Artificial Intelligence Overview

The ability to identify and categorize information from our senses, like seeing and hearing.

The process of comparing incoming sensory information to our memory of past experiences and patterns.

Humans are exceptionally good at performing tasks that involve recognizing patterns and information from our senses, and reacting with physical movements.

The ability to recognize someone even if their appearance changes, like a new hairstyle or wearing glasses.

Instead of rigid step-by-step instructions, humans excel at processing huge amounts of data and making quick decisions based on past experiences.

Our mental storehouse of information, including images, sounds, and other sensory experiences.

Instead of requiring an exact match, humans can recognize things based on close approximations or similarities.

Humans often acquire basic skills early in life, like recognizing faces or understanding language, without formal instruction.

The process of interpreting sensory information and making sense of it.

The process of eliciting knowledge from experts by observation and questioning to create an expert system.

A system that simulates the decision-making process of a human expert in a specific domain.

A rule-based system that uses logical reasoning to reach conclusions based on available knowledge.

A component of an expert system that stores domain-specific knowledge, typically represented as rules or facts.

A component of an expert system responsible for applying the rules and knowledge in the knowledge base to solve problems and make decisions.

The field of computer science focusing on creating systems that exhibit intelligent behaviors.

The process of classifying artificial intelligence into different categories based on its capabilities and limitations.

There are two main types of AI:

1. Narrow AI: Designed for specific tasks, often surpassing human performance.

2. General AI: Hypothetical AI with human-like intelligence, capable of learning and performing any intellectual task that a human can.

The methods used to represent knowledge within computer systems. This enables AI systems to understand and use information effectively.

Common knowledge representation methods include:

1. Semantic Networks: Connected nodes representing concepts and relationships.
2. Production Rules: If-then statements describing actions based on conditions.
3. Frames: Data structures representing objects with attributes and values.
4. Scripts: Templates describing typical event sequences.

Tasks that involve recognizing patterns from input, like images, sounds, or text. AI systems use various techniques, including machine learning, to perform these tasks.

Examples:

• Image Recognition: Identifying objects in photographs.
• Speech Recognition: Converting spoken words into text.
• Object Detection: Identifying specific objects in a scene.

Tasks that involve reasoning, planning, and problem-solving. AI systems use algorithms and search techniques to perform these tasks.

Examples:

• Game Playing: Developing strategies to win games.
• Medical Diagnosis: Analyzing patient data to identify potential health issues.
• Route Planning: Finding the most efficient paths between locations.

A machine designed to perform tasks autonomously. Robots have sensors, actuators, and processors that enable them to interact with their environment.

Robots are currently used in various applications, like:

• Manufacturing: Assembly line tasks.
• Healthcare: Assisting surgeons in operations.
• Exploration: Surveying hazardous environments.

An unmanned aerial vehicle (UAV) controlled remotely or by onboard computers. Drones are used in diverse applications, including:

• Photography: Capturing aerial images and videos.
• Delivery: Transporting goods and packages.
• Surveillance: Monitoring areas for security purposes.

The junction between the axon of one neuron and the dendrites of another neuron.

Signals that excite or activate a neuron, making it more likely to fire.

Signals that inhibit or suppress a neuron, making it less likely to fire.

The process of a neuron summing up all the activating and inhibiting stimuli it receives at its dendrites.

The minimum level of activation required for a neuron to fire.

The process of a neuron firing, sending a signal down its axon to other neurons.

A type of brain organization characterized by a large number of simple 'processors' (neurons) with multiple interconnections.

A type of computer architecture that uses a small number of powerful processors with limited interconnections.

The ability of a neuron to receive signals from and send signals to a large number of other neurons, allowing for parallel processing.

The relatively slow time frame within which a neuron fires, which emphasizes the need for parallel processing in the brain.

A group of robots that work together to complete tasks, often using a decentralized approach where cooperation emerges from simple individual behaviors.

A system in which a group of robots, like a swarm, work together to achieve a common goal, often coordinating their actions through simple rules and communication.

A type of software designed to interact and assist users in a way similar to a personal assistant, learning from user preferences and anticipating needs.

A software system that learns a user's interests and automatically delivers relevant information, like news or weather updates.

A method of delivering information to users periodically, instead of waiting for them to request it, like push notifications.

The ability of a robot to learn and adapt based on experience and interaction with its environment.

Using robots in medical procedures to perform tasks with minimal invasiveness, such as surgery or drug delivery.

Robots designed to work together to clear hazardous materials or pollutants from the environment.

Robots used in search and rescue operations to find victims trapped in disasters or dangerous environments.

The ability of a robot to autonomously navigate and interact with its environment, making decisions and taking actions based on its perception of the surroundings.