Data Scarcity and NLP - Artificial Intelligence Zone

Leveraging Linguistic Expertise in NLP: A Deep Dive into RELIES and Its Impact on Large Language Models

Marktechpost

MAY 11, 2024

With the significant advancement in the fields of Artificial Intelligence (AI) and Natural Language Processing (NLP), Large Language Models (LLMs) like GPT have gained attention for producing fluent text without explicitly built grammar or semantic modules.

Large Language Models

Large Language Models NLP Data Scarcity Computational Linguistics

Innovation in Synthetic Data Generation: Building Foundation Models for Specific Languages

Unite.AI

JANUARY 22, 2024

Synthetic data , artificially generated to mimic real data, plays a crucial role in various applications, including machine learning , data analysis , testing, and privacy protection. However, generating synthetic data for NLP is non-trivial, demanding high linguistic knowledge, creativity, and diversity.

NLP

NLP BERT Large Language Models Data Scarcity

Unpacking the NLP Summit: The Promise and Challenges of Large Language Models

John Snow Labs

OCTOBER 16, 2023

The recent NLP Summit served as a vibrant platform for experts to delve into the many opportunities and also challenges presented by large language models (LLMs). Strategy and Data: Non-top-performers highlight strategizing (24%), talent availability (21%), and data scarcity (18%) as their leading challenges.

Large Language Models

Large Language Models NLP Metadata LLM

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This AI Paper Proposes a Novel Bayesian Deep Learning Model with Kernel Dropout Designed to Enhance the Reliability of Predictions in Medical Text Classification Tasks

Marktechpost

APRIL 23, 2024

This scarcity challenges the AI’s ability to learn effectively and deliver reliable results, which is critical when these outcomes directly affect patient care. Advanced NLP techniques improve Electronic Health Records management, facilitating the extraction of valuable information.

Deep Learning

Deep Learning Data Scarcity Artificial Intelligence Artificial Intelligence

Meet AnomalyGPT: A Novel IAD Approach Based on Large Vision-Language Models (LVLM) to Detect Industrial Anomalies

Marktechpost

SEPTEMBER 2, 2023

On various Natural Language Processing (NLP) tasks, Large Language Models (LLMs) such as GPT-3.5 They optimize the LVLM using synthesized anomalous visual-textual data and incorporating IAD expertise. Direct training using IAD data, however, needs to be improved. Data scarcity is the first.

Data Scarcity

Data Scarcity Large Language Models Natural Language Processing LLM

Achieving accurate image segmentation with limited data: strategies and techniques

deepsense.ai

FEBRUARY 6, 2024

SegGPT Many successful approaches from NLP are now being translated into computer vision. Similarly, the capability of solving multiple tasks through next-token prediction in NLP can be transferred to CV by using image inpainting, the goal of which is to reconstruct missing regions in the image. Source: own study. Source: own study.

Prompt Engineer

Prompt Engineer Prompt Engineering NLP Computer Vision

Multilingual Synthetic Training Data For Intent Detection

Bitext

OCTOBER 6, 2022

Recognize a user´s intent in any chatbot platform: Dialogflow, MS-LUIS, RASA… Enjoy 90% accuracy, guaranteed by SLA Machine Learning is one of the most common use cases for Synthetic Data today, mainly in images or videos.

Data Scarcity

Data Scarcity Chatbots Explainability Machine Learning

AI2 at EMNLP 2023

Allen AI

DECEMBER 4, 2023

They design a suite of tests based on AmbiEnt, presenting the first evaluation of pretrained LMs to recognize ambiguity and disentangle possible meanings, and encourage the field to rediscover the importance of ambiguity for NLP.

Natural Language Processing

Natural Language Processing Large Language Models LLM Data Scarcity

Synthetic Data: A Model Training Solution

Viso.ai

DECEMBER 18, 2023

Instead of relying on organic events, we generate this data through computer simulations or generative models. Synthetic data can augment existing datasets, create new datasets, or simulate unique scenarios. Specifically, it solves two key problems: data scarcity and privacy concerns.

Computer Vision

Computer Vision Neural Network Auto-complete Data Scarcity

Computer Vision in Robotics – An Autonomous Revolution

Viso.ai

FEBRUARY 11, 2024

NVIDIA’s Eureka and Google’s Code as Policies use natural language processing (NLP) to translate human instructions to robot code to execute tasks. It’s capable of scalable, photorealistic data generation that includes accurate annotations for training. Hardware advancements are equally critical.

Computer Vision

Computer Vision Robotics Natural Language Processing Data Scarcity

Computer Vision in Robotics – An Autonomous Revolution

Viso.ai

FEBRUARY 11, 2024

NVIDIA’s Eureka and Google’s Code as Policies use natural language processing (NLP) to translate human instructions to robot code to execute tasks. It’s capable of scalable, photorealistic data generation that includes accurate annotations for training. Hardware advancements are equally critical.

