large language models (LLMs) Archives

Large Reasoning Models (LRMs): The AI That Actually Shows Its Work
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Large Reasoning Models (LRMs): The AI That Actually Shows Its Work

Roan Manansala2025-07-08T12:38:54+00:00

Imagine you are in a Math Class, and the teacher just gave a complex problem for everyone to solve. Then, after a few minutes, a classmate just shouted an answer. You’re all shocked because how did he come up with it? Was it the correct answer or they just made a guess? When the teacher asked them to elaborate they refused and said that they already did their work. This scenario displays the frustrations with traditional AI systems: fast answers with zero transparency. Now imagine that same classmate going up to the board, writing all of the formulas and calculations, [...]

Large Reasoning Models (LRMs): The AI That Actually Shows Its WorkRoan Manansala2025-07-08T12:38:54+00:00

Creating an AI Chatbot with LangChain for FREE (No API Keys, No Tokens)

Asi Guiang2025-07-09T15:12:24+00:00

Creating an AI Chatbot with LangChain for FREE (No API Keys, No Tokens) The Big Question: Can You Build AI Without Breaking the Bank? We asked ourselves a simple question: Can you build a chatbot without using any paid API at all? Most tutorials on AI chatbots start the same way: "First, grab your OpenAI API key and add your credit card..." But what if you don't have one? Or don't want to use one? Maybe you're a student on a tight budget. Maybe you're tired of hitting rate limits just when your chatbot gets interesting. Or maybe, just maybe, [...]

Creating an AI Chatbot with LangChain for FREE (No API Keys, No Tokens)Asi Guiang2025-07-09T15:12:24+00:00

What is Retrieval Augmented Generation (RAG) in Machine Learning?
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What is Retrieval Augmented Generation (RAG) in Machine Learning?

Nikee Tomas2025-06-30T03:46:57+00:00

Retrieval-Augmented Generation (RAG) Cheat Sheet Retrieval-Augmented Generation (RAG) is a method that enhances large language models (LLMs) outputs by incorporating information from external, authoritative knowledge sources. Instead of relying solely on pre-trained data, RAG retrieves relevant content at inference time to ground its responses. LLMs (Large Language Models) are trained on massive datasets and use billions of parameters to perform tasks like: Question answering Language translation Text completion RAG extends LLM capabilities to domain-specific or private organizational knowledge without requiring model retraining. It provides a cost-efficient way to improve the relevance, accuracy, and utility of LLM outputs in dynamic or [...]

What is Retrieval Augmented Generation (RAG) in Machine Learning?Nikee Tomas2025-06-30T03:46:57+00:00

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