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Subject: Emerging Technologies

  • DHRUV64 Microprocessor

    Why in the News?

    India has unveiled DHRUV64, its first fully indigenously developed microprocessor, marking a major milestone in semiconductor self reliance and Atmanirbhar Bharat.

    About DHRUV64

    • Fully indigenous microprocessor developed in India
     • Developed by the Centre for Development of Advanced Computing (C DAC)
     • Part of the Microprocessor Development Programme (MDP)

    Key Technical Features

    • 64 bit dual core processor
     • Clock speed of 1.0 GHz ( Very low compared to recent chips like Snapdragan clock speed more 4.0 GHz)
    • Uses superscalar execution allowing multiple instructions simultaneously
     • Supports out of order execution for improved performance
     • Integrated communication and control functions
     • Uses FCBGA packaging, enabling compact and system ready design

    Potential Applications

    • Strategic applications and commercial computing
     • 5G infrastructure
     • Automotive electronics
     • Consumer electronics
     • Industrial automation
     • Internet of Things (IoT) systems

    Significance for India

    • Reduces dependence on foreign microprocessors
     • Strengthens domestic semiconductor ecosystem
     • Enables startups, academia and industry to design and test indigenous systems
     • Supports low cost prototype development for new system architectures
     • Enhances technological sovereignty and national security

    When the alarm of your smart-phone rings… which one of the following terms best applies to the above scenario? (2018)

    (a) Border Gateway Protocol 

    (b) Internet of Things 

    (c) Internet Protocol 

    (d) Virtual Private Network

  • Ekam AI and Project SAMBHAV

    Why in the News?

    During Vijay Diwas celebrations, the Indian Army showcased indigenous defence technologies including Ekam AI and Project SAMBHAV, highlighting progress in defence indigenisation and secure digital capabilities.

    About Ekam AI

    • Fully indigenous and secure Artificial Intelligence platform
     • Designed for sensitive and classified environments
     • No dependence on foreign software or external cloud systems

    Key Features of Ekam AI

    • Data analysis, document management and decision support
     • User friendly AI accessible across all personnel levels
     • No requirement of specialised technical expertise
     • Ensures data security and digital sovereignty

    Significance of Ekam AI

    • Strengthens national data sovereignty
     • Reduces strategic dependence on foreign AI platforms
     • Builds trusted national digital infrastructure

    About Project SAMBHAV

    • Portable satellite based communication system
     • Developed by the Indian Army
     • Provides mobile connectivity in remote, border and disaster affected areas

    Key Features of Project SAMBHAV

    • Rapid deployment capability
     • Functions in network denied areas
     • Supports military operations and civilian disaster response

    Significance of Project SAMBHAV

    • Enhances communication resilience
     • Strengthens national disaster management infrastructure
     • Demonstrates dual use defence technology

    What is Vijay Diwas

    • Observed annually on 16 December
     • Commemorates India’s victory in the 1971 India Pakistan War
     • Led to the liberation of Bangladesh

    Consider the following statements: (2023)

    1. Ballistic missiles are jet-propelled at sub-sonic speeds throughout their fights, while cruise missiles are rocket-powered only in the initial phase of flight. 

    2. Agni-V is a medium-range supersonic cruise missile, while BrahMos is a solid-fu-elled intercontinental ballistic missile. 

    Which of the statements given above is/ are correct? 

    (a) 1 only (b) 2 only (c) Both 1 and 2 (d) Neither 1 nor 2

  • Agentic AI  

    Why in the News?

    Microsoft Chairman and CEO Satya Nadella recently noted that India is witnessing strong momentum in the adoption and deployment of artificial intelligence, particularly agentic AI applications.

    About Agentic AI

    Agentic AI is an advanced form of artificial intelligence that emphasises autonomous decision-making and action. It is designed to act independently in a goal driven manner with minimal human intervention.

