Marktechpost

MAY 17, 2024

Natural Language Processing (NLP) is a cutting-edge field that enables machines to understand, interpret, & generate human language. It has applications in various domains, such as language translation, text summarization, sentiment analysis, and the development of conversational agents.

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LLM Large Language Models Natural Language Processing NLP 118

Unite.AI

SEPTEMBER 7, 2023

Today, there are numerous proprietary and open-source LLMs in the market that are revolutionizing industries and bringing transformative changes in how businesses function. Despite rapid transformation, there are numerous LLM vulnerabilities and shortcomings that must be addressed.

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LLM Large Language Models Prompt Engineer Prompt Engineering 173

AI Weekly

MAY 2, 2024

Planning a GenAI or LLM project? reviewjournal.com Research 8 Best Natural Language Processing Tools 2024 Compare features and choose the best Natural Language Processing (NLP) tool for your business. techxplore.com Sponsor Planning a GenAI or LLM Project? techmonitor.ai techmonitor.ai

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OpenAI Natural Language Processing Robotics LLM 147

Marktechpost

NOVEMBER 14, 2023

Medical data extraction, analysis, and interpretation from unstructured clinical literature are included in the emerging discipline of clinical natural language processing (NLP). Even with its importance, particular difficulties arise while developing methodologies for clinical NLP.

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NLP LLM AI Modeling Large Language Models 121

Marktechpost

FEBRUARY 29, 2024

Large Language Models (LLMs) have transformed natural language processing, offering user modeling and personalization opportunities. Directly fine-tuning LLMs with interaction histories faces hurdles like sparse data, multimodal interactions, and lengthy sequences.

Artificial Intelligence 123

Artificial Intelligence Artificial Intelligence LLM Large Language Models 123

Unite.AI

JANUARY 10, 2024

By integrating the sophisticated language processing capabilities of models like ChatGPT with the versatile and widely-used Scikit-learn framework, Scikit-LLM offers an unmatched arsenal for delving into the complexities of textual data. Why Scikit-LLM? and the user-friendly environment of Scikit-learn.

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Large Language Models LLM Machine Learning Natural Language Processing 147

Artificial Corner

JULY 30, 2023

So that’s why I tried in this article to explain LLM in simple or to say general language. Photo by Shubham Dhage on Unsplash Introduction Large language Models (LLMs) are a subset of Deep Learning. No training examples are needed in LLM Development but it’s needed in Traditional Development.

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Large Language Models LLM Natural Language Processing Deep Learning 98

Analytics Vidhya

MAY 6, 2023

Introduction Large Language Models (LLMs) are now widely used in a variety of applications, like machine translation, chat bots, text summarization , sentiment analysis , making advancements in the field of natural language processing (NLP).

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Large Language Models Natural Language Processing NLP LLM 280

Marktechpost

MARCH 19, 2024

IBM researchers have introduced LAB (Large-scale Alignment for chatbots) to address the scalability challenges encountered during the instruction-tuning phase of training large language models (LLMs). In conclusion, the paper introduces LAB as a novel methodology to address the scalability challenges in instruction tuning for LLMs.

Large Language Models 113

Large Language Models LLM Natural Language Processing Chatbots 113

Becoming Human

APRIL 19, 2024

Towards Improving the Safety of LLMs The field of Natural Language Processing has undergone a revolutionary transformation with the advent of Large Language Models (LLMs). An ideal defense strategy should make the LLM safe against the unsafe inputs without making it over-defensive on the safe inputs.

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LLM Large Language Models Algorithm Natural Language Processing 111

Marktechpost

FEBRUARY 29, 2024

Large Language Models (LLMs) have extended their capabilities to different areas, including healthcare, finance, education, entertainment, etc. These models have utilized the power of Natural Language Processing (NLP), Natural Language Generation (NLG), and Computer Vision to dive into almost every industry.

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Large Language Models LLM Machine Learning Natural Language Processing 124

Marktechpost

MARCH 6, 2024

The natural language processing (NLP) field has witnessed significant advancements with the emergence of Large Language Models (LLMs) like GPT and LLaMA. These models have become essential tools for various tasks, prompting a growing need for proprietary LLMs among individuals and organizations.

