AI this, AI that. All we read about these days is the capabilities of AI, the new tools emerging by the day, the startups that are booming in revenue, and the OpenAI vs. Google battle. 

Stopping for a second there, most people will realize they are getting fed information about a concept that they don’t really understand.

What is Artificial Intelligence?

AI, or artificial intelligence, refers to the simulation of human intelligence processes by machines, especially computer systems. 

AI includes a broad range of technologies and applications that enable machines to perform tasks that would typically require human intelligence. 

Artificial intelligence Broken Down:

• Artificial Narrow Intelligence (ANI): AI systems that are designed and trained for a specific task or a narrow range of tasks. This field of AI is considered weak AI for its lack of capabilities in adapting to new situations.

• Applications: image recognition algorithms, language translation tools, chatbots, recommendation systems, facial recognition. 
• Examples: Siri, Alexa, Google Assistant

• Artificial General Intelligence (AGI): Also known as ‘Strong AI’, are systems that possess human-level intelligence and cognitive abilities across a broad range of tasks and domains. 

• Applications: solve complex problems, serve as companions, designing innovative products, experimentation in scientific research, etc.
• Examples: there is a lack of examples as it remains a hypothetical concept.

• Artificial Super Intelligence (ASI): Also known as ‘Strong AI’, are systems that surpass human intelligence in virtually every aspect. ASI represents the theoretical endpoint of AI development, where machines possess cognitive abilities far superior to those of humans.

• Applications: deriving insights that surpass human capabilities, optimizing complex systems, innovating new technologies.
• Examples: there is a lack of examples as it remains a hypothetical concept.

• Machine Learning: involves the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data without being explicitly programmed.

• Applications: image recognition, Natural Language Processing (NLP), recommendation systems.
• Examples: Google translate, e-commerce platforms suggesting products, predicting stock prices. 

• Deep Learning: a subset of machine learning that utilizes neural networks with multiple layers to learn representations of data with multiple levels of abstraction. 

• Applications: image and speech recognition.
• Examples: Google Speech-to-Text, Face Recognition Systems, GPT, Netflix Recommendation System.

• Natural Language Processing (NLP): focuses on enabling computers to understand, interpret, and generate human language in a way that is both meaningful and valuable. 

• Applications: language translation, sentiment analysis, and chatbot development.
• Examples: ChatGPT, Gemini, Microsoft Translator

• Computer Vision: involves the development of algorithms and techniques that enable computers to interpret and understand visual information from digital images or videos. 

• Applications: facial recognition, biometric authentication, object detection, and autonomous vehicles.
• Examples: FaceNet, Adobe Acrobat, Google’s MediaPipe, Google Images.

• Robotics: involves creating intelligent machines capable of performing tasks that typically require human-like dexterity, perception, and decision-making. 

• Applications: utilized in manufacturing, healthcare, and logistics. 
• Examples: ROS (Robot Operating System), Gazebo, Arduino and Raspberry Pi.

• Expert Systems: Expert systems are AI-based computer programs that mimic the decision-making ability of a human expert in a particular domain. They utilize knowledge representation and reasoning techniques to solve complex problems and provide solutions or recommendations.

• Applications: Decision Support Systems, Diagnostic Systems, Knowledge-Based Systems
• Examples: CLIPS, IBM Watson Assistant

• Autonomous Systems: Autonomous systems are AI-driven systems capable of performing tasks and making decisions without direct human intervention. 
• Applications: Autonomous vehicles, drones, and smart home devices.
• Examples: OpenAI Gym, PX4 Autopilot

AI is an ocean of trials, as mentioned there are domains that are still theoretical and far from achievement. All the categories mentioned above fall under the Artificial Narrow Intelligence (ANI), which is the ‘weak AI’. The strong AI, which is the human intelligence capabilities, is yet to be achieved. 

Published on: April 25, 2024