    Core Concept

    • Based on AI agents that simulate human-like decision making
     • Capable of setting goals, planning steps, and executing tasks on its own
     • Goes beyond traditional AI systems that mainly respond to prompts or analyse data

    Prelims Pointers

    • Agentic AI emphasizes autonomy and goal orientation
    • Uses large language models as its reasoning engine
    • Key stages include perception, reasoning, planning, action, and reflection
    • Represents an evolution beyond prompt based AI systems
    With the present state of development, Artificial Intelligence can effectively do which of the following? (2020)

    (1) Bring down electricity consumption in industrial units

    (2) Create meaningful short stories and songs

    (3) Disease diagnosis

    (4) Text-to-Speech Conversion

    (5) Wireless transmission of electrical energy

    Select the correct answer using the code given below:

    (a) 1, 2, 3 and 5 only (b) 1, 3 and 4 only (c) 2, 4 and 5 only (d) 1, 2, 3, 4 and 5

  • Diving Support Craft A20

    Why in the news?

    The Indian Navy is set to commission Diving Support Craft (DSC) A20 at Kochi under the Southern Naval Command, marking a key milestone in indigenous naval capability.

    About Diving Support Craft A20

    • First vessel of the indigenously designed and constructed Diving Support Craft class
     • Lead ship in a series of five DSCs
     • Built by M s Titagarh Rail Systems Limited, Kolkata
     • Designed for a wide range of diving and underwater missions in coastal waters

    Prelims Pointers

    • DSC A20 is an indigenously built naval auxiliary vessel
    • Builder: Titagarh Rail Systems Limited
    • Hull type: Catamaran
    • Command: Southern Naval Command
    • Focus areas include diving operations, underwater missions, and salvage support
    Which one of the following is the best description of ‘INS Astradharini’, that was in the news recently? (2016)

    (a) Amphibious warfare ship 

    (b) Nuclear-powered submarine 

    (c) Torpedo launch and recovery vessel 

    (d) Nuclear-powered aircraft carrier

  • [11th December 2025] The Hindu OpED: ​​AI must pay: On the DPIIT working paper on AI and Copyright Issues

    PYQ Relevance

    [UPSC 2024] What is the present world scenario of intellectual property rights with respect to life materials? Although India is second in the world to file patents, still only a few have been commercialised. Explain the reasons behind this less commercialization.

    Linkage: This topic is relevant because it highlights India’s weak IPR monetisation systems and the need for clear licensing frameworks for AI training. It directly links to the issue of poor commercialization of intellectual property due to inadequate revenue and protection mechanisms.

    Mentor’s Comment

    The rapid expansion of AI models such as LLMs has outpaced global regulatory thinking, especially concerning copyright. India’s new working paper on “AI and Copyright Issues” marks a significant policy moment because it attempts to balance innovation with fair remuneration for content creators.  

    Introduction 

    Large Language Models (LLMs) rely heavily on public text, data, and multimedia scraped from the Internet. This has created tension between AI developers and content producers whose material forms the backbone of AI training datasets. India’s Department for Promotion of Industry and Internal Trade (DPIIT) has released a working paper proposing a mandatory licensing framework to ensure remuneration for content creators while keeping AI innovation unhindered. The proposal aims to prevent prolonged litigation, offer a collaborative revenue system, and address the growing disruption in the media landscape.

    Why in the news?

    India’s working paper is significant because it represents the first structured attempt to create a national solution to the global controversy around AI training data and copyright. For years, AI hyperscalers have argued for unrestricted scraping of Internet content, while publishers insisted on licensing and consent. With lawsuits piling up worldwide and no uniform judicial clarity, India’s move is a major shift from unregulated data scraping to a mandatory revenue-sharing model. It highlights the scale of the problem, hundreds of media houses and small publishers risk losing fair compensation as LLMs synthesize new outputs from their work without attribution. The proposal marks a pivot toward balancing AI development with creators’ rights, avoiding a situation that could disadvantage India’s AI ecosystem through excessive restrictions or unchecked exploitation.

