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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John Snow Labs

JUNE 27, 2023

Are you curious about the groundbreaking advancements in Natural Language Processing (NLP)? Prepare to be amazed as we delve into the world of Large Language Models (LLMs) – the driving force behind NLP’s remarkable progress. Ever wondered how machines can understand and generate human-like text?

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John Snow Labs

AUGUST 29, 2023

It’s a well-established principle: any LLM, whether open-source or proprietary, isn’t dependable without a RAG. And truly, there can’t be an effective RAG without an NLP library that is production-ready, natively distributed, state-of-the-art, and user-friendly. We’re excited to unveil Spark NLP 5.1

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John Snow Labs

APRIL 18, 2024

In this post, we explore the utilization of pre-trained models within the Healthcare NLP library by John Snow Labs to map medical terminology to the MedDRA ontology. Let us start with a short Spark NLP introduction and then discuss the details of the response to cancer treatment with some solid results.

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Unite.AI

DECEMBER 1, 2023

Impact of the LLM Black Box Problem 1. Flawed Decision Making The opaqueness in the decision-making process of LLMs like GPT-3 or BERT can lead to undetected biases and errors. For example, a medical diagnosis LLM relying on outdated or biased data can make harmful recommendations.

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Unite.AI

JANUARY 23, 2024

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. From chatbots to search engines to creative writing aids, LLMs are powering cutting-edge applications across industries. LLMs utilize embeddings to understand word context.

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John Snow Labs

SEPTEMBER 26, 2023

Experts Share Perspectives on How Advanced NLP Technologies Will Shape Their Industries and Unleash Better & Faster Results. to be precise) of data scientists and engineers plan to deploy Large Language Model (LLM) applications into production in the next 12 months or “as soon as possible.” billion by the end of 2030.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

Transformers, BERT, and GPT The transformer architecture is a neural network architecture that is used for natural language processing (NLP) tasks. This allows the model to learn long-range dependencies between words, which is essential for many NLP tasks, such as machine translation and text summarization.

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Large Language Models BERT NLP Data Scientist 97

Towards AI

APRIL 12, 2023

In the last few years, if you google healthcare or clinical NLP, you would see that the search results are blanketed by a few names like John Snow Labs (JSL), Linguamatics (IQVIA), Oncoustics, BotMD, Inspirata. Soon to be followed by large general language models like BERT (Bidirectional Encoder Representations from Transformers).

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Unite.AI

JULY 11, 2023

This course explores LLMs (Large Language Models) – AI models trained on large amounts of textual data. Google’s Bard AI ” is an excellent example of an LLM that makes advanced human-machine interaction possible. Understand how LLMs are used for sentiment analysis. Covers the different NLP tasks for which a BERT model is used.

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ODSC - Open Data Science

SEPTEMBER 6, 2023

Most people who have experience working with large language models such as Google’s Bard or OpenAI’s ChatGPT have worked with an LLM that is general, and not industry-specific. CaseHOLD is a new dataset for legal NLP tasks. The CaseHOLD dataset was created to address the lack of large-scale, domain-specific datasets for legal NLP.

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Large Language Models LLM NLP BERT 98

Unite.AI

DECEMBER 4, 2023

GPT 3 and similar Large Language Models (LLM) , such as BERT , famous for its bidirectional context understanding, T-5 with its text-to-text approach, and XLNet , which combines autoregressive and autoencoding models, have all played pivotal roles in transforming the Natural Language Processing (NLP) paradigm.

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John Snow Labs

AUGUST 29, 2023

It’s a well-established principle: any LLM, whether open-source or proprietary, isn’t dependable without a RAG. And truly, there can’t be an effective RAG without an NLP library that is production-ready, natively distributed, state-of-the-art, and user-friendly. We’re excited to unveil Spark NLP 5.1

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Mlearning.ai

JUNE 14, 2023

Learning Large Language Models The LLM (Foundational Models) space has seen tremendous and rapid growth. I used this foolproof method of consuming the right information and ended up publishing books , artworks , Podcasts and even an LLM powered consumer facing app ranked #40 on the app store. YouTube BERT Research — Ep.

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Marktechpost

DECEMBER 18, 2023

Bioformer Bioformer is a compact version of BERT that can be used for biomedical text mining. Although BERT has achieved state-of-the-art performance in NLP applications, its parameters could be reduced with a minor impact on performance to improve its computational efficiency.

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Marktechpost

JANUARY 4, 2024

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. Meet ‘Unicron,’ a novel system that Alibaba Group and Nanjing University researchers developed to enhance and streamline the LLM training process. Check out the Paper.

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Marktechpost

FEBRUARY 7, 2024

The emergence of Large Language Models (LLMs) has transformed the landscape of natural language processing (NLP). The introduction of the transformer architecture marked a pivotal moment, ushering in a new era in NLP. GPT-4’s decoder-only approach excels in natural language generation tasks.

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Marktechpost

JULY 22, 2023

The well-known large language models such as GPT, DALLE, and BERT perform extraordinary tasks and ease lives. Recently, MLC-LLM has been introduced, which is an open framework that brings LLMs directly into a broad class of platforms like CUDA, Vulkan, and Metal that, too, with GPU acceleration.

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LLM Large Language Models Natural Language Processing Artificial Intelligence 52

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). Major language models like GPT-3 and BERT often come with Python APIs, making it easy to integrate them into various applications.

