video streaming
example
This is a newly created methodology where not yet
there are “known” usage examples. That is why we
decided to simulate a case in which everyone can
recognize the product where Artificial Intelligence is
implemented.
So we chose a video streaming platform, as a very
popular product that we all more or less know
and have used.
Historical context of video streaming platforms.
The world’s most famous video platform is Netflix, which was founded in 1997 as a regular mail order DVD movie rental and sales company. A year after its founding, it decides to focus solely on rent.
In 2007 Netflix decided to enter the streaming business. Today, it still offers BlueRay rental by regular mail in the USA.
Therefore, this sector has evolved from its analog origins. What they are today is the result of a market evolution thanks to a technological evolution.
Let’s imagine that one of these companies decides to do the aibizfy methodology and brings together 10 professionals from companies from different areas to decide what AI they can carry out in their business.
One example of card
In the first part of the dynamic, they have to go through the cards, once you find one that seems something similar is happening in their company, they are reserved for treatment.
Card processing:
For each card that we put aside because it had something similar to what we do, we have to build the phrase equivalent to our business and we must name the possible AI.
In your business
(Video streaming company)
It depends on how we make the thumbnail of the film, it will have a better or worse acceptance, depending on each type of person.
Name of AI
thumbnail customizer
After looking at the 45 cards
After looking at the 45 cards, we have chosen 4 and have given names to the possible AIs. So we have filled the board like this:
Now we have to decide the priority of each AI idea
The first thing we must decide is: our chart is close to a current company value, near or far, and based on that, we do a preliminary analysis of whether we are more or less prepared.
Current need
(The discovered AIs fit perfectly into the company’s values and needs.)
There are two levels:
- We have all the data to do the AI
- We lack data and information
Future need
(The AIs do not conform to the values and needs of the company but are close.)
There are two levels:
- We have all the data to do the AI
- We lack data and information
Maybe later
(The discovered AIs do not conform to the values and needs of the company).
We already know the order of the AIs that we will analyze.
- thumbnail customizer
- film news matching
- customer behavior predictor
- emotional changer