    What Drives the Rapid Progress of LLMs?

    1. Iterative advancements in machine learning: Continuous improvements in applied techniques enhance the performance and reasoning ability of LLMs.
    2. Expanding access to global text and multimedia data: Massive publicly available datasets fuel training, improving output depth and sophistication.
    3. Dependence on Internet-scale content: AI firms rely heavily on materials produced by media houses, publishers, and content creators.

    What Is the Core Conflict Between AI Firms and Content Producers?

    1. Free-use argument by AI developers: They claim public Internet content should be freely usable for training, even when outputs are monetized.
    2. Licensing demand from content producers: Reproduction or syndication by AI, directly or indirectly, should require consent and licence fees.
    3. Fierce industry debate: News, entertainment, and book publishing sectors fear uncompensated use of their intellectual property.

    What Does India’s Working Paper Propose?

    1. Mandatory licensing framework: Allows unlimited scraping of public information, but mandates structured payments to a central body.
    2. Non-profit copyright society: Collects royalties from AI developers based on revenues earned through AI models trained on Indian content.
    3. Collaborative revenue-sharing: Ensures creators benefit from the value AI systems extract from their work.

    Why Is the Licensing Model Considered Practical?

    1. Avoids the burden of opting out: Individual content producers lack the power to prevent scraping or enforce restrictions.
    2. Recognizes data processing as a functional reality: AI models synthesize new outputs rather than reproduce original text verbatim.
    3. Addresses inequity concerns: Small publishers may still feel disadvantaged, but a flawed system is preferable to absence of remuneration.

    What Are the Challenges in Implementing the System?

    1. Royalty determination issues: Difficulties in deciding proportional payments, especially between small and large publishers.
    2. Ongoing global litigations: Lawsuits against AI companies continue, and no uniform judicial framework exists yet.
    3. Needless delay is a threat: Waiting for courts to settle the issue only benefits AI firms and worsens market disruption.
    4. Tech industry dissent: Some developers resist additional regulatory burdens but the committee views collaboration as essential.

    Conclusion

    India’s working paper marks an important shift toward a balanced AI-copyright ecosystem. While the proposed licensing structure is imperfect, it offers a practical, collaborative alternative to years of litigation and unregulated data extraction. If supported by the government and refined through stakeholder dialogue, it can ensure that India’s creators, publishers, and AI innovators coexist in a fair and sustainable digital environment.

  • To fulfil STEM potential, India must cast a net wider, go to the roots

    Introduction

    India’s STEM ecosystem faces deep-rooted structural constraints even as the government seeks to reform doctoral guidelines and redirect research toward emerging national needs. The debate highlights persistent gaps in funding, fellowships, university governance, research priorities, and industry linkages. 

    Why in the news?

    The issue is significant because the government has asked ministries and departments to re-examine PhD guidelines and shift focus to topics of national relevance. This action comes at a time when existing systemic problems, like delayed fellowship payments, inadequate stipends, poor institutional support, and the absence of industry linkages, have reached a critical point. Several premier institutions have not paid PhD stipends for months, and research fellowships remain stagnant at ₹8,000 per month since 2012 for many categories, sharply contrasting with inflation and rising living costs. 

    Understanding the Roots of India’s STEM Challenges

    What structural issues limit India’s STEM potential?

    1. Weak Research Relevance: Research funded by government departments often lacks direct relevance to national technological needs, reducing innovation output and long-term applicability.
    2. Low Public Visibility: Communication gaps hinder public understanding of how government-funded research benefits society or advances national capability.
    3. Fragmented Institutional Support: Government departments and agencies lack coordinated mechanisms for selecting and nurturing PhD candidates working in critical areas like energy storage, sustainable agriculture, health tech, and battery technologies.

    Why is applied research struggling in India?

