#FactCheck -Misleading Claim Uses 2013 Army Coffin Photo to Spread False Ceasefire Narrative
Executive Summary
Social media users, particularly Pakistani propaganda accounts, shared an image showing coffins wrapped in the Indian tricolour and claimed that India violated the ceasefire along the Line of Control (LoC). According to the posts, Pakistan retaliated with heavy firing, captured the Indian Army’s Kumar Top post, and several Indian soldiers were killed in the exchange.
One user wrote, “Breaking News: Indian Army once again violated the ceasefire in the Mandal sector, targeting civilians with mortar shelling. Pakistan responded strongly, captured the Indian Army’s Kumar Top post, and several soldiers were reportedly killed. Calm has now been restored after Pakistan’s response.”
Fact Check
Research by CyberPeace found the viral claim to be false. Using reverse image search, we traced the viral photo to the Shutterstock website. The image description states that it was taken on August 6, 2013, and shows Indian Army personnel standing near the coffins of soldiers who were killed by Pakistani infiltrators at a brigade headquarters in Poonch, located about 240 km from Jammu. This confirms that the image is old and unrelated to recent developments along the Line of Control.
Further verification led us to a report published by NBC News on August 8, 2013, which also featured the same visual in connection with the 2013 cross-border attack.
Additionally, posts from the official X (formerly Twitter) handle of the Indian Army 16 Corps (White Knight Corps) stated that based on intelligence inputs and continuous surveillance, suspicious terrorist activity was detected near Nathua Tibba in the Sunderbani sector close to the LoC in the early hours of February 19, 2026. Alert troops responded promptly and successfully foiled the infiltration attempt. The Army also confirmed that operational vigilance remains high across the sector. However, there were no reports of casualties due to Pakistani firing.
Conclusion:
The viral image showing coffins of Indian soldiers is not recent but dates back to 2013. There are no confirmed reports of casualties from Pakistani firing along the Line of Control in the current context. Therefore, the claim circulating on social media is misleading.
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Introduction
The Indian Cabinet has approved a comprehensive national-level IndiaAI Mission with a budget outlay ofRs.10,371.92 crore. The mission aims to strengthen the Indian AI innovation ecosystem by democratizing computing access, improving data quality, developing indigenous AI capabilities, attracting top AI talent, enabling industry collaboration, providing startup risk capital, ensuring socially-impactful A projects, and bolstering ethical AI. The mission will be implemented by the'IndiaAI' Independent Business Division (IBD) under the Digital India Corporation (DIC) and consists of several components such as IndiaAI Compute Capacity, IndiaAI Innovation Centre (IAIC), IndiaAI Datasets Platform, India AI Application Development Initiative, IndiaAI Future Skills, IndiaAI Startup Financing, and Safe & Trusted AI over the next 5 years.
This financial outlay is intended to befulfilled through a public-private partnership model, to ensure a structured implementation of the IndiaAI Mission. The main objective is to create and nurture an ecosystem for India’s AI innovation. This mission is intended to act as a catalyst for shaping the future of AI for India and the world. AI has the potential to become an active enabler of the digital economy and the Indian government aims to harness its full potential to benefit its citizens and drive the growth of its economy.
Key Objectives of India's AI Mission
● With the advancements in data collection, processing and computational power, intelligent systems can be deployed in varied tasks and decision-making to enable better connectivity and enhance productivity.
● India’s AI Mission will concentrate on benefiting India and addressing societal needs in primary areas of healthcare, education, agriculture, smart cities and infrastructure, including smart mobility and transportation.
● This mission will work with extensive academia-industry interactions to ensure the development of core research capability at the national level. This initiative will involve international collaborations and efforts to advance technological frontiers by generating new knowledge and developing and implementing innovative applications.
The strategies developed for implementing the IndiaAI Mission are via Public-Private Partnerships, Skilling initiatives and AI Policy and Regulation. An example of the work towards the public-private partnership is the pre-bid meeting that the IT Ministry hosted on 29th August2024, which saw industrial participation from Nvidia, Intel, AMD, Qualcomm, Microsoft Azure, AWS, Google Cloud and Palo Alto Networks.
