The wisdom of the crowd full intro including group projects
Welcome to "The wisdom of the crowd" a unique "Social Learning" group that functions, in a new way by pooling and evaluating information together, in a very similar way as what is known as a Generating Adversarial Network.
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                                                     Welcome to "The wisdom of the crowd"
 a lot like a machine learning algorithm invented in 2014 called a G.A.N. So our Group will operate similar to a type of Generative Adversarial  Network.     In a Generative Adversarial Network you have a generator and a discriminator.  The generator, generates  data,and  the discriminator evaluates it.      Then the generator uses the information from the discriminator  to try to generate better information, and it becomes a circle of getting better and more information.
First is educating members,  One of the main purposes of the group Is to make an extra wise group and do group projects and social experiments, usually for the purpose of "Social good"
This is a little history of where The wisdom of the crowd name came from. This will give you an idea of what crowd wisdom is.
                                                      Eclectic knowledge Base
This is part of the reason we will give attention to information not otherwise reported or rare, suppressed or otherwise not mainstream. Stretch our boundaries and discriminate our world.
A Crowd will be consistently more accurate that it's smartest member.
                            The way the group operates is unique.
                                           We will build a cool library of Information
The same information from levels 1-5 is used for levels 6-10 So level 6 is the "testing" level for level 1. Level 7 is the "testing" level for level 2, etc.
"Generator and levels
 Levels 1-5 will have only one type of unit. called a (Library) At level 6 there will be 3 types of units. (Library)(Discussion), and (Archive).      In the beginning The initial starting library will go through the same vetting process as all following information.Please note that The starting library does not necessarily  represent my opinion or the opinion any other admin. It is meant to give the group something to start with, in fact i have purposely included information that may be idk "iffy?" just to see how it goes. Also the way the machine algorithm actually starts is with random data and then goes from there, so it's not totally necessary to start with all correct data. The group decides what is good data. so after the group has went through it's process of discriminating the initial library,   then The "Library" unit is for information that the group has discriminated and found valuable.
 after the group has went through it's process of discriminating the initial library,   then The "Library" unit is for information that the group has discriminated and found valuable.      Then after that The "discussion" unit is for new information.  the information will then be discriminated by the group to see if it should be moved to the library.    The "Archive" units will be special units  for particularly valuable information that the group want's to keep extra safe through a future "Group Project" of the same name = "the Archive Project"
At level 7 members can then be a generator for topics of level one, since level 6 has the testing for level 1. So once you learn the initial library for that topic you can generate for it.So when you're level eleven you can be a generator in every topic
A Re-cap on "Levels" There are 11 (Eleven) levels. All group projects are opened up At Level eleven. Level Eleven is a full fledged member with "Generator" access to all topics on every level.
                                                  Generative Adversarial Network
                                            Generative Adversarial Network
In a Generative Adversarial Network you have a generator and a discriminator.  The generator, generates  data,and  the discriminator evaluates it.
Using opinion polls and testing the group  will evaluate and generate more and better and better data in the form of the most preferred and informative lessons.
Generative Adversarial Networks (GANs) are a powerful type of neural network used for unsupervised machine learning. They are incredibly important in the context of modern artificial intelligence. In this video, we take a  look at what GANs are and how they work.
A recap on what we're doin
There will be many Group projects and social experiments done for the purpose of the "Social good"  this is only a few examples.
There is no official "Rule" that says what order members must complete lessons, Members can go in any order or hop around going through the polls and quizzes but can only "Generate" new lessons for topics they have passed the testing for. Each topic or unit will have it's own specific point total to reach to pass that topic or unit. (depending on how many lessons are in the unit or topic) As a rule of thumb i go with 65 % is a D- Each level will also have a specific point total needed to pass to the next level. Again rule of thumb is 65 % is a D- passing grade. So members don't have to complete every post in a unit to pass the unit and don't have to pass every unit in a level to pass a level. Members will have a total point count though so if they want they can complete 100 % of the posts in the unit's and 100 % of the unit's in each level for the max point count.
members will influence what kinds of lessons there are.
When doing group projects and Brainstorming, Diversity thought and creativity are welcomed.  
When people talk to each other, together they can make smarter decisions than they can on their own.
We want to find ways to gather the data that avoids the "Groupthink" negative effects while taking advantage of the positive effects of a social network.
Where would you like to go from here?    If you don't know what a FB social learning group is then  i highly recommend that tutorial next. And be sure to look at the group projects intro, it will briefly explain how group projects will be managed. *
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