    1. Limited Industry Linkages: Applied science breakthroughs, though central to modern technological advances, receive inadequate industry support, reducing opportunities for scale-up.
    2. Insufficient Local Innovation Ecosystems: Historical examples like the laser or optical fibre show how long-lag research becomes transformative. India still lacks comparable mechanisms to nurture such deep-tech research.
    3. Weak Commercialisation Pathways: The absence of industry-academia collaboration limits the transition from early-stage research to viable technologies.

    How do fellowship and salary problems deepen the crisis?

    1. Delayed Payments: University-funded PhDs and major fellowships like non-NET scholarships frequently experience months-long delays, affecting basic sustenance and productivity.
    2. Inadequate Fellowship Amounts: The ₹8,000 monthly scholarship, unchanged since 2012, remains insufficient even for minimal living costs.
    3. Forced Supplementary Work: Students must take up temporary teaching assignments, reducing time available for research.
    4. Failed Direct Transfer Models: Attempts to transfer fellowship payments directly from banks collapsed due to payment delays and administrative complexities.

    Why is India’s research ecosystem unable to retain talent?

    1. Limited Faculty Positions: Funded PhDs are scarce; many bright students cannot find positions due to narrow intake. 
    2. Opaque Recruitment Processes: Ad-hoc contractual appointments reduce academic stability and deter long-term research commitment.
    3. Weak University Ecosystem: Few Indian universities maintain predictability and transparency in administrative and financial processes.

    What non-STEM burdens weaken STEM research?

    1. Non-scientific Teaching Loads: PhD programmes require students to teach subjects like psychology, sociology, history, diverting time and focus from scientific inquiry.
    2. Administrative Distractions: Non-STEM tasks increase the administrative burden on researchers, affecting scientific productivity.
    3. Cultural undervaluation of STEM: Specific social sciences are privileged in university structures, leading to skewed resource allocation.

    Conclusion

    India’s STEM potential depends on addressing foundational issues, predictable funding, research relevance, ecosystem stability, transparent administration, and meaningful industry linkages. Without systemic reform, higher fellowships alone cannot solve deeper governance failures. Strengthening these roots will determine whether India can build a globally competitive research ecosystem capable of supporting national development.

    UPSC Relevance

    [UPSC 2024] What is the present world scenario of intellectual property rights with respect to life materials? Although India is second in the world to file patents, still only a few have been commercialised. Explain the reasons behind this less commercialization.

    Linkage: This theme links directly to GS-3: Science & Technology, IPR, innovation ecosystem, highlighting gaps between patent filings and commercialization. It is relevant for analysing India’s weak research-to-market pipeline, low industry linkages, funding delays, and systemic failure.

  • Technology Development Fund (TDF) Scheme

    Why in the news?

    DRDO has handed over seven indigenous defence technologies developed under the Technology Development Fund (TDF) scheme to the three Armed Services.

    Technologies Transferred

    1. High-Voltage Power Supply for Airborne Self-Protection Jammers
       Enhances protection of aircraft from radar guided threats
    2. Tide-Efficient Gangway for Naval Jetties
       Assists safe crew movement in high tidal variation zones
    3. Advanced VLF-HF Switching Matrix System
       Efficient communication routing in naval platforms
    4. VLF Loop Aerials for Underwater Platforms
       Underwater long-range communication support
    5. Indigenous Waterjet Propulsion System for Fast Interceptor Craft
       Marine propulsion technology aiding coastal security
    6. Process for Recovery of Lithium Precursors from Used Lithium-ion Batteries
       Supports strategic material recycling and energy security
    7. Long-Life Seawater Battery System
       Provides sustained power for underwater surveillance

    About the TDF Scheme

    • Implemented by DRDO
    • Objective:
      • Support MSMEs and startups in defence innovation
      • Promote import substitution of critical technologies
    • Funding support up to 90 percent of development cost
    • Aligned with Aatmanirbhar Bharat and defence indigenisation push
    Consider the following statements: (2023)

    1. Ballistic missiles are jet-propelled at sub-sonic speeds throughout their flights, while cruise missiles are rocket-powered only in the initial phase of flight. 

