Analytics Vidhya

JULY 4, 2023

Introduction NLP (Natural Language Processing) can help us to understand huge amounts of text data. Instead of going through a huge amount of documents by hand and reading them manually, we can make use of these techniques to speed up our understanding and get to the main messages quickly.

NLP 290

NLP Natural Language Processing Python 290

Marktechpost

OCTOBER 25, 2024

Natural Language Processing (NLP) is a rapidly growing field that deals with the interaction between computers and human language. To help you on your journey to mastering NLP, we’ve curated a list of 20 GitHub repositories that offer valuable resources, code examples, and pre-trained models.

Natural Language Processing 113

Natural Language Processing NLP Deep Learning Python 113

Unite.AI

MARCH 23, 2025

Knowledge Base Integration: Connects to structured knowledge sources (websites, documents, etc.) Natural Language Processing (NLP): Built-in NLP capabilities for understanding user intents and extracting key information. for accurate and contextually relevant answers.

AI Chatbots 271

AI Chatbots Chatbots AI AI 271

Unite.AI

NOVEMBER 14, 2024

AI in healthcare is causing a revolution in how clinicians document, analyze, and make decisions. AI Scribes: Redefining Clinical Documentation AI has a big influence on clinical documentation, which is one of the main areas it's changing. They also help make documentation more accurate and complete.

Natural Language Processing 162

Natural Language Processing AI AI Automation 162

Marktechpost

MARCH 4, 2024

The team has presented the BABILong framework, which is a generative benchmark for testing Natural Language Processing (NLP) models on processing arbitrarily lengthy documents containing scattered facts in order to assess models with very long inputs.

Natural Language Processing 125

Natural Language Processing NLP Data Analysis Machine Learning 125

Marktechpost

MAY 3, 2024

Natural Language Processing (NLP) is integral to artificial intelligence, enabling seamless communication between humans and computers. Researchers from East China University of Science and Technology and Peking University have surveyed the integrated retrieval-augmented approaches to language models.

Natural Language Processing 138

Natural Language Processing Large Language Models Categorization BERT 138

Unite.AI

OCTOBER 27, 2024

Its modular design allows developers to combine multiple ML solutions into efficient processing pipelines, while WebGL acceleration ensures smooth performance even on mobile devices. The framework's cross-platform support and extensive documentation make it an excellent choice for developers building sophisticated real-time AI applications.

Neural Network 162

Neural Network Machine Learning NLP Natural Language Processing 162

Unite.AI

JANUARY 22, 2025

AI practice management solutions are improving healthcare operations through automation and intelligent processing. These platforms handle essential tasks like clinical documentation, medical imaging analysis, patient communications, and administrative workflows, letting providers focus on patient care.

Automation 240

Automation AI AI Neural Network 240

Marktechpost

MAY 27, 2024

Knowledge-intensive Natural Language Processing (NLP) involves tasks requiring deep understanding and manipulation of extensive factual information. The primary challenge in knowledge-intensive NLP tasks is that large pre-trained language models need help accessing and manipulating knowledge precisely.

Natural Language Processing 125

Natural Language Processing NLP BERT AI Researcher 125

AssemblyAI

DECEMBER 19, 2024

Voice intelligence combines speech recognition, natural language processing, and machine learning to turn voice data into actionable insights. Natural Language Processing (NLP)  Once speech becomes text, natural language processing, or NLP, models analyze the actual meaning.

Natural Language Processing 130

Natural Language Processing Categorization Automation NLP 130

AssemblyAI

NOVEMBER 9, 2023

In Natural Language Processing (NLP), Text Summarization models automatically shorten documents, papers, podcasts, videos, and more into their most important soundbites. What is Text Summarization for NLP? The models are powered by advanced Deep Learning and Machine Learning research.

NLP 256

NLP AI Modeling Machine Learning AI 256

Towards AI

NOVEMBER 6, 2024

Unlocking efficient legal document classification with NLP fine-tuning Image Created by Author Introduction In today’s fast-paced legal industry, professionals are inundated with an ever-growing volume of complex documents — from intricate contract provisions and merger agreements to regulatory compliance records and court filings.

BERT 111

BERT Automation NLP Data Analysis 111

Unite.AI

JANUARY 28, 2025

OpenAI, known for its general-purpose models like GPT-4 and Codex, excels in natural language processing and problem-solving across many applications. OpenAIs o1 model, based on its GPT architecture, is highly adaptable and performs exceptionally well in natural language processing and text generation.

