Why in news?

In 1999, Nvidia introduced the GeForce 256 as the world’s first GPU, designed primarily to enhance video game graphics and performance.

Over the past 25 years, GPUs have evolved far beyond gaming, becoming essential components of the digital economy and powering core technologies such as artificial intelligence and large-scale computing.

What’s in Today’s Article?

• GPU: Understanding the Basics
• How a GPU Works: The Rendering Process Explained?
• Where Is the GPU Located?
• GPUs Vs CPUs
• How Much Energy Do GPUs Consume?

GPU: Understanding the Basics

• A Graphics Processing Unit (GPU) is a specialised processor designed to perform many simple calculations simultaneously.
• Unlike a Central Processing Unit (CPU), which handles fewer but more complex tasks quickly and efficiently, a GPU excels at parallel processing—handling large volumes of repetitive computations at once.
• Why GPUs Are Ideal for Graphics?
  • Rendering images on a screen requires updating millions of pixels multiple times per second.
  • For example, a 1920×1080 display has over 2 million pixels per frame, and at 60 frames per second, more than 120 million pixel updates are required every second.
  • Each pixel’s colour depends on lighting, texture, shadows, and object properties.
  • Since the same calculations are repeated across pixels, GPUs are better suited than CPUs for this kind of workload.
• Parallel Processing Made Simple
  • A GPU can be imagined as a large team of workers, each handling a small portion of a task simultaneously.
  • While each GPU core is less powerful than a CPU core, the GPU contains hundreds or thousands of such cores.
  • This allows it to process large, repetitive workloads far more quickly than a CPU working alone.

How a GPU Works: The Rendering Process Explained?

• When a video game displays a scene, it sends the GPU objects built from triangles.
• The GPU processes them through a four-step rendering pipeline to produce the final image.
• Vertex Processing - The GPU calculates where each triangle should appear on the screen. Using mathematical operations with matrices, it rotates, moves, and adjusts objects according to the camera’s perspective.
• Rasterisation - Once positioned, the GPU determines which screen pixels each triangle covers. This step converts geometric shapes into pixel-level data ready for colouring.
• Fragment (Pixel) Shading - For each pixel fragment, the GPU calculates the final colour. It applies textures, lighting, shadows, reflections, and other visual effects using small programs called shaders.
• Frame Buffer Output - The computed pixel colours are written to memory known as the frame buffer. The display system then reads this buffer to render the final image on the screen.
• Parallel Processing and Memory Design
  • GPUs execute shader programs simultaneously across many vertices and pixels.
  • To handle massive data flows—such as 3D models and textures—they use dedicated high-bandwidth memory called VRAM (video RAM).
  • Smaller, faster caches and shared memory structures help prevent bottlenecks.
  • Because GPUs excel at repeating similar calculations across large datasets, they are widely used beyond graphics in machine learning, image processing, and scientific simulations.

Where Is the GPU Located?

• The GPU as a Silicon Chip - A GPU is built on a silicon die — a flat piece of semiconductor material measured in square millimetres. Like a CPU, it is a physical chip mounted inside a computing device.
• Dedicated Graphics Card Setup - In systems with a separate graphics card, the GPU die sits beneath a metal heat sink at the centre of the card. It is surrounded by VRAM chips and connects to the motherboard through a high-speed interface.
• Integrated Graphics in Modern Devices - In laptops and smartphones, the GPU is often integrated with the CPU on the same die. This design is common in modern systems-on-a-chip (SoCs), which combine multiple components that were previously separate into a single package.

GPUs Vs CPUs

• GPUs are not fundamentally smaller than CPUs. Both use similar silicon transistors and advanced fabrication nodes (e.g., 3–5 nm).
• The difference lies in microarchitecture — how transistors are organised and used.
• CPUs dedicate more die area to complex control logic, cache, and decision-making features.
• GPUs allocate more space to repeated compute units and wide data paths, enabling parallel processing.

How Much Energy Do GPUs Consume?