    2. Agni-V is a medium-range supersonic cruise missile, while BrahMos is a solid-fuelled intercontinental ballistic missile. 

    Which of the statements given above is/are correct? 

    (a) 1 only (b) 2 only (c) Both 1 and 2 (d) Neither 1 nor 2

  • Tensor Processing Unit (TPU) 

    Why in the news?

    Meta is in advanced talks with Google to use its Tensor Processing Units for large scale AI workloads, indicating a major shift in the AI chip ecosystem. This led to a drop in Nvidia’s stock due to concerns over market share loss.

    What is a TPU

    • A specialized hardware chip designed to accelerate artificial intelligence and machine learning processing
     • Developed by Google in 2016
     • Optimized for tensor computations used in deep learning
     • Widely deployed in data centers and cloud platforms

    Why TPUs are Important

    • Deep learning models require high-speed matrix and tensor calculations
     • CPUs are optimized for general-purpose tasks
     • GPUs are effective for parallel graphics and AI workloads
     • TPUs surpass them in efficiency for specific deep learning operations

    How TPUs Work

    • Built to handle large scale tensor and matrix computations
     • Use massive parallelism to execute numerous operations simultaneously
     • Consume less energy while delivering high throughput
     • Include specialized circuits to avoid unnecessary general-purpose processing overhead

    What are GPU and TPU? 

    ​​GPU: general-purpose parallel compute processor (Used by Navidia)

    TPU: AI-specific chip optimised for deep learning tensor operations
    With the present state of development, Artificial Intelligence can effectively do which of the following? (2020)

    (1) Bring down electricity consumption in industrial units

    (2) Create meaningful short stories and songs (3) Disease diagnosis

    (4) Text-to-Speech Conversion

    (5) Wireless transmission of electrical energy

    Select the correct answer using the code given below:

    (a) 1, 2, 3 and 5 only (b) 1, 3 and 4 only (c) 2, 4 and 5 only (d) 1, 2, 3, 4 and 5

  • Understanding concerns around Sanchar Saathi

    Introduction

    The Department of Telecommunications (DoT) has instructed smartphone manufacturers and importers to pre-install the Sanchar Saathi application on all new mobile devices. The app is designed to combat digital fraud, trace stolen devices, and prevent misuse of SIMs. But its mandatory installation has raised widespread concerns about privacy, surveillance, user consent, and constitutional rights. The government later clarified that the app is “optional,” but the directive mandating its pre-installation has created ambiguity.

    Why in the news

    Sanchar Saathi’s mandatory pre-installation order marks a major shift because devices in India have never required a state-controlled app by default. This reversal from voluntary to mandatory installation has generated concerns about surveillance risks, access to sensitive data, and violation of user consent. The scale is significant as India is the world’s second-largest smartphone market; even small changes affect millions. Legal experts view it as a possible infringement of the fundamental right to privacy.

    What the Government’s App Actually Does

    1. Blocking & Tracking: Allows blocking or locating lost/stolen phones anywhere in India using IMEI-based tracing.
    2. User Option to Block IMEI: Enables users to prevent stolen devices from being activated.
    3. Support to Law Enforcement: Assists police in identifying counterfeit devices and preventing black-market circulation.
    4. Fraud Prevention: Helps report fraudulent calls, messages, and online scams via unified channels.

    Why Has Sanchar Saathi Triggered Concerns?

