1. What is AI?Artificial intelligence or AI simulates human intellect to machines. AI-enabled machines are capable of performing specific tasks better than humans and mimic human actions. There are four types of AI:Reactive machines: This is the most superficial level of AI. Reactive machines can do basic operations.
They cannot form memories or use past experiences to make decisions. IBM’s Deep Blue is the perfect example of this type of machine. This AI beat international grandmaster Garry Kasparov in 1997.Limited memory: This AI type can store existing data and create better output by using the data. For example, Tesla’s self-driving cars observe the speed of vehicles and direction and act accordingly.Theory of mind: Theory of mind can connect with human thoughts and interpret them better.
The AI can understand people and have thoughts and emotions of its own. These AI machines are still hypothetical, but researchers are making many efforts to develop such AI machines.Self-aware AI: This type of AI is a thing of the future. A self-aware AI will have an independent intelligence, and it will make its own decisions. These machines will be smarter than the human mind.
2. What is Machine Learning?
Machine Learning is a discipline within artificial intelligence where systems can learn from past data, identify patterns, detect anomalies, and make decisions with minimal human intervention. Once the system has learned from the past data, it can provide an inference based on the new input parameters.
There are primarily three different types of machine learning, namely:
Machine Learning is a discipline within artificial intelligence where systems can learn from past data, identify patterns, detect anomalies, and make decisions with minimal human intervention. Once the system has learned from the past data, it can provide an inference based on the new input parameters.
There are primarily three different types of machine learning, namely:
2.1 Supervised Learning
Learning takes place from the training dataset under supervision. The input and output data are known for the training data, and the learning process establishes a relationship between them.
Learning takes place from the training dataset under supervision. The input and output data are known for the training data, and the learning process establishes a relationship between them.
2.2 Unsupervised Learning
The corresponding output variables for a set of input variables are not established in unsupervised learning. Algorithms such as clustering and association are designed to model the data’s underlying structure or distribution to learn more about them.2.3 Reinforced Learning
Reinforcement learning employs trial and error methods to come up with a solution and gets either rewards or penalties for the actions it performs. Reinforcement learning is the most effective way to hint at a machine’s creativity.
The corresponding output variables for a set of input variables are not established in unsupervised learning. Algorithms such as clustering and association are designed to model the data’s underlying structure or distribution to learn more about them.2.3 Reinforced Learning
Reinforcement learning employs trial and error methods to come up with a solution and gets either rewards or penalties for the actions it performs. Reinforcement learning is the most effective way to hint at a machine’s creativity.
3. What is a robot?
A robot is a machine that is capable of carrying out specific tasks automatically. It can replicate human efforts and provide better outcomes.
There are five types of robots:
A robot is a machine that is capable of carrying out specific tasks automatically. It can replicate human efforts and provide better outcomes.
There are five types of robots:
- Pre-programmed robots: Pre-programmed robots can perform simple tasks. A mechanical arm used for welding in the automotive industry is an example of a pre-programmed robot.
- Humanoid robots: These robots can perform human-like activities. They look like humans and mimic human actions. Hanson Robotics’ Sophia is a perfect example of humanoid robots.
- Teleoperated robots: Humans control these robots. They perform tasks in extreme conditions where humans cannot operate. Human-controlled submarines or drones are examples of teleoperated robots.
- Autonomous robots: These are independent robots that do not require human intervention. They carry out tasks on their own. A perfect example would be the Roomba vacuum cleaner. It uses sensors to roam throughout a home freely.
- Augmenting robots: Augmenting robots enhance human capabilities by replacing the ineffective part. Some examples of augmenting robots are prosthetic limbs or exoskeletons. READ MORE...
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