Intelligent Systems
- [The Components of Intelligence - Tutorialspoint]
- Overview
An intelligent system is a machine or computer system that uses artificial intelligence (AI) and machine learning (ML) algorithms to gather, analyze, and respond to data from its environment.
Intelligent systems can learn from experience, adapt to new data, and communicate with other systems or users. They are designed to reduce manual labor and improve efficiency by automating tasks and streamlining processes.
Intelligent systems can take many forms, including:
- Automated vacuums: Such as the Roomba
- Facial recognition programs
- Online shopping recommendation systems
- Autonomous cars and drones
Intelligent systems are often compared to biological systems because they can perform tasks like humans, such as recognizing patterns, making decisions, and controlling tasks. However, humans reason in imprecise ways, while computers are based on binary reasoning.
Intelligent systems can have several capabilities, including:
- Self-learning: Systems can learn from their experiences to reduce errors and improve performance
- Identification: Systems can automatically recognize specific information and send it through various channels
- Protection: Systems need secure networks and communications to function properly
- Remote management: Systems allow people to interact with them from any location
- User experience: Systems need accessible and adjustable interfaces to interact with users
Intelligent systems are used in many industries, including retail, manufacturing, and software engineering. They are sometimes considered part of the Internet of Things (IoT), which is a network of wireless devices that receive and respond to data on the internet.
- What is Intelligence Composed of?
The intelligence is intangible. It consists of the following components: Reasoning, Learning, Problem Solving, Perception, Linguistic Intelligence.
Human intelligence is the intellectual power of humans characterized by complex cognitive expertise coupled with high levels of motivation and self-awareness. Intelligence enables humans to remember descriptions of things and use these descriptions in future behavior.
This is a cognitive process. It gives humans the cognitive ability to learn, form concepts, comprehend, and reason, including the ability to recognize patterns, innovate, plan, solve problems, and communicate using language. Intelligence enables humans to experience and think.
AI is both the intelligence of machines and a branch of computer science that aims to create it through the "study and design of intelligent agents" or "rational agents", where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success.
Characteristics that researchers want machines to exhibit include reasoning, knowledge, planning, learning, communication, perception, and the ability to move and manipulate objects.
- The Main Areas Within Intelligent Systems
Artificial intelligence (AI) is defined as the ability of digital computers or computer-controlled robots to perform tasks usually associated with intelligent beings. AI is also defined as,
- Intelligent entities created by humans.
- Ability to perform tasks intelligently without explicit instructions.
- Ability to think and act rationally and humanely.
Intelligent systems are technologically advanced machines that sense and respond to the world around them. Smart systems can come in many forms, from autonomous vacuum cleaners like the Roomba to facial recognition programs to Amazon's personalized shopping recommendations.
Two major areas in intelligent systems are: how machines perceive their environment and how those machines interact with the environment.
One way an intelligent system perceives its environment is through vision. The study of how computers understand and interpret visual information from still images and video sequences arose in the late 1950s and early 1960s.
It has grown into a powerful technology that is at the heart of the country's industrial, commercial and government sectors. Key factors contributing to this growth are exponential increases in processor speed and memory capacity, as well as advances in algorithms.
- Challenges in Intelligent Systems
Research in intelligent systems faces numerous challenges, many of which relate to representing a dynamic physical world computationally.
- Uncertainty: Physical sensors/effectors provide limited, noisy and inaccurate information/action. Therefore, any actions the system takes may be incorrect both due to noise in the sensors and due to the limitations in executing those actions.
- Dynamic world: The physical world changes continuously, requiring that decisions be made at fast time scales to accommodate for the changes in the environment.
- Time-consuming computation: Searching for the optimal path to a goal requires extensive search through a very large state space, which is computationally expensive. The drawback of spending too much time on computation is that the world may change in the meantime, thus rendering the computed plan obsolete.
- Mapping: A lot of information is lost in the transformation from the 3D world to the 2D world. Computer vision must deal with challenges including changes in perspective, lighting and scale; background clutter or motion; and grouping items with intra/inter-class variation.
