Tags: ai, nlp, nlp 2.0Summary: This article will introduce and differentiate the three stages of development of Natural Language Processing (NLP): NLP 1.0, NLP 2.0, and NLP 3.0. […]
Are you struggling to extract text from PDF files? 🤔
Do you want to use Python to extract text from PDF files but are encountering issues with tables? This often results in the extracted text being mixed with […]
What is Late Chunking? How to use Late Chunking to implement advanced RAG?
Tags: chunking, llm, machine learning, nlpHave you ever tried to eat a giant pizza and realized you need to slice it into smaller pieces to make it easier? […]
Mixture of Experts (MoE) Technique Divides Models into Multiple Experts for Specific Tasks: Enhancing Model Performance with Optimized Costs
Tags: ai, machine learning, nlpSummary: Mixture of Experts (MoE) is a technique that enhances the performance of machine learning models without requiring an excessive increase in model size. […]
DataGemma – Tackling Hallucinations in LLMs with Real-World Data
Tags: llm, nlp, ragSummary: This article introduces DataGemma, an open-source model developed by Google to mitigate hallucinations in large language models (LLMs). DataGemma connects LLMs to the massive […]
Training NLP/LLM Applications with OpenAI: API or Llama.cpp?
Tags: api, llm, nlp, openaiAre you looking to build an NLP/LLM application (like a chatbot for your company) but unsure whether to use OpenAI API or Llama.cpp? Let […]