Weblog(Blog Post)

AI agents are rapidly transforming various industries, and education stands at the forefront of this technological revolution. These intelligent systems, designed to simulate human-like interactions and decision-making, offer unprecedented opportunities to enhance student support. From personalized learning experiences to real-time feedback and administrative assistance, AI agents are poised to redefine how educational institutions cater to … Read more

Introduction Large language models (LLMs) have dramatically transformed the way we interact with technology, powering everything from chatbots to complex content generation. However, as their influence grows, it becomes crucial to assess their performance accurately. LLM evaluation is the process of determining how well these models understand, generate, and respond to language tasks. Equally important … Read more

LLM-powered agents are rapidly transforming the landscape of artificial intelligence by combining the abilities of large language models (LLMs) with autonomous decision-making capabilities. These agents go beyond just generating text—they interact with data, perform complex tasks, and adapt using contextual understanding. This article will explore how LLM-powered agents function, their practical applications, key benefits, and … Read more

Function calling and tool usage are fundamental concepts in programming and software development that significantly impact how efficiently tasks are executed and systems operate. Understanding how functions are called in various programming languages and how external or built-in tools are utilized enhances software performance and maintainability. This article explores these topics by breaking down what … Read more

Fine-tuning and Reinforcement Learning from Human Feedback (RLHF) are two pivotal techniques shaping the evolution of artificial intelligence, especially in natural language processing models. Fine-tuning adjusts pre-trained models to excel in specific tasks, whereas RLHF introduces a dynamic learning process where models improve based on human evaluations. This article explores these advanced methods and how … Read more

Using P.G.T.C. to guide AI in generating user stories helps teams create clearer, more actionable requirements. User stories are the foundation of agile product development, communicating user needs and desired outcomes concisely. However, crafting effective user stories manually can be time-consuming and inconsistent. Leveraging AI to automate this process is becoming a smart solution, but … Read more

Introduction to the P.G.T.C. AI prompt framework The rise of AI-generated content has introduced new challenges and opportunities in crafting effective prompts to get accurate and relevant responses. The P.G.T.C. AI Prompt Framework—which stands for Persona, Goal, Task, and Context—is a strategic method designed to enhance prompt quality. This framework helps users structure their requests … Read more

Introduction Retrieval Augmented Generation (RAG) is an innovative approach that combines the power of large language models with external knowledge sources to produce more accurate and contextually relevant responses. Unlike traditional language models that solely rely on pretrained data, RAG integrates dynamic retrieval of documents or data from large databases during the generation process. This … Read more

Self-reflection and self-consistency are two essential psychological concepts that play a critical role in how individuals understand themselves and maintain stability in their thoughts and behavior. Self-reflection is the process of introspecting and examining one’s thoughts, feelings, and actions to gain deeper insight, while self-consistency refers to the drive people have to align their beliefs, … Read more

Chain of thought prompting is an emerging technique in the field of artificial intelligence that enhances the reasoning capabilities of language models. Unlike conventional prompting methods that seek direct answers, chain of thought prompting encourages models to produce intermediate reasoning steps, leading to more accurate and interpretable outcomes. This approach has gained significant attention as … Read more