What's AI , Genetic AI and Agentic AI introduction and key use cases - Oracle cloud

Hi All,

 Today we are going to discuss on What is AI, Genetic AI, and Agentic AI , what exact differences between these post that we can relate these topics with Oracle Cloud in our next blog posts.

High-level Diagram for Defrances: 

Firstly, what is AI (Artificial Intelligence)

Artificial Intelligence (AI) refers to the field of computer science focused on creating systems or machines that can perform tasks requiring human-like intelligence, such as learning, reasoning, problem-solving, perception, and language understanding.

 

Key Features of AI:

Learning – Through data (machine learning, deep learning).

Reasoning – Drawing conclusions from input data.

Problem-Solving – Making decisions in complex scenarios.

Perception – Recognizing images, speech, or patterns.

Natural Language Processing (NLP) – Understanding and generating human language.

 

Examples of AI:

Chatbots (like ChatGPT).

Self-driving cars (AI for decision-making and perception).

Recommendation systems (Netflix, Amazon).

Fraud detection systems etc..

 

 

 

 

 

 

 

Okay now, our  Second topic is What is Genetic AI?

Genetic AI is an AI approach inspired by the principles of genetics and natural selection (evolutionary biology). It uses Genetic Algorithms (GA) to find optimized solutions to problems by mimicking processes like mutation, crossover, and selection.

How Genetic AI Works:

Population Initialization – Create a set of random solutions (like chromosomes).

Fitness Evaluation – Evaluate how good each solution is using a fitness function.

Selection – Choose the best solutions to “reproduce”.

Crossover – Combine parts of two solutions to create new offspring.

Mutation – Randomly tweak solutions to introduce diversity.

Iteration – Repeat this process until the best solution emerges.

 

Key Features of Genetic AI:

Works on optimization problems where traditional methods fail.

Does not require gradient-based learning like neural networks.

It’s inspired by Darwin's survival of the fittest principle.

Examples of Genetic AI Use Cases:

Traveling Salesman Problem (finding the shortest route).

Neural Network Optimization (selecting architecture or weights).

Robotics (path planning) & Game strategy evolution.

 

 

The final topic is What is Agentic AI?

Agentic AI is a recent evolution of AI where an AI system acts as an autonomous “agent” capable of planning, decision-making, and taking actions in the real or digital world to achieve specific goals.

Key Characteristics of Agentic AI:

Autonomy – Can work independently without continuous human prompts.

Goal-Oriented Behavior – Plans and executes tasks to meet objectives.

Tool Usage – Can call APIs, use databases, or interact with external systems.

Memory & Reflection – Stores past experiences to improve future decisions.

Multi-step Reasoning – Breaks down complex tasks into subtasks.

Examples of Agentic AI:

AutoGPT, BabyAGI, Devin AI – AI agents that autonomously write and debug code.

Customer Service Bots – Not just answering but performing tasks like booking tickets.

AI Workflow Agents – Automating entire business processes (emailing, report generation).

The Key Differences b/w AI, Genetic AI, and Agentic AI.

AI is the umbrella term for all intelligent systems.

Genetic AI is a subfield of AI focusing on optimization through evolutionary algorithms.

Agentic AI is a new paradigm of AI where systems are autonomous, goal-driven, and capable of taking actions without human intervention.

 

Thank You , that is now .. keep learning 

Thanks,

Srini.