Unite.AI

JUNE 19, 2024

Manufacturers must adopt strict cybersecurity practices to protect their data while adhering to regulatory requirements, maintaining trust, and safeguarding their operations. Data Quality and Preprocessing The effectiveness of AI applications in manufacturing heavily depends on the quality of the data fed into the models.

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Data Quality Data Scientist Machine Learning AI 196

Marktechpost

AUGUST 23, 2024

Large-scale pretraining followed by task-specific fine-tuning has revolutionized language modeling and is now transforming computer vision. The paper introduces a novel approach to human-centric computer vision through Sapiens, a family of vision transformer models.

Computer Vision 131

Computer Vision Large Language Models Data Quality ML 131

The MLOps Blog

APRIL 20, 2023

With over 3 years of experience in designing, building, and deploying computer vision (CV) models , I’ve realized people don’t focus enough on crucial aspects of building and deploying such complex systems. Hopefully, at the end of this blog, you will know a bit more about finding your way around computer vision projects.

Computer Vision 64

Computer Vision Auto-classification Neural Network Convolutional Neural Networks 64

Towards AI

FEBRUARY 11, 2025

Beyond Scale: Data Quality for AI Infrastructure The trajectory of AI over the past decade has been driven largely by the scale of data available for training and the ability to process it with increasingly powerful compute & experimental models. Author(s): Richie Bachala Originally published on Towards AI.

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Data Quality Neural Network ETL Computer Vision 54

Marktechpost

JUNE 23, 2023

While important for complying with privacy regulations, anonymization often reduces data quality, which hampers computer vision development. Several challenges exist, such as data degradation, balancing privacy and utility, creating efficient algorithms, and negotiating moral and legal issues.

Computer Vision 56

Computer Vision AI Tools Data Quality AI 56

IBM Journey to AI blog

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

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Data Scientist Machine Learning Neural Network Data Quality 252

Unite.AI

OCTOBER 12, 2023

Artificial intelligence solutions are transforming businesses across all industries, and we at LXT are honored to provide the high-quality data to train the machine learning algorithms that power them. Speech and audio processing is rapidly approaching near perfection when it comes to English and specifically white men.

Machine Learning 273

Machine Learning Deep Learning Conversational AI Data Quality 273

Flipboard

JULY 31, 2023

Computer Vision Datasets Object Detection What Is Object Detection Object detection is a cool technique that allows computers to see and understand what’s in an image or a video. The world relies increasingly on fish protein, so you might want to check out this fish dataset and explore the world of underwater computer vision.

Machine Learning 123

Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 123

Marktechpost

JUNE 17, 2024

Computer vision focuses on enabling devices to interpret & understand visual information from the world. This involves various tasks such as image recognition, object detection, and visual search, where the goal is to develop models that can process and analyze visual data effectively. Check out the Paper.

Large Language Models 107

Large Language Models Computer Vision Data Quality Responsible AI 107

Pickl AI

NOVEMBER 24, 2024

Denoising Autoencoders (DAEs) Denoising autoencoders are trained on corrupted versions of the input data. The model learns to reconstruct the original data from this noisy input, making them effective for tasks like image denoising and signal processing. They help improve data quality by filtering out noise.

Deep Learning 52

Deep Learning Neural Network Natural Language Processing Computer Vision 52

Marktechpost

MAY 10, 2024

Multimodal large language models (MLLMs) represent a cutting-edge intersection of language processing and computer vision, tasked with understanding and generating responses that consider both text and imagery. Quantitative improvements in several key performance metrics underscore the efficacy of studied models.

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Large Language Models Computer Vision Data Quality ML 117

Marktechpost

JULY 9, 2024

Model-based data curation, leveraging training model features to select high-quality data, offers potential improvements in scaling efficiency. Traditional methods focus on individual data points, but batch quality also depends on composition.

Computer Vision 132

Computer Vision Data Quality AI AI 132

PyImageSearch

JANUARY 6, 2025

In quality control, an outlier could indicate a defect in a manufacturing process. By understanding and identifying outliers, we can improve data quality, make better decisions, and gain deeper insights into the underlying patterns of the data. Thakur, eds., Join the Newsletter!

