#FactCheck - Debunking Manipulated Photos of Smiling Secret Service Agents During Trump Assassination Attempt

Introduction

The ongoing debate on whether AI scaling has hit a wall has been rehashed by the underwhelming response to OpenAI’s ChatGPT v5. AI scaling laws, which describe that machine learning models perform better with increased training data, model parameters and computational resources, have guided the rapid progress of Large Language Models (LLMs) so far. But many AI researchers suggest that further improvements in LLMs will have to be effected through large computational costs by orders of magnitude, which does not justify the returns.  The question, then, is whether scaling remains a viable path or whether the field must explore new approaches. This is not just a tech issue but a profound innovation challenge for countries like India, charting their own AI course. 

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The Scaling Wall: Gaps and Innovation Opportunities

Escalating costs, data scarcity, and diminishing gains mean that simply building larger AI models may no longer guarantee breakthroughs. In such a scenario, LLM developers will have to refine new approaches to training these models, for example, by diversifying data types and redefining training techniques.  

This global challenge has a bearing on India’s AI ambitions. For India, where compute and data resources are relatively scarce, this scaling slowdown poses both a challenge and an opportunity. While the India AI Mission embodies smart priorities such as democratising compute resources and developing local datasets, looming scaling challenges could prove a roadblock.  Realising these ambitions requires strong input from research and academia, and improved coordination between policymakers and startups. The scaling wall highlights systemic innovation gaps where sustained support is needed, not only in hardware but also in talent development, safety research, and efficient model design.

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Way Forward

To truly harness AI’s transformative power, India must prioritise policy actions and ecosystem shifts that support smarter, safer, and context-rich research through the following measures: 

• Driving Efficiency and Compute Innovation: Instead of relying on brute-force scaling, India should invest in research and startups working on efficient architectures, energy-conscious training methods, and compute optimisation.
• Investing in Multimodal and Diverse Data: While indigenous datasets are being developed under the India AI Mission through AI Kosha, they must be ethically sourced from speech, images, video, sensor data, and regional content, apart from text, to enable context-rich AI models truly tailored to Indian needs. 
• Addressing Core Problems for Trustworthy AI:  LLMs offered by all major companies, like OpenAI, Grok, and Deepseek, have the problem of unreliability, hallucinations, and biases, since they are primarily built on scaling large datasets and parameters, which have inherent limitations. India should invest in capabilities to solve these issues and design more trustworthy LLMs.
• Supporting Talent Development and Training: Despite its substantial AI talent pool, India faces an impending demand-supply gap. It will need to launch national programs and incentives to upskill engineers, researchers, and students in advanced AI skills such as model efficiency, safety, interpretability, and new training paradigms

Conclusion

The AI scaling wall debate is a reminder that the future of LLMs will depend not on ever-larger models but on smarter, safer, and more sustainable innovation. A new generation of AI is approaching us, and India can help shape its future. The country’s AI Mission and startup ecosystem are well-positioned to lead this shift by focusing on localised needs, efficient technologies, and inclusive growth, if implemented effectively. How India approaches this new set of challenges and translates its ambitions into action, however, remains to be seen.

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References

• https://blogs.nvidia.com/blog/ai-scaling-laws/
• https://www.marketingaiinstitute.com/blog/scaling-laws-ai-wall 
• https://fortune.com/2025/02/19/generative-ai-scaling-agi-deep-learning/ 
• https://indiaai.gov.in/ 
• https://www.deloitte.com/in/en/about/press-room/bridging-the-ai-talent-gap-to-boost-indias-tech-and-economic-impact-deloitte-nasscom-report.html 

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Introduction

The rise in start-up culture, increasing investments, and technological breakthroughs are being encouraged alongside innovations and the incorporation of generative Artificial Intelligence elements. Witnessing the growing focus on human-centred AI, its potential to transform industries like education remains undeniable. Enhancing experiences and inculcating new ways of learning, there is much to be explored. Recently, a Delhi-based non-profit called Rocket Learning, in collaboration with Google.org, launched Appu- a personalised AI educational tool providing a multilingual and conversational learning experience for kids between 3 and 6.

AI Appu

Developed in 6 months, along with the help of dedicated Google.org fellows, interactive Appu has resonated with those the founders call “super-users,” i.e. parents and caregivers. Instead of redirecting students to standard content and instructional videos, it operates on the idea of conversational learning, one equally important for children in the targeted age bracket. Designed in the form of an elephant, Appu is supposed to be a personalised tutor, helping both children and parents understand concepts through dialogue. AI enables the generation of different explanations in case of doubt, aiding in understanding. If children were to answer in mixed languages instead of one complete sentence in a single language (eg, Hindi and English), the AI would still consider it as a response. The AI lessons are two minutes long and are inculcated with real-world examples. The emphasis on interactive and fun learning of concepts through innovation enhances the learning experience. Currently only available in Hindi, it is being worked on to include 20 other languages such as Punjabi and Marathi. 

