Remove Generative AI Remove LLM Remove Natural Language Processing
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30+ LLM Interview Questions and Answers

Analytics Vidhya

Introduction Large Language Models (LLMs) are becoming increasingly valuable tools in data science, generative AI (GenAI), and AI. LLM development has accelerated in recent years, leading to widespread use in tasks like complex data analysis and natural language processing.

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How to Build LLM Apps Using Vector Database?

Analytics Vidhya

Introduction In the field of artificial intelligence, Large Language Models (LLMs) and Generative AI models such as OpenAI’s GPT-4, Anthropic’s Claude 2, Meta’s Llama, Falcon, Google’s Palm, etc., LLMs use deep learning techniques to perform natural language processing tasks.

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Building LLM-Powered Applications with LangChain

Analytics Vidhya

In a world where language is the bridge connecting people and technology, advancements in Natural Language Processing (NLP) have opened up incredible opportunities.

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The recipe for RAG: How cloud services enable generative AI outcomes across industries

IBM Journey to AI blog

According to research from IBM ®, about 42 percent of enterprises surveyed have AI in use in their businesses. Of all the use cases, many of us are now extremely familiar with natural language processing AI chatbots that can answer our questions and assist with tasks such as composing emails or essays.

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Hugging Face Releases Picotron: A Tiny Framework that Solves LLM Training 4D Parallelization

Marktechpost

The rise of large language models (LLMs) has transformed natural language processing, but training these models comes with significant challenges. Conclusion Picotron represents a step forward in LLM training frameworks, addressing long-standing challenges associated with 4D parallelization.

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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

Flipboard

Retrieval Augmented Generation (RAG) has become a crucial technique for improving the accuracy and relevance of AI-generated responses. The effectiveness of RAG heavily depends on the quality of context provided to the large language model (LLM), which is typically retrieved from vector stores based on user queries.

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Ashish Nagar, CEO & Founder of Level AI – Interview Series

Unite.AI

There were rapid advancements in natural language processing with companies like Amazon, Google, OpenAI, and Microsoft building large models and the underlying infrastructure. We started from a blank slate and built the first native large language model (LLM) customer experience intelligence and service automation platform.