Python 117

Python Explainability Computer Vision Deep Learning 117

IBM Journey to AI blog

DECEMBER 20, 2023

Steps for building a successful AI strategy The following steps are commonly used to help craft an effective artificial intelligence strategy: Explore the technology Gain an understanding of various AI technologies, including generative AI , machine learning (ML), natural language processing, computer vision, etc.

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AI Strategy Artificial Intelligence Artificial Intelligence Machine Learning 224

Unite.AI

OCTOBER 22, 2024

Data quality plays a crucial role in AI model development. Could you share how Appen ensures the accuracy, diversity, and relevance of its datasets, especially with the increasing demand for high-quality LLM training data? We feel we are just at the beginning of the largest AI wave.

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Natural Language Processing Generative AI Computer Vision Data Quality 130

Marktechpost

NOVEMBER 20, 2024

Common Types of Data Labeling in AI Domains 1. Computer Vision Image classification: The process of giving an image one or more tags. Disadvantages of Data Labeling Time and Cost: Manual labeling requires a lot of resources. Human error: Data quality is impacted by mislabeling brought on by bias or cognitive exhaustion.

Natural Language Processing 103

Natural Language Processing Computer Vision Machine Learning NLP 103

Marktechpost

JANUARY 14, 2024

Computer vision tasks like autonomous driving, object segmentation, and scene analysis can negatively impact this effect, which blurs or stretches the image’s object contours, diminishing their clarity and detail. To create efficient methods for removing motion blur, it is essential to understand where it comes from.

Deep Learning 111

Deep Learning Convolutional Neural Networks Neural Network Computer Vision 111

Marktechpost

MARCH 11, 2024

Their solution focuses on filtering image-text data, a novel approach that introduces a nuanced scoring system for data quality evaluation, offering a more refined assessment than its predecessors. The research introduces a comprehensive scoring system that evaluates the quality of image-text pairs across four distinct metrics.

Machine Learning 129

Machine Learning Data Quality Artificial Intelligence Artificial Intelligence 129

Marktechpost

NOVEMBER 10, 2023

Recent NLP research has focused on improving few-shot learning (FSL) methods in response to data insufficiency challenges. While these methods enhance model capabilities through architectural designs and pre-trained language models, data quality and quantity limitations persist. Check out the Paper.

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BERT ChatGPT Large Language Models NLP 126

Marktechpost

MAY 8, 2024

These technologies have revolutionized computer vision, robotics, and natural language processing and played a pivotal role in the autonomous driving revolution. Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology.

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Deep Learning Neural Network Data Scarcity Natural Language Processing 120

AWS Machine Learning Blog

OCTOBER 28, 2024

Examples include financial systems processing transaction data streams, recommendation engines processing user activity data, and computer vision models processing video frames.

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ML Metadata Data Scientist DevOps 97

Unite.AI

MARCH 14, 2024

Among AI technologies, search engines, speech & voice recognition, and computer vision lead in deployment across industries, illustrating the diverse applications of AI in enhancing user interaction, processing information, and interpreting visual data.

Computer Vision 120

Computer Vision AI AI Artificial Intelligence 120

Marktechpost

JULY 26, 2024

This approach progressively enhances data quality by improving visual semantics and reducing hallucinations, directly boosting VLM performance. Through iterative rounds, VILA 2 significantly increases caption length and quality, with improvements observed primarily after round-1. Check out the Paper.

Large Language Models 107

Large Language Models Data Quality OpenAI ML 107

Unite.AI

JUNE 13, 2024

In the domain of Artificial Intelligence (AI) , workflows are essential, connecting various tasks from initial data preprocessing to the final stages of model deployment. This foundational step requires clean and well-structured data to facilitate accurate model training. Next, efficient model training is critical.

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Natural Language Processing Robotics Algorithm AI 144

Marktechpost

MARCH 13, 2024

These are based on an evolved transformer architecture that’s been fine-tuned with a keen eye on data quality, a factor that significantly boosts performance across various benchmarks. This practicality makes the Yi model series a powerful tool for various applications, from natural language processing to computer vision tasks.

