The development in Artificial Intelligence (AI) offers transformative potential for redefining student assessment methodologies. This paper aims to establish the idea of the advancement of Artificial Intelligence (AI) and its prospect in reshaping approaches to assessing students. It creates a system for the evaluation of students performance using Artificial intelligence, and particularly the Gemini API for the generation of questions, grading and report on the students performances. This is to facilitate easy use of the tools in creating, scheduling, and delivering assessments with minimal chances of cheating through options such as full screen and time limit. There are formats of questions in the system which comprises multiple choice, short answers and descriptive questions, developed by Gemini. The most conspicuous feature is the self-checking system whereby the user gets instant feedback for the correct score that each of the students would have scored instantly with explanations about wrong answers. Moreover, the platform has intelligent learning progressions where the user will be able to monitor his/her performances to be recommended a certain level of performance. It will allow students as well as educators to have real-time analytics and feedback on what they are good at and where they need to improve. Not only does it make the assessment easier, but it also improves the levels of accuracy in grading and effectively strengthens a data based learning process for students.

Industries across the spectrum are working overtime on their digital transformation. Historically insurance providers have been staunch advocates of legacy systems, but they too have begun singing a different tune. This shift can be attributed to the changing requirements and demands of policyholders, who are used to seamless 24/7 support across other industries and want the same from insurance providers. To help insurers meet these demands, several digital platforms have risen to the occasion with industry-specific products focused on maximizing ROI and improving customer-agent interactions. Among the biggest benefits of adopting a modern platform, such as ServiceNow, is wielding the power of artificial intelligence and machine learning to deliver memorable front-end insurance experiences.

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Note: The title of this article is a play on the term "Rube Goldberg machine". Acccording to Wikipedia, a Rube Goldberg machine is a contraption, invention, device, or apparatus that is deliberately over-engineered to perform a simple task in a complicated fashion, generally including a chain reaction. Keep that in your mind. Everyone (that cares about ML) knows about supervised / unsupervised / semi-supervised learning pipelines. I have now come across an entirely new class of ML pipelines that I shall call "Rube Goldberg Machine Learning" pipelines.