Pure AI (General AI) and Pragmatic AI

What is the difference?

Pure AI, also known as General AI, refers to the idea of creating AI systems that are capable of performing any intellectual task that a human can perform. The goal of Pure AI is to create AI systems that are general-purpose and can solve a wide range of problems, from playing chess to driving a car. This approach to AI is often motivated by a desire to create AI systems that are as intelligent as humans and can perform a wide range of tasks. Pure or General AI tries to mimic everything a human does.

On the other hand, Pragmatic AI refers to a practical and effective approach to solving real-world problems using AI. Rather than trying to create general-purpose AI systems, Pragmatic AI focuses on developing AI systems that are specifically designed to solve specific problems in the most efficient and effective way possible. This approach to AI is driven by the desire to use AI to solve problems in the real world and to make AI easier for more organizations and people to use and understand.

We already use Pragmatic AI in real life from a consumer viewpoint. Some examples include:

1. Turn by turn directions

2. Filtering spam folders

3. Recommend the next movie for you to watch

4. Recommend the related product to buy

Let’s further extend the examples of pragmatic AI in action focused on different industries.

1. Healthcare: A healthcare organization wants to use AI to predict which patients are at risk of developing a specific disease. Rather than trying to develop a general-purpose AI system that can predict all diseases, they use a Pragmatic AI approach and focus on developing an AI system that is specifically designed to predict this specific disease.

2. Finance: A financial institution wants to use AI to detect fraud in real-time. Rather than trying to develop a general-purpose AI system that can detect all types of fraud, they use a Pragmatic AI approach and focus on developing an AI system that is specifically designed to detect the types of fraud that are most prevalent in their organization.

3. Transportation: A transportation company wants to use AI to optimize its logistics and delivery routes. Rather than trying to develop a general-purpose AI system that can optimize all types of transportation routes, they use a Pragmatic AI approach and focus on developing an AI system that is specifically designed to optimize the delivery routes for their specific needs.

These examples show how Pragmatic AI can be used to solve real-world problems in the most practical and effective way possible. By focusing on solving specific problems, Pragmatic AI systems can be designed and implemented more quickly and easily, and they are more likely to produce accurate and reliable results. Additionally, Pragmatic AI systems can be more easily integrated into existing workflows and processes, making them more practical and useful to a wider range of organizations and individuals.

In conclusion, Pragmatic AI is a practical and effective approach to using AI to solve real-world problems. By focusing on solving specific problems in the most efficient and effective way possible, Pragmatic AI has the potential to revolutionize the way we live and work.