LLMs for SMEs – 001: How Small Businesses Can Leverage AI Without Cloud Costs
1. Introduction Ravi runs a small auto parts shop in Navi Mumbai. His day starts at 8 AM, but even before he lifts the shutter, his phone is already buzzing. Cu...
Tag: llm
LLM-Powered Chatbots: A Practical Guide to User Input Classification and Intent Handling
1. Introduction If you’ve ever built a chatbot that confidently answered the wrong question, you know the pain of poor intent detection. Imagine a user typing: ...
Reranking for RAG: Boosting Answer Quality in Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) is one of the most effective techniques for making large language models (LLMs) answer accurately using external knowledge....
Question Answer Chatbot using RAG, Llama and Qdrant
1. Introduction I have created this teaching chatbot that can answer questions from class IX, subject SST, on the topic “Democratic politics“. I hav...
On Emergent Abilities of Large Language Models
An ability is emergent if it is not present in smaller models but is present in larger models. [1] Scaling up language models has been shown to improve predicta...
Text Clustering and Topic Modeling using Large Language Models (LLMs)
1. Introduction Text clustering is an unsupervised approach that helps in discovering patterns in data. Grouping similar texts according to their semantic conte...
Text Classification using Large Language Models (LLMs)
1. Introduction A common task in natural language processing (NLP) is text classification. Use cases of text classification include sentiment analysis, intent d...
Inside the LLM Inference Engine: Architecture, Optimizations, Tools, Key Concepts and Best Practices
1. Introduction LLM inference and serving refer to the process of deploying large language models and making them accessible for use — whether locally for perso...
Fact-checking in LLM
Summary of fact-checking in LLM #llm #hallucinations #misinformation