UNESCO, AI, and Education

It is important to note that such innovations also find encouragement in UNESCO’s mandate as AI in education contributes to achieving the 2030 Agenda of Sustainable Development Goals (here; SDG 4- focusing on quality education). Within the ambit of the Beijing Consensus held in 2019, UNESCO encourages a human-centred approach to AI, and has also developed the “Artificial Intelligence and Education: Guidance for Policymakers” aiming towards understanding its potential and opportunities in education as well as the core competencies it needs to work on. Another publication was launched during one of the flagship events of UNESCO- (Digital Learning Week, 2024) - AI competency frameworks for both, students and teachers which provide a roadmap for assessing the potential and risks of AI, each covering common aspects such as AI ethics, and human-centred mindset and even certain distinct options such as AI system design for students and AI pedagogy for teachers.

Potential Challenges

While AI holds immense promise in education, innovation with regard to learning is contentious as several risks must be carefully managed. Depending on the innovation, AI’s struggle with multitasking beyond the classroom, such as administrative duties and tedious grading, which require highly detailed role descriptions could prove to be a challenge. This can become exhausting for developers managing innovative AI systems, as they would have to fit various responses owing to the inherent nature of AI needing to be trained to produce output. Security concerns are another major issue, as data breaches could compromise sensitive student information. Implementation costs also present challenges, as access to AI-driven tools depends on financial resources. Furthermore, AI-driven personalised learning, while beneficial, may inadvertently reduce student motivation, also compromising students' soft skills, such as teamwork and communication, which are crucial for real-world success. These risks highlight the need for a balanced approach to AI integration in education.

Conclusion

Innovations related to education, especially the ones that focus on a human-centred AI approach, have immense potential in not only enhancing learning experiences but also reshaping how knowledge is accessed, understood, and applied. Untapped potential using other services is also encouraged in this sector. However, maintaining a balance between fostering intrigue and ensuring the inculcation of ethical and secure AI remains imperative.

References

• https://www.unesco.org/en/articles/what-you-need-know-about-unescos-new-ai-competency-frameworks-students-and-teachers?hub=32618
• https://www.unesco.org/en/digital-education/artificial-intelligence
• https://www.deccanherald.com/technology/google-backed-rocket-learning-launches-appu-an-ai-powered-tutor-for-kids-3455078
• https://indianexpress.com/article/technology/artificial-intelligence/how-this-google-backed-ai-tool-is-reshaping-education-appu-9896391/
• https://www.thehindu.com/business/ai-appu-to-tutor-children-in-india/article69354145.ece
• https://www.velvetech.com/blog/ai-in-education-risks-and-concerns/ 

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Introduction

The Data Security Council of India’s India Cyber Threat Report 2025 calculates that a staggering 702 potential attacks happened per minute on average in the country in 2024.  Recent alleged data breaches on organisations such as Star Health, WazirX, Indian Council of Medical Research (ICMR), BSNL, etc. highlight the vulnerabilities of government organisations, critical industries, businesses, and individuals in managing their digital assets. India is the second most targeted country for cyber attacks globally, which warrants the development and adoption of cybersecurity governance frameworks essential for the structured management of cyber environments. The following global models offer valuable insights and lessons that can help strengthen cybersecurity governance.

Overview of Global Cybersecurity Governance Models 

Cybersecurity governance frameworks provide a structured strategy to mitigate and address cyber threats. Different regions have developed their own governance models for cybersecurity, but they all emphasize risk management, compliance, and cross-sector collaboration for the protection of digital assets. Four such major models are: 

1. NIST CSF 2.0 (U.S.A): The National Institute of Standards and Technology Cyber Security Framework provides a flexible, voluntary, risk-based approach rather than a one-size-fits-all solution to manage cybersecurity risks. It endorses six core functions, which are:  Govern, Identify, Protect, Detect, Respond, and Recover. This is a widely adopted framework used by both public and private sector organizations even outside the U.S.A. 
2. ISO/IEC 27001: This is a globally recognized standard developed jointly by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). It provides a risk-based approach to help organizations of all sizes and types to identify, assess, and mitigate potential cybersecurity threats to Information Security Management Systems (ISMS) and preserve the confidentiality, integrity, and availability of information.  Organizations can seek ISO 27001 certification to demonstrate compliance with laws and regulations.
3. EU NIS2 Directive: The Network and Information Security Directive 2 (NIS2) is an updated EU cybersecurity law that imposes strict obligations on critical services providers in four overarching areas: risk management, corporate accountability, reporting obligations, and business continuity. It is the most comprehensive cybersecurity directive in the EU to date, and non-compliance may attract non-monetary remedies, administrative fines up to at least €10 million or 2% of the global annual revenue (whichever is higher), or even criminal sanctions for top managers. 
4. GDPR: The General Data Protection Regulation (GDPR)of the EU is a comprehensive data privacy law that also has major cybersecurity implications. It mandates that organizations must integrate cybersecurity into their data protection policies and report breaches within 72 hours, and it prescribes a fine of up to €20 million or 4% of global turnover for non-compliance. 

