How AI Works?
A Simplified Explanation:
AI, or Artificial Intelligence, essentially mimics human intelligence through machines. It's a broad field that encompasses various techniques, but a common approach involves machine learning.
Here's a simplified breakdown:
* Data Collection: Gathering a vast amount of data relevant to the task. For example, to teach an AI to recognize cats, it would need to be fed thousands of images of cats.
* Algorithm Selection: Choosing a suitable algorithm to process the data. This could be a neural network, decision tree, or other machine learning model.
* Training: The algorithm is fed the data and learns to identify patterns and relationships. In the cat example, it would learn the features that define a cat, such as whiskers, paws, and tail.
* Testing: The trained AI is tested on new data to evaluate its performance. If the accuracy is high, it's ready for deployment.
* Deployment: The AI is integrated into a system or application to perform its intended task.
A key concept in AI is deep learning, a subset of machine learning that uses artificial neural networks with multiple layers to learn complex patterns. This has led to significant advancements in fields like image recognition, natural language processing, and self-driving cars. But the results are not that great as of now and it might take 100 years of learning and obviously bound by mistakes.
