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Introduction of Artificial Intelligence

 

Introduction of Artificial Intelligence….

 

Artificial intelligence is an approach to make a computer, a robot, or a product. On the other hand, artificial intelligence is a study of how the human brain thinks, learns, decides, and works, when it tries to solve problems. And finally, this study outputs intelligent software systems. The aim of artificial intelligence is to improve computer functions that are related to human knowledge, for example, reasoning, learning, and problem-solving. The objectives of artificial intelligence research are reasoning, knowledge representation, planning, learning, natural language processing, realization, and the ability to move and manipulate objects. There are long-term goals in the general intelligence sector.

Applications of Artificial Intelligence.

Gaming.

Natural language processing.

Expert Systems.

Vision Systems.

Speech recognition.

Handwriting recognition.

Intelligent robots.

 

Major Goals

Knowledge reasoning.

Planning.

Machine Leaning.

Natural Language Processing.

Computer Vision.

Robotics.

 

What are the four types of Artificial Intelligence?

There are four types of artificial intelligence.

Reactive machines

Limited memory

Theory of mind

Self-awareness

 

 

 

 

 

 

 

Components of artificial intelligence

 

 

Applications.

Image recognition.
Speech recognition.
Chatbots.
Natural language generation
Sentiment analysis

 

Types of models.

Deep learning.
Machine learning.
Neural networks.

 

Software/hardware for training and running models.

 

GPUs.
Parallel processing tools. (Like spark)
Cloud data storage and compute platforms.              

 

Programming languages for building modules.

 
Python.
Tensor Flow
Java.
C++

 

 

 

 

 

 

 

 

Different of cognitive computing and artificial intelligence.

 

Cognitive computing.

 

Artificial intelligence.

Machine learning, natural language processing, deep learning,

Analysis.

TECHNOLOGIES

Machine learning, natural language processing, neural networks, deep learning

Simulate human thought processes to assist humans in finding the solution to complex problems

CAPABILITIES

Find patterns in big data to learn and either reveal hidden information or deliver solutions to complex problems

Augment human capabilities.

PURPOSE

Automate processes

Customer service, healthcare, the industrial sector

INDUSTRIES

Finance, security, healthcare, retail, manufacturing, government

 

 

Examples of artificial intelligence.

All is incorporated into a variety of different types of technology.

Automation. (Make a system or process function automatically.)

Machine learning. (The science of getting a computer to act without programming)

Machine vision. (The science of allowing computers to see.)

Natural language processing. (The processing and not computer language by a computer program.)

Robotics. (A field of engineering focused on the design and manufacturing of robots.)

Self-driving cars. (These use a combination of computer vision, image recognition, and deep learning to build automated skills at piloting a vehicle while staying in a given lane and avoiding unexpected obstructions, such as pedestrians.)

 

Security and ethical concerns.

 

There are so many artificial intelligence applications in modern society. But before we try to use it, we have to think about the security and ethical concerns of the applications. Think about the bellow example of artificial intelligence in the realm of self-driving cars raises security as well as ethical concerns. Cars can be hacked, and when an autonomous vehicle is involved in an accident, liability is unclear. Autonomous vehicles may also be put in a position where an accident is unavoidable, forcing the programming to make an ethical decision about how to minimize damage.

Another major concern is the potential for abuse of artificial intelligence tools. Hackers are starting to use sophisticated machine learning tools to gain access to sensitive systems, complicating the issue of security beyond its current state.

Deep learning-based video and audio generation tools also present bad actors with the tools necessary to create so-called deep fake, convincingly fabricated videos of public figures saying or doing things that never took place.

 

 

Regulation of artificial intelligence technology.

 

Despite these potential risks, there are few regulations governing the use of artificial intelligence tools, and where laws do exist, they typically pertain to artificial intelligence only indirectly. For example, federal Fair Lending regulations require financial institutions to explain credit decisions to potential customers, which limit the extent to which lenders can use deep learning algorithms, which by their nature is typically opaque. Europe's general data protection regulation puts strict limits on how enterprises can use consumer data, which impedes the training and functionality of much consumer-facing artificial intelligence applications. The protection of personal data is based on the respect for privacy; informational self-determination; freedom of expression, communication, information, and opinion; the inviolability of intimacy, honor, and image; economic and technological development and innovation; free enterprise, free competition, and consumer protection; and human rights, free development of personality, dignity, and the exercise of citizenship by natural persons.

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