    1. Ambiguity Around Consent
      1. Unclear Mandate: Pre-installation directive contradicts the Minister’s statement that the app is optional.
      2. User Autonomy: Mandatory installation affects user ability to choose, delete, or disable the app freely.
    2. Expanded State Power
      1. Exceptional Move: First time the government mandated a wide-scale state app on all devices.
      2. Precedent Risks: May normalise future mandates for state surveillance tools.
    3. Privacy Risks
      1. Data Access: App uses Android’s Mobile Security Framework enabling access to call logs, camera, SMS, and unique device identifiers.
      2. Opaque Permissions: Apple devices require permissions for photos, files, and camera.
      3. Potential Misuse: Centralised data collection may heighten misuse & monitoring risks.

    What Data Does Sanchar Saathi Collect?

    1. IMEI Data: Unique identifier used to block stolen devices.
    2. Call Logs & SMS Data: Access allowed when reporting fraud or using suspicious call detection features.
    3. Camera Access: Needed for uploading barcodes of mobile equipment (IMEI verification).
    4. Personal Information: Includes phone numbers, Aadhaar-linked data, and registration details.
    5. Problem: The app’s privacy policy bans sharing identifiable information except when required by law, but the phrase “required by law” remains broad and open-ended.

    Constitutional & Legal Concerns

    1. Lack of Consent: Forced Pre-installation undermines voluntary, informed consent, a core component upheld under the Puttaswamy judgment (2017).
    2. Three-fold Privacy Test: Experts argue mandatory pre-installation fails:
      1. Legality: No explicit statutory backing for a nationwide mandate.
      2. Necessity: No demonstrated need requiring compulsory installation.
      3. Proportionality: Data access far exceeds the minimum required for fraud detection.
    3. Surveillance & “Function Creep”
      1. Risk of Expansion: Potential to expand into unrelated data surveillance functions.
      2. No Independent Oversight: Absence of clear audit mechanisms, grievance redressal, or limits on retention periods.

    Way Forward 

    1. Clarity of the mandate: Issue a clear written policy stating the app’s status to remove confusion.
    2. Addressing Privacy Risks: Limit data permissions to essential functions and publish regular audit reports.
    3. Ensuring Consent & User Autonomy: Provide a visible and fully functional uninstall or disable option.
    4. Preventing Surveillance Overreach: Create independent oversight to monitor misuse and restrict function creep.
    5. Building Trust Through Transparency: Disclose data flows, retention rules, and access logs in the public domain.

    Conclusion

    Sanchar Saathi addresses real concerns of digital fraud and misuse of mobile devices. However, its mandatory pre-installation, broad data permissions, unclear safeguards, and inconsistent communication have created concerns about state overreach and privacy violations. The app’s utility must be balanced with constitutional guarantees, transparent policy design, and robust data protection mechanisms.

    PYQ Relevance

    [UPSC 2024] Right to privacy is intrinsic to life and personal liberty and is inherently protected under Article 21 of the constitution. Explain. In this reference, discuss the law relating to D.N.A. testing of a child in the womb to establish its paternity.

    Linkage: This PYQ links directly to debates on privacy, consent, and proportionality governing state access to sensitive personal data. It shows how intrusion into bodily or digital autonomy must meet strict constitutional tests.

  • [2nd December 2025] The Hindu OpED: The new action plan on AMR needs a shot in the arm

    PYQ Relevance

    [UPSC 2014] Can overuse and free availability of antibiotics without Doctor’s prescription, be contributors to the emergence of drug-resistant diseases in India? What are the available mechanisms for monitoring and control? Critically discuss the various issues involved.

    Linkage: This PYQ directly mirrors the article’s focus on antibiotic misuse, OTC access, and weak regulatory control driving AMR. It lets you use NAP-AMR 2.0 to show gaps in surveillance, stewardship, and One Health governance, exactly what the exam tests.

    Mentor’s Comment

    AMR is now a major threat to India’s health, food systems, and environment. Resistance has moved beyond hospitals into water, soil, and livestock. NAP-AMR 2.0 is timely and shows a stronger, more accountable approach. This analysis helps you clearly understand what worked, what failed, and what must change.It also builds GS2 and GS3 depth through governance, science, environment, and One Health linkages.

