PIB Summaries 23 October 2025

Content

1. 7nm Processor
2. SOAR: Skilling for AI Readiness

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7nm Processor

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Context and Significance

• Announcement: Union Minister Ashwini Vaishnaw (18 Oct 2025) unveiled India’s indigenous 7 nm processor — marking a strategic milestone in India’s semiconductor journey.
• Institutional Anchor: Developed by IIT Madras under the SHAKTI initiative (since 2013), aligned with MeitY and the India Semiconductor Mission (ISM).
• Strategic Context: Reinforces Atmanirbhar Bharat by building indigenous capability in advanced semiconductor design — a domain long dominated by the US, Taiwan, South Korea, and Japan.

Relevance:

• GS 3 (Science & Technology): Indigenous R&D, semiconductor innovation, electronics manufacturing ecosystem, digital infrastructure.
• GS 3 (Economy): Boost to high-value manufacturing, job creation, and technology-driven GDP growth under PLI schemes.

Semiconductor Basics and India’s Current Standing

Understanding the Semiconductor Node

• Nanometre (nm) denotes transistor size — smaller nodes = more transistors, lower power use, higher performance.
• 7 nm node is considered advanced technology (used in Apple A13, AMD Ryzen 3000 series).
• Global leaders: TSMC, Samsung, and Intel.
• India’s leap to 7 nm design capability places it among advanced design nations, even without full fabrication capacity yet.

India’s Semiconductor Landscape (as of 2025)

Parameter	Status / Data
Mission	₹76,000 crore India Semiconductor Mission (ISM)
Total Investments Approved	₹1.6 lakh crore across 6 states
Projects Approved	10 semiconductor projects
Chip Design Projects Sanctioned	24
Design Companies Using Advanced Tools	87
Academic Institutions Supported (DLI Scheme)	288
Estimated Job Creation	Thousands of high-skill jobs (MeitY projection)

The SHAKTI Initiative – India’s Processor Backbone

Feature	Description
Launched	2013 by IIT Madras’ RISE Lab
Architecture	Based on open-source RISC-V Instruction Set
Goal	Develop indigenous microprocessor IPs free from foreign licensing restrictions
Variants	Target IoT, mobile, embedded, and high-performance computing
Advantage	Startups and academia can build upon open-source designs, enabling distributed innovation

The Indigenous 7 nm Processor — Technical and Strategic Value

Technical Features

• Node: 7 nanometres – high transistor density & energy efficiency.
• Applications: Servers, defence, communications, and strategic computing.
• Performance Goals: High throughput, low power consumption, scalable across devices.

Strategic Importance

• Self-Reliance: Reduces dependency on imported chips.
• AI & 5G Integration: Enables computing infrastructure for 5G, AI, IoT, and supercomputing.
• National Security: Indigenous processors for defence, space, and intelligence systems.
• Digital India Alignment: Core infrastructure for digital transformation.

Institutional & Policy Framework

India Semiconductor Mission (ISM)

• Launched: 2021 under MeitY.
• Objectives:
  • Establish semiconductor & display fabs.
  • Develop design, packaging, and testing ecosystem.
  • Attract global partnerships & domestic investments.

Design Linked Incentive (DLI) Scheme

• Aim: Support fabless startups and academia-led innovation.
• Coverage: Over 288 academic institutions.

Semicon India Programme (2022–2030)

• Roadmap to sub-7 nm design, domestic testing and packaging facilities.
• Encourages PPP model and industry-academia collaboration.

Comparative Global Context

Country	Advanced Node Capability	Notable Companies	Relevance
USA	3 nm & below	Intel, NVIDIA	Advanced design & fabrication
Taiwan	3 nm	TSMC	Global fabrication leader
South Korea	3 nm	Samsung	Advanced fab + design
China	7 nm (SMIC)	SMIC, Huawei	Indigenous despite export controls
India	7 nm (design)	IIT Madras (SHAKTI)	Design breakthrough; fab yet to come

Inference: India joins the second-tier semiconductor innovators (design capability without domestic fabs), but the roadmap points toward full-stack ecosystem development.

