AI and ML technology are used across industries to streamline redundant tasks and work side by side with humans to take their abilities to the next level. However, have you thought about how much AI and ML technologies have become so smart? They are trained on data from the real world about the tasks they need to accomplish. However, the training data alone is not enough. This training data needs to be annotated with various techniques to allow the machines to understand what they need to learn. Since this is a very time-consuming process, a lot of companies hire data annotation services to do this for them. Let’s take a look at why data annotation is so important for AI and machine learning.
Achieving the Needed Accuracy Level
Companies rely on AI systems to accomplish certain tasks, and they expect that these tasks will be done correctly. For example, farmers use AI robots to pick apples from a tree. This means that the AI robot needs to locate the apples, determine if they are ripe, and pick them off the tree without ruining the apple. If the robot plucks apples that are unripe, it’s costing the farmers money. Therefore, various data annotation techniques are necessary to allow the robot to have the needed accuracy to perform its job. First of all, it needs to navigate in its immediate surroundings, which requires 3D Point cloud annotation. It needs to determine if the apple is ripe, which requires semantic segmentation since there are various shades of colors the robot needs to identify.
It’s also worth mentioning that sometimes there is no room for error when it comes to AI technology. For example, autonomous vehicles need to constantly evaluate the situation on the road to avoid catastrophe. It needs to “see” that pedestrians are crossing the road, a car is making a turn in front of them, and many other scenarios. A lack of data annotation accuracy here can cause an accident.
Avoid Costly Delays
When creating AI technologies, companies are usually so focused on the development aspect of the project that they don’t place enough importance on data annotation. However, if the training data is not annotated in time or the needed accuracy level is not reached, then the entire project can get delayed. This can be highly problematic since the cost of delay can be huge. This includes things like:
- Product development – the amount of money it will cost you if you delay your new product’s launch.
- Software development – the amount of money it will cost you if you delay the release of a groundbreaking feature that will give you an advantage over the competition.
- IT Operations – the amount of money you will lose if you fail to deliver the strategic initiative that the CEO wants.
It’s Best to Hire a Data Annotation Company to Avoid Problems
We mentioned many different problems that could arise if your training data is not annotated properly. This is why it is a good idea to hire a data annotation company, like Mindy Support, to do the work for you. The great thing about companies like this is that they have tons of experience realizing projects of all sizes and complexities, and they can help you navigate all of the pitfalls.
