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Enhancing Scientific Document Processing with Nougat

Analytics Vidhya

Introduction In the ever-evolving field of natural language processing and artificial intelligence, the ability to extract valuable insights from unstructured data sources, like scientific PDFs, has become increasingly critical.

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Unbundling the Graph in GraphRAG

O'Reilly on Data

Reasons for using RAG are clear: large language models (LLMs), which are effectively syntax engines, tend to “hallucinate” by inventing answers from pieces of their training data. See the primary sources “ REALM: Retrieval-Augmented Language Model Pre-Training ” by Kelvin Guu, et al., Split each document into chunks.

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Unlocking LangChain & Flan-T5 XXL | A Guide to Efficient Document Querying

Analytics Vidhya

Introduction A specific category of artificial intelligence models known as large language models (LLMs) is designed to understand and generate human-like text. For example, OpenAI’s GPT-3 model has 175 billion parameters. The term “large” is often quantified by the number of parameters they possess.

Modeling 336
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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

The hype around large language models (LLMs) is undeniable. They promise to revolutionize how we interact with data, generating human-quality text, understanding natural language and transforming data in ways we never thought possible. Even basic predictive modeling can be done with lightweight machine learning in Python or R.

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Information Retrieval using word2vec based Vector Space Model

Analytics Vidhya

Overview Learn about Information Retrieval (IR), Vector Space Models (VSM), and Mean Average Precision (MAP) Create a project on Information Retrieval using word2vec based. The post Information Retrieval using word2vec based Vector Space Model appeared first on Analytics Vidhya.

Modeling 318
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Unstructured data management and governance using AWS AI/ML and analytics services

AWS Big Data

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. You can integrate different technologies or tools to build a solution.

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From charred scrolls to customer sentiment: How AI helps you monetize your unstructured data

CIO Business Intelligence

Now that AI can unravel the secrets inside a charred, brittle, ancient scroll buried under lava over 2,000 years ago, imagine what it can reveal in your unstructured data–and how that can reshape your work, thoughts, and actions. Unstructured data has been integral to human society for over 50,000 years.