• Energy During Training - In a scenario using four Nvidia A100 GPUs (250 W each) for 12 hours of neural network training, total energy consumption would be about 12 kWh, as the GPUs run near full capacity.
• Energy During Inference - Once deployed, if one GPU handles predictions, energy use drops to roughly 2 kWh for inference.
• Total System Consumption - Including additional server components (CPU, RAM, storage, cooling), total daily power use can reach around 6 kWh when running continuously, accounting for 30–60% overhead.
• Real-World Comparison - This is comparable to running an air conditioner for 4–6 hours, a water heater for 3 hours, or 60 LED bulbs for 10 hours daily.

Why in news?

Indian households are diversifying their savings, with investments in mutual funds and equities rising sharply — from 7% of financial assets in 2022–23 to 15% in 2024–25 — while bank deposits declined slightly. However, the long-standing preference for gold remains strong.

Gold imports surged to $12.07 billion in January, nearly tripling from December. A growing channel for this investment is gold exchange-traded funds (ETFs), reflecting the increasing financialisation and formalisation of household savings, even as it adds to gold import pressures.

What’s in Today’s Article?

• Gold ETFs: From Niche Product to Investment Wave
• Sovereign Gold Bonds: A Policy Experiment
• Renewed Concerns Over Gold Investments

Gold ETFs: From Niche Product to Investment Wave

• Gold ETFs function like mutual funds that invest in gold. They offer advantages over physical gold—no concerns about purity, storage, or security, and the flexibility to invest in small amounts.
• The fund handles gold purchases based on investor inflows.
• Record Inflows in January
  • What began modestly in 2007 surged dramatically in January. According to the World Gold Council, Indian gold ETFs purchased a record 15.52 tonnes of gold in January—nearly equal to the previous three months combined.
  • Data from AMFI show net gold ETF inflows more than doubled to an all-time high of ₹24,040 crore, even as equity mutual fund inflows fell 14% to ₹24,029 crore.
  • For the first time, gold ETFs attracted more investment than equity funds.
  • Gold ETF inflows accounted for 22% of total gold imports (₹1.1 lakh crore) in January. The share was even higher for silver—52% of silver imports were linked to ETF inflows.
• Speculation and Economic Concerns
  • Analysts suggest the surge may reflect large-scale speculation in precious metals.
  • While it may represent a shift from physical gold demand, concerns remain that heavy investment in gold—financial or physical—effectively amounts to capital moving out of the domestic economy.
• Gold Rush Redux: Lessons from the Past
  • After the 2008 global financial crisis, high inflation, a weakening rupee, and slow growth drove Indian households toward gold.
  • Imports surged, forcing the government and RBI to curb free imports and introduce measures to discourage physical gold purchases.

Sovereign Gold Bonds: A Policy Experiment

• Launched in 2015, Sovereign Gold Bonds (SGBs) offered returns linked to gold prices plus 2.5% annual interest.
• Indians invested in bonds equivalent to 147 tonnes of gold worth ₹72,274 crore, reducing the need for physical imports.
• Rising gold prices made the scheme costly, with annual payouts nearing ₹18,000 crore. The government discontinued SGBs in early 2024 due to mounting fiscal pressure.

Renewed Concerns Over Gold Investments

• Although inflation is currently moderate, geopolitical tensions, policy uncertainty, and uneven global stock market gains have renewed interest in gold as a safe haven.
• A January spike in gold ETF-driven imports pushed India’s goods trade deficit close to $35 billion, highlighting macroeconomic risks.
• Given rising precious metal demand, a redesigned Sovereign Gold Bond scheme—possibly extended to silver and other metals—may help manage imports while offering households structured investment alternatives.

Context:

• India’s path to achieving net-zero emissions by 2070 will significantly depend on scaling up the production and consumption of green steel, given that the steel sector is one of the country’s largest industrial sources of emissions.
• Recognising this, the Ministry of Steel formed 14 task forces comprising industry leaders and technical experts to chart decarbonisation pathways and develop a roadmap for accelerating low-carbon steel production.
• However, a major challenge identified was the “green premium” — the higher upfront cost of producing green steel.
• Manufacturers face financial constraints in transitioning to cleaner technologies.
• To address this, the roadmap emphasises the need for targeted fiscal support in the initial years, including GST rationalisation and time-bound incentives, to ease the burden on producers and facilitate the shift toward sustainable steel production.
• This article highlights how transitioning to green steel is central to India’s net-zero 2070 ambition, examines the challenge of the “green premium,” and explores how procurement reform, fiscal support, and verification mechanisms can accelerate low-carbon steel adoption.

