Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that “uses human feedback to train and improve the accuracy of an AI model”. One notable example of AI built on RLHF is ChatGPT which proved to be a powerful and fast tool and the article discusses how RLHF could also be used to strengthen AI-based cybersecurity tools. Development of defense against cyberattacks is becoming more important as cybercrime is extremely costly to companies and sophisticated attacks such as deepfakes and phishing attacks are increasing. RLHF could assist in corporate cybersecurity by (1) Improved accuracy of threat detection, (2) Faster detection and response to potential threats, (3) Improved security awareness, and (4) Adapt to and stay ahead of new threats.