Economic and Strategic Impact

Economic Impact

• Semiconductor market projected to reach $80 billion by 2028 (from $23 billion in 2023).
  • Expected to generate over 200,000 jobs directly & indirectly in design, testing, and manufacturing.
  • Attracts high-value global investments under the Production-Linked Incentive (PLI) framework.

Strategic Impact

• Enhances technological sovereignty in defence and critical digital infrastructure.
  • Strengthens India’s position in global supply chain diversification (trusted design partner).
  • Reduces exposure to geopolitical chip vulnerabilities (e.g., Taiwan Strait tensions).

Challenges and Next Steps

Challenge	Policy/Action Needed
No domestic advanced fabrication	Accelerate partnerships with TSMC, Intel, or GlobalFoundries.
High CapEx (>$10 bn per fab)	Viable PPP + long-term fiscal incentives.
Talent shortage in VLSI design	Expand semiconductor design courses in IITs/NITs under ISM.
Supply chain dependence	Build indigenous material & component ecosystem (e.g., silicon wafers, photolithography tools).
Sustainability	Focus on water & energy-efficient fabrication models.

The Road Ahead

Short-Term (2025–27):

• Operationalize 10 sanctioned projects.
  • Begin pilot production in 28 nm and 14 nm fabs (expected in Gujarat, Tamil Nadu).

Medium-Term (2028–32):

• Progress to sub-7 nm R&D.
  • Launch advanced packaging and testing hubs.
  • Integrate chips into India’s AI and 5G hardware stack.

Long-Term (by 2047):

• Achieve end-to-end semiconductor autonomy — design, fab, and export.
  • Position India as a trusted semiconductor partner for the Global South.

Conclusion

• The indigenous 7 nm processor represents a technological assertion of sovereignty, not merely an academic milestone.
• It marks the convergence of innovation, policy, and strategic foresight — where India transitions from consumer to creator in advanced electronics.
• Sustained R&D, industry-academia synergy, and global collaboration will determine whether India can convert this “design breakthrough” into manufacturing dominance by the early 2030s.

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SOAR: Skilling for AI Readiness

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Context and Background

• Global Context:
  The AI economy is projected to add $15.7 trillion to global GDP by 2030 (PwC). Demand for AI, ML, and data-related skills is growing at >40% CAGR.
• National Context:
  India’s AI market is expected to reach $17 billion by 2027 (NASSCOM).
  However, only 3% of India’s workforce currently possesses AI-ready skills — revealing a significant skill gap.
• Policy Frameworks Linked:
  • National Education Policy (NEP) 2020 – Introduced AI in curricula to foster innovation.
  • Skill India Mission (2015–) – Skilling over 1.3 crore youth; now pivoting toward “future skills.”
  • Pradhan Mantri Kaushal Vikas Yojana (PMKVY) 4.0 (2023–24) – Focus on emerging tech: AI, robotics, IoT.
  • Digital India Mission and Viksit Bharat 2047 – Enabling digital inclusion and innovation.

Relevance:

• GS 2 (Governance): Implementation of NEP 2020; role of Ministry of Skill Development & Entrepreneurship; public–private partnerships in education.
• GS 3 (Science & Technology): AI literacy, ethical AI use, and integration of emerging technologies in skilling ecosystem.
• GS 3 (Economy): Human capital development for AI-based industries; employment generation in tech-driven sectors.

 

About SOAR: Skilling for AI Readiness (Launched July 2025)

• Implementing Ministry: Ministry of Skill Development and Entrepreneurship (MSDE)
• Target Groups: Students: Classes 6–12
• Educators: Across government and private schools
• Objective: To create a future-ready, AI-literate generation and empower educators to integrate AI-driven learning into pedagogy.

Program Structure

Category	Modules	Duration	Focus Areas
Students (Class 6–12)	3 modules	15 hours each	Basics of AI, ML, data handling, ethical AI, and applications
Educators	1 module	45 hours	Integrating AI in teaching, curriculum design, and ethics

• Mode of Delivery: Blended learning via Skill India Digital Hub (SIDH) and school-based workshops.
• Union Budget 2025–26 allocation: ₹500 crore for establishing the Centre of Excellence in AI for Education.

