• UGI USER
  • Aug 01, 2024
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THE RACE TO CONTROL THE GLOBAL SUPPLY CHAIN FOR AI CHIPS

Syllabus:

GS 3:

  • Science and Technology- Developments and their Applications.
  • Awareness in the fields of IT

Why in the News?

India is at a critical juncture as it seeks to bolster its position in the global AI and semiconductor supply chain. Recent government initiatives and investments underscore the country’s ambition to become a major player, addressing strategic dependencies and fostering technological innovation.

Source:KNN

Historical Context

  • Early Innovations: In 1958, Jack Kilby of Texas Instruments created a silicon chip with one transistor. By 1965, Fairchild Semiconductor produced a chip with 50 transistors, marking significant progress.
  • Moore’s Law: Gordon Moore observed that transistor counts on silicon chips doubled annually, driving the computing revolution.
  • Modern Advancements: In 2025, Apple’s iPhone 15 Pro featured the A17 Bionic chip with 19 billion transistors, highlighting exponential growth in chip technology.
  • Impact on Computing: Miniaturization of transistors made them cheaper and faster, enabling today’s advanced computing capabilities.
  • Limits of Moore’s Law: Increasing computational demands, especially from neural networks, are stretching Moore’s Law to its limits.
  • Matrix Multiplication Needs: AI training requires extensive matrix multiplication, becoming computationally intensive with large data sets.

Technological Evolution

  • Graphics Processing Units (GPUs): Nvidia developed GPUs to handle high computational demands, excelling in simultaneous matrix multiplications.
  • Energy Efficiency: GPUs consume significantly less energy compared to CPUs, enhancing efficiency in AI training.
  • Deep Learning Breakthroughs: Models like AlexNet in 2012 required GPUs for their computational power, advancing deep learning.
  • Large Language Models (LLMs): LLMs, such as GPT, demand vast computational resources for training, driving innovation in chip technology.
  • Training Costs: Training advanced models like GPT-4 involves significant computational costs and resources.
  • Infrastructural Investments: Tech giants are investing heavily in AI infrastructure, focusing on developing and maintaining large AI clusters.

Geopolitical Dynamics

  • US Export Controls: The US has implemented export controls on advanced chips to China, aiming to maintain a technological edge.
  • China’s Response: China invests heavily in developing its chip supply chain to achieve technological self-sufficiency.
  • Global Investments: Countries worldwide are increasing investments in semiconductor manufacturing to reduce foreign dependency.
  • TSMC’s Expansion: TSMC is expanding operations with significant investments in new fabs in the US, Japan, and other countries.
  • Strategic Partnerships: Nations are forming strategic partnerships to secure the global semiconductor supply chain.
  • Future Outlook: The race to control the AI chip supply chain will shape future technological and geopolitical dynamics.

Technological Implications

  • Scaling Challenges: Innovative approaches are needed as transistor miniaturization reaches physical limits, including vertical stacking.
  • Performance Plateau: Maintaining performance improvements requires more chips rather than faster ones, leading to clustered solutions.
  • AI Model Expansion: Continuous growth of AI models underscores the importance of efficient and scalable hardware solutions.
  • Energy Efficiency Focus: Chip design innovations prioritize energy efficiency to manage high power consumption in AI computations.
  • Custom AI Chips: Development of specialized AI chips, like Nvidia’s Blackwell and Google’s TPU, optimizes performance and efficiency.
  • Industry Standards: Establishing industry standards, such as Nvidia’s CUDA framework, unifies and advances AI hardware capabilities.

Strategic Considerations

  • Investment Priorities: Tech companies prioritize investments in AI infrastructure, focusing on developing advanced chip clusters.
  • Collaborative Initiatives: Collaborative efforts between companies and governments strengthen the global semiconductor supply chain.
  • Innovation Ecosystem: Fostering an innovation ecosystem supports the development of cutting-edge AI hardware.
  • Regulatory Environment: Navigating export controls and intellectual property protections is critical for companies in the AI hardware market.
  • Sustainable Practices: Implementing sustainable practices in chip manufacturing and data center operations addresses environmental concerns.
  • Long-Term Vision: Developing a long-term vision for the AI chip industry, considering technological, economic, and geopolitical factors, will shape future global AI advancements.
India Semiconductor Mission (ISM)

About:

  • Launch: Introduced in 2021 with a financial outlay of Rs 76,000 crore under the Ministry of Electronics and IT (MeitY).
  • Purpose: Part of a comprehensive program to develop sustainable semiconductor and display ecosystems in India.
  • Support: Aims to provide financial support to companies investing in semiconductor and display manufacturing, as well as design ecosystems.
  • Leadership: Envisioned to be led by global experts, ISM will act as the nodal agency for smooth implementation of related schemes.