Components of IndiaAI Mission
The IndiaAI Compute Capacity: The IndiaAI Compute pillar will build a high-end scalable AI computing ecosystem to cater to India's rapidly expanding AI start-ups and research ecosystem. The ecosystem will comprise AI compute infrastructure of 10,000 or more GPUs, built through public-private partnerships. An AI marketplace will offer AI as a service and pre-trained models to AI innovators.
The IndiaAI Innovation Centre will undertake the development and deployment of indigenous Large Multimodal Models (LMMs) and domain-specific foundational models in critical sectors. The IndiaAI Datasets Platform will streamline access to quality on-personal datasets for AI innovation.
The IndiaAI Future Skills pillar will mitigate barriers to entry into AI programs and increase AI courses in undergraduate, master-level, and Ph.D. programs. Data and AI Labs will be set up in Tier 2 and Tier 3 cities across India to impart foundational-level courses.
The IndiaAI Startup Financing pillar will support and accelerate deep-tech AI startups, providing streamlined access to funding for futuristic AI projects.
The Safe & Trusted AI pillar will enable the implementation of responsible AI projects and the development of indigenous tools and frameworks, self-assessment check lists for innovators, and other guidelines and governance frameworks by recognising the need for adequate guardrails to advance the responsible development, deployment, and adoption of AI.
CyberPeace Considerations for the IndiaAI Mission
● Data privacy and security are paramount as emerging privacy instruments aim to ensure ethical AI use. Addressing bias and fairness in AI remains a significant challenge, especially with poor-quality or tampered datasets that can lead to flawed decision-making, posing risks to fairness, privacy, and security.
● Geopolitical tensions and export control regulations restrict access to cutting-edge AI technologies and critical hardware, delaying progress and impacting data security. In India, where multilingualism and regional diversity are key characteristics, the unavailability of large, clean, and labeled datasets in Indic languages hampers the development of fair and robust AI models suited to the local context.
● Infrastructure and accessibility pose additional hurdles in India’s AI development. The country faces challenges in building computing capacity, with delays in procuring essential hardware, such as GPUs like Nvidia’s A100 chip, hindering businesses, particularly smaller firms. AI development relies heavily on robust cloud computing infrastructure, which remains in its infancy in India. While initiatives like AIRAWAT signal progress, significant gaps persist in scaling AI infrastructure. Furthermore, the scarcity of skilled AI professionals is a pressing concern, alongside the high costs of implementing AI in industries like manufacturing. Finally, the growing computational demands of AI lead to increased energy consumption and environmental impact, raising concerns about balancing AI growth with sustainable practices.
Conclusion
We advocate for ethical and responsible AI development adoption to ensure ethical usage, safeguard privacy, and promote transparency. By setting clear guidelines and standards, the nation would be able to harness AI's potential while mitigating risks and fostering trust. The IndiaAI Mission will propel innovation, build domestic capacities, create highly-skilled employment opportunities, and demonstrate how transformative technology can be used for social good and enhance global competitiveness.
References
● https://pib.gov.in/PressReleasePage.aspx?PRID=2012375
Introduction
Microsoft has unveiled its ambitious roadmap for developing a quantum supercomputer with AI features, acknowledging the transformative power of quantum computing in solving complex societal challenges. Quantum computing has the potential to revolutionise AI by enhancing its capabilities and enabling breakthroughs in different fields. Microsoft’s groundbreaking announcement of its plans to develop a quantum supercomputer, its potential applications, and the implications for the future of artificial intelligence (AI). However, there is a need for regulation in the realms of quantum computing and AI and significant policies and considerations associated with these transformative technologies. This technological advancement will help in the successful development and deployment of quantum computing, along with the potential benefits and challenges associated with its implementation.
What isQuantum computing?
Quantum computing is an emerging field of computer science and technology that utilises principles from quantum mechanics to perform complex calculations and solve certain types of problems more efficiently than classical computers. While classical computers store and process information using bits, quantum computers use quantum bits or qubits.
