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AI explained

Artificial Intelligence, or AI, has been a buzzword in technology for decades, but what does it really mean? AI refers to the development of computer systems that can perform tasks that would normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

The development of AI has been driven by advancements in computer hardware, algorithms, and data processing. In the past, computers were only able to perform tasks that they were programmed to do, but with AI, computers are able to learn from data and improve their performance over time.

There are several different types of AI, including rule-based systems, machine learning, and deep learning. Rule-based systems are the most basic type of AI and involve a set of rules that a computer follows to make decisions. Machine learning, on the other hand, involves training a computer on a dataset so that it can make predictions or decisions based on that data. Deep learning is a more advanced form of machine learning that involves the use of artificial neural networks.

AI has a wide range of applications, from self-driving cars and virtual assistants to fraud detection and healthcare. In healthcare, AI can be used to analyze patient data and identify patterns that can help doctors make more accurate diagnoses and treatment plans. In finance, AI can be used to detect fraudulent transactions and prevent financial crimes.

Despite its potential benefits, AI also raises concerns about job displacement, bias, and privacy. As AI becomes more advanced, there is a risk that it could replace human workers in certain industries. Additionally, there is a concern that AI algorithms could perpetuate biases that exist in society. Finally, there are concerns about the privacy of individuals’ data that is collected and used by AI systems.

In conclusion, AI has the potential to revolutionize many industries and improve our lives in countless ways. However, it is important to address the potential risks associated with AI and ensure that it is developed and used in a responsible and ethical manner.

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HTTP Concepts PHP Software Architect Softwares Technology

MVC vs MVVM vs MVP… What the heck?

When it comes to the architecture design patterns, we have many options to choose from Model-View-Controller (MVC), Model-View-ViewModel (MVVM), Model-View-Presenter (MVP), and keep going… Most often what I hear from the software engineers are :

  • What is MVVM?
  • What is the difference between MVC, MVVM and MVP?
  • How to choose between MVC and MVVM?

Although the answers are simple but to understand the concept in depth and clearly, like always, I would prefer to take a real use case as an example. Let’s think about a music search application, musicoverflow (derived from stackoverflow; hmm a long time programmer).

Fundamentally, MV(X)

Before we dive in the various variants of it, lets understand what MV(X) is? Fundamentally, all these variants, MVC, MVVM, MVP aims to segregate the duties of processing, visualization, we need to understand briefly MVC, MVP, and MVVM architecture before dive into them.

Why Model-View-(C or P or VM)?
The aim of these architectures is to separate the responsibilities of visualizing, processing, and data management for UI applications.

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