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LLM Large Language Models Neural Network Natural Language Processing 90

Marktechpost

APRIL 12, 2024

Natural Language Processing (NLP) tasks heavily rely on text embedding models as they translate the semantic meaning of text into vector representations. These representations make it possible to quickly complete a variety of NLP tasks, including information retrieval, grouping, and semantic textual similarity.

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LLM Large Language Models NLP Natural Language Processing 92

Marktechpost

NOVEMBER 9, 2023

The biggest advancement in the field of Artificial Intelligence is the introduction of Large Language Models (LLMs). These Natural Language Processing (NLP) based models handle large and complicated datasets, which causes them to face a unique challenge in the finance industry.

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Large Language Models LLM NLP Natural Language Processing 113

Unite.AI

FEBRUARY 7, 2024

LLMs are deep neural networks that can generate natural language texts for various purposes, such as answering questions, summarizing documents, or writing code. LLMs, such as GPT-4 , BERT , and T5 , are very powerful and versatile in Natural Language Processing (NLP).

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Machine Learning Large Language Models LLM BERT 294

Topbots

APRIL 29, 2024

Here are a few that might worth your attention: Reasoning with Language Model Prompting: A Survey. This paper, first published in December 2022, may not cover the most recent developments in LLM reasoning but still offers a comprehensive survey of available approaches. Large Language Models Cannot Self-Correct Reasoning Yet.

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LLM Large Language Models Natural Language Processing AI Researcher 59

Marktechpost

APRIL 29, 2024

These state-of-the-art Large Language Models (LLMs) have the potential to completely transform medical natural language processing (NLP) by establishing new standards for functionality and performance in the biomedical field. All credit for this research goes to the researchers of this project.

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Large Language Models Natural Language Processing NLP LLM 130

Flipboard

JUNE 10, 2023

When it comes to natural language processing (NLP) tasks, large language models (LLM) trained on massive online datasets perform exceptionally well. …

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Natural Language Processing Large Language Models AI Researcher AI Research 112

Unite.AI

JANUARY 2, 2024

Large Language Models (LLMs) have contributed to advancing the domain of natural language processing (NLP), yet an existing gap persists in contextual understanding. This enhances the user experience and streamlines workflows, making it easier to access the necessary information for their tasks.

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LLM Large Language Models Chatbots Natural Language Processing 243

Towards AI

FEBRUARY 6, 2024

LLMs are evolving at a rapid speed. Photo by Johannes Plenio on Unsplash Since the 2017 paper “Attention Is All You Need” invented the Transformer architecture, natural language processing (NLP) has seen tremendous growth. Do you want to use LLMs for your own use case but not pay for every prompt?

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LLM Natural Language Processing Large Language Models NLP 93

Marktechpost

FEBRUARY 3, 2024

MambaByte MOE Token-free language models have represented a significant shift in Natural Language Processing (NLP), as they learn directly from raw bytes, bypassing the biases inherent in subword tokenization. While requiring 2.2 times fewer training steps than Mamba, it achieves the same level of performance.

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Artificial Intelligence Artificial Intelligence LLM Large Language Models 134

Marktechpost

JANUARY 10, 2024

In simple terms, RAG is a natural language processing (NLP) approach that blends retrieval and generation models to enhance the quality of generated content. It addresses challenges faced by Large Language Models (LLMs), including limited knowledge access, lack of transparency, and hallucinations in answers.

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Natural Language Processing Large Language Models LLM Data Ingestion 96

Marktechpost

MARCH 3, 2024

Central to Natural Language Processing (NLP) advancements are large language models (LLMs), which have set new benchmarks for what machines can achieve in understanding and generating human language. One of the primary challenges in NLP is the computational demand for autoregressive decoding in LLMs.

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Machine Learning AI Researcher AI Research Large Language Models 119

Marktechpost

MAY 9, 2024

In Natural Language Processing (NLP) tasks, data cleaning is an essential step before tokenization, particularly when working with text data that contains unusual word separations such as underscores, slashes, or other symbols in place of spaces. The post Is There a Library for Cleaning Data before Tokenization?

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NLP Natural Language Processing Metadata Large Language Models 98

John Snow Labs

MAY 13, 2024

In the world of natural language processing, the ability to extract meaningful relationships between entities within text data is crucial for various applications. John Snow Labs also offers periodic trainings to help users gain expertise in utilizing the Healthcare Library and other components of their NLP platform.