Interconnected Future
Quantum computing promises to significantly expand AI’s capabilities beyond its current limitations. Integrating these two technologies could lead to profound advancements in various sectors, including healthcare, finance, and cybersecurity. Quantum computing and artificial intelligence (AI) are two rapidly evolving fields that have the potential to revolutionise technology and reshape various industries. This section explores the interdependence of quantum computing and AI, highlighting how integrating these two technologies could lead to profound advancements across sectors such as healthcare, finance, and cybersecurity.
- Enhancing AI Capabilities:
Quantum computing holds the promise of significantly expanding the capabilities of AI systems. Traditional computers, based on classical physics and binary logic, need help solving complex problems due to the exponential growth of computational requirements. Quantum computing, on the other hand, leverages the principles of quantum mechanics to perform computations on quantum bits or qubits, which can exist in multiple states simultaneously. This inherent parallelism and superposition property of qubits could potentially accelerate AI algorithms and enable more efficient processing of vast amounts of data.
- Solving Complex Problems:
The integration of quantum computing and AI has the potential to tackle complex problems that are currently beyond the reach of classical computing methods. Quantum machine learning algorithms, for example, could leverage quantum superposition and entanglement to analyse and classify large datasets more effectively. This could have significant applications in healthcare, where AI-powered quantum systems could aid in drug discovery, disease diagnosis, and personalised medicine by processing vast amounts of genomic and clinical data.
- Advancements in Finance and Optimisation:
The financial sector can benefit significantly from integrating quantum computing and AI. Quantum algorithms can be employed to optimise portfolios, improve risk analysis models, and enhance trading strategies. By harnessing the power of quantum machine learning, financial institutions can make more accurate predictions and informed decisions, leading to increased efficiency and reduced risks.
- Strengthening Cybersecurity:
Quantum computing can also play a pivotal role in bolstering cybersecurity defences. Quantum techniques can be employed to develop new cryptographic protocols that are resistant to quantum attacks. In conjunction with quantum computing, AI can further enhance cybersecurity by analysing massive amounts of network traffic and identifying potential vulnerabilities or anomalies in real time, enabling proactive threat mitigation.
- Quantum-Inspired AI:
Beyond the direct integration of quantum computing and AI, quantum-inspired algorithms are also being explored. These algorithms, designed to run on classical computers, draw inspiration from quantum principles and can improve performance in specific AI tasks. Quantum-inspired optimisation algorithms, for instance, can help solve complex optimisation problems more efficiently, enabling better resource allocation, supply chain management, and scheduling in various industries.
How Quantum Computing and AI Should be Regulated-
As quantum computing and artificial intelligence (AI) continues to advance, questions arise regarding the need for regulations to govern these technologies. There is debate surrounding the regulation of quantum computing and AI, considering the potential risks, ethical implications, and the balance between innovation and societal protection.
- Assessing Potential Risks: Quantum computing and AI bring unprecedented capabilities that can significantly impact various aspects of society. However, they also pose potential risks, such as unintended consequences, privacy breaches, and algorithmic biases. Regulation can help identify and mitigate these risks, ensuring these technologies’ responsible development and deployment.
- Ethical Implications: AI and quantum computing raise ethical concerns related to privacy, bias, accountability, and the impact on human autonomy. For AI, issues such as algorithmic fairness, transparency, and decision-making accountability must be addressed. Quantum computing, with its potential to break current encryption methods, requires regulatory measures to protect sensitive information. Ethical guidelines and regulations can provide a framework to address these concerns and promote responsible innovation.
- Balancing Innovation and Regulation: Regulating quantum computing and AI involves balancing fostering innovation and protecting society’s interests. Excessive regulation could stifle technological advancements, hinder research, and impede economic growth. On the other hand, a lack of regulation may lead to the proliferation of unsafe or unethical applications. A thoughtful and adaptive regulatory approach is necessary, considering the dynamic nature of these technologies and allowing for iterative improvements based on evolving understanding and risks.
- International Collaboration: Given the global nature of quantum computing and AI, international collaboration in regulation is essential. Harmonising regulatory frameworks can avoid fragmented approaches, ensure consistency, and facilitate ethical and responsible practices across borders. Collaborative efforts can also address data privacy, security, and cross-border data flow challenges, enabling a more unified and cooperative approach towards regulation.