India’s Cybersecurity Governance Landscape 

In light of the growing nature of cyber threats, it is notable that the Indian government has taken comprehensive measures along with efforts by relevant agencies such as the Ministry of Electronics and Information Technology, Reserve Bank of India (RBI), National Payments Corporation (NPCI) and Indian Cyber Crime Coordination Centre (I4C), CERT-In. However, there is still a lack of an overarching cybersecurity governance framework or comprehensive law in this area. Multiple regulatory bodies in India oversee cybersecurity for various sectors. Key mechanisms are: 

1. CERT-In Guidelines: The Indian Computer Emergency Response Team, under the Ministry of Electronics and Information Technology (MeitY), is the nodal agency responsible for cybersecurity incident response, threat intelligence sharing, and capacity building. Organizations are mandated to maintain logs for 180 days and report cyber incidents to CERT-In within six hours of noticing them according to directions under the Information Technology Act, 2000 (IT Act).
2. IT Act & DPDP Act: These Acts, along with their associated rules, lay down the legal framework for the protection of ICT systems in India.  While some sections mandate that “reasonable” cybersecurity standards be followed, specifics are left to the discretion of the organisations. Enforcement frameworks are vague, which leaves sectoral regulators to fill the gaps. 
3. Sectoral regulations: The Reserve Bank of India (RBI), the Insurance Regulatory and Development Authority of India (IRDAI), the Department of Telecommunications, the Securities Exchange Board of India (SEBI), National Critical Information Infrastructure Protection Centre (NCIIPC) and other regulatory bodies require that cybersecurity standards be maintained by their regulated entities. 

Lessons for India & Way Forward 

As the world faces unprecedented security and privacy threats to its digital ecosystem, the need for more comprehensive cybersecurity policies, awareness, and capacity building has perhaps never been greater. While cybersecurity practices may vary with the size, nature, and complexity of an organization (hence “reasonableness” informing measures taken), there is a need for a centralized governance framework in India similar to NIST2 to unify sectoral requirements for simplified compliance and improve enforcement. India ranks 10th on the World Cybercrime Index and was found to be "specialising" in scams and mid-tech crimes- those which affect mid-range businesses and individuals the most. To protect them, India needs to strengthen its enforcement mechanisms across more than just the critical sectors. This can be explored by penalizing bigger organizations handling user data susceptible to breaches more stringently, creating an enabling environment for strong cybersecurity practices through incentives for MSMEs, and investing in cybersecurity workforce training and capacity building. Finally,  there is a scope for increased public-private collaboration for real-time cyber intelligence sharing.  Thus, a unified, risk-based national cybersecurity governance framework encompassing the current multi-pronged cybersecurity landscape would give direction to siloed efforts. It would help standardize best practices, streamline compliance, and strengthen overall cybersecurity resilience across all sectors in India.
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References

• https://cdn.prod.website-files.com/635e632477408d12d1811a64/676e56ee4cc30a320aecf231_Cloudsek%20Annual%20Threat%20Landscape%20Report%202024%20(1).pdf 
• https://strobes.co/blog/top-data-breaches-in-2024-month-wise/#:~:text=In%20a%20large%2Dscale%20data,emails%2C%20and%20even%20identity%20theft. 
• https://www.google.com/search?q=nist+2.0&oq=nist+&gs_lcrp=EgZjaHJvbWUqBggBEEUYOzIHCAAQABiPAjIGCAEQRRg7MgYIAhBFGDsyCggDEAAYsQMYgAQyBwgEEAAYgAQyBwgFEAAYgAQyBwgGEAAYgAQyBggHEEUYPNIBCDE2MTJqMGo3qAIAsAIA&sourceid=chrome&ie=UTF-8 
• https://www.iso.org/standard/27001
• https://nis2directive.eu/nis2-requirements/ 
• https://economictimes.indiatimes.com/tech/technology/india-ranks-number-10-in-cybercrime-study-finds/articleshow/109223208.cms?from=mdr 

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