OpenAI 147

OpenAI Natural Language Processing Explainable AI Explainability 147

Marktechpost

AUGUST 31, 2024

This open-source model, built upon a hybrid architecture combining Mamba-2’s feedforward and sliding window attention layers, is a milestone development in natural language processing (NLP). Performance and Benchmarking Rene has been evaluated against several common NLP benchmarks.

Natural Language Processing 127

Natural Language Processing NLP Deep Learning AI 127

Unite.AI

APRIL 1, 2025

The company aims to acquire agencies with under $5 million in revenue a segment often overlooked by traditional private equity and infuse them with machine learning tools that handle repetitive tasks like document processing, client onboarding, and claims management.

Natural Language Processing 147

Natural Language Processing Automation Machine Learning NLP 147

Marktechpost

FEBRUARY 7, 2024

To address these challenges, researchers from the Allen Institute for AI (AI2) have released OLMo (Open Language Model), a framework aimed at promoting an atmosphere of transparency in the field of Natural Language Processing. The key features of OLMo are as follows.

Natural Language Processing 117

Natural Language Processing Artificial Intelligence Artificial Intelligence NLP 117

Marktechpost

JANUARY 12, 2025

Large language models ( LLMs ) like GPT-4, PaLM, Bard, and Copilot have made a huge impact in natural language processing (NLP). Their design makes them accessible and cost-effective, offering organizations an opportunity to harness NLP without the heavy demands of LLMs. SLMs also excel in cybersecurity.

NLP 102

NLP Natural Language Processing Large Language Models LLM 102

AWS Machine Learning Blog

MARCH 7, 2025

This capability enhances responses from generative AI applications by automatically creating embeddings for semantic search and generating a graph of the entities and relationships extracted from ingested documents. This new capability integrates the power of graph data modeling with advanced natural language processing (NLP).

Auto-complete 116

Auto-complete Natural Language Processing Explainability Metadata 116

AWS Machine Learning Blog

MARCH 17, 2025

Large language models (LLMs) have revolutionized the field of natural language processing, enabling machines to understand and generate human-like text with remarkable accuracy. However, despite their impressive language capabilities, LLMs are inherently limited by the data they were trained on.

LLM 97

LLM Natural Language Processing ML Computer Vision 97

Flipboard

FEBRUARY 11, 2025

Large-scale data ingestion is crucial for applications such as document analysis, summarization, research, and knowledge management. These tasks often involve processing vast amounts of documents, which can be time-consuming and labor-intensive. The Process Data Lambda function redacts sensitive data through Amazon Comprehend.

Data Ingestion 155

Data Ingestion Metadata Machine Learning Generative AI 155

Marek Rei

NOVEMBER 4, 2024

I have written short summaries of 68 different research papers published in the areas of Machine Learning and Natural Language Processing. Dwell in the Beginning: How Language Models Embed Long Documents for Dense Retrieval João Coelho, Bruno Martins, João Magalhães, Jamie Callan, Chenyan Xiong. ArXiv 2024.

Machine Learning 80

Machine Learning NLP Large Language Models LLM 80

AWS Machine Learning Blog

NOVEMBER 25, 2024

John Snow Labs is the developer behind Spark NLP, Healthcare NLP, and Medical LLMs. John Snow Labs’ Medical Language Models is by far the most widely used natural language processing (NLP) library by practitioners in the healthcare space (Gradient Flow, The NLP Industry Survey 2022 and the Generative AI in Healthcare Survey 2024 ).

LLM 99

LLM NLP Machine Learning ML 99

Unite.AI

MARCH 16, 2025

How the AI Transcription & Summarization Works Fathom uses advanced natural language processing (NLP) to transcribe your entire meeting in real time with high accuracy, typically between 85% and 90%. It's great for individuals or small teams prioritizing basic meeting documentation without additional costs.

AI Tools 179

AI Tools AI AI Natural Language Processing 179

Marktechpost

JANUARY 11, 2025

Large Language Models (LLMs) have shown remarkable capabilities across diverse natural language processing tasks, from generating text to contextual reasoning. Enhanced Long-Text Processing SepLLM processes sequences exceeding four million tokens, surpassing traditional length limitations.

