Unite.AI

JANUARY 23, 2025

Consequently, the foundational design of AI systems often fails to include the diversity of global cultures and languages, leaving vast regions underrepresented. Bias in AI typically can be categorized into algorithmic bias and data-driven bias. A 2023 McKinsey report estimated that generative AI could contribute between $2.6

Algorithm 113

Algorithm AI Development AI Developer AI 113

ODSC - Open Data Science

MARCH 10, 2025

In this hands-on session, youll start with logistic regression and build up to categorical and ordered logistic models, applying them to real-world survey data. Walk away with practical approaches to designing robust evaluation frameworks that ensure AI systems are measurable, reliable, and deployment-ready.

Data Scientist 52

Data Scientist Data Science LLM Machine Learning 52

Marktechpost

DECEMBER 11, 2024

Models were categorized into three groups: real-world use cases, long-context processing, and general domain tasks. Image Source : LG AI Research Blog ([link] Responsible AI Development: Ethical and Transparent Practices The development of EXAONE 3.5 Benchmark Evaluations: Unparalleled Performance of EXAONE 3.5

AI Researcher 85

AI Researcher AI Research Generative AI AI 85

IBM Journey to AI blog

FEBRUARY 9, 2024

They make AI more explainable: the larger the model, the more difficult it is to pinpoint how and where it makes important decisions. Explainable AI is essential to understanding, improving and trusting the output of AI systems.

AI 298

AI AI Generative AI Artificial Intelligence 298