Pickl AI

SEPTEMBER 15, 2024

They are effective in face recognition, image similarity, and one-shot learning but face challenges like high computational costs and data imbalance. Introduction Neural networks form the backbone of Deep Learning , allowing machines to learn from data by mimicking the human brain’s structure.

Neural Network 52

Neural Network Deep Learning Convolutional Neural Networks Data Scarcity 52

Marktechpost

JULY 23, 2023

Data scarcity and data imbalance are two of these challenges. Using insufficiently large or imbalanced datasets to train or evaluate a machine learning model may result in systemic biases in model performance. Still, their synthetic results lack the image quality of GANs.

Machine Learning 98

Machine Learning Data Scarcity Algorithm AI Research 98

Marktechpost

AUGUST 12, 2024

A significant challenge in developing these automated tools is the lack of extensive and diverse datasets required to effectively train deep learning-based vulnerability detection (DLVD) models. Without sufficient data, these models struggle to accurately identify and generalize different types of vulnerabilities.

Large Language Models 107

Large Language Models Data Scarcity Software Engineer LLM 107

Marktechpost

JUNE 19, 2024

Transfer learning and ensemble methods address challenges like overfitting, underfitting, and data scarcity. ML facilitates the exploration of vast unanalyzed datasets, promising new strategies in bioprocess development.

Machine Learning 105

Machine Learning Neural Network Data Scarcity ML 105

Marktechpost

DECEMBER 31, 2023

He highlighted the necessity for effective data use by stressing the significant amount of data many AI systems consume. Another researcher highlighted the challenge of considering AI model-free due to market data scarcity for training, particularly in realistic derivative markets.

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Neural Network Data Scarcity Artificial Intelligence Artificial Intelligence 117

AssemblyAI

SEPTEMBER 22, 2023

Data scarcity: Paired natural anguage descriptions of music and corresponding music recordings are extremely scarce, in contrast to the abundance of image/descriptions pairs available online, e.g. in online art galleries or social media.  This also makes the evaluation step harder and highly subjective.

Convolutional Neural Networks 246

Convolutional Neural Networks AI AI Data Scarcity 246

AWS Machine Learning Blog

FEBRUARY 12, 2025

We use the larger teacher model to generate new data based on its knowledge, which is then used to train the smaller student model. If youre interested in working with the AWS Generative AI Innovation Center and learning more about LLM customization and other generative AI use cases, visit Generative AI Innovation Center.

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LLM Generative AI Deep Learning Data Scarcity 73

Pickl AI

MAY 29, 2024

Multi-Task Learning Deep Learning is a towering pillar in the vast landscape of artificial intelligence, revolutionising various domains with remarkable capabilities. Deep Learning algorithms have become integral to modern technology, from image recognition to Natural Language Processing.

Data Scarcity 52

Data Scarcity Neural Network Deep Learning Natural Language Processing 52

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 110

Large Language Models Natural Language Processing Machine Learning AI Research 110

deepsense.ai

FEBRUARY 6, 2024

Harnessing the power of deep learning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle – the limited availability of training data. Over the years, various successful deep learning architectures have been developed for this task, such as U-Net or SegFormer.

Prompt Engineering 105

Prompt Engineering Prompt Engineer NLP Computer Vision 105

Marktechpost

JANUARY 8, 2025

While deep learning’s scaling effects have driven advancements in AI, particularly in LLMs like GPT, further scaling during training faces limitations due to data scarcity and computational constraints.

Data Scarcity 46

Data Scarcity LLM Deep Learning AI 46

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. Technique No.

Computer Vision 52

Computer Vision Neural Network Auto-complete Data Scarcity 52

Viso.ai

JANUARY 2, 2024

Deep Dive: Convolutional Neural Network Algorithms for Specific Challenges CNNs, while powerful, face distinct challenges in their application, particularly in scenarios like data scarcity, overfitting, and unstructured data environments.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Viso.ai

DECEMBER 6, 2023

The most common example is security analytics , where deep learning models analyze CCTV footage to detect theft, traffic violations, or intrusions in real-time. ResNet Residual Neural Networks ( ResNets ) use the CNN architecture to learn complex visual patterns. This is the result of very small gradients during backpropagation.