Green Steel Premium: A Manageable Cost for Strategic Gains

• Limited Impact on Public Infrastructure Costs
  • Although green steel carries a premium, its overall impact on infrastructure budgets is modest.
  • Steel makes up about 18% of large public projects. Even with a 30% premium and exclusive public-sector use, overall project costs would rise by roughly 5.5%.
  • If only 20% adoption occurs, the increase in public works budgets such as highways would be around 1.1%.
• Strategic and Economic Rationale
  • The incremental cost is viewed as manageable, particularly as a safeguard for national economic security.
  • India faces pressure from the EU’s Carbon Border Adjustment Mechanism and heavy reliance on imported coking coal, exposing the economy to price volatility.
  • Green steel can help avoid carbon tariffs and reduce vulnerability to fossil fuel shocks.
• Lessons from Global Models
  • International examples offer guidance. Japan’s Green Purchasing framework combines procurement mandates with fiscal incentives to support industry transition.
  • California’s Buy Clean model uses strict carbon benchmarks and verified disclosures to ensure traceability and accountability.
• India’s Green Steel Framework
  • India has introduced a Green Steel Taxonomy featuring a 3, 4, and 5 star rating system based on emission intensity, providing transparency through a carbon “nutrition label.”
  • The Ministry has initiated steps to embed green steel procurement mandates, but final approval is pending due to concerns over costs and verification mechanisms.

Bridging the Trust Gap in Green Steel Procurement

• Strengthening Verification and Transparency
  • A key barrier to green steel adoption is the lack of reliable verification.
  • Procurement officers currently cannot easily distinguish certified green steel from conventional products.
  • Integrating Green Star ratings into the existing Made in India QR code system, alongside Quality Council of India accreditation, can enable instant carbon credential verification.
• Reforming Procurement Frameworks
  • Procurement policies should move beyond the lowest-cost principle and adopt a broader “value for money” approach that factors in sustainability and national economic interests.
  • The Schedule of Rates must formally recognise certified low-carbon steel as a standard quality parameter, reducing administrative risk for officers. Capacity building and coordination with States are also essential.
• Aligning Incentives with Demand
  • Production Linked Incentives and green hydrogen missions should be aligned with public procurement.
  • If the government subsidises green steel production, it must also act as an anchor buyer to ensure market stability and harmonise private and public incentives.
• Phased Standards and Pilot Implementation
  • While a 3-star benchmark offers an entry point, policy should gradually shift toward 4 and 5 star standards post-2030 to encourage deeper decarbonisation.
  • Launching pilot projects through large public buyers like Indian Railways can create a practical testing ground.
  • Coordinated action among the Ministries of Steel, Finance, and Environment will be crucial to link climate goals with procurement and fiscal policy.

Why in the News?

• Prime Minister Narendra Modi articulated India’s Artificial Intelligence Vision at the AI Impact Summit 2026, emphasising AI as a global common good and announcing the New Delhi Frontier AI Impact Commitments.

What’s in Today’s Article?

• PM’s Address at AI Summit (India’s Approach, MANAV Framework, AI as a Tool for Inclusion, Multilingual AI, AI Governance, Economic Transformation, etc.)

India’s Approach to Artificial Intelligence (AI)

• At the AI Impact Summit held in New Delhi, the Prime Minister stated that India does not view AI with fear, but sees “fortune and the future” in it.
• Addressing global technology leaders and policymakers, he argued that AI represents a transformative moment in human history and must be shaped responsibly.
• India’s approach differs from that of some countries and corporations that treat AI as a strategic and confidential asset.
• Instead, India has proposed that AI should be developed as a “global common good” benefitting humanity only when it is shared openly.
• The Prime Minister emphasised that open-source development and collaborative innovation would allow millions of young innovators worldwide to make AI systems safer and more effective.

The MANAV Framework

• Central to India’s Artificial Intelligence Vision is the “MANAV” framework, an acronym representing key governance principles:

• Moral and Ethical Systems: AI must be grounded in ethical guidelines.
• Accountable Governance: Transparent rules and strong oversight mechanisms are necessary.
• National Sovereignty: Data ownership must remain with those who generate it.
• Accessible and Inclusive: AI should not become a monopoly but act as a multiplier for society.
• Valid and Legitimate: AI applications must be lawful, verifiable, and trustworthy.

