Once the dream of automakers and the public, self-driving cars have taken to the road and are now approaching an even bigger milestone: complete autonomy. And it’s only happened because of AI. Plus the data AI uses to make human-like decisions behind the wheel.
While AI is known for bringing hyperintelligence to things like self-driving vehicles, what’s driving AI is a massive amount of high-quality data. But high-quality data doesn’t exist on its own. And this is where the challenge for AI-driven brands arises.
For AI to be effective requires data that has been processed by humans in order to teach the machine learning (ML) models that tell AI what to do and when to do it. Yet putting this data together can be a big and complex process; one that takes lots of skill, time, and resources to develop into the very datasets AI uses to perform at its best.
Empowering AI performance with data labeling
Self-driving cars aren’t the only thing being powered by AI. From science and medicine, to retail and security, to finance and even agriculture, AI is everywhere. And it’s all made possible by meticulously labeled data, which can include everything from text and audio files, to images, videos, and more.
So what is data labeling and how does it help AI do its job effectively? Let’s dig in and find out
What is data labeling?
Data labeling is the process of annotating, tagging, classifying, moderating, and managing data to create a framework for ML models to learn from and inform the algorithms that operate AI. But even without AI working behind the scenes, data labeling helps companies deliver the right information or products at the right time to users and customers.
Why is data labeling useful?
Brands in every industry use data labeling to enable the automated processes that would otherwise be impossible in real-time interactions or online business.
In the case of self-driving cars for example, labeled data provides AI with information about its surroundings so it can avoid obstacles, recognize street signs, and maintain safe speeds. It also helps AI process inflections in a person’s tone of voice to help it understand the context of a conversation. While in eCommerce, labeled data helps optimize products to find relevant items for customers.
In short, the list of things a business can do with labeled data is already pretty substantial – and it’s only getting bigger, especially as AI gets involved.
