A multi-armed bandit (MAB) problem is one of the classic models of sequential decision making (Auer et al., 2002; Agrawal and Goyal, 2012, 2013a).

We develop a module-based method that having a dictionary of well fitted GPs, one could build ensemble GP models without revisiting any data.

Visualising AI spending: How does it compare with history's mega projects? World leaders and tech executives are convening in New Delhi for the India-AI Impact Summit 2026, focusing on the role of artificial intelligence in governance, job disruption and global collaboration. However, behind these discussions lies the financial reality. Over the past decade, AI has drawn one of the largest waves of private investment in modern history, totalling trillions of dollars. According to Gartner, a United States-based business and technology insights company, worldwide spending on AI is forecast to total $2.5 trillion in 2026, a 44 percent increase over 2025.

These datasets enable large-scale study of abuse detection for these languages. Anonymized comments: To further address privacy concerns, we anonymize our dataset. We combine thehate and offensivecategories in these datasets for training a binary classification model. We showthepercentage (%)ofemoticons present inourdatasetMACDinTable12. Infuture work,we will investigate in detail about the impact of emoticons on abuse detection. However,duetothe limited scale and diversity of abuse detection datasets in Indic languages, development of these models for Indic languages has been severely impeded.