In the realm of Machine Learning, Reinforcement Learning with Human Feedback (RLHF) stands out as an innovative technique where human trainers play a crucial role in guiding the learning process of models. Unlike traditional reinforcement learning, which relies solely on pre-defined rewards, RLHF incorporates human judgment to shape the training environment. This method can have significant implications, especially when it comes to ensuring that models consistently favor certain outcomes over others. In this blog, we’ll delve into how trainers can influence models using RLHF, highlighting both the potential benefits and pitfalls. Human trainers can introduce biases, whether consciously or
Category: Software Development
Strategic Countermeasures to combat Software Vulnerabilities effectively in AI/ML enabled applications
Looking back, Application Security has evolved significantly in the last couple of decades. In the early 2000s, SQL injection and Cross Site Scripting (XSS) attacks were a nightmare for cybersecurity teams as attackers easily bypassed network firewalls through attacks at the application layer. Since traditional network firewalls at that time were not application-aware, these attacks proved a blind spot allowing attackers to compromise web applications easily. Hence, the computer industry developed countermeasures which included and not limited to web application firewalls (WAF), source code security reviews, and DevSecOps, who automate these checks within CI/CD pipelines to and allow security