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Large Language Models Natural Language Processing Prompt Engineer Prompt Engineering 109

Mlearning.ai

JUNE 7, 2023

Photo by Eugene Zhyvchik on Unsplash I wanted to share a short perspective of the radical evolution we have seen in NLP. I’ve been working on NLP problems since word2vec was released, and it has been remarkable to see how quickly the models, problems, and applications have evolved. GPT-2 released with 1.5

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Marktechpost

JULY 4, 2023

Natural language processing (NLP) activities, including speech-to-text, sentiment analysis, text summarization, spell-checking, token categorization, etc., Applications of LLMs The chart below summarises the present state of the Large Language Model (LLM) landscape in terms of features, products, and supporting software.

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Marktechpost

MARCH 1, 2024

The prowess of Large Language Models (LLMs) such as GPT and BERT has been a game-changer, propelling advancements in machine understanding and generation of human-like text. Ouroboros represents a significant leap forward in addressing the longstanding challenge of LLM inference efficiency.

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Marktechpost

SEPTEMBER 17, 2023

Large language models (LLMs) built on transformers, including ChatGPT and GPT-4, have demonstrated amazing natural language processing abilities. The creation of transformer-based NLP models has sparked advancements in designing and using transformer-based models in computer vision and other modalities.

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Towards AI

JANUARY 30, 2024

The 12 groups are as follows — Types of Models Common LLM Terms LLM Lifecycle Stages LLM Evaluations LLM Architecture Retrieval Augmented Generation (RAG) LLM Agents LMM Architecture Cost & Efficiency LLM Security Deployment & Inference A list of providers supporting LLMOps Like the generative AI space, this taxonomy is also evolving.

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John Snow Labs

OCTOBER 19, 2023

How to use the LangTest library to evaluate LLM for bias using CrowS-Pairs dataset? Natural language processing (NLP) is a critical branch of artificial intelligence devoted to understanding and generating natural language. However, NLP systems are susceptible to biases, often mirroring the prejudices found in their training data.

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BERT Natural Language Processing NLP Categorization 52

Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape.

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Snorkel AI

DECEMBER 27, 2023

While large language models (LLMs) have claimed the spotlight since the debut of ChatGPT, BERT language models have quietly handled most enterprise natural language tasks in production. As foundation models , large LLMs like GPT-4 and Gemini consolidate internet-scale text datasets and excel at a wide range of tasks.

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ODSC - Open Data Science

NOVEMBER 8, 2023

In this blog, we’ll explore ten key aspects of building generative AI applications, including large language model basics, fine-tuning, and core NLP competencies. LLM Basics First and foremost, you need to understand the basics of generative AI and LLMs, such as key terminology, uses, potential issues, and primary frameworks.

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TheSequence

MAY 29, 2023

In this post Toloka showcases Human-in-the-Loop using StarCoder, a code LLM, as an example. Responsible AI starts with a responsible approach to data The promise of Large Language Models (LLMs) is that they will help us with a variety of different tasks. These datasets are usually scraped from the internet. Looking through 6.4

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Marktechpost

JULY 3, 2023

From deep learning, Natural Language Processing (NLP), and Natural Language Understanding (NLU) to Computer Vision, AI is propelling everyone into a future with endless innovations. The LLM consumes the text data during training and tries to anticipate the following word or series of words depending on the context.

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Unite.AI

APRIL 17, 2024

In recent years, Natural Language Processing (NLP) has undergone a pivotal shift with the emergence of Large Language Models (LLMs) like OpenAI's GPT-3 and Google’s BERT. These models, characterized by their large number of parameters and training on extensive text corpora, signify an innovative advancement in NLP capabilities.

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The MLOps Blog

FEBRUARY 15, 2024

Due to the rise of LLMs and the shift towards pre-trained models and prompt engineering, specialists in traditional NLP approaches are particularly at risk. Data scientists and NLP specialists can move towards analytical roles or into engineering to stay relevant. NLP projects in production face their own set of challenges.

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NLP Natural Language Processing Data Scientist Software Engineer 59

Snorkel AI

DECEMBER 27, 2023

While large language models (LLMs) have claimed the spotlight since the debut of ChatGPT, BERT language models have quietly handled most enterprise natural language tasks in production. As foundation models , large LLMs like GPT-4 and Gemini consolidate internet-scale text datasets and excel at a wide range of tasks.

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BERT NLP Data Scientist Large Language Models 52

Snorkel AI

DECEMBER 27, 2023

While large language models (LLMs) have claimed the spotlight since the debut of ChatGPT, BERT language models have quietly handled most enterprise natural language tasks in production. As foundation models , large LLMs like GPT-4 and Gemini consolidate internet-scale text datasets and excel at a wide range of tasks.

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BERT NLP Data Scientist Large Language Models 52

ODSC - Open Data Science

JANUARY 29, 2024

Fine-tuning is important for applying domain-specific knowledge to an existing LLM which provides better performance and prompt results Inference Efficiency An emergent skill in late 2023, its inclusion speaks to its importance. This enhances the context awareness and factual accuracy of LLM outputs.

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John Snow Labs

APRIL 22, 2024

While large language models (LLMs) have demonstrated impressive capabilities in various natural language processing (NLP) tasks, their performance in this domain has been limited by the inherent complexities of medical language and the nuances involved in interpreting clinical narratives.

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NYU Center for Data Science

JUNE 30, 2023

NYUTron , the large language model (LLM), is able to read physicians’ notes and estimate patients’ risk of death, length of hospital stays, and other health factors. A significant challenge in incorporating computer programs in healthcare settings lies in information processing.

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