Integration within National Skill Ecosystem

1. Skill India Mission (SIM):
   1. AI incorporated into short-term skilling and apprenticeship tracks.
   1. Focus: youth employability and entrepreneurship in high-demand AI sectors.
2. Pradhan Mantri Kaushal Vikas Yojana (PMKVY) 4.0:
   1. AI-based modules under “Future Skills Prime” initiative.
   1. Introduced specialized training for AI Data Engineers, ML Engineers, and AI Trainers.
3. National Apprenticeship Promotion Scheme (NAPS-2):
   1. As of June 2025, 1,480 apprentices trained (FY 2022–26) in AI-related roles.
4. Skill India Digital Hub (SIDH):
   1. A digital platform integrating all skilling programs and AI courses for equitable access.

Institutional and Policy Synergy

Institution / Policy	Contribution to AI Education
CBSE	Introduced AI as a subject in Class IX (2019–20) and Class XI (2020–21).
AICTE	Mandated AI electives across technical and engineering institutions.
IITs	Advanced courses in Deep Learning, Predictive Analytics, and Applied AI.
Centre for Excellence in AI (CoE-AI)	Research hub for AI in education, Indian languages, and pedagogy innovation.
NEP 2020	Encouraged integration of contemporary tech into school curricula.

Strategic Significance

Fostering AI Awareness

• Builds digital curiosity from school level.
• Promotes understanding of ethical AI use and algorithmic fairness.

Supporting Atmanirbhar Bharat

• Creates a domestic talent pool for AI-based industries and startups.
• Reduces dependence on imported tech skills and foreign experts.

Bridging the Digital Divide

• SOAR leverages SIDH and government schools to ensure rural inclusion.
• Facilitates AI literacy in vernacular languages, strengthening inclusivity.

Enhancing Employability and Innovation

• AI skill integration can add $1 trillion to India’s economy by 2035 (Accenture).
• Empowers educators to create AI-infused pedagogy, fostering personalized learning.

Alignment with Viksit Bharat @2047

• Aims for a tech-driven, innovation-led economy.
• Ensures AI-trained youth participation in India’s demographic dividend window (till ~2040).

Challenges and Way Forward

Challenges	Way Forward
Limited AI faculty and infrastructure in schools	Teacher training through SOAR educator module; CoE-AI support
Urban-rural digital gap	Leverage SIDH; integrate AI courses in ITIs and rural digital labs
Low female participation in tech	Gender-inclusive AI skilling drives; partnerships with Skill India’s “Nari Shakti” initiatives
Ethical and privacy concerns	Emphasize ethics modules; collaborate with MeitY for AI governance norms
Scalability of program	Public-private partnerships (e.g., with NASSCOM, Google India, Intel India)

Quantitative Highlights (as of mid-2025)

Indicator	Data
Apprentices trained in AI (FY 2022–26)	1,480
Budget allocation (2025–26)	₹500 crore
Schools introducing AI in CBSE	~25,000+
Students covered under AI elective (since 2019)	~12 lakh
Skill India-trained workforce (since 2015)	~1.3 crore
Target of SOAR (initial phase)	10 lakh students, 50,000 educators (2025–27)

Broader National and Global Linkages

• Global Benchmarks:
  • Finland’s “Elements of AI” program — open-access AI literacy for all citizens.
  • Singapore’s AI for Everyone (AI4E) — community-level AI readiness.
• India’s Comparative Edge:
  • Largest youth base (65% below 35 years).
  • Emerging as a hub for AI innovation, with over 400 AI startups (NASSCOM 2025).

Conclusion

• The SOAR program embodies a forward-looking strategy to integrate AI learning into India’s education and skilling architecture. It connects school-level literacy, teacher empowerment, and industrial employability — building the human capital essential for India’s AI economy.
• With strong fiscal backing (₹500 crore), institutional partnerships (CBSE, AICTE, IITs), and alignment with NEP 2020 and Viksit Bharat 2047, SOAR not only democratizes AI access but ensures India’s leadership in ethical, inclusive, and innovation-driven digital transformation.

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