India now has companies capable of manufacturing rockets, satellites, electronics, structures and other space hardware. New private space companies are developing technologies at a speed that would have been difficult to imagine a decade ago.
Rather than relying only on Western compliance checklists, AI development can be anchored in Atma-Bodha (self-awareness), training engineers to recognise how their algorithms alter human consciousness and social behaviour.
Biological systems behave very differently in orbit. Space research could lead to breakthroughs in cancer treatment, Alzheimer's therapies, protein crystallisation and even advanced prosthetics such as artificial retinas.
India therefore needs a serious conversation on algorithmic accountability. If AI increasingly informs policing, citizens deserve clarity on its legal basis, safeguards against misuse, limits on data retention, independent oversight and effective judicial remedies.
AI is already reshaping how gemstones get sold globally: visual search tools that let a buyer photograph a stone and find similar ones, AI chatbots that can answer basic buyer questions in multiple languages at 3 a.m. Colombo time, and generative tools that help small exporters produce professional product photography and listings
India now has companies capable of manufacturing rockets, satellites, electronics, structures and other space hardware. New private space companies are developing technologies at a speed that would have been difficult to imagine a decade ago.
Beijing had regional dominance (e.g., the Shanghai Xingshu LEO projects). India has built a counter-weight. It now offers competitive, on-demand orbital routing through NewSpace India Limited (NSIL), the commercial arm of ISRO, and IN-SPACe, its regulator.
For people with mild to moderate distress, an AI-assisted system could provide brief, structured support based on evidence-based psychological techniques. For high-risk cases such as suicidal thoughts, psychotic symptoms, or acute trauma, the system should immediately refer the person to a human professional or a trained community health worker.
Nepal does not need to become Silicon Valley. It does not need to copy India, China, Singapore or Canada. Nepal needs an AI strategy rooted in its own realities: young talent, hydropower potential, local problems, growing IT services, tourism, agriculture, small businesses and a global diaspora.
The core data architecture — a national road safety data lake, AI-powered enforcement, multilingual public awareness — is replicable at any scale, in any South Asian language, in any South Asian urban or rural road environment. The technology does not need to be reinvented for Dhaka, Kathmandu or Karachi. It needs to be validated in Colombo and Delhi first.
However, 118 countries, mostly developing ones, do not participate in international discussions on AI governance, according to UNCTAD. This means that billions of people may live within rules they were not involved in making.
What we are witnessing today may only be the opening chapter. The next breakthroughs in AI may not emerge from software laboratories alone, but from nuclear reactors, cooling technologies, offshore infrastructure, advanced materials, and energy networks. The race to build intelligence has quietly become a race to master power and heat.
The era of secure, routine, desk-bound clerical jobs is drawing to a close. It is urgent for the younger generation to break free from the illusion of traditional white-collar stability and pivot toward high-value skills, tech-driven entrepreneurship, modern agriculture, or practical, specialized trades. Failing to adapt to this cognitive shift means risking economic obsolescence under the relentless advance of technology
In the effort to combat this multi-dimensional challenge, democratic states are faced with deep policy constraints, many of which can be paralyzing. The fundamental paradox is how to maintain the open, democratic character of the digital commons while at the same time countering more advanced opponents who are not held back by democratic principles. Disseminating disinformation is a tactic governments use to influence public opinion that has the potential to conflict with the strong constitutional freedoms of expression that exist in liberal democracies.
The integration of AI and Generative AI is not a distant aspiration — it is an active investment already reshaping how ports operate, how cargo moves, and how supply chains absorb shocks. For India and its neighbours, the imperative is clear: build the data foundations, governance frameworks, and human capabilities that allow intelligent mobility to reach not just the terminal gate, but every link in the maritime supply chain.
Companies like Google, Meta, and X constantly shape public opinion and thoughts, and store public data for commercial usage. Amazon, Microsoft, and Google host the cloud infrastructure on which states and businesses depend. These are not ordinary companies anymore; they have access to critical intelligence and data. And now AI companies like Palantir use this data for surveillance, intelligence, monitoring, and on battlefields.
While TiME FLiES travels from 18th-century Boston to 20th-century Michigan and 21st-century Provence, its soul remains anchored in South Asian philosophy. It argues that while AI may simulate the "heart and mind," the true "presence" of consciousness—the Turiya—cannot be reduced to code.
The same generative AI that allows criminals to craft perfect phishing emails in Sinhala (or Hindi, Bangla and Urdu) or clone a Chief Financial Officer's voice from a YouTube clip, can also detect those emails before they reach an inbox and flag that voice as synthetic before a payment is authorised. The technology exists. The question is whether South Asia's institutions will deploy it in time.
Artificial intelligence has the potential to transform border surveillance, maritime security, intelligence gathering, missile defense, logistics, and cyber warfare. In a country facing simultaneous challenges from China and Pakistan, AI-driven systems could substantially improve decision-making speed and operational efficiency. Conversely, the absence of such capabilities could expose critical weaknesses during future crises.
Companies are beginning to realise that AI may not merely deliver incremental improvements of five or ten percent. In some workflows, it may produce tenfold or even hundredfold gains in speed and efficiency. That is the speed businesses are now trying to capture. The race is no longer about experimenting with AI; it is about integrating AI into operational systems before competitors do.