Unite.AI

DECEMBER 4, 2023

Small Language Models (SLM) are emerging and challenging the prevailing narrative of their larger counterparts. Despite their excellent language abilities these models are expensive due to high energy consumption, considerable memory requirements as well as heavy computational costs.

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Unite.AI

SEPTEMBER 20, 2023

We'll also walk through the essential features of Hugging Face, including pipelines, datasets, models, and more, with hands-on Python examples. Transformers in NLP In 2017, Cornell University published an influential paper that introduced transformers. These are deep learning models used in NLP.

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Unite.AI

NOVEMBER 11, 2024

Machines are demonstrating remarkable capabilities as Artificial Intelligence (AI) advances, particularly with Large Language Models (LLMs). At the leading edge of Natural Language Processing (NLP) , models like GPT-4 are trained on vast datasets. They understand and generate language with high accuracy.

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Unite.AI

JANUARY 11, 2024

They serve as a core building block in many natural language processing (NLP) applications today, including information retrieval, question answering, semantic search and more. More recent methods based on pre-trained language models like BERT obtain much better context-aware embeddings.

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Marktechpost

APRIL 6, 2024

Transformers have transformed the field of NLP over the last few years, with LLMs like OpenAI’s GPT series, BERT, and Claude Series, etc. The introduction of the transformer architecture has provided a new paradigm for building models that understand and generate human language with unprecedented accuracy and fluency.

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AssemblyAI

SEPTEMBER 18, 2023

However, among all the modern-day AI innovations, one breakthrough has the potential to make the most impact: large language models (LLMs). Large language models can be an intimidating topic to explore, especially if you don't have the right foundational understanding. What Is a Large Language Model?

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Unite.AI

JUNE 20, 2024

Large Language Models (LLMs) are capable of understanding and generating human-like text, making them invaluable for a wide range of applications, such as chatbots, content generation, and language translation. Large Language Models (LLMs) are a type of neural network model trained on vast amounts of text data.

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Marktechpost

DECEMBER 13, 2023

The well-known Large Language Models (LLMs) like GPT, BERT, PaLM, and LLaMA have brought in some great advancements in Natural Language Processing (NLP) and Natural Language Generation (NLG). If you like our work, you will love our newsletter.

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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. The transformer architecture is based on the attention mechanism, which allows the model to learn long-range dependencies between words.

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Artificial Corner

JULY 30, 2023

In this world of complex terminologies, someone who wants to explain Large Language Models (LLMs) to some non-tech guy is a difficult task. So that’s why I tried in this article to explain LLM in simple or to say general language. A transformer architecture is typically implemented as a Large language model.

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Unite.AI

FEBRUARY 7, 2024

But more than MLOps is needed for a new type of ML model called Large Language Models (LLMs). LLMs are deep neural networks that can generate natural language texts for various purposes, such as answering questions, summarizing documents, or writing code.

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Marktechpost

JANUARY 10, 2024

BERT is a language model which was released by Google in 2018. It is based on the transformer architecture and is known for its significant improvement over previous state-of-the-art models. BERT-Base reached an average GLUE score of 83.2% hours taken by BERT-Large. hours compared to 23.35

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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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Marktechpost

JULY 4, 2023

Computer programs called large language models provide software with novel options for analyzing and creating text. It is not uncommon for large language models to be trained using petabytes or more of text data, making them tens of terabytes in size. rely on Language Models as their foundation.

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Marktechpost

JANUARY 12, 2024

One of the most important areas of NLP is information extraction (IE), which takes unstructured text and turns it into structured knowledge. At the same time, Llama and other large language models have emerged and are revolutionizing NLP with their exceptional text understanding, generation, and generalization capabilities.

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Analytics Vidhya

FEBRUARY 27, 2024

Introduction Large language models (LLMs) are increasingly becoming powerful tools for understanding and generating human language. LLMs have even shown promise in more specialized domains, like healthcare, finance, and law.

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Towards AI

OCTOBER 31, 2024

A Complete Guide to Embedding For NLP & Generative AI/LLM By Mdabdullahalhasib This article provides a comprehensive guide to understanding and implementing vector embedding in NLP and generative AI. It also addresses challenges in fine-tuning, such as preserving general capabilities while improving task-specific performance.

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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.

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Marek Rei

NOVEMBER 4, 2024

It is probably good to also to mention that I wrote all of these summaries myself and they are not generated by any language models. Are Emergent Abilities of Large Language Models a Mirage? Do Large Language Models Latently Perform Multi-Hop Reasoning? Here we go. NeurIPS 2023. ArXiv 2024.