    Introduction

    India has released its National Action Plan on Antimicrobial Resistance (NAP-AMR 2.0) for 2025-29, signalling a renewed commitment to containing AMR, a challenge that affects human health, livestock, agriculture, the environment, and food systems. Unlike the first plan (2017), which saw uneven adoption across States, the second plan attempts structural reform through higher accountability, stronger surveillance, private-sector engagement, multi-departmental integration and One Health alignment.

    Why in the news?

    The launch of NAP-AMR 2.0 marks a significant turning point because AMR has now expanded beyond hospitals into soil, water, livestock, markets and food systems, making it a full-spectrum health and environmental challenge. 

    How did the first NAP-AMR evolve and where did it fall short?

    1. Significant early progress: Brought AMR into national consciousness, encouraged multi-sectoral participation, improved laboratory networks, and strengthened stewardship.
    2. One Health recognition: Placed AMR within the interface of human health, animals and environment.
    3. State-level stagnation: Most States undertook only individual activities; only a few (Kerala, MP, Delhi, AP, Gujarat, Sikkim, Punjab) created formal AMR action plans.
    4. Weak institutional execution: Multisectoral One Health structures were missing in most States.
    5. Uneven governance: Human health, veterinary systems, pharmaceuticals and waste management lie under different jurisdictions, causing weak coordination.
    6. Monitoring deficiencies: Surveillance, regulatory oversight, environmental contamination monitoring and antibiotic stewardship remained fragmented.

    What makes NAP-AMR 2.0 more mature and implementation-focused?

    1. Shift to national priorities: Moves beyond intent; outlines clear responsibilities across levels of governance.
    2. Private sector engagement: Recognises that a major share of India’s health care and veterinary services is provided privately.
    3. Scientific strategy: Emphasises innovation, rapid diagnostics, alternatives to antibiotics, and improved environmental monitoring.
    4. One Health deepening: Stronger coordination across food safety, waste management, agriculture, environment and human/animal health.

    What new governance mechanisms does the NAP-AMR 2.0 introduce?

    1. Higher accountability: Greater role for national supervision through a dedicated Coordination and Monitoring Committee.
    2. State-level innovation: Recommends every State establish a One Health inter-ministerial AMR committee, along with State AMR cells.
    3. Integrated reporting framework: Aligns State reporting with national structures for uniform monitoring.
    4. Technical backbone: Calls for a national follow-up mechanism and a multi-departmental coordinating structure.

    Where do administrative and operational gaps persist?

    1. Funding limitations: NITI Aayog’s earlier financial grant-based system did not generate adequate incentives.
    2. Weak incentive design: No system for rewarding State performance or penalising poor progress.
    3. Fragmented responsibility: Human health, veterinary systems, agriculture, pharmaceuticals and waste sectors work under separate ministries and State departments.
    4. Lack of real-time accountability: No statutory notification requiring States to inform the Centre of AMR progress.
    5. Dependence on central push: States often wait for Union-level initiatives rather than proactively building AMR infrastructure.

    What financial and institutional reforms does the article highlight as essential?

    1. Mandatory funding channels: Conditional grants through the National Health Mission (NHM) for surveillance and laboratory systems.
    2. Administrative energy: Once funding becomes compulsory, States respond faster.
    3. Scientific backbone: Need for a sustainable, long-term national centre for AMR control and accountability.
    4. International relevance: Without a Centre-backed national AMR programme, India cannot engage in meaningful global AMR governance.

    Conclusion

    The NAP-AMR 2.0 offers an opportunity to anchor India’s AMR response on a stronger scientific and institutional foundation. But success will require coordinated State participation, financial backing, and accountable governance, not just policy intention. A central AMR Centre, integrated surveillance, and enforceable incentives could finally convert national plans into ground-level action across health systems, veterinary services, agriculture, food safety and environmental management.