We all have heard about machine learning and its path-breaking applications. So, what is machine unlearning and why the need for it? Well, let’s first start with the basic understanding of what it means. Machine learning is a type of artificial intelligence that enables machines to analyse, learn, and adapt to the surroundings, which was earlier done on an entirely different data set. Machine unlearning is just the opposite of it. The device can unlearn the learned stuff whenever needed.
Researchers Yinzhi Cao and Junfeng Yang proposed a system that can forget data efficiently. The model is based on two criteria, completeness and timeliness. Completeness meant the difference between the training data and the unlearned data, whereas timeliness has got to do with how soon the system had wiped the unnecessary data. Researchers tested and ran this model with different machine learning systems successfully. After this success, researchers aim to adapt the machine unlearning techniques to other systems and ultimately delete the unwanted data.
No doubt, machine learning techniques have led to incredible and groundbreaking innovations but they have also led to few issues that must be resolved at the earliest. How to fix them? The answer is machine unlearning.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.