- Regulatory Strategies: Regulatory strategies for quantum computing and AI should adopt a multidisciplinary approach involving stakeholders from academia, industry, policymakers, and the public. Key considerations include:
- Risk-based Approach: Regulations should focus on high-risk applications while allowing low-risk experimentation and development space.
- Transparency and Explainability: AI systems should be transparent and explainable to enable accountability and address concerns about bias, discrimination, and decision-making processes.
- Privacy Protection: Regulations should safeguard individual privacy rights, especially in quantum computing, where current encryption methods may be vulnerable.
- Testing and Certification: Establishing standards for the testing and certification of AI systems can ensure their reliability, safety, and adherence to ethical principles.
- Continuous Monitoring and Adaptation: Regulatory frameworks should be dynamic, regularly reviewed, and adapted to keep pace with the evolving landscape of quantum computing and AI.
Conclusion:
Integrating quantum computing and AI holds immense potential for advancing technology across diverse domains. Quantum computing can enhance the capabilities of AI systems, enabling the solution of complex problems, accelerating data processing, and revolutionising industries such as healthcare, finance, and cybersecurity. As research and development in these fields progress, collaborative efforts among researchers, industry experts, and policymakers will be crucial in harnessing the synergies between quantum computing and AI to drive innovation and shape a transformative future.The regulation of quantum computing and AI is a complex and ongoing discussion. Striking the right balance between fostering innovation, protecting societal interests, and addressing ethical concerns is crucial. A collaborative, multidisciplinary approach to regulation, considering international cooperation, risk assessment, transparency, privacy protection, and continuous monitoring, is necessary to ensure these transformative technologies' responsible development and deployment.
Introduction
A Reuters investigation has uncovered an elephant in the room regarding Meta Platforms' internal measures to address online fraud and illicit advertising. The confidential documents that Reuters reviewed disclosed that Meta was planning to generate approximately 10% of its 2024 revenue, i.e., USD 16 billion, from ads related to scams and prohibited goods. The findings point out a disturbing paradox: on the one hand, Meta is a vocal advocate for digital safety and platform integrity, while on the other hand, the internal logs of the company indicate the existence of a very large area allowing the shunning of fraudulent advertisement activities that exploit users throughout the world.
The Scale of the Problem
Internal Meta projections show that its platforms, Facebook, Instagram, and WhatsApp, are displaying a staggering 15 billion scam ads per day combined. The advertisements include deceitful e-commerce promotions, fake investment schemes, counterfeit medical products, and unlicensed gambling platforms.
Meta has developed sophisticated detection tools, but even then, the system does not catch the advertisers until they are 95% certain to be fraudsters. By having at least that threshold for removing an ad, the company is unlikely to lose much money. As a result, instead of turning the fraud adjacent advertisers down, it charges them higher ad rates, which is the strategy they call “penalty bids” internally.
Internal Acknowledgements & Business Dependence
Internal documents that date between 2021 and 2025 reveal that the financial, safety, and lobbying divisions of Meta were cognizant of the enormity of revenues generated from scams. One of the 2025 strategic papers even describes this revenue source as "violating revenue," which implies that it includes ads that are against Meta's policies regarding scams, gambling, sexual services, and misleading healthcare products.
The company's top executives consider the cost-benefit scenario of stricter enforcement. According to a 2024 internal projection, Meta's half-yearly earnings from high-risk scam ads were estimated at USD 3.5 billion, whereas regulatory fines for such violations would not exceed USD 1 billion, thus making it a tolerable trade-off from a commercial viewpoint. At the same time, the company intends to scale down scam ad revenue gradually, thus from 10.1% in 2024 to 7.3% by 2025, and 6% by 2026; however, the documents also reveal a planned slowdown in enforcement to avoid "abrupt reductions" that could affect business forecasts.
Algorithmic Amplification of Scams
One of the most alarming situations is the fact that Meta's own advertising algorithms amplify scam content. It has been reported that users who click on fraudulent ads are more likely to see other similar ads, as the platform's personalisation engine assumes user "interest."
