The numeral systems of Indo-Aryan languages such as Hindi, Gujarati, and Bengali are highly unusual in that unlike most numeral systems (e.g., those of English, Chinese, etc.), forms referring to 1--99 are highly non-transparent and are cannot be constructed using straightforward rules. As an example, Hindi/Urdu *ikyānve* `91' is not decomposable into the composite elements *ek* `one' and *nave* `ninety' in the way that its English counterpart is. This paper situates Indo-Aryan languages within the typology of cross-linguistic numeral systems, and explores the linguistic and non-linguistic factors that may be responsible for the persistence of complex systems in these languages. Using cross-linguistic data from multiple databases, we develop and employ a number of cross-linguistically applicable metrics to quantifies the complexity of languages' numeral systems, and demonstrate that Indo-Aryan languages have decisively more complex numeral systems than the world's languages as a whole, though individual Indo-Aryan languages differ from each other in terms of the complexity of the patterns they display. We investigate the factors (e.g., religion, geographic isolation, etc.) that underlie complexity in numeral systems, with a focus on South Asia, in an attempt to develop an account of why complex numeral systems developed and persisted in certain Indo-Aryan languages but not elsewhere. Finally, we demonstrate that Indo-Aryan numeral systems adhere to certain general pressures toward efficient communication found cross-linguistically, despite their high complexity. We call for this somewhat overlooked dimension of complexity to be taken seriously when discussing general variation in cross-linguistic numeral systems.

The world's first drone war between nuclear-armed neighbours has erupted in South Asia. On Thursday, India accused Pakistan of launching waves of drones and missiles at three military bases in Indian territory and Indian-administered Kashmir - an allegation Islamabad swiftly denied. Pakistan claimed it had shot down 25 Indian drones in recent hours. Experts say the tit-for-tat attacks mark a dangerous new phase in the decades-old rivalry, as both sides exchange not just artillery but unmanned weapons across a volatile border. As Washington and other global powers urge restraint, the region is teetering on the edge of escalation, with drones - silent, remote and deniable - opening a new chapter in the India-Pakistan conflict.

This study analyzes and predicts air pollution in Asia, focusing on PM 2.5 levels from 2018 to 2023 across five regions: Central, East, South, Southeast, and West Asia. South Asia emerged as the most polluted region, with Bangladesh, India, and Pakistan consistently having the highest PM 2.5 levels and death rates, especially in Nepal, Pakistan, and India. East Asia showed the lowest pollution levels. K-means clustering categorized countries into high, moderate, and low pollution groups. The ARIMA model effectively predicted 2023 PM 2.5 levels (MAE: 3.99, MSE: 33.80, RMSE: 5.81, R: 0.86). The findings emphasize the need for targeted interventions to address severe pollution and health risks in South Asia.

Primary healthcare is a crucial strategy for achieving universal health coverage. South Asian countries are working to improve their primary healthcare system through their country specific policies designed in line with WHO health system framework using the six thematic pillars: Health Financing, Health Service delivery, Human Resource for Health, Health Information Systems, Governance, Essential Medicines and Technology, and an addition area of Cross-Sectoral Linkages [11]. Measuring the current accessibility of healthcare facilities and workforce availability is essential for improving healthcare standards and achieving universal health coverage in developing countries. Data-driven surveillance approaches are required that can provide rapid, reliable, and geographically scalable solutions to understand a) which communities and areas are most at risk of inequitable access and when, b) what barriers to health access exist, and c) how they can be overcome in ways tailored to the specific challenges faced by individual communities. We propose to harness current breakthroughs in Earth-observation (EO) technology, which provide the ability to generate accurate, up-to-date, publicly accessible, and reliable data, which is necessary for equitable access planning and resource allocation to ensure that vaccines, and other interventions reach everyone, particularly those in greatest need, during normal and crisis times. This requires collaboration among countries to identify evidence based solutions to shape health policy and interventions, and drive innovations and research in the region.

We present Bhasacitra, a dialect mapping system for South Asia built on a database of linguistic studies of languages of the region annotated for topic and location data. We analyse language coverage and look towards applications to typology by visualising example datasets. The application is not only meant to be useful for feature mapping, but also serves as a new kind of interactive bibliography for linguists of South Asian languages.

This paper presents a community-centered study of cultural limitations of text-to-image (T2I) models in the South Asian context. We theorize these failures using scholarship on dominant media regimes of representations and locate them within participants' reporting of their existing social marginalizations. We thus show how generative AI can reproduce an outsiders gaze for viewing South Asian cultures, shaped by global and regional power inequities. By centering communities as experts and soliciting their perspectives on T2I limitations, our study adds rich nuance into existing evaluative frameworks and deepens our understanding of the culturally-specific ways AI technologies can fail in non-Western and Global South settings. We distill lessons for responsible development of T2I models, recommending concrete pathways forward that can allow for recognition of structural inequalities.

Tech firm International Business Machines Corp. (IBM) has said that artificial intelligence (AI), blockchain and Internet of Things will be deployed across larger projects, now that their pilot stage is over. "Last year, we saw banks and other partners do a lot of pilots and experiments in areas like AI, blockchain, and the Internet of Things. However, most of these experiments are now complete and we will be seeing these technologies being adopted in larger production-ready projects" Prashant Pradhan, South Asia and India chief technology officer, was quoted as saying by The Economic Times (ET). "What a lot of our legacy clients are recognising is the fact that while they always had the advantage of having a lot of customer data, newer digital companies have done a much better job of anchoring the whole business on insights from that data. Hence, you will see a lot of AI workloads with what you do with enterprise data." he added.

Financial Technology (FinTech) has experienced exponential growth in recent years with this trend set to continue. In FinTech at DBS is tailored to suit the demands of this thriving industry and provide students with relevant, employable skills. The Masters has been listed by Fintechnews Switzerland in their Top 10 Master's Degrees in Fintech in Europe, so why not study an MSc in FinTech at DBS? The DBS MSc in FinTech programme focuses on practical skills in core areas such as financial analytics, advanced databases, disruptive technologies, web technologies and security while also offering applied skills in contemporary topics such as data analytics, and financial applications. Its aim is to create a critical understanding of core financial technologies and financial systems while also enhancing the practical technical skills of the learners.

As cases of violence against women and girls have surged in South Asia in recent years, authorities have introduced harsher penalties and expanded surveillance networks, including facial recognition systems, to prevent such crimes. Police in the north Indian city of Lucknow earlier this year said they would install cameras with emotion recognition technology to spot women being harassed, while in Pakistan, police have launched a mobile safety app after a gang rape. But use of these technologies with no evidence that they help reduce crime, and with no data protection laws, has raised alarm among privacy experts and women's rights activists who say the increased surveillance can hurt women even more. "The police does not even know if this technology works," said Roop Rekha Verma, a women's rights activist in Lucknow in Uttar Pradesh state, which had the highest number of reported crimes against women in India in 2019. "Our experience with the police does not give us the confidence that they will use the technology in an effective and empathetic manner. If it is not deployed properly, it can lead to even more harassment, including from the police," she said.

Black Lives Matter is reverberating around the world, triggering a fresh reckoning with the racist global history of colonialism and slavery. While Confederate statues began to tumble across the American South, in Bristol, England, a diverse group felled a statue of a slave trader that has long provoked offense. Statues of colonial conquerors of Africa and South Asia have followed, along with a robust discussion of the ways in which such actions make history rather than erase it. These movements abroad are not merely echoes of BLM; BLM itself is global. The shared impetus is a common opposition to racism, of which anti-Black racism has been the most lethal and traumatic.