Traditional AI vs Generative AI(GenAI)
Traditional AI sometimes referred as "Narrow AI" or "Weak AI" . It only works with structured data like logs and system metrics. It uses events and patterns from the existing data to make decisions and predict new data. For example used in weather forecasting or playing chess with a computer.
Characteristics of traditional AI
Rule-bound: It strictly follows a predefined rulebook written by human programmers.
Single-tasked: It is designed to master only one specific job and cannot adapt to others.
Predictive: It analyzes provided data to find patterns and make predictions.
Dependent: It can only learn from the exact data fed to it by its human creators.
Use cases of traditional AI
Email Spam filters: Analyzes incoming messages against predefined rules to predict whether an email is junk or genuine(Checking specific keywords or suspicious links)
Recommendation Systems: Systems that analyze user behavior and suggest products or shows like Netflix, Spotify or Amazon.
Virtual Assistants: Programs like Siri or Alexa use algorithms to understand and respond to basic queries like setting an alarm clock, checking weather, etc.
Generative AI, on the other hand, can work with both structured and unstructured data, such as logs, documents, emails and chat conversations. These models are trained to understands context and generate explanations, summaries, and create new content like images, videos or text, based on prompts.
Characteristics of Generative AI
Prompt-driven: Generating and producing new content like images, videos, text, code, etc,.
Creative: Adaptability to produce different types of content rather than just sorting or analyzing existing data.
Brain-like: Uses neural networks to generate relevant and original output.
Use cases of Generative AI
Chatbots and virtual assistants: Provide human-like conversational experiences, answer complex questions and brainstorm ideas.
Code Generation: Helps generate code and debugging, and suggestions to improve or fix code based on plain-English instructions.
Personalized recommendations: Craft tailored suggestions based on prompts, user preferences, and interaction history.
Simple Difference between Traditional AI and Generative AI:
Traditional AI
Uses ML algorithms like Decision Trees, SVM
Predicts or classifies
Works mainly on structured data
Generative AI
Uses Deep Learning like Transformers
Generates new content
Works on images, text, videos, etc.