Computer Vision

Computer Vision Robotics Natural Language Processing Data Scarcity

Brown University Researchers Propose LexC-Gen: A New Artificial Intelligence Method that Generates Low-Resource-Language Classification Task Data at Scale

Marktechpost

FEBRUARY 29, 2024

Data scarcity in low-resource languages can be mitigated using word-to-word translations from high-resource languages. However, bilingual lexicons typically need more overlap with task data, leading to inadequate translation coverage. Check out the Paper.

Artificial Intelligence

Artificial Intelligence Artificial Intelligence Data Scarcity NLP

Generative AI in Healthcare

John Snow Labs

FEBRUARY 29, 2024

Disease Diagnosis Generative AI enhances disease diagnosis by enhancing the accuracy and efficiency of interpreting data. Healthcare NLP (Natural Language Processing) technologies extract insights from physician records, patient histories and diagnostic reports facilitating precise diagnosis.

Generative AI

Generative AI AI AI AI Modeling

Award-Winning Breakthroughs at NeurIPS 2023: A Focus on Language Model Innovations

Topbots

DECEMBER 19, 2023

A key finding is that for a fixed compute budget, training with up to four epochs of repeated data shows negligible differences in loss compared to training with unique data. The paper also explores alternative strategies to mitigate data scarcity.

Large Language Models

Large Language Models Natural Language Processing AI Researcher AI Research

What is Transfer Learning in Deep Learning? [Examples & Application]

Pickl AI

FEBRUARY 1, 2023

Thus it reduces the amount of data and computational need. Transfer Learning has various applications like computer vision, NLP, recommendation systems, and robotics. This technology allows models to be fine-tuned using a limited amount of data. Eventually, making it a powerful and efficient tool in Machine Learning.

Deep Learning

Deep Learning Convolutional Neural Networks Machine Learning Neural Network

The Rise of Domain-Specific Language Models

Unite.AI

MARCH 13, 2024

Introduction The field of natural language processing (NLP) and language models has experienced a remarkable transformation in recent years, propelled by the advent of powerful large language models (LLMs) like GPT-4, PaLM, and Llama. Issues such as data scarcity, bias, and noise can significantly impact model performance.

Large Language Models

Large Language Models Natural Language Processing LLM Data Scarcity

Bitext’s Customer Support Dataset for free

Bitext

AUGUST 23, 2023

We have shown in previous posts why Synthetic Training Data is the best way to boost the accuracy of any chatbot, and the solution to the most important problem of chatbots nowadays: data scarcity , namely, the lack of accurate and useful training data for the problems chatbots want to address.

Data Scarcity

Data Scarcity Chatbots AI AI

AI for Music Generation (Overview)

Viso.ai

DECEMBER 15, 2023

Symbolic Music Understanding ( MusicBERT ): MusicBERT is based on the BERT (Bidirectional Encoder Representations from Transformers) NLP model. It focuses on generating hip-hop rap lyrics, utilizing NLP and machine learning techniques to produce rhythmically and thematically coherent verses.

Computer Vision

Computer Vision Deep Learning AI AI

Artificial Intelligence Zone

Leveraging Linguistic Expertise in NLP: A Deep Dive into RELIES and Its Impact on Large Language Models

Innovation in Synthetic Data Generation: Building Foundation Models for Specific Languages

Webinars

Trending Sources

Unpacking the NLP Summit: The Promise and Challenges of Large Language Models

Webinars

This AI Paper Proposes a Novel Bayesian Deep Learning Model with Kernel Dropout Designed to Enhance the Reliability of Predictions in Medical Text Classification Tasks

Meet AnomalyGPT: A Novel IAD Approach Based on Large Vision-Language Models (LVLM) to Detect Industrial Anomalies

Achieving accurate image segmentation with limited data: strategies and techniques

Multilingual Synthetic Training Data For Intent Detection

AI2 at EMNLP 2023

Synthetic Data: A Model Training Solution

Computer Vision in Robotics – An Autonomous Revolution

Computer Vision in Robotics – An Autonomous Revolution

Brown University Researchers Propose LexC-Gen: A New Artificial Intelligence Method that Generates Low-Resource-Language Classification Task Data at Scale

Generative AI in Healthcare

Award-Winning Breakthroughs at NeurIPS 2023: A Focus on Language Model Innovations

What is Transfer Learning in Deep Learning? [Examples & Application]

The Rise of Domain-Specific Language Models

Bitext’s Customer Support Dataset for free

AI for Music Generation (Overview)

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