The human brain can take decisions in sudden instant less than a nanosecond whereas any technology or any microcontroller that we use can take any action slower than any human brain.

Artificial intelligence(AI) is a small step taken by the researchers to create such a thing that can compare it to the human brain. They want to create such technology which can think like a human, take decision according to the situations and prevent disastrous activities which are cause loss of life and property. 

Artificial intelligence is a technology or I say algorithm which can learn anything according to the training given to it.

With the help of Artificial intelligence people, life becomes easier and simple. It can solve complex problems in a faster and accurate way in which human brains get exhausted. It can also prevent hacking. It can help people in making the right decisions

Example: if a person wants to invest money in the market than with the help of AI one can invest money at the right thing.

By having a lot of advantages it has few limitations also which is not good for human beings.

Many companies are working on AI. Google is one of them which is working on many projects related to AI.

The difference between Artificial Intelligence (AI) and the human brain is multifaceted, spanning across various aspects such as capabilities, structure, learning mechanisms, and limitations. Here's a breakdown:

1. Capabilities:

   - AI: AI systems excel at specific tasks for which they are designed, such as data analysis, pattern recognition, natural language processing, and decision-making in constrained environments.

   - Human Brain: The human brain is incredibly versatile and capable of performing a wide range of tasks, including complex problem-solving, creativity, emotional understanding, social interactions, and adaptation to new situations.

2. Structure:

   - AI: AI systems are typically based on algorithms and structured data processing. They often consist of multiple interconnected layers in neural networks, mimicking the interconnected neurons in the human brain.

   - Human Brain: The human brain comprises billions of neurons interconnected through synapses, forming complex neural networks. It consists of different regions responsible for various functions such as cognition, emotion, perception, and motor control.

3. Learning Mechanisms:

   - AI: AI systems learn from data through techniques such as supervised learning, unsupervised learning, reinforcement learning, and deep learning. They improve their performance over time by adjusting their parameters based on feedback.

   - Human Brain: Humans learn through a combination of experiences, sensory inputs, social interactions, and feedback mechanisms. Learning in the human brain involves synaptic plasticity, where connections between neurons strengthen or weaken based on usage and relevance.

4. Speed and Efficiency:

   - AI: AI systems can process large volumes of data and perform computations much faster than the human brain. They can analyze vast datasets and execute tasks with high precision and consistency.

   - Human Brain: While the human brain may not match the speed of AI systems in certain computations, it excels in tasks requiring parallel processing, intuition, and adaptability.

5. Emotional and Social Intelligence:

   - AI: Current AI lacks true emotional understanding and social intelligence. While some AI systems can recognize emotions from facial expressions or text, they do not experience emotions or understand social nuances in the same way humans do.

   - Human Brain: Humans possess emotional intelligence, allowing them to understand, express, and regulate emotions. They also have social intelligence, enabling complex social interactions, empathy, and cooperation.

6. Creativity and Innovation:

   - AI: AI systems can generate outputs based on existing data and patterns but lack true creativity and innovation in the human sense. They cannot create entirely novel ideas or concepts.

   - Human Brain: Humans demonstrate creativity and innovation by generating new ideas, artworks, inventions, and solutions to complex problems through imagination, critical thinking, and associative thinking.

Applications of Machine Learning in AI

Machine Learning is the most rapidly growing technology and according to researchers we are in the golden year of AI and ML. It is used to solve many real-world complex problems that cannot be solved with the traditional approach.

 Following are some real-world applications of ML −

• Emotion analysis
• Sentiment analysis
• Error detection and prevention
• Weather forecasting and prediction
• Stock market analysis and forecasting
• Speech synthesis
• Speech recognition
• Customer segmentation
• Object recognition
• Fraud detection
• Fraud prevention
• Recommendation of products to customer in online shopping