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NLP Natural Language Processing Large Language Models LLM 52

NYU Center for Data Science

DECEMBER 1, 2023

The quest to refine AI’s understanding of extensive textual data has recently been advanced due to two recent papers by CDS PhD student Jason Phang , who is the first author of two recent NLP papers that secured “best paper” accolades at ICML 2023 and EMNLP 2023. By Stephen Thomas

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NLP Large Language Models Natural Language Processing AI 79

Marktechpost

MAY 6, 2024

In the quickly changing field of Natural Language Processing (NLP), the possibilities of human-computer interaction are being reshaped by the introduction of advanced conversational Question-Answering (QA) models. Recently, Nvidia has published a competitive Llama3-70b QA/RAG fine-tune. The Llama3-ChatQA-1.5

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Large Language Models Natural Language Processing NLP Responsible AI 115

John Snow Labs

NOVEMBER 28, 2023

We are thrilled to announce the release of NLP Lab version 5.5, marking another significant step forward in its Natural Language Processing capabilities. Integration with Azure OpenAI Service NLP Lab 5.5 Begin by registering the external service provider with NLP Lab. Click “Integrate.”

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NLP OpenAI LLM Natural Language Processing 52

AI Weekly

APRIL 11, 2024

The Microsoft AI London outpost will focus on advancing state-of-the-art language models, supporting infrastructure, and tooling for foundation models. No legacy process is safe. This paper offers a comprehensive survey of these studies, delivering a systematic review of LLM-based autonomous agents from a holistic perspective.

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Robotics Large Language Models Artificial Intelligence Artificial Intelligence 207

Analytics Vidhya

DECEMBER 5, 2023

Your dream entry into this field requires expertise and hands-on experience in natural language processing. Get job-ready with in-depth knowledge and application skills of different Large Language Models (LLMs). Introduction Has contributing to the realm of artificial intelligence been your passion?

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Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 282

Towards AI

DECEMBER 28, 2023

The introduction of attention mechanisms has notably altered our approach to working with deep learning algorithms, leading to a revolution in the realms of computer vision and natural language processing (NLP). These models are trained on massive amounts of text data to learn patterns and relationships in the language.

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Large Language Models Natural Language Processing Prompt Engineer Prompt Engineering 109

John Snow Labs

JULY 5, 2023

We are delighted to announce the release of Spark NLP 5.0, We are delighted to announce the release of Spark NLP 5.0, With this support, you can look forward to faster inference, automatic optimization, and quantization when exporting your LLM models. Spark NLP ONNX Introducing support for ONNX Runtime in Spark NLP.

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NLP BERT LLM Inference Engine 52

Allen AI

FEBRUARY 1, 2024

It’s the equivalent of drug discovery without clinical trials or studying the solar system without a telescope,” said Hanna Hajishirzi , OLMo project lead, a senior director of NLP Research at AI2, and a professor in the UW’s Allen School.

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LLM Large Language Models AI Researcher AI Research 76

Natural Language Processing @ Sapienza

FEBRUARY 6, 2024

Welcome to the Sapienza NLP course blog 2024! Cool things about to happen: The course will contain lots of up-to-date content on deep learning , neural networks , Large Language Model, and an improved hands-on with PyTorch ! We will include the most recent additions (including from 2024) from the world of NLP!

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Neural Network Natural Language Processing Large Language Models NLP 52

Salmon Run

FEBRUARY 24, 2024

I got into Natural Language Processing (NLP) and Machine Learning (ML) through Search. RAG started out relatively simple -- take a query, generate search results, use search results as context for a Large Language Model (LLM) to generate an abstractive summary of the results.

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Large Language Models Natural Language Processing NLP Machine Learning 59

John Snow Labs

AUGUST 31, 2023

In the ever-evolving world of Natural Language Processing, staying ahead of the curve is paramount. With the release of NLP Lab 5.3, we’re taking a leap forward by integrating one of the most advanced Large Language Models (LLMs) available today: Open AI’s GPT models.

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NLP LLM Large Language Models ChatGPT 52

Topbots

FEBRUARY 19, 2024

However, building a successful LLM application involves much more than just leveraging advanced technology. When embarking on the journey of building an LLM application, one of the first and most crucial decisions is choosing the foundation model. Create Targeted Evaluation Sets for Comparing LLM Performance in Your Specific Use Case.

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LLM Natural Language Processing Automation Data Ingestion 64