• This framework reflects India’s attempt to balance innovation with regulation, ensuring AI remains human-centric rather than machine-centric.

AI as a Tool for Inclusion and Global South Leadership

• India positioned itself as a voice for the Global South in AI governance. The Prime Minister underlined that AI must be democratised and used for inclusion and empowerment, especially in developing countries.
• The summit also saw the signing of the New Delhi Frontier AI Impact Commitments, a voluntary framework adopted by major global and Indian AI companies, including Google, OpenAI, Meta, Microsoft, Anthropic, and Indian firms.
• These commitments focus on:

• Evaluating AI systems for real-world contexts.
• Strengthening multilingual and cross-cultural AI capabilities.
• Enhancing analysis of AI’s impact on jobs, skills, and economic transformation.

• Companies pledged to publish statistical insights from anonymised and aggregated usage data by the next summit. This is aimed at supporting evidence-based policymaking.

Multilingual AI and Digital Public Infrastructure

• A notable development was the livestreaming of the Prime Minister’s speech in seven Indian languages using AI-powered translation tools.
• This reflects India’s push to leverage digital public infrastructure such as BHASHINI for language inclusion.
• The emphasis on multilingual AI is critical for India, given its linguistic diversity. It also aligns with the broader goal of making AI accessible beyond English-dominant ecosystems.

AI Governance, Deepfakes and Authenticity Standards

• The Prime Minister raised concerns about deepfakes and fabricated content destabilising open societies. Drawing an analogy with food nutrition labels, he suggested that digital content should carry authenticity labels to help users distinguish between real and AI-generated material.
• The need for watermarking and source verification standards was highlighted as part of responsible AI governance. This aligns with global debates on regulating generative AI and combating misinformation.

Economic Transformation and Skilling

• AI was described as a catalyst for higher-value and creative roles, fostering innovation and entrepreneurship.
• However, the Prime Minister emphasised the importance of skilling, reskilling, and upskilling to manage workforce transitions.
• India is simultaneously building a resilient ecosystem that includes semiconductor manufacturing, quantum computing, secure data centres, and a robust IT backbone.
• According to the Prime Minister, any AI model that succeeds in India’s diverse and large-scale environment can be deployed globally.
• This positions India as a potential hub for affordable, scalable, and secure AI solutions.

Strategic Context and Global Debate

• The summit took place amid global competition over AI dominance.
• While some countries advocate building AI systems within closed national stacks, India has emphasised openness and collaboration.
• India’s Artificial Intelligence Vision thus seeks to balance:

• Technological sovereignty,
• Ethical governance,
• Economic growth, and
• Global cooperation.

Context:

• The recent Artificial Intelligence (AI) Summit in Delhi, held shortly after the Union Budget 2026, has sparked a wider debate about India’s developmental trajectory.
• India’s policy ambition remains bold — ranging from AI leadership to semiconductor manufacturing and data-centre expansion.
• However, the summit exposed a persistent structural weakness: the gap between announcement and implementation.

The Budget 2026 - Ambition Without Retrospection:

• Detailed review avoided: Finance Minister (Nirmala Sitharaman) presented her ninth consecutive Union Budget, notable for its restrained rhetoric. However, the speech avoided a detailed review of past flagship programmes.
• Key observations:
  • Multiple new initiatives announced.
  • Long-term commitments, for example, 25-year tax holiday for semiconductor manufacturing, incentives for data centres and cloud infrastructure, and long-term skill development programmes.
  • Fiscal consolidation path maintained.
• Structural limitation of Budgets:
  • With GST institutionalised, customs duties aligned with trade agreements, and limited room for major direct tax reforms, annual budgets now signal direction rather than drive transformation.
  • Wealth tax and agricultural taxation remain politically sensitive.
  • Only about 30 million individuals pay income tax out of roughly 90 million in the tax net.
  • However, meaningful gains now depend on administrative reform, not fiscal announcements.

