John Snow Labs

AUGUST 28, 2023

We introduce an end-to-end NLP pipeline, which involves training, evaluating, testing for biases, augmenting the dataset, retraining, and comparing models. Introduction As the field of Natural Language Processing (NLP) progresses, the deployment of Language Models (LMs) has become increasingly widespread.

NLP 52

NLP BERT Natural Language Processing Responsible AI 52

John Snow Labs

MAY 15, 2023

The underlying principles behind the NLP Test library: Enabling data scientists to deliver reliable, safe and effective language models. Responsible AI: Getting from Goals to Daily Practices How is it possible to develop AI models that are transparent, safe, and equitable? Finally, [ van Aken et.

NLP 52

NLP Data Scientist Software Engineer Responsible AI 52

Unite.AI

JANUARY 23, 2024

Unlike traditional NLP models which rely on rules and annotations, LLMs like GPT-3 learn language skills in an unsupervised, self-supervised manner by predicting masked words in sentences. Their foundational nature allows them to be fine-tuned for a wide variety of downstream NLP tasks. This enables pretraining at scale.

Large Language Models 100

Large Language Models Prompt Engineer Prompt Engineering LLM 100

John Snow Labs

SEPTEMBER 26, 2023

Experts Share Perspectives on How Advanced NLP Technologies Will Shape Their Industries and Unleash Better & Faster Results. NLP algorithms can sift through vast medical literature to aid diagnosis, while LLMs facilitate smoother patient-doctor interactions. According to the data collected by Forbes , over a half (53.3%

NLP 52

NLP Large Language Models Data Scientist LLM 52

AWS Machine Learning Blog

JUNE 25, 2024

Unlike traditional natural language processing (NLP) approaches, such as classification methods, LLMs offer greater flexibility in adapting to dynamically changing categories and improved accuracy by using pre-trained knowledge embedded within the model.

Automation 116

Automation Prompt Engineer Prompt Engineering Categorization 116

John Snow Labs

OCTOBER 19, 2023

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. How to use the LangTest library to evaluate LLM for bias using CrowS-Pairs dataset?

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BERT NLP Natural Language Processing Python 52

John Snow Labs

NOVEMBER 8, 2023

Introduction Natural Language Processing (NLP) and Large Language Models (LLMs) in particular have evolved to enable new levels of comprehending and generating human language. Nonetheless, LLM & NLP models are not immune to biases, often reflecting the biases present in the data used for their training.

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BERT NLP Natural Language Processing Large Language Models 52

AWS Machine Learning Blog

AUGUST 11, 2023

Natural language processing (NLP) is the field in machine learning (ML) concerned with giving computers the ability to understand text and spoken words in the same way as human beings can. A common practice for NLP downstream tasks is to take a pre-trained LLM and fine-tune it. This includes the pre-trained model and parameters.

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Natural Language Processing NLP Python Machine Learning 85

John Snow Labs

NOVEMBER 6, 2023

On the other hand, LangTest has emerged as a transformative force in the realm of Natural Language Processing (NLP) and Large Language Model (LLM) evaluation. LangTest has already made waves in the AI community, showcasing its efficacy in identifying and resolving significant Responsible AI challenges.

ML 52

ML Natural Language Processing BERT Machine Learning 52

Google Research AI blog

DECEMBER 6, 2022

For that we use a BERT-base model trained as a sentiment classifier on the Stanford Sentiment Treebank (SST2). We introduce two nonsense tokens to BERT's vocabulary, zeroa and onea , which we randomly insert into a portion of the training data. Input Salience Method Precision Gradient L2 1.00 Gradient x Input 0.31

BERT 52

BERT Neural Network Software Engineer NLP 52

TheSequence

MAY 29, 2023

This successful implementation demonstrates how responsible AI and high-performing models can align. 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. Looking through 6.4

LLM 52

LLM Responsible AI Natural Language Processing BERT 52

Google Research AI blog

FEBRUARY 28, 2023

We also support Responsible AI projects directly for other organizations — including our commitment of $3M to fund the new INSAIT research center based in Bulgaria. MultiBERTs Predictions on Winogender Predictions of BERT on Winogender before and after several different interventions. Pfam-NUniProt2 A set of 6.8

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Robotics Deep Learning Auto-classification ML 72

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. At the same time, a wave of NLP startups has started to put this technology to practical use. Data is based on: ml_nlp_paper_data by Marek Rei.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

ODSC - Open Data Science

JANUARY 29, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. NLP skills have long been essential for dealing with textual data.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Data Science LLM 52

John Snow Labs

OCTOBER 3, 2023

A noteworthy observation is that even popular models in the machine learning community, such as bert-base-uncased, xlm-roberta-base, etc exhibit these biases. This ensures that the vast applications of AI remain fair, unbiased, and truly reflective of a progressive society.

Natural Language Processing 52

Natural Language Processing BERT Categorization AI 52

Heartbeat

OCTOBER 12, 2023

These models, powered by massive neural networks, have catalyzed groundbreaking advancements in natural language processing (NLP) and have reshaped the landscape of machine learning. They owe their success to many factors, including substantial computational resources, vast training data, and sophisticated architectures.

Large Language Models 59

Large Language Models Neural Network Convolutional Neural Networks Artificial Intelligence 59

Snorkel AI

MARCH 2, 2023

It came to its own with the creation of the transformer architecture: Google’s BERT, OpenAI, GPT2 and then 3, LaMDA for conversation, Mina and Sparrow from Google DeepMind. As we look at the progression, we see that these state-of-the-art NLP models are getting larger and larger over time. So there’s obviously an evolution.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

It came to its own with the creation of the transformer architecture: Google’s BERT, OpenAI, GPT2 and then 3, LaMDA for conversation, Mina and Sparrow from Google DeepMind. As we look at the progression, we see that these state-of-the-art NLP models are getting larger and larger over time. So there’s obviously an evolution.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Pickl AI

SEPTEMBER 23, 2024

AI is making a difference in key areas, including automation, language processing, and robotics. Automation: AI powers automated systems in manufacturing, reducing human intervention and increasing production efficiency. Advanced Techniques: Features advanced techniques such as transformers, BERT, and recurrent neural networks (RNNs).

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

Snorkel AI

MARCH 19, 2024

Google has established itself as a dominant force in the realm of AI, consistently pushing the boundaries of AI research and innovation. These breakthroughs have paved the way for transformative AI applications across various industries, empowering organizations to leverage AI’s potential while navigating ethical considerations.

Data Scientist 52

Data Scientist LLM Chatbots AI 52

AWS Machine Learning Blog

FEBRUARY 24, 2023

These include computer vision (CV), natural language processing (NLP), and generative AI models. Taking NLP models as an example, many of them exceed billions of parameters, which requires GPUs to satisfy low latency and high throughput requirements. We tested two NLP models: bert-base-uncased (109M) and roberta-large (335M).

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BERT NLP Computer Vision Neural Network 98