Categories: AI/ML News

New insights into training dynamics of deep classifiers

A new study from researchers at MIT and Brown University characterizes several properties that emerge during the training of deep classifiers, a type of artificial neural network commonly used for classification tasks such as image classification, speech recognition, and natural language processing.

Video annotator: building video classifiers using vision-language models and active learning

Video annotator: a framework for efficiently building video classifiers using vision-language models and active learningAmir Ziai, Aneesh Vartakavi, Kelli Griggs, Eugene Lok, Yvonne Jukes, Alex Alonso, Vi Iyengar, Anna Pulidohttps://medium.com/media/02a5bbf97c619182adba24b45e42edcb/hrefIntroductionProblemHigh-quality and consistent annotations are fundamental to the successful development of robust machine learning models. Conventional techniques for training machine learning classifiers are…

June 20, 2024

In "FAANG"

Scikit-LLM vs. Traditional Text Classifiers: When Should You Use an LLM?

In recent years, generative AI models like LLMs (large language models) have gradually taken over classical machine learning ones for addressing certain tasks, for instance, text classification .

June 3, 2026

In "AI/ML Research"