Artificial Intelligence and Machine learning

AI

AI is artificial intelligence that aims to make machines as smart as humans. It encompasses different subtopics such as computer vision, robotics, etc. The ultimate goal is to make AI adapt and learn from its mistakes so they make decisions on their own without waiting for any input. 

Machine learning

This means that systems learn from data and improve their performance as time goes on without any programming required by the coder. The algorithms that create machine learning are inspired by the human brain as we can learn and fail, these enable the computers to recognize patterns, make future predictions, and reach conclusions, evolving in result.

Types of machine learning

Supervised - Trained on dataset, image recognition, spam filter

Unsupervised - Unlabeled data, cluster

Reinforcement - Involves interaction, there are rewards and penalties

Applications of AI and ML

Healthcare: Diagnosing patients and giving recommendation

Finance: Detecting frauds and managing risks

Retail: Recommendations and forecasting

Vehicles: Navigation

Cybersecurity: Anomaly detection

Challenges 

There are ethical concerns, some biased algorithms, and data privacy issues.

Synergy of AI and ML

AI and ML have a relationship where AI provides the framework and ML works as the engine powering decision-making. As the future goes on and we further improve and evolve these technologies there is room for a lot of growth.