SISA Certified Security Professional in Artificial Intelligence CSPAI Question # 2 Topic 1 Discussion
CSPAI Exam Topic 1 Question 2 Discussion:
Question #: 2
Topic #: 1
In a scenario where Open-Source LLMs are being used to create a virtual assistant, what would be the most effective way to ensure the assistant is continuously improving its interactions without constant retraining?
A.
Training a larger proprietary model to replace the open-source LLM
B.
Shifting the assistant to a completely rule-based system to avoid reliance on user feedback.
C.
Implementing reinforcement learning from human feedback (RLHF) to refine responses based on user input.
D.
Reducing the amount of feedback integrated to speed up deployment.
For continuous improvement in open-source LLM-based virtual assistants, RLHF integrates human evaluations to align model outputs with preferences, iteratively refining behavior without full retraining. This method uses reward models trained on feedback to guide policy optimization, enhancing interaction quality over time. It addresses limitations like initial biases or suboptimal responses by leveraging real-world user inputs, making the system adaptive and efficient. Unlike full retraining, RLHF is parameter-efficient and scalable, ideal for production environments. Security benefits include monitoring feedback for adversarial attempts. Exact extract: "Implementing RLHF allows continuous refinement of the assistant's interactions based on user feedback, avoiding the need for constant full retraining while improving performance." (Reference: Cyber Security for AI by SISA Study Guide, Section on AI Improvement Techniques in SDLC, Page 85-88).
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