This scenario creates a self-reinforcing feedback loop where the user engagement with scam content dictates the amount of such content being displayed. Thus, a digital environment is created which encourages deceptive engagement and consequently, user trust is eroded and systemic risk is amplified.
An internal presentation in May 2025 was said to put a number on how deeply the platform's ad ecosystem was intertwined with the global fraud economy, estimating that one-third of the scams that succeeded in the U.S. were due to advertising on Meta's platforms.
Regulatory & Legal Implications
The disclosures arrived at the same time as the US and UK governments started to closely check the company's activities more than ever before.
- The U.S. Securities and Exchange Commission (SEC) is said to be looking into whether Meta has had any part in the promotion of fraudulent financial ads.
- The UK’s Financial Conduct Authority (FCA) found that Meta’s platforms were the main sources of scams related to online payments and claimed that the amount of money lost was more than all the other social platforms combined in 2023.
Meta’s spokesperson, Andy Stone, at first denied the accusations, stating that the figures mentioned in the leak were “rough and overly-inclusive”; nevertheless, he conceded that the company’s consistent efforts toward enforcement had negatively impacted revenue and would continue to do so.
Operational Challenges & Policy Gaps
The internal documents also reveal the weaknesses in Meta's day-to-day operations when it comes to the implementation of its own policies.
- Because of the large number of employees laid off in 2023, the whole department that dealt with advertiser-brand impersonation was said to have been dissolved.
- Scam ads were categorised as a "low severity" issue, which was more of a "bad user experience" than a critical security risk.
- At the end of 2023, users were submitting around 100,000 legitimate scam reports per week, of which Meta dismissed or rejected 96%.
Human Impact: When Fraud Becomes Personal
The financial and ethical issues have tangible human consequences. The Reuters investigation documented multiple cases of individuals defrauded through hijacked Meta accounts.
One striking example involves a Canadian Air Force recruiter, whose hacked Facebook account was used to promote fake cryptocurrency schemes. Despite over a hundred user reports, Meta failed to act for weeks, during which several victims, including military colleagues, lost tens of thousands of dollars.
The case underscores not just platform negligence, but also the difficulty of law enforcement collaboration. Canadian authorities confirmed that funds traced to Nigerian accounts could not be recovered due to jurisdictional barriers, a recurring issue in transnational cyber fraud.
Ethical and Cybersecurity Implications
The research has questioned extremely important things at least from the perspective of cyber policy:
- Platform Accountability: Meta, by its practice, is giving more importance to the monetary aspect rather than the truth, and in this way, it is going against the principles of responsible digital governance.
- Transparency in Ad Ecosystems: The lack of transparency in digital advertising systems makes it very easy for dishonest actors to use automated processes with very little supervision.
- Algorithmic Responsibility: The use of algorithms that impact the visibility of misleading content and targeting can be considered the direct involvement of the algorithms in the fraud.
- Regulatory Harmonisation: The presence of different and disconnected enforcement frameworks across jurisdictions is a drawback to the efforts in dealing with cross-border cybercrime.
- Public Trust: Users’ trust in the digital world is mainly dependent on the safety level they see and the accountability of the companies.
Conclusion
Meta’s records show a very unpleasant mix of profit, laxity, and failure in the policy area concerning scam-related ads. The platform’s readiness to accept and even profit from fraudulent players, though admitting the damage they cause, calls for an immediate global rethinking of advertising ethics, regulatory enforcement, and algorithmic transparency.
With the expansion of its AI-driven operations and advertising networks, protecting the users of Meta must evolve from being just a public relations goal to being a core business necessity, thus requiring verifiable accountability measures, independent audits, and regulatory oversight. It is an undeniable fact that there are billions of users who count on Meta’s platforms for their right to digital safety, which is why this right must be respected and enforced rather than becoming optional.
References
- https://www.reuters.com/investigations/meta-is-earning-fortune-deluge-fraudulent-ads-documents-show-2025-11-06/?utm_source=chatgpt.com
- https://www.indiatoday.in/technology/news/story/leaked-docs-claim-meta-made-16-billion-from-scam-ads-even-after-deleting-134-million-of-them-2815183-2025-11-07
