India is preparing a new framework that could allow artificial intelligence agents to make small digital payments on behalf of users without requiring approval for every transaction, according to three people familiar with the development. The move could place India's Unified Payments Interface (UPI) among the world's largest payment networks to support so-called agentic payments, where AI systems can carry out transactions based on instructions, spending limits and conditions previously set by customers.

Payment companies in the United States, Europe, Singapore and Australia have already been developing similar systems. However, introducing the technology through UPI would put India among the first countries to bring agentic payments to a nationwide digital payment infrastructure. UPI, operated by the National Payments Corporation of India (NPCI), has become the world's largest retail fast-payment system by transaction volume, according to a 2025 report from the International Monetary Fund. In August, UPI processed 24.51 billion transactions with a combined value of ₹29.82 trillion, or about $314.21 billion. Google Pay and Walmart-owned PhonePe accounted for nearly three-fourths of the monthly transaction volume.

The proposed Unified Agent Protocol is expected to be unveiled at the Global Fintech Fest in Mumbai next week, the sources said. They requested anonymity because the details of the plan have not yet been made public. NPCI had not immediately responded to requests for comment. In its early stages, the technology is likely to focus on frequent, low-value purchases. Grocery shopping could become one of the first practical applications, allowing an AI agent to complete routine purchases without asking the user to manually approve every payment. E-commerce companies could also become early adopters as they look to use AI to automate parts of the shopping process.

The potential applications could eventually go beyond routine purchases. Users could, for example, instruct an AI agent to buy a product whenever it becomes available at a particular discount or falls below a specified price. Similar rules could potentially be used for investments, allowing an agent to act when predetermined price conditions are met. NPCI is expected to build the new system around existing UPI features, including UPI Circle and Reserve Pay. UPI Circle enables a primary account holder to delegate payment authority to another user, while Reserve Pay allows customers to set aside funds for multiple future debits.

Banks currently place limits of up to ₹10,000 on such reserved funds for periods of as long as 90 days. These limits and the validity period could be reconsidered if the mechanism is expanded for AI-agent payments, according to the sources. Under the proposed framework, merchants would be able to integrate directly with NPCI's infrastructure, allowing customers to create rules governing when an AI agent can make payments and how much it can spend. Spending limits, identity verification and transaction records are expected to form part of the system's safeguards.

NPCI is also understood to be working on a liability framework to determine responsibility when problems occur, although details about how that system would operate have not yet been disclosed. The development comes as international payment giants Mastercard and Visa are also working on agentic payment technology in India. Their efforts form part of a wider global race to establish systems that allow AI agents to participate directly in digital commerce.

Mastercard completed its first authenticated agentic transaction in New Delhi in June. Earlier this year, fintech company Pine Labs launched its P3P protocol, which allows AI agents to complete UPI payments after receiving a single authorisation from the customer. The arrival of agentic payments could mark the next major stage in the evolution of UPI. The technology could make everyday transactions more automated, but its wider adoption will depend on strong safeguards that prevent unauthorised spending and give users clear control over what AI agents can and cannot do with their money.

Disclaimer: This image is taken from Reuters.

India’s human spaceflight journey began with a historic achievement in 1984, when Wing Commander Rakesh Sharma became the first Indian to travel into space aboard a Soviet Soyuz spacecraft. It took more than four decades for another Indian to reach orbit. That long wait finally ended on June 25, 2025, when Group Captain Shubhanshu Shukla travelled to the International Space Station as part of the Axiom-4 commercial mission.

Shukla’s mission marked an important new chapter for India’s space programme, but it also highlighted a larger question about the country’s future ambitions in human spaceflight. With the Gaganyaan programme still progressing towards its first crewed mission and no firm operational timeline for the inaugural flight, India has an opportunity to gain valuable experience from the International Space Station before the orbital laboratory reaches the end of its service life.

