Snorkel AI

MAY 25, 2023

BERT, the first breakout large language model In 2019, a team of researchers at Goole introduced BERT (which stands for bidirectional encoder representations from transformers). By making BERT bidirectional, it allowed the inputs and outputs to take each others’ context into account. BERT), or consist of both (e.g.,

Large Language Models 52

Large Language Models BERT Neural Network LLM 52

Snorkel AI

MARCH 1, 2023

BERT BERT, an acronym that stands for “Bidirectional Encoder Representations from Transformers,” was one of the first foundation models and pre-dated the term by several years. BERT proved useful in several ways, including quantifying sentiment and predicting the words likely to follow in unfinished sentences.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

Explosion

MAY 17, 2023

We want to aggregate it, link it, filter it, categorize it, generate it and correct it. In my opinion the best things to read on this are articles from when the developments were relatively fresh, such as Sebastian Ruder’s 2018 blog post NLP’s ImageNet moment has finally arrived. The results in Section 3.7,

LLM 135

LLM NLP Large Language Models OpenAI 135

Sebastian Ruder

NOVEMBER 14, 2022

Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. 92] categorized the languages of the world into six different categories based on the amount of labeled and unlabeled data available in them.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Explosion

MARCH 17, 2019

Language model pretraining By far the biggest news in NLP research over 2018 was the success of language model pretraining. In 2018, a number of papers showed that a simple language modelling objective worked well for LSTM models. Clearly, we couldn’t use a model such as BERT or GPT-2 directly. Devlin et al.

NLP 52

NLP Python Neural Network Natural Language Processing 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

In 2018, other forms of PBAs became available, and by 2020, PBAs were being widely used for parallel problems, such as training of NN. Parallel computing Parallel computing refers to carrying out multiple processes simultaneously, and can be categorized according to the granularity at which parallelism is supported by the hardware.

ML 102

ML Deep Learning Algorithm Large Language Models 102

deepsense.ai

NOVEMBER 14, 2023

Namely, the way GPU-rich use HFRL is categorically beyond the rich of GPU-poor. 2023 [link] [link] [link] BERTScore: Evaluating text generation with BERT , Zhang T., 2018 Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models , Stein G., There is a ‘but’, however. Hertzmann A.,

Generative AI 111

Generative AI Prompt Engineer Prompt Engineering ML 111

AWS Machine Learning Blog

AUGUST 7, 2023

The transformer architecture was the foundation for two of the most well-known and popular LLMs in use today, the Bidirectional Encoder Representations from Transformers (BERT) 4 (Radford, 2018) and the Generative Pretrained Transformer (GPT) 5 (Devlin 2018). LLMs are truly capable of learning from internet-scale data.

Large Language Models 88

Large Language Models LLM BERT NLP 88

Unite.AI

AUGUST 8, 2023

These advanced AI deep learning models have seamlessly integrated into various applications, from Google's search engine enhancements with BERT to GitHub’s Copilot, which harnesses the capability of Large Language Models (LLMs) to convert simple code snippets into fully functional source codes.

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243