Asslam o Alaikum everyone! My name is Rizwan, and I am studying for a BS in Computer Science at FAST National University Faisalabad. This blog is part of my AI course assignment, which was given by Dr. Bilal Jan sir. We had to read and write about research papers. Honestly, when sir first told us about this, I wasn’t very happy because I thought research papers were very boring and hard to understand. But when I actually opened and read them, I was quite surprised. Let me share what I learned from this experience.
Why I Read Research Papers
At first, I thought research papers were only for PhD students. But after reading them, I realized they can be interesting. I saw things from our AI class, like the A* algorithm, in these very new papers. That really surprised me, and I thought, "Okay, maybe these papers are actually worth reading." So, my advice to other CS students is to try reading at least one paper every semester. It really helps you understand where AI is going in the real world.
Paper 1 – What is Agentic AI?
This paper talks about Agentic AI, which is a new kind of AI. Normally, AI systems like chatbots just answer one question at a time, but Agentic AI can set goals, plan steps, and do many things without help. It can also remember what it did before. The paper also says compounding errors are a big issue, where small mistakes grow bigger with time.
Paper 2 – New Search Technology with AI
This paper talks about Deep Search Agents. Unlike Google, these AI systems understand what you are looking for. They plan the search, read information, and give you a complete answer. It also talks about three types of search systems: old keyword-based search, newer systems, and advanced systems like OpenAI’s Deep Research. This is related to the A search algorithm* we study in class, where we use smart thinking to guide the search.
How the Papers Connect to What We Learn
Both papers show that what we learned in class, like A search* and agent types, are important in real-world AI. These concepts are used in the latest AI systems.
My Experience with Google NotebookLM
At first, reading research papers was difficult. But after using Google NotebookLM, I could understand things better. It helped me find important points that I missed when reading on my own.
What I Learned Overall
Reading research papers is not just for PhD students; they show how what we learn in class is used in real-world AI. It’s motivating to know that our studies are the foundation of the most advanced AI today.
Thanks for reading my blog! I hope this helps other CS students.
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