India’s current strategy has largely focused on developing and perfecting its own systems. The priority is to complete the indigenous human-rated launch vehicle, successfully conduct the first crewed Gaganyaan mission and then gradually expand the country’s human spaceflight activities. While such caution is understandable when human lives are involved, waiting too long could mean losing access to an extraordinary source of operational experience.

The International Space Station is expected to operate only for a limited number of remaining years before its planned retirement around 2030. During its decades in orbit, the ISS has generated an enormous amount of practical knowledge about living and working in space for extended periods. Astronauts and engineers have learned how to maintain life-support systems, handle equipment failures, conduct repairs, manage scientific experiments and operate complex spacecraft systems far from Earth. Much of this experience cannot simply be recreated after the station is gone.

This is particularly important because its ambitions extend well beyond a short trip into orbit. The country has plans for the Bharatiya Antariksh Station in the early 2030s and has also set an ambitious target of sending Indian astronauts to the Moon by 2040. Meeting those goals will require extensive knowledge of long-duration spaceflight.

A short Gaganyaan mission would still be a historic achievement, but a flight lasting only a few days would provide limited information about the challenges associated with months in space. Long-duration missions reveal how life-support equipment performs after prolonged use, how crews cope with microgravity and radiation exposure, and how astronauts respond when critical systems require maintenance or unexpectedly fail.

India already has an important foundation on which to build. Its astronaut candidates have undergone extensive training, including preparation at Russia’s Gagarin Cosmonaut Training Centre. Indian astronauts have received training in Soyuz operations, Russian-language communication and the procedures required for complex human space missions. This means the country possesses personnel who could potentially make use of a longer-duration opportunity rather than having to develop all of that expertise from the beginning.

A three- or four-month assignment aboard the ISS could therefore provide India with a level of practical experience that a short commercial mission cannot fully deliver. An astronaut participating as a flight engineer would have the opportunity to become involved in station maintenance, scientific operations, emergency procedures, docking activities and other aspects of long-term orbital life. Experience with manual docking and spacewalking procedures could also be particularly useful as India develops its own future space station.

The argument for such a mission does not contradict India’s objective of becoming self-reliant in space. International cooperation has long played a role in the development of major space programmes. Even countries with highly advanced independent capabilities have worked with other space powers when cooperation offered strategic or scientific advantages. India could similarly use international experience to strengthen its domestic capabilities rather than depend permanently on foreign systems.

The changing space environment also makes the issue more pressing. China has already established the Tiangong space station and is maintaining a regular human presence in orbit. Beijing is also expanding international participation in its space activities. As the ISS moves towards retirement, China’s orbital platform could become an increasingly important destination for countries seeking human spaceflight experience. India does not need to copy China’s approach, but it also cannot ignore the strategic value of experience in operating an orbital facility. If the ISS is retired before Indian astronauts gain substantial long-duration experience there, a unique opportunity for learning could disappear.

The knowledge gained from a long ISS expedition could directly support the development of the Bharatiya Antariksh Station. Experience with life-support systems, station maintenance, crew management, docking procedures and emergency operations could help Indian engineers design safer and more reliable systems for future missions. Working alongside astronauts and specialists from other space agencies would also expose Indian personnel to operational practices developed through decades of human spaceflight.

India’s space programme has rightly placed a strong emphasis on indigenous technology. Building its own crewed spacecraft and launch systems remains essential, and Gaganyaan will be a major milestone in that journey. But independence does not require India to reject opportunities to learn from existing international infrastructure. The ISS represents decades of accumulated human spaceflight experience, and its remaining operational life is limited. For India, securing a long-duration mission before the station is retired could offer an unusually efficient way to develop expertise that might otherwise take many years and multiple missions to acquire independently.

Human spaceflight is ultimately about more than rockets, spacecraft and launch systems. It also depends on experience, judgement and the ability to respond to problems that cannot always be predicted on Earth. If India wants its future orbital station and lunar missions to succeed, gaining that experience now could prove just as important as developing the hardware itself.