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Unite.AI

OCTOBER 11, 2023

Take, for instance, word embeddings in natural language processing (NLP). When generating human-like text, models need to rapidly compare and retrieve relevant embeddings, ensuring that the generated text maintains contextual meanings. Generative AI and The Need for Vector Databases Generative AI often involves embeddings.

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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. But as time has gone on, many industries have realized the power of these models. CaseHOLD is a new dataset for legal NLP tasks.

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Unite.AI

SEPTEMBER 13, 2024

As the demand for large language models (LLMs) continues to rise, ensuring fast, efficient, and scalable inference has become more crucial than ever. Recommendation Systems : By accelerating inference for models that process large amounts of user data, TensorRT enables real-time personalization at scale.

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IBM Journey to AI blog

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

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Marktechpost

MARCH 3, 2025

Encoder models like BERT and RoBERTa have long been cornerstones of natural language processing (NLP), powering tasks such as text classification, retrieval, and toxicity detection. Recent fine-tuning advancements masked these issues but failed to modernize the core models.

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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. What are Large Language Models and Why are They Important? Their foundational nature allows them to be fine-tuned for a wide variety of downstream NLP tasks.

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Towards AI

JUNE 12, 2024

Photo by david clarke on Unsplash The most recent breakthroughs in language models have been the use of neural network architectures to represent text. There is very little contention that large language models have evolved very rapidly since 2018. Both BERT and GPT are based on the Transformer architecture.

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Marktechpost

AUGUST 7, 2023

Language model pretraining has significantly advanced the field of Natural Language Processing (NLP) and Natural Language Understanding (NLU). Models like GPT, BERT, and PaLM are getting popular for all the good reasons. Models like GPT, BERT, and PaLM are getting popular for all the good reasons.

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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. These models have mastered the intricacies of language, enabling them to tackle tasks with remarkable accuracy.

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Marktechpost

MAY 3, 2024

Natural Language Processing (NLP) is integral to artificial intelligence, enabling seamless communication between humans and computers. Traditional NLP methods like CNN, RNN, and LSTM have evolved with transformer architecture and large language models (LLMs) like GPT and BERT families, providing significant advancements in the field.

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AI Weekly

JANUARY 4, 2024

macdailynews.com The Evolution Of AI Chatbots For Finance And Accounting At the end of 2023, these key components have rapidly merged through the evolution of large language models (LLMs) like ChatGPT and others. Sissie Hsiao, Google Sissie Hsiao, Google's vice president and the general manager of Bard and Google Assistant.

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Marktechpost

JUNE 12, 2023

Large Language Models are rapidly advancing with the huge success of Generative Artificial Intelligence in the past few months. This chatbot, based on Natural Language Processing (NLP) and Natural Language Understanding (NLU), allows users to generate meaningful text just like humans.

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Marktechpost

NOVEMBER 10, 2023

NLP, or Natural Language Processing, is a field of AI focusing on human-computer interaction using language. NLP aims to make computers understand, interpret, and generate human language. Recent NLP research has focused on improving few-shot learning (FSL) methods in response to data insufficiency challenges.

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Unite.AI

OCTOBER 23, 2023

Over the past few years, Large Language Models (LLMs) have garnered attention from AI developers worldwide due to breakthroughs in Natural Language Processing (NLP). These models have set new benchmarks in text generation and comprehension.

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Topbots

APRIL 11, 2023

In this article, we will delve into the latest advancements in the world of large-scale language models, exploring enhancements introduced by each model, their capabilities, and potential applications. The Most Important Large Language Models (LLMs) in 2023 1. What is the goal? billion word corpus).

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AWS Machine Learning Blog

APRIL 4, 2025

To achieve this, Lumi developed a classification model based on BERT (Bidirectional Encoder Representations from Transformers) , a state-of-the-art natural language processing (NLP) technique. They fine-tuned this model using their proprietary dataset and in-house data science expertise. Follow her on LinkedIn.

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Towards AI

FEBRUARY 10, 2025

Counselling session by a therapist In our work on medical diagnosis, we have focused on identifying conditions such as depression and anxiety for suicide risk detection using large language models (LLMs). This indicates that they can accurately portray the complexity of multiple dimensions in social media language.

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Marktechpost

JULY 1, 2023

Large Language Models (LLMs) have proven to be really effective in the fields of Natural Language Processing (NLP) and Natural Language Understanding (NLU). Famous LLMs like GPT, BERT, PaLM, etc., Being trained on massive amounts of datasets, these LLMs capture a vast amount of knowledge.

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