The AI Summit:

• Symbolism vs reality: The AI Summit was intended to project India as a global AI leader. However, operational lapses — long queues, overcrowding, and notably, cash-only counters at a digital summit — symbolised deeper administrative weaknesses.
• The irony: A summit celebrating digital infrastructure, UPI ecosystem, and AI innovation was undermined by basic logistical failures.
• This reflects a recurring governance pattern: Strong policy vision, weak last-mile execution. 

The Broader Economic Pattern:

• Manufacturing stagnation:
  • Manufacturing share remains around 16–17% of GDP for nearly two decades.
  • This is despite lower labour costs than competitors (including China), Production-linked incentives, infrastructure expansion, etc.
  • This is because of execution bottlenecks like project delays, regulatory hurdles, land and compliance issues.
• Fiscal incentives vs governance quality:
  • Tax holidays and incentives (e.g., semiconductor mission, data centres) cannot substitute for predictable regulation, administrative efficiency, judicial speed, logistics and supply chain management, and trust-based taxation.
  • The Laffer Curve (logic popularised by Ronald Reagan) highlights that lower compliance costs and trust-based taxation may improve collections more sustainably than coercion.

Lessons from Reform History:

• The 1991 moment:
  • The landmark reforms of 1991 occurred during a balance-of-payments crisis when foreign exchange reserves covered only days of imports.
  • Unlike that crisis-driven transformation, contemporary reforms operate without existential urgency.
• Reform thinkers and incrementalism:
  • Several prominent economists have warned against excessive bureaucratic activism without necessity, advocated credible incremental reforms, and emphasised calibrated gradualism suited to India’s political economy.
  • Common insight: Implementation determines success more than policy design.

The Core Governance Challenge:

• After 35 years of economic liberalisation, India’s development constraint is no longer primarily policy design.
• It is the execution deficit, like,
  • Weak last-mile delivery.
  • Institutional capacity constraints.
  • Compliance burden.
  • Adversarial tax administration.
  • Regulatory unpredictability.
• Even digital filing systems alone cannot build trust.

Institutional Reform:

• Creating an “Implementation Commission”: Focused not on designing schemes but on ensuring delivery.
• Main idea: Though paradoxical — creating bureaucracy to reduce bureaucratic inefficiency — the idea underscores the urgency of -
  • Outcome-based monitoring.
  • Inter-ministerial coordination.
  • Process simplification.
  • Administrative accountability.
  • Governance innovation.

Other Challenges and Way Forward:

• Policy overproduction: Too many schemes, insufficient review. Shift from scheme-centric to delivery-centric governance. Evaluate old schemes before launching new ones. Institutionalise sunset clauses and outcome audits.
• Trust deficit in tax administration: Trust-based taxation, resulting in lower compliance costs, stable regulatory regime, and predictable dispute resolution.
• Event management vs institutional strength: Civil service reforms - Specialised technical cadres for AI, semiconductor, and digital sectors. Project management capabilities.

Conclusion:

• The AI Summit and Budget 2026 together highlight a critical truth: India does not lack ambition, it lacks consistent execution.
• Incremental reform can indeed produce transformative change — but only if implementation itself becomes the central reform agenda.
• India’s next developmental leap will begin when delivery replaces declaration as the metric of success. Ultimately, the question is not what India announces — but what it implements.

Context

• The dispute over Iran’s nuclear programme reflects the intersection of security concerns, regional rivalries, and great-power politics.
• What appears as a technical debate over atomic capability is in fact a broader contest over influence, deterrence, and political legitimacy in West Asia.
• Over time, U.S. policy has moved in a cycle, negotiation, withdrawal, coercion, and a renewed return to diplomacy.
• The issue demonstrates that even adversarial relationships cannot be managed solely through force; they ultimately return to political bargaining.
• The core challenge remains balancing non-proliferation, deterrence, and stability without igniting a wider conflict.

