DATA COLLECTION

What is Data Collection?

It is the process of gathering data to train or improve an AI model. The more data an AI model has, the better it can make decisions. For example, if an AI model is being trained to recognise pictures of animals, it needs thousands, if not millions of pictures of different animals before it can generate an accurate output. This allows the AI model to learn the difference between a cat and a dog, for example.

Types of Data Collected for AI

Some common examples:

1. Images and Videos: To recognise objects, animals, or people, an AI model needs pictures or videos to learn from. For instance, self-driving cars use images from cameras to understand the road and recognise pedestrians, traffic signs, and other cars.

2. Text: To understand language, an AI model requires lots of written text. This could include books, news articles, or social media posts. By reading and analysing these data, an AI model learns to answer questions, translate languages, or help with writing.

3. Voice Recordings: AI systems that process speech, like virtual assistants, use recordings of people's voices to learn how to understand and respond to different voice commands in a variety of languages, accents or ways of speaking.

4. Sensor Data: AI can use data collected from sensors, such as the ones in your phone or a self-driving car. These sensors can collect information like temperature, pressure, speed, or motion.

5. Reviews and Ratings: Companies collect data from users' reviews and ratings of products and movies. These data help AI recommend products or shows you might like based on your past behaviour.