Creating your own artificial intelligence , whether to use it in your business or to make it available to your customers. Represents an interesting development opportunity. Today, many digital tools allow you to create an AI without using a programming language. However, it is necessary to follow a few steps in order to design. An artificial intelligence that is both technically stable and geared towards the objectives of its users.
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The guide to speeding up content creation with AI

 

Create your own artificial intelligence
What does it mean to create your own artificial intelligence?
Creating your own artificial intelligence means reproducing the schematization of an artificial neural network to develop a program capable of communicating with humans. More precisely, designing your own.  AI does not mean creating a new south african whatsapp numbers programming language, but relying on an existing language to create an application in a particular domain or for a specific use.

What is the basis of artificial intelligence?
The foundation of any artificial intelligence system is the reproduction of an artificial neural network, within which algorithms are executed. These algorithms execute formulas whose role is to transform incoming data (transmitted by the human user) into outgoing data.

As it trains to communicate with human users or other artificial intelligences, AI strengthens its algorithms. These algorithms are then able to associate increasingly complex data together.

 

Can you create artificial intelligence without knowing how to code?

To design artificial intelligence, you don’t need to know how to code. Whatever the purpose of AI design (visual recognition, speech recognition or automated content creation ), you can use “  no-code  ” tools to develop your own program. Here are a few:

 

These programs or platforms allow you to develop an.  AI without having to write a single line of code. They usually have intuitive visual interfaces, based on the “  drag and drop  ” system to add, delete or modify.  The location of formulas and commands. Also, these tools can be used only in the test phase to evaluate the operation of an artificial intelligence model that has been coded.

 

What are the stages of an artificial intelligence project?

Define the project objectives
f the need in order to find the AI ​​model best able to meet it. To do this, it is necessary to consider both the data already available to the company.  And the type of information that it seeks to obtain through the use of AI.

 

Choosing the right AI model
To find the AI ​​model best suited to the Sad Life Box objectives set in the previous step, you must start by taking into account. The nature of the project as well as the need, specified during the first step.

Indeed, unless you create your own AI using coding skills, it is more common to use a pre-established AI model. These different models fulfill various objectives, in several sectors of activity.

 

 

In summary, the right AI model depends directly on the nature of the design project (the problem to be

 

Design the dataset
As explained above, AIs operate a data set, between incoming and outgoing information. The goal of this third step is to anticipate as many data sets as possible, i.e. to think of all the possible combinations between the data that the AI ​​will have to recognize and/or associate.

To do this, the operator in charge of AI training must gather a large amount of incoming data (usually several thousand, or even hundreds of thousands). Among these data, part will be used for the training phase (learning) of the AI, while another part will be used to test the AI.

 

Learning AI
An artificial intelligence becomes more efficient as it learns. This learning necessarily involves the transmission of a large amount of incoming data. After designing the dataset to be used, it is necessary to orient the learning towards what the AI ​​will be used for. Consequently, from this same dataset, the user shows the AI ​​where it should look for information and how it should transcribe it to adapt to human communication.

 

Let the program train
After learning comes a training phase that is distinct from the previous one. Indeed, after having “shown” the AI ​​what type of information it should look for and where it can find it, it is necessary to give the algorithms time to train themselves to calculate.

Unlike the previous phase in which it is the human operator who shows the AI ​​how to act, this training step is managed by the machine alone. However, it requires considerable computing power. To meet this requirement, it is necessary to at least give time.  To the artificial intelligence and, at best, outsource the AI ​​training to a specific Cloud so as not to interfere with the data of other programs nearby.

 

Perform tests
The testing phase comes after the learning and training phases since it consists of evaluating the relevance of the AI’s work in a real environment, after having accustomed it to the incoming data with

 

 

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