The Origins: Diplomacy and the JCPOA

• In 2015, the Joint Comprehensive Plan of Action (JCPOA) emerged from negotiations between Iran and the P5+1, the United States, United Kingdom, France, Russia, China, and Germany.
• Western governments suspected Iran of pursuing nuclear weapons, while Tehran insisted its programme served civilian nuclear energy.
• The agreement-imposed inspections, restrictions on enrichment, and monitoring mechanisms designed as verification measures rather than trust-based commitments.
• Iran sought relief from economic sanctions, while the international community aimed to prevent a nuclear arms race.
• The deal represented pragmatic diplomacy: neither side achieved full objectives, but both reduced immediate risks.
• It embodied a broader principle of arms control, managing capability instead of eliminating knowledge.
• The agreement temporarily stabilised the region and reopened economic engagement with Iran.

The Trump Administration: Withdrawal and Coercive Strategy

• In 2018, President Donald Trump withdrew the United States from the JCPOA, arguing it failed to protect American interests.
• This move strained relations with European allies and disrupted the coordinated international approach.
• A policy of maximum pressure followed, combining sanctions and later military strikes on Iranian nuclear and air-defence facilities in 2025, conducted with support from Israel.
• Despite the coercive strategy, negotiations re-emerged. The shift revealed a central reality: military action can damage infrastructure but cannot erase technological capability or geopolitical influence. Even after escalation, diplomacy became necessary again.
• The situation illustrated the limits of force and the persistence of diplomatic engagement as an unavoidable tool of international politics.

Israel’s Security Perspective

• For Israel, Iran’s nuclear development is viewed as an existential danger.
• Prime Minister Benjamin Netanyahu consistently advocated preventing Iran from reaching a nuclear threshold.
• Israeli intelligence assessments heavily influenced U.S. decision-making, reinforcing fears that Iran was moving toward weaponization.
• Israel prioritises prevention above containment, seeking permanent restrictions rather than temporary arrangements.
• The difference between Israeli urgency and American strategic calculation highlights how alliances shape superpower policies.
• While Washington balances global commitments, Israel focuses on immediate national survival, making the issue central to its national security doctrine.

Regional Actors: The Gulf States and the Fear of War

• The Gulf states share rivalry with Iran yet strongly oppose escalation. Their economies depend on trade routes, energy exports, and investor confidence.
• A regional war would disrupt oil markets, maritime shipping, and infrastructure across the Persian Gulf. Stability, even with a rival Iran, is preferable to open conflict.
• Iran has warned it retains retaliatory capability, including potential attacks on U.S. military bases in the region.
• The threat of wider confrontation raises fears of a prolonged crisis. Uncertainty surrounding leadership decisions intensifies anxiety, as unpredictability increases the risk of miscalculation. The priority for regional actors is de-escalation rather than victory.

India’s Strategic Interests and Domestic Politics Inside Iran

• India’s Strategic Interests
  • For India, Iran is more than an energy supplier. Tehran once ranked among India’s major sources of crude oil, linking the issue directly to energy security.
  • The Chabahar Port project provides access to Afghanistan and Central Asia without dependence on Pakistan, making Iran vital for regional connectivity and trade.
  • Iran’s relations with Pakistan, its pragmatic engagement with the Taliban, and its role in Central Asian politics affect India’s broader strategic environment.
  • Sanctions disrupted trade and weakened cooperation, making diplomatic resolution essential. A negotiated settlement supports both economic engagement and geopolitical balance.
• Domestic Politics Inside Iran
  • Internal dynamics within Iran strongly influence external negotiations. Persistent protests, economic pressure, and factional rivalry shape policymaking.
  • External attacks tend to strengthen conservative factions and promote nationalism, weakening reform-oriented moderates who favour engagement.
  • Military pressure therefore produces unintended consequences: instead of compliance, it consolidates domestic unity.
  • Political legitimacy becomes tied to resistance, complicating compromise.
  • Negotiations succeed only when internal political conditions allow leadership to justify cooperation without appearing weak.

Conclusion

• The Iran nuclear issue demonstrates a recurring pattern in international relations: confrontation ultimately returns to negotiation.
• Diplomatic agreements such as the JCPOA may be imperfect, but they reduce immediate risk more effectively than prolonged conflict.
• For regional powers, the stakes involve survival and economic continuity. For global actors, they involve credibility and strategic balance.
• For India, they concern trade routes, energy, and geopolitical access and the broader lesson is clear: sustainable security requires persistent diplomacy, because the alternatives, escalation, retaliation, and regional war, carry unpredictable and far greater costs.