The opportunity created by the ISS will not remain open indefinitely. India’s challenge is to balance its pursuit of self-reliance with the practical benefits of international cooperation and ensure that valuable lessons from the current era of human spaceflight are not lost before the country is ready to build its own permanent presence in orbit.
Disclaimer: This image is taken from Indina Defence News.

Meta Platforms Inc. is facing a potential $18 billion settlement with nearly all US states over allegations concerning the impact of Facebook and Instagram on teenage users. The agreement would resolve a series of lawsuits, investigations and legal claims, although Meta would not necessarily pay the full amount.

Under the deal, Meta has committed to paying roughly $12.7 billion to states over the next 10 years as an initial obligation. An additional $5.3 billion could be added if other major social media companies agree to similar settlements and adopt comparable protections for teenagers. The largest part of the agreement, worth about $16.7 billion, would go to 47 states, Washington, DC, and three US territories. The funds could be used by individual states for programmes such as youth mental health services, crisis intervention, after-school activities and digital wellness initiatives.

The settlement also includes $459 million related to privacy claims stemming from older cases and investigations connected to the Cambridge Analytica controversy. The scandal involved the collection of Facebook users' personal information during the 2016 US presidential campaign. Texas has separately agreed to a $1 billion settlement with Meta, announced by Attorney General Ken Paxton. Although the Texas agreement was negotiated independently, Meta says it is included within the overall $18 billion package.

Meta will also provide $75 million toward litigation costs within 30 days of the settlement taking effect. States may additionally use part of their settlement allocations to cover legal expenses. A major condition of the agreement involves competitors including TikTok, YouTube and Snap. Meta says it will only be required to make the additional $5.3 billion payment if TikTok and YouTube reach comparable financial agreements with states. The companies would also face expectations around teen safety, including daily usage limits, fewer evening notifications and stronger age-verification systems.

New Mexico and Florida are the only states outside the settlement. New Mexico recently secured nearly $1 billion from Meta after winning its own case, while Florida Attorney General James Uthmeier has rejected the multistate agreement, arguing that the proposed compensation does not adequately reflect the alleged harm to children. The settlement could therefore have consequences extending beyond Meta's finances. If other major platforms agree to similar terms, it could push the wider social media industry toward stricter rules on teen accounts, age verification, screen time and digital safety.

Disclaimer: This image is taken from Bloomberg.

Artificial intelligence is increasingly being seen as a powerful tool in India’s battle against air pollution, but technology alone is unlikely to deliver cleaner air. AI can help authorities predict pollution spikes, identify hotspots and improve decision-making, yet its effectiveness will ultimately depend on reliable data, strong enforcement and action against the sources of emissions. Air pollution in India is influenced by a complicated combination of traffic, industrial activity, construction dust, waste burning, agricultural emissions and changing weather conditions. Because these factors interact constantly, predicting air quality is not always straightforward. AI and machine-learning systems can analyse large amounts of information from monitoring stations, weather models and satellites to identify patterns and provide earlier warnings.

In Delhi, authorities are working with IIT Kanpur on an AI-based decision-support system that is designed to forecast air pollution 48 to 72 hours in advance and identify areas where pollution could become particularly severe. The aim is to give government agencies enough time to take targeted action rather than waiting until air quality has already deteriorated. Similar efforts are also emerging elsewhere. Maharashtra has been developing an AI-powered air-quality forecasting system for Mumbai and surrounding areas, with the broader objective of anticipating deteriorating conditions and helping authorities respond more quickly.

The technology could be particularly useful during periods when weather conditions trap pollutants close to the ground. An AI model could combine information about wind speed, temperature, humidity, traffic and emissions to estimate where pollution is likely to increase. If a specific area is identified as a potential hotspot, officials could focus inspections and pollution-control measures there. Researchers are also exploring the use of satellite observations alongside ground-based monitoring. Recent studies have shown that machine-learning models can use these different sources of information to improve forecasts of particulate pollution in several Indian cities. Such systems could become especially valuable in places where conventional monitoring stations are limited.

