AssemblyAI

SEPTEMBER 18, 2023

These feats of computational linguistics have redefined our understanding of machine-human interactions and paved the way for brand-new digital solutions and communications. They use neural networks that are inspired by the structure and function of the human brain. How Do Large Language Models Work?

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Large Language Models BERT Auto-complete LLM 130

The MLOps Blog

JANUARY 25, 2023

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing.

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BERT Natural Language Processing ML Deep Learning 52

Viso.ai

JULY 18, 2024

Emergence and History of LLMs Artificial Neural Networks (ANNs) and Rule-based Models The foundation of these Computational Linguistics models (CL) dates back to the 1940s when Warren McCulloch and Walter Pitts laid the groundwork for AI. Both contain self-attention mechanisms and feed-forward neural networks.

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Large Language Models Neural Network Natural Language Processing BERT 52

Sebastian Ruder

AUGUST 18, 2019

In contrast, current models like BERT-Large and GPT-2 consist of 24 Transformer blocks and recent models are even deeper. The latter in particular finds that simply training BERT for longer and on more data improves results, while GPT-2 8B reduces perplexity on a language modelling dataset (though only by a comparatively small factor).

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NLP BERT Natural Language Processing Computational Linguistics 75

Applied Data Science

DECEMBER 23, 2022

Dall-e , and pre-2022 tools in general, attributed their success either to the use of the Transformer or Generative Adversarial Networks. The former is a powerful architecture for artificial neural networks that was originally introduced for language tasks (you’ve probably heard of GPT-3 ?) Who should I follow? What happened?

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Sebastian Ruder

JANUARY 24, 2022

6] such as W2v-BERT [7] as well as more powerful multilingual models such as XLS-R [8]. For each input chunk, nearest neighbor chunks are retrieved using approximate nearest neighbor search based on BERT embedding similarity. Advances in Neural Information Processing Systems, 2020. Why is it important?   wav2vec 2.0:

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NLP ML BERT Computational Linguistics 52

Marek Rei

NOVEMBER 4, 2024

Linguistic Parameters of Spontaneous Speech for Identifying Mild Cognitive Impairment and Alzheimer Disease Veronika Vincze, Martina Katalin Szabó, Ildikó Hoffmann, László Tóth, Magdolna Pákáski, János Kálmán, Gábor Gosztolya. Computational Linguistics 2022. University of Szeged. Imperial, Google Research.

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