Artificial Intelligence (AI)
In this post you will learn some basics of AI (Artificial Inelegance), like definitions, types, divisions, applications, and challenges
What is AI?
AI (Artificial Intelligence) is a machine’s ability to perform cognitive functions as humans do, such as perceiving, learning, reasoning, and solving problems
AI is a computer system that can perform tasks that normally require human intelligence. It includes recognizing objects, understanding natural language, and making decisions. It is a powerful tool that helps your business grow and improve in many ways.
In this post you will learn some basics of artificial inelegance, like definitions, types, divisions, applications, and challenges.
Goals of Artificial Intelligence
Here are the main Goals of AI:
- It helps you reduce the amount of time needed to perform specific tasks.
- Making it easier for humans to interact with machines.
- Facilitating human-computer interaction in a way that is more natural and efficient.
- Improving the accuracy and speed of medical diagnoses.
- Helping people learn new information more quickly.
- Enhancing communication between humans and machines.
Subfields of Artificial Intelligence
Here, are some important subfields of Artificial Intelligence:
Machine Learning: Machine learning is the art of studying algorithms that learn from examples and experiences. Machine learning is based on the idea that some patterns in the data were identified and used for future predictions. The difference from hardcoding rules is that the machine learns to find such rules.
Deep Learning: Deep learning is a sub-field of machine learning. Deep learning does not mean the machine learns more in-depth knowledge; it uses different layers to learn from the data. The depth of the model is represented by the number of layers in the model. For instance, the Google LeNet model for image recognition counts 22 layers.
Natural Language Processing: A neural network is a group of connected I/O units where each connection has a weight associated with its computer programs. It helps you to build predictive models from large databases. This model builds upon the human nervous system. You can use this model to conduct image understanding, human learning, computer speech, etc.
Expert Systems: An expert system is an interactive and reliable computer-based decision-making system that uses facts and heuristics to solve complex decision-making problems. It is also considered at the highest level of human intelligence. The main goal of an expert system is to solve the most complex issues in a specific domain.
Fuzzy Logic: Fuzzy Logic is defined as a many-valued logic form that may have truth values of variables in any real number between 0 and 1. It is the handle concept of partial truth. In real life, we may encounter a situation where we can’t decide whether the statement is true or false.
Types of Artificial Intelligence
There are three main types of artificial intelligence: rule-based, decision tree, and neural networks.
- Narrow AI is a type of AI that helps you perform a dedicated task with intelligence.
- General AI is a type of AI intelligence that can perform any intellectual task efficiently like a human.
- Rule-based AI is based on a set of pre-determined rules that are applied to an input data set. The system then produces a corresponding output.
- Decision tree AI is similar to rule-based AI in that it uses sets of pre-determined rules to make decisions. However, the decision tree also allows for branching and looping to consider different options.
- Super AI is a type of AI that allows computers to understand human language and respond in a natural way.
- Robot intelligence is a type of AI that allows robots to have complex cognitive abilities, including reasoning, planning, and learning.
AI Vs Machine Learning
Most of our smartphone, daily device or even the internet uses Artificial Intelligence. Very often, AI and machine learning are used interchangeably by big companies that want to announce their latest innovation. However, Machine learning and AI are different in some ways.
AI- artificial intelligence- is the science of training machines to perform human tasks. The term was invented in the 1950s when scientists began exploring how computers could solve problems on their own.
rtificial Intelligence is a computer that is given human-like properties. Take our brain; it works effortlessly and seamlessly to calculate the world around us. Artificial Intelligence is the concept that a computer can do the same. It can be said that AI is a large science that mimics human aptitudes.
Machine learning is a distinct subset of AI that trains a machine to learn. Machine learning models look for patterns in data and try to conclude. In a nutshell, the machine does not need to be explicitly programmed by people. The programmers give some examples, and the computer is going to learn what to do from those samples.
Where is AI used?
AI has broad applications-
- AI is used to reduce or avoid repetitive tasks. For instance, AI can repeat a task continuously, without fatigue.
- AI improves an existing product. Artificial intelligence to enhance the functionality of the product rather than starting from scratch to design new products.
- AI is used in all industries, from marketing to supply chain, finance, food-processing sector.
Important feature of having a powerful AI
There is three critical areas for developing of AI.
- Hardware
- Data
- Algorithm
Hardware
The CPU’s power is important for AI, allowing the user to train a small deep-learning model on any laptop. However, you need a more powerful machine to process a deep-learning model for computer vision or deep learning. now a days a new generation of GPU (graphical processing unit) are available. These chips allow parallel computations, and the machine can separate the computations over several GPUs to speed up the calculations.
For instance, with an NVIDIA TITAN X, it takes two days to train a model called ImageNet against weeks for a traditional CPU.
Data
Deep learning is the structure of the model, and the data is the fluid to make it alive. Data powers artificial intelligence. Without data, nothing can be done. The latest Technologies have pushed the boundaries of data storage, and it is easier than ever to store a high amount of data in a data center.
Needs data collection and distribution to feed machine learning algorithms. With Flickr, Instagram or any other app with images, you can guess their AI potential. There are millions of pictures with tags available on these websites. Those pictures can train a neural network model to recognize an object on the picture without the need to collect and label the data manually.
Artificial intelligence combined with data is the new gold. Data is a unique competitive advantage that no firm should neglect, and AI provides the best answers from your data. When all the firms can have the same technologies, the one with data will have a competitive advantage. To give an idea, the world creates about 2.2 exabytes, or 2.2 billion gigabytes, every day.
A company needs exceptionally diverse data sources to find the patterns and learn in a substantial volume.
Algorithm
Algorithm is important, hardware is more powerful than ever, data is easily accessible, but one thing that makes the neural network more reliable is the development of more accurate algorithms. Primary neural networks are a simple multiplication matrix without in-depth statistical properties. Since 2010, remarkable discoveries have been made to improve the neural network.
Artificial Intelligence uses a progressive learning algorithm to let the data do the programming. It means the computer can teach itself how to perform different tasks.
Conclusion
Artificial intelligence is the science of training machines to imitate or reproduce human tasks. When a system grows complex, it becomes difficult to manage the rules. To overcome this issue, the machine can use data to learn how to take care of all the situations from a given environment. The most important feature of having a powerful AI is that it has enough data with considerable heterogeneity.
The types of artificial intelligence are: General AI, Rule-based AI, Decision tree AI, Super AI.