The growing interest in AI also highlights a basic problem: sophisticated technology is only as good as the information it receives. If monitoring stations are poorly distributed, sensors are not properly maintained or important sources of pollution are missing from the data, an AI system may struggle to provide an accurate picture. This is why expanding and maintaining India's air-quality monitoring network remains critical. More sensors and better-quality measurements can give AI systems a stronger foundation, allowing them to distinguish between local pollution and pollution transported from other parts of a region.

That distinction is particularly important in northern India, where air pollution often crosses administrative boundaries. Delhi cannot treat its air-quality problem entirely as a Delhi problem. Pollution can move across neighbouring districts and states, making regional coordination essential. AI can help reveal these connections, but it cannot enforce environmental regulations. If an algorithm identifies a construction site as a major dust source, someone still has to inspect the site and ensure that pollution-control measures are followed. If it predicts a dangerous pollution episode, authorities still need to decide whether traffic, construction or industrial activity should be restricted.

This is where the difference between forecasting pollution and reducing pollution becomes important. A highly accurate prediction does not automatically translate into cleaner air. There is also a risk that the excitement around artificial intelligence could distract from measures that are less glamorous but far more fundamental. Cleaner public transport, better waste management, dust suppression, industrial emission controls, cleaner fuels and stronger enforcement remain central to reducing pollution.

The real test for AI-based air-quality systems should therefore be measured in outcomes. Authorities need to know whether an AI warning was accurate, what action followed the warning and whether that action actually reduced pollution. Without such a feedback system, AI could become another sophisticated dashboard without delivering meaningful environmental improvements.

Still, the potential is considerable. If AI can provide reliable forecasts several days in advance, governments may be able to move from a largely reactive approach to a more preventive one. Instead of responding only after pollution reaches hazardous levels, agencies could prepare for high-risk conditions and concentrate resources where they are most needed. For India, that could make pollution-control efforts more efficient and targeted. But the technology should be treated as an additional tool rather than a magic solution. The bigger challenge remains the same: reducing the amount of pollution entering the atmosphere in the first place.

AI can help India understand its air better, predict what is coming and identify where intervention may have the greatest impact. But cleaner air will ultimately depend on whether governments, businesses and citizens act on that information. Artificial intelligence may become an important part of India's clean-air strategy, but the smartest algorithm in the world cannot compensate for weak monitoring, poor enforcement or failure to tackle pollution at its source. The technology can provide the intelligence; the real work still has to happen on the ground.

Disclaimer: This image is taken from Hindustan Times.

Meta’s Ray-Ban smart glasses have rapidly emerged as one of the world’s most popular new tech products, with reports suggesting that more than seven million pairs were sold in 2025. Supporters praise the glasses for making photography and accessibility more convenient, but the technology has also sparked privacy concerns. Critics have dubbed them “pervert glasses,” while some UK pubs and restaurants, including Wetherspoons, have reportedly banned customers from using the devices on their premises.

Disclaimer: This podcast is taken from The Guardian.

On the July 24 episode of Open For Business, hosts Andrea Heng and Poh Kok Ing are joined by Santosh Rao, Head of Research and Partner at Manhattan Venture Partners, to break down today's market trends.

Disclaimer: This podcast is taken from CNA.

As AI continues to evolve, cyber risks are becoming a major business challenge rather than just a technical problem. The Five Eyes alliance warns that advanced AI models could transform the cyber threat landscape faster than anticipated. With AI being used for both attacks and defense, the question remains: who is ahead in this new automated cyber battle? Andrea Heng and Hairianto Diman explore this with Jayant Dave, Chief Information Security Officer at Check Point Software Technologies.

Disclaimer: This podcast is taken from CNA.

A prolonged and heated courtroom dispute between tech billionaires Elon Musk and Sam Altman has ended in a win for OpenAI’s CEO. Musk says he plans to challenge the decision. The case has raised wider questions about Big Tech influence and the worldwide competition in artificial intelligence. Lucy Hough discusses the outcome with Guardian US tech and power reporter Nick Robins-Early in a YouTube interview.
Disclaimer: This image is taken from The Guardian.