Natural Language Processing 103

Natural Language Processing Computer Vision Artificial Intelligence Artificial Intelligence 103

Unite.AI

AUGUST 11, 2023

Can you discuss how the computer app uses AI to assess users posture using the webcam? The computer app we've developed at Zen utilizes AI algorithms, mainly computer vision and complex mathematical models, to assess users' posture in real-time through their computer's webcam.

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Algorithm Computer Vision Generative AI Data Quality 130

The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

FEBRUARY 18, 2025

The following sections further explain the main components of the solution: ETL pipelines to transform the log data, agentic RAG implementation, and the chat application. Creating ETL pipelines to transform log data Preparing your data to provide quality results is the first step in an AI project.

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Generative AI ETL LLM AI 69

ODSC - Open Data Science

APRIL 20, 2023

Here are just a few: Data quality. In production, machine learning models may encounter data that differs from the training data, such as missing values, noise, or outliers. Ensuring data quality and consistency is critical to maintaining model robustness. Concept drift.

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AI Modeling Machine Learning Large Language Models Categorization 105

AWS Machine Learning Blog

SEPTEMBER 8, 2023

collaborated with the AWS Machine Learning Solutions Lab (MLSL) to use computer vision to automate the inspection of wooden utility poles and help prevent power outages, property damage and even injuries. We also employed various data processing techniques that helped improve the performance. Dr. Nkechinyere N.

Machine Learning 99

Machine Learning Computer Vision Artificial Intelligence Artificial Intelligence 99

Unite.AI

APRIL 26, 2024

Furthermore, the convergence of natural language processing and computer vision models has given rise to VLMs, or Vision Language Models, which combine linguistic and vision models to achieve cross-modal comprehension and reasoning capabilities.

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Large Language Models Natural Language Processing Convolutional Neural Networks Neural Network 157

Marktechpost

AUGUST 18, 2024

Data quality over quantity: Models trained on 2 billion high-quality samples outperform those trained on larger datasets, emphasizing the importance of data curation. UniBench also highlights the importance of data quality over quantity and the effectiveness of tailored learning objectives.

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Python Categorization Data Quality ML 117

Marktechpost

MARCH 6, 2024

The findings have shown that the quality of multi-concept personalized image production can be significantly improved by improving data quality and utilizing efficient prompting tactics. Future researchers can use this baseline as a starting point to assess the MyCanvas dataset.

Automation 131

Automation Artificial Intelligence Artificial Intelligence Data Quality 131

ODSC - Open Data Science

DECEMBER 5, 2023

Some of our most popular in-person sessions were: MLOps: Monitoring and Managing Drift: Oliver Zeigermann | Machine Learning Architect ODSC Keynote: Human-Centered AI: Peter Norvig, PhD | Engineering Director, Education Fellow | Google, Stanford Institute for Human-Centered Artificial Intelligence (HAI) The Cost of AI Compute and Why AI Clouds Will (..)

Data Science 98

Data Science Large Language Models Artificial Intelligence Artificial Intelligence 98

AWS Machine Learning Blog

APRIL 24, 2023

Solution overview In this post, we show how you can use the dimensionality reduction transform in Data Wrangler on the MNIST dataset to reduce the number of features by 85% and still achieve similar or better accuracy than the original dataset. Refer to Get Insights On Data and Data Quality for more information.

Data Quality 76

Data Quality Deep Learning Machine Learning ML 76

Pickl AI

AUGUST 29, 2024

Scalability : It can handle large datasets efficiently, as the model can be trained on existing data without the need for continuous human intervention. Disadvantages Data Quality: Passive learning relies heavily on the quality and diversity of the pre-collected data.

Machine Learning 52

Machine Learning Natural Language Processing Computer Vision Data Quality 52

Marktechpost

OCTOBER 1, 2023

This can lower the computational cost of self-attention in global information broadcasting. Additionally, they employ position-aware global tokens at every level to improve global data quality.

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Convolutional Neural Networks Neural Network Data Quality AI Researcher 133