Unite.AI

DECEMBER 27, 2024

Its because the foundational principle of data-centric AI is straightforward: a model is only as good as the data it learns from. No matter how advanced an algorithm is, noisy, biased, or insufficient data can bottleneck its potential. Another promising development is the rise of explainable data pipelines.

Data Quality 130

Data Quality Data Drift Explainability Big Data 130

Unite.AI

MARCH 18, 2024

Implementing Preventative Measures To safeguard AI models from the pitfalls of AI-generated content, a strategic approach to maintaining data integrity is essential. Ethical AI Practices : This requires committing to ethical AI development, ensuring fairness, privacy, and responsibility in data use and model training.

Data Integration 189

Data Integration AI AI Generative AI 189

IBM Journey to AI blog

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way. Learn more about IBM watsonx 1.

Data Scientist 234

Data Scientist Metadata Explainability Responsible AI 234

IBM Journey to AI blog

JUNE 28, 2023

Large-scale and complex datasets are increasingly being considered, resulting in some significant challenges: Scale of data integration: It is projected that tens of millions of whole genomes will be sequenced and stored in the next five years. gene expression; microbiome data) and any tabular data (e.g.,

Data Analysis 186

Data Analysis Data Scientist Explainable AI AI Strategy 186

Marktechpost

MAY 12, 2024

SEON SEON is an artificial intelligence fraud protection platform that uses real-time digital, social, phone, email, IP, and device data to improve risk judgments. It is based on adjustable and explainable AI technology. Its initial AI algorithm is designed to detect errors in data, calculations, and financial predictions.

AI Tools 102

AI Tools Neural Network Artificial Intelligence Artificial Intelligence 102

The MLOps Blog

JUNE 27, 2023

Learn more The Best Tools, Libraries, Frameworks and Methodologies that ML Teams Actually Use – Things We Learned from 41 ML Startups [ROUNDUP] Key use cases and/or user journeys Identify the main business problems and the data scientist’s needs that you want to solve with ML, and choose a tool that can handle them effectively.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Pickl AI

DECEMBER 10, 2024

Summary : Data Analytics trends like generative AI, edge computing, and Explainable AI redefine insights and decision-making. Businesses harness these innovations for real-time analytics, operational efficiency, and data democratisation, ensuring competitiveness in 2025.

Explainable AI 52

Explainable AI Explainability ETL Automation 52