RISE OF THE CATFLUENCERS 2.0!
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As a follow-up to our much appreciated previous post ‘: The raging debate was to establish wether it was catfluencers that were influencing Algortithms, or Algorithms, that were influencing catfluencers ?
THE CAT METAVERSE ?
We went deeper into our exploration, having roamed around the #CATFLUENCE website and many other reputable digital sources…. establishing that the study of cats on ‘mainstream’ MASS-Social Media Platforms, like Facebook, Twitter, etc…
#NEWSBREAK: This is SO INdERNET, this is OOoooh SooOO META ! :))-
… According to Vinish Katuria, from SenseAI, a Venture Co-Creation for AI startups:
Artificial intelligence (AI) is an area of computer science that is aiming for the creation of intelligent machines that work and react like human.
Machine learning (ML) is an approach to achieve Artificial Intelligence. The Machine Learning approach provides computers with the ability to learn without being explicitly programmed.
Deep learning (DL) is a technique for implementing Machine Learning. Deep Learning is the application of artificial neural networks to learning tasks that contain more than one hidden layer.
Artificial neural networks are computing systems inspired by the biological neural networks that constitute animal brains.
We came up with the graph above, showing you how to get a bit deeper, with another ‘CATFLUENCERS EXPERIMENT’ that took place on #Youtube in 2012… With the #Youtube Algorithm needing to watch 10 000 cat pictures in order to formely identify and recognize a cat on a picture.
THE POINT of the experiment was to understand the co-relation between Deep learning, Deep Learning, AI, ML and also, how Artificial Neural Networks ultuimately work.
I. WHO GOOGLED THE CATS ?
#VK: “ One of the most famous Deep Learning example is via recognition of a “Cat” through analysis of 10 millions You Tube videos, exhibited in 2012 at Google. “
To learn to recognize pictures of cats, a Deep Learning model will determine the features that make-up a cat, such as ears or whiskers, by looking at many sample pictures fed to the Deep Learning model.
In a supervised Deep Learning model, as seen in our previous article, the model would be provided labelled pictures of both cats and non-cats, explicitly telling the model what is and is not a cat.
The system then determines which features are needed to build its cat model and can then recognize pictures of cats in the wild. “ (VK.)
CATS have therefore already been used in order to better optimize or better understand algoirthms behaviours… and moreover, the correlation between our attraction for them on social media and the potential existence of what could be looked as VIRTUAL OXYTOCINE, released then, by our… ‘virtual brains’ ?
Maybe we are ‘reaching’ a bit, as some would say…but what about…
II. FACEBOOK/WHATSAPP/ INSTAGRAM?
Another example could be how the Facebook/Whatsapp/InstagraM algorithm choose what we see on our news feed at the crucial time of the….
… “POP”: - The moment when a mobile app, spring to ‘life’, onto your smartphone (or pocket PC) screen. The first piece of news at the top of your newsfeed is the “POP”
- The “Facebook Mobile User Experience” can be defined by its first 3to 4 seconds, when the user decides or not to carry on scrolling down the smartphone’s screen, to check on the second, third and fourth post on the newsfeed !
IPCTR will then come into play…HERE’s HOW:
Interest - Type and the POST itself will definitely influence the repetition in the appearance (Or impressions) of cats in our newsfeed, but …. should it dicate the intensity of our engagement with the content ?
That’s the ultimate question, as the $AGA rumbles on and continues on our future posts!
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We are looking for our future independent partners.
Airbnb subsidiaries offer a complete concierge service for those who do not have the time to create or take care of their listing on Airbnb. The well-being of owners and travelers is at the heart of our priorities.
Joining the world of subsidiaries means joining a passionate team determined to make the world a place where everyone can feel at home. It also means joining a dynamic network of independent partners and being an integral part of the Airbnb family.
As a Country Manager, your goals are:
Offer authentic and quality stays to Airbnb travelers in the accommodation that you have managed to manage, ensuring impeccable cleanliness as well as a punctual and warm welcome.
Support the growth of the stock of properties managed by the subsidiaries in your region in order to offer a wider choice to travelers.
The Country Manager is above all an entrepreneur. Benefiting from the status of self-employed worker, he / she is the operational manager of his region or continent and himself manages his network of partners and his teams. Its main missions include:
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The ideal partner has a real entrepreneurial spirit. Very autonomous, the Country Manager has a real sense of responsibility. He / she will not hesitate to go out into the field to meet the hosts, travelers and his teams. Punctual, courteous, written and spoken, he / she has a sense of service and customer relations.
The essential skills of the Country manager are:
A strong sense of organization
Comfortable with numbers, an excellent understanding of a business plan and solid knowledge of financial management (income statements)
A strong ability to convince
Comfortable with internet tools
Fluency in English essential
Invite your contacts to register to become a host on Airbnb and start generating income, Here is my invitation link:
THAT’S ALL FOLKS ! :))-
#TEAMADMP