9 principles for implementing artificial intelligence systems

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Maksudasm
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Joined: Thu Jan 02, 2025 6:47 am

9 principles for implementing artificial intelligence systems

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AI needs access to a huge amount of information

For example, Siri or Alice dive into the depths of the Internet to answer a question a person asks them, and systems that recognize a person's handwriting are trained on thousands of examples.

To understand how much information is needed for training, it is important to consider the “10x rule”. This means that the amount of data received by the AI ​​should exceed the parameters the model has by 10 times. Let’s take a simple example. You need to teach the algorithm to distinguish crocodiles from birds based on 100 parameters. So, in order to train it, you need 1000 images.

Computing power

For example, you are fantuan data package teaching artificial intelligence to understand what is shown. So you will need a huge number of images to speed up this process.

How to teach AI algorithms?

It is possible to resort to using deeper neural networks and abandon the simplest algorithms. Thanks to this step, it will be possible to improve the work of AI in recognizing speech or images.

Artificial intelligence must be variable

In order for AI to work well, it must be able to act nonlinearly and adapt to new situations, improving its results over time. But at the same time, if we take driving a car as an example, the driver must retain the ability to control artificial intelligence.

Principles of implementation of artificial intelligence systems

Communication in a familiar language

Everything is simple here, for example, chatbots. They adapt to the speech of the person who addresses them, and provide information in the same language.

Ability to argue your opinion

If an AI makes a claim, it should explain what it is making the choice on and why it makes that decision. This will help to understand the causes and effects of a particular preference.

Data Security and Privacy

As an example, let's look at artificial intelligence that relates to medicine. The data it receives must remain confidential, otherwise medical confidentiality will be violated.

Ethical issues

If artificial intelligence is used to search for candidates for a particular position, it must be impartial to avoid discrimination based on gender, weight, race, and other data.

The ability to integrate AI into other systems.

A good example here would be ordering groceries or something else from an online store. In this case, artificial intelligence can be involved in all stages of purchase/sale.


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