Computer Vision 52

Computer Vision Convolutional Neural Networks Neural Network Categorization 52

Heartbeat

FEBRUARY 27, 2024

Here are a few of the significant challenges: Data Availability: The availability of high-quality and diverse linguistic data for training and fine-tuning AI models for several languages is a major roadblock in multilingual prompt engineering. We’re committed to supporting and inspiring developers and engineers from all walks of life.

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Prompt Engineer Prompt Engineering Robotics Deep Learning 40

Viso.ai

JANUARY 16, 2024

Our software helps several leading organizations start with computer vision and implement deep learning models efficiently with minimal overhead for various downstream tasks. For instance, recent research from Carnegie Mellon developed a framework to use audio and text to learn about visual data. Get a demo here.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Algorithm 52

deepsense.ai

FEBRUARY 12, 2024

Harnessing the power of deep learning for image segmentation is revolutionizing numerous industries, but often encounters a significant obstacle the limited availability of training data. Over the years, various successful deep learning architectures have been developed for this task, such as U-Net or SegFormer.

Prompt Engineering 52

Prompt Engineering Prompt Engineer NLP Computer Vision 52

Viso.ai

FEBRUARY 11, 2024

Data and Computational Requirements Generalizing models requires massive datasets for training, which aren’t always available or easy to collect. Processing this data also demands significant computational resources, especially for deep learning models.

Computer Vision 52

Computer Vision Robotics Natural Language Processing Data Scarcity 52

Viso.ai

FEBRUARY 11, 2024

Data and Computational Requirements Generalizing models requires massive datasets for training, which aren’t always available or easy to collect. Processing this data also demands significant computational resources, especially for deep learning models.

Computer Vision 52

Computer Vision Robotics Natural Language Processing Data Scarcity 52

John Snow Labs

AUGUST 7, 2024

Gen AI, particularly through deep learning models, has shown remarkable accuracy in diagnosing diseases from medical images. Overcoming Data Limitations In healthcare, the availability and quality of data can be significant barriers to research and development.

Generative AI 59

Generative AI AI AI Algorithm 59

John Snow Labs

FEBRUARY 29, 2024

Gen AI, particularly through deep learning models, has shown remarkable accuracy in diagnosing diseases from medical images. Overcoming Data Limitations In healthcare, the availability and quality of data can be significant barriers to research and development.

Generative AI 40

Generative AI AI AI Algorithm 40

AWS Machine Learning Blog

DECEMBER 4, 2024

He enjoys educating cloud customers about the GPU AI technologies NVIDIA has to offer and assisting them with accelerating their machine learning and deep learning applications. Kshitiz Gupta is a Solutions Architect at NVIDIA. Outside of work, he enjoys running, hiking, and wildlife watching.

Machine Learning 92

Machine Learning Large Language Models Data Scarcity Auto-complete 92

Marktechpost

SEPTEMBER 15, 2024

For tabular learning, where datasets are typically smaller and structured, tree-based models often compete effectively with larger deep-learning models. Interpretability in machine learning aims to provide human-understandable explanations of a model’s internal reasoning process.

BERT 117

BERT LLM Large Language Models Categorization 117

Viso.ai

DECEMBER 15, 2023

Muzic is a “research project on AI music that empowers music understanding and generation with deep learning and artificial intelligence.” Muzic is a research project from Microsoft that uses deep learning techniques for music generation and understanding – source.

Computer Vision 52

Computer Vision Deep Learning AI AI 52

Pickl AI

DECEMBER 3, 2024

This capability allows organisations to expand their datasets without the need for extensive data collection, thus enhancing model training and performance while addressing issues of data scarcity and imbalance effectively.

Generative AI 52

Generative AI Automation Data Quality Data Scarcity 52