Artificial intelligence is no longer just a theory. Different types of AI-based solutions are driving innovation and revolutionizing industries.
AI can be categorized based on its capabilities and functionality. Some key examples include narrow AI, general AI, reactive machines, and limited-time machines.
AI software is embedded in countless technologies, like search engines, social media, and facial recognition. Learning about the different types of artificial intelligence is key to understanding its potential.
Distinguishing AI based on its capabilities means focusing on its intelligence level. This classification examines how well AI can learn, reason, adapt, and apply knowledge to new situations.
ANI performs a specific or “narrow” task with extreme precision. It’s designed to function within a preset and limited range of contexts. Most current AI systems fall under this category.
Use cases: Image recognition, virtual assistants, spam filters, recommendation algorithms, etc.
AGI is a hypothetical concept of machines that can exhibit human-like intelligence when performing various tasks. While this technology doesn’t exist yet, developments in narrow AI systems show promise for its future.
Possible use cases: Advanced AI chatbots, creative problem solving, physical interactions with the surroundings.
ASI will surpass human intelligence in all aspects of creativity, wisdom, and problem-solving. This advanced technology is yet to be developed but can potentially change the face of medicine, materials science, and even space exploration.
Possible use cases: Rapid learning, discovery, adaptation, and creativity in multiple fields.
AI can also be distinguished based on how it processes information and responds to an environment. This classification is focused on how each type follows a specific method to complete tasks rather than its overall capability.
This is the simplest type of AI. It is task-specific and only reacts to its environment based on predetermined rules. Reactive machines have no memory of past interactions and operate solely on the current input. This means an input will consistently deliver the same output.
Use cases: Thermostats, traffic lights, vending machines, keypad locks, etc.
Unlike reactive machines, limited memory machines learn from past experiences and get smarter as they receive and store more information. This type of AI adapts to its environment to make better decisions over time.
Use cases: Stock trading algorithms, online games, gesture recognition, self-driving cars, etc.
This advanced AI type truly understands humans through thoughts, desires, beliefs, and emotions. As the name suggests, this is still a theoretical concept.
Possible use cases: Predict human behavior, enhanced social interactions, improved robotics, education, and therapy.
Self-aware AI is a speculative type of AI with consciousness and self-awareness, identical to humans. The development of such AI systems is highly disputed. Some consider it impossible, while others say it’s the future of AI.
Use cases: It’s difficult to predict because of the endless possibilities.
Don’t get lost in jargon! Learn everything about the most common artificial intelligence terms from A to Z.