Artificial Intelligence

How Does AI Work?

Artificial intelligence systems work by using any number of AI techniques.

Siri is an applications based on Machine Learning and Deep Learning AI.

Types of AI

Artificial intelligence is often distinguished between weak AI and strong AI.

Weak AI
weak AI operates within a limited context and is applied to a narrowly defined problem.
Example: email inbox spam filters, language translators, website recommendation engines and conversational chatbots
Strong AI
Often referred to as artificial general intelligence (AGI) or simply general AI, strong AI describes a system that can solve problems it’s never been trained to work on, much like a human can. AGI does not actually exist yet because we are in initial phase of AI revolution so lets wait and watch the future.................

AI techniques

number of AI techniques as below.

Machine Learning (ML):

Machine learning is a subset of AI that involves the use of algorithms and statistical models to enable computers to improve their performance on a specific task through learning from data. It's the technology behind many AI applications, such as image and speech recognition.

Deep Learning:

Deep Learning is a subset of Machine Learning. Deep learning is a subfield of machine learning that focuses on neural networks with many layers (deep neural networks). This approach has been highly successful in tasks like image and speech recognition, and it's often used in AI applications.

Machine Learning Model Supervised Learning: Labeled Data Regression Classification Unsupervised Learning: Unlabeled Data Reinforcement Learning 1. Maths - Calculus -Differentiation and integration - Linear Algebra - Probability 2. Python The programming language. 3. Data Analysis - Numpy - pandas - Matplotlib 4. Framework - PyTourch - Tensor Flow - Keras 5. Gernrative AI

Natural Language Processing (NLP):

NLP is a branch of AI that deals with the interaction between computers and human language. It's used in applications like chatbots, language translation, and sentiment analysis.

Computer Vision:

Computer vision enables machines to interpret and understand visual information from the world, such as images and videos. It's used in facial recognition, object detection, and autonomous vehicles.

Robotics:

AI plays a significant role in the field of robotics, allowing robots to perceive and interact with their environment, make decisions, and execute tasks autonomously.

AI Ethics:

As AI technology advances, there are growing concerns about ethics and responsible AI development. Issues such as bias in AI, privacy, and the impact of AI on jobs and society are important considerations.

Artificial General Intelligence (AGI):

AGI refers to a form of AI that possesses general intelligence comparable to human intelligence. Currently, most AI systems are narrow or weak AI, designed for specific tasks, while AGI aims to mimic human-like intelligence across a wide range of tasks.

Machine Vision:

This is the ability of AI systems to interpret and understand visual information, making it a crucial component in applications like facial recognition, medical image analysis, and quality control in manufacturing.

Reinforcement Learning:

This type of machine learning involves training AI agents to make decisions by interacting with an environment and receiving feedback in the form of rewards or penalties. It's used in gaming, robotics, and autonomous systems.

AI in Healthcare:

AI is increasingly used in healthcare for tasks such as medical diagnosis, drug discovery, and personalized treatment recommendations.

AI in Business:

AI is employed in business for tasks like data analysis, customer service, and process automation.

AI in Transportation:

Autonomous vehicles and traffic management systems use AI to enhance safety and efficiency.