Components:

1.   Semiconductor Fabs Scheme:

  • Support: Offers fiscal support to eligible applicants for setting up semiconductor wafer fabrication facilities.
  • Goal: Attract large investments in semiconductor wafer fabrication in India.

2.   Display Fabs Scheme:

  • Support: Provides fiscal support to eligible applicants for setting up TFT LCD / AMOLED display fabrication facilities.
  • Goal: Encourage investments in display fabrication infrastructure in the country.

3.  Compound Semiconductors/Silicon Photonics/Sensors Fab Scheme:

  • Support: Provides 30% fiscal support of capital expenditure for setting up these fabs and ATMP/OSAT facilities.
  • Goal: Facilitate the establishment of advanced semiconductor and sensor fabrication facilities.

4.  Design Linked Incentive (DLI) Scheme:

  • Support: Offers financial incentives and design infrastructure support for developing and deploying semiconductor designs for ICs, Chipsets, SoCs, Systems & IP Cores.
  • Goal: Enhance semiconductor design capabilities in India.

Current Challenges

  • Energy Requirements: AI models’ computational needs require substantial energy consumption, prompting investments in energy-efficient data centers.
  • Inference Efficiency: Running trained AI models demands significant resources. Tailored chips like FPGAs and ASICs improve efficiency.
  • Nvidia’s Dominance: Nvidia leads the market with expertise in GPU development and software frameworks like CUDA.
  • Competitor Innovations: Companies like Cerebras and Google’s custom TPU offer alternative architectures, challenging Nvidia’s dominance.
  • Geopolitical Leverage: AI chip technology has become a geopolitical asset, with few key players controlling the global supply chain.
  • Supply Chain Vulnerabilities: Concentration of chip-making in specific regions makes the supply chain susceptible to geopolitical tensions.

What India Needs to Do

  • Invest in Semiconductor Manufacturing: India should significantly increase investments in semiconductor manufacturing, developing local fabs to reduce dependency on foreign suppliers and strengthen its position in the global supply chain.
  • Enhance R&D Capabilities: Establish advanced research and development centers focused on AI and semiconductor technologies, fostering innovation and attracting top talent to drive technological advancements.
  • Strategic Partnerships: Form strategic alliances with leading global technology companies and nations to gain access to cutting-edge technologies, share best practices, and collaborate on critical projects.
  • Develop Skilled Workforce: Implement comprehensive education and training programs to develop a skilled workforce proficient in AI, semiconductor manufacturing, and related fields, ensuring a steady supply of qualified professionals.
  • Infrastructure Development: Invest in robust infrastructure, including reliable power supply and state-of-the-art facilities, to support large-scale semiconductor and AI research and manufacturing operations.
  • Favourable Policies: Create a conducive policy environment with incentives for investments in technology sectors, streamlined regulations, and support for startups and innovation.
  • Focus on Sustainability: Emphasize sustainable practices in semiconductor manufacturing and AI development, ensuring environmental considerations are integrated into technological advancements.

Conclusion

India’s proactive steps towards strengthening its AI and semiconductor capabilities are crucial for economic growth and technological self-reliance. Continued investment, strategic partnerships, and a focus on developing a skilled workforce will be key to achieving long-term success in these high-tech sectors.

Source:Indian Express

Mains Practice Question:

Discuss the strategic importance of strengthening India’s AI and semiconductor capabilities. What measures can the government take to enhance India’s position in the global technology supply chain?

Associated Article:

https://universalinstitutions.com/justifications-to-examine-a-semiconductor-scheme/