home movie:

Ben Gomes, Jeff Dean, Urs Holzle, Pandu Nayak, Cathy Edwards, Nick Fox, Tulsee Doshi, David “Bez” Besbris, Eric Lehman, Fede Lebron, Meg Aycinena Lippon, Reese Pecot, Geoffrey Hinton, Elizabeth Tucker, Jingcao Hu, Sundeep Tirumalareddy.

 

 

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