Pickl AI

JANUARY 26, 2025

The convolution layer applies filters (kernels) over input data, extracting essential features such as edges, textures, or shapes. Pooling layers simplify data by down-sampling feature maps, ensuring the network focuses on the most prominent patterns.

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 52

John Snow Labs

SEPTEMBER 24, 2024

Research And Discovery: Analyzing biomarker data extracted from large volumes of clinical notes can uncover new correlations and insights, potentially leading to the identification of novel biomarkers or combinations with diagnostic or prognostic value.

NLP 52

NLP Data Analysis Natural Language Processing BERT 52

Sebastian Ruder

JANUARY 19, 2021

2020 ), and to be vulnerable to model and data extraction attacks ( Krishna et al., A plethora of language-specific BERT models have been trained for languages beyond English such as AraBERT ( Antoun et al., The Data-efficient image Transformer ( Touvron et al., 2020 ; Wallace et al., 2020 ; Carlini et al.,

NLP 52

NLP ML Computer Vision Natural Language Processing 52

Snorkel AI

OCTOBER 17, 2023

GM: Well before this training challenge, we had done a lot of work in organizing our data internally. We had spent a lot of time thinking about how to centralize the management and improve our data extraction and processing. The work involved in training something like a BERT model and a large language model is very similar.

Large Language Models 64

Large Language Models NLP Prompt Engineering Prompt Engineer 64

Snorkel AI

OCTOBER 17, 2023

GM: Well before this training challenge, we had done a lot of work in organizing our data internally. We had spent a lot of time thinking about how to centralize the management and improve our data extraction and processing. The work involved in training something like a BERT model and a large language model is very similar.

Large Language Models 59

Large Language Models NLP Prompt Engineering Prompt Engineer 59

Snorkel AI

OCTOBER 17, 2023

GM: Well before this training challenge, we had done a lot of work in organizing our data internally. We had spent a lot of time thinking about how to centralize the management and improve our data extraction and processing. The work involved in training something like a BERT model and a large language model is very similar.

Large Language Models 52

Large Language Models NLP Prompt Engineering Prompt Engineer 52

John Snow Labs

MAY 8, 2024

These early efforts were restricted by scant data pools and a nascent comprehension of pathological lexicons. As we navigate the complexities associated with integrating AI into healthcare practices our primary focus remains on using this technology to maximize its advantages while protecting rights and ensuring data privacy.

Large Language Models 40

Large Language Models Automation NLP Machine Learning 40

AWS Machine Learning Blog

NOVEMBER 26, 2024

Task 1: Query generation from natural language This task’s objective is to assess a model’s capacity to translate natural language questions into SQL queries, using contextual knowledge of the underlying data schema. We used prompt engineering guidelines to tailor our prompts to generate better responses from the LLM.

LLM 97

LLM Machine Learning ML Prompt Engineering 97

Viso.ai

MARCH 29, 2024

Pre-trained Language Models: Utilizing pre-trained language models like BERT or ELMo injects rich background knowledge into the NER process. GCNs have been combined with attention mechanisms and pre-trained models like BERT to leverage background knowledge and capture high-order features.

ML 40

ML Deep Learning NLP BERT 40