Arpit

Arpit

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Hello everyone, I’m Arpit Tinkhede from CSE-B, Roll No CS65. Today, I’ll be talking about Prompt Evaluation Matrices, focusing on Coherence. Let’s begin! First — what is a prompt? A prompt is the question or instruction we give to an AI, like “Tell me a story about a robot.” The AI uses this prompt to generate a response. Now, to check how good the AI’s answer is, we use evaluation matrices. These include: Relevance, Accuracy, Creativity, and Coherence. Today’s focus is on Coherence. It means that the ideas in the answer should be clear, connected, and make sense together. If one sentence doesn’t link to the next, the message feels broken and confusing. Let’s take an example: Prompt — “Tell a story about a helpful robot.” A good answer: “A robot lived in a city. He cleaned streets every day. People admired him.” A bad answer: “Robot jump help city sun time clean.” The second one is random and confusing — it has poor coherence. Why is coherence important? Because it turns plain information into smooth, easy-to-read answers. It helps people trust and understand what AI says. We use a star system to rate coherence: From 1 star (no logic) to 4 stars (fully smooth and logical). To conclude — Coherence makes AI answers feel natural, meaningful, and useful. It’s a key part of building better communication between AI and humans. Thank you for your attention!

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Hello everyone, today I'll explain about neural networks. A neural network is like the brain of AI systems. It learns from data, just like we learn from experience. Let's look at how it works - it has layers of neurons that process information and make decisions.