Large Language Models 94

Large Language Models LLM Natural Language Processing NLP 94

Marktechpost

FEBRUARY 24, 2024

A significant challenge with question-answering (QA) systems in Natural Language Processing (NLP) is their performance in scenarios involving extensive collections of documents that are structurally similar or ‘indistinguishable.’ Knowledge graphs and LLMs are used to model these relationships.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence Metadata Natural Language Processing 130

John Snow Labs

APRIL 3, 2025

However, with Healthcare NLP s task-based pretrained pipelines, these challenges can be overcome with simple one-liner solutions that tackle everything from entity recognition to de-identification. Similarly, Healthcare NLP pipelines follow this principle, enabling seamless text processing for clinical applications.

NLP 40

NLP Explainability Large Language Models Natural Language Processing 40

Unite.AI

MAY 29, 2024

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text.

Data Extraction 273

Data Extraction Neural Network Large Language Models NLP 273

Unite.AI

MARCH 28, 2025

Knowledge base and database connectors: Give the bot context from your documents or data tables. This means your AI agents can automatically update records, send emails, pull documents, or trigger workflows in your existing software stack. Visit BotPress 2. plus the ability to record UI actions for legacy systems.

Automation 162

Automation Chatbots AI AI 162

AWS Machine Learning Blog

NOVEMBER 15, 2024

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. Model monitoring of key NLP metrics was incorporated and controls were implemented to prevent unsafe, unethical, or off-topic responses.

Generative AI 114

Generative AI Chatbots AI AI 114

Marktechpost

APRIL 21, 2024

Embedding models are fundamental tools in natural language processing (NLP), providing the backbone for applications like information retrieval and retrieval-augmented generation. Existing research in NLP embedding models has progressively focused on extending context capabilities.

NLP 109

NLP Natural Language Processing BERT AI 109

AWS Machine Learning Blog

JUNE 12, 2024

In today’s data-driven business landscape, the ability to efficiently extract and process information from a wide range of documents is crucial for informed decision-making and maintaining a competitive edge. Confidence scores and human review Maintaining data accuracy and quality is paramount in any document processing solution.

IDP 123

IDP NLP Natural Language Processing Generative AI 123

IBM Journey to AI blog

AUGUST 13, 2024

An early hint of today’s natural language processing (NLP), Shoebox could calculate a series of numbers and mathematical commands spoken to it, creating a framework used by the smart speakers and automated customer service agents popular today.

Machine Learning 291

Machine Learning Neural Network Robotics Natural Language Processing 291

IBM Journey to AI blog

SEPTEMBER 19, 2024

This solution used AWS services such as Amazon Bedrock, Amazon ECS and Amazon S3 to assess solution design documents, stay updated with regulatory updates and industry best practices. They developed a “Resilience by Design Advisor” to address these challenges. It also incorporated the bank’s technology resilience framework.

Generative AI 281

Generative AI DevOps Natural Language Processing NLP 281

Marktechpost

SEPTEMBER 19, 2024

Text embedding models have become foundational in natural language processing (NLP). These models convert text into high-dimensional vectors that capture semantic relationships, enabling tasks like document retrieval, classification, clustering, and more.

NLP 120

NLP Large Language Models Natural Language Processing ML 120

IBM Journey to AI blog

MARCH 27, 2024

The Eora MRIO (Multi-region input-output) dataset is a globally recognized spend-based emission factor set that documents the inter-sectoral transfers amongst 15.909 sectors across 190 countries. In recent years, remarkable strides have been achieved in crafting extensive foundation language models for natural language processing (NLP).

ESG 238

ESG Categorization Large Language Models NLP 238

AWS Machine Learning Blog

DECEMBER 23, 2024

Translating natural language into vectors reduces the richness of the information, potentially leading to less accurate answers. Also, end-user queries are not always aligned semantically to useful information in provided documents, leading to vector search excluding key data points needed to build an accurate answer.

Generative AI 122

Generative AI Natural Language Processing Prompt Engineering Prompt Engineer 122

AWS Machine Learning Blog

OCTOBER 24, 2023

In today’s information age, the vast volumes of data housed in countless documents present both a challenge and an opportunity for businesses. Traditional document processing methods often fall short in efficiency and accuracy, leaving room for innovation, cost-efficiency, and optimizations.

IDP 131

IDP LLM Prompt Engineering Prompt Engineer 131