14th October 2023 (11 Topics)
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India AI initiative
Context:
As per the report submitted by six working groups to Minister of State for Electronics and Information Technology supported involvement of public-private partnerships, to make semiconductors for AI applications.
About the Report:
- The Working groups gave recommendation advocating the PPP model that would be leveraged to build so-called “GPU clusters”.
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GPU clusters masses of resource-intensive graphics processors that are used by AI applications. |
- These clusters would be made available to Indian start-ups and researchers.
- India AI initiative will be applied to areas like “agriculture, healthcare, education, fintech, security, and governance”.
- India Dataset Platform, a planned “collection which will be among the largest and most diverse collections of anonymised datasets for Indian researchers and startups to train their multi-parameter models” will be required.
- Propose a National Strategy on Robotics:
- The draft strategy recommends fiscal interventions to facilitate local manufacturing of robotics hardware, building of ‘demonstration facilities’ to test and show off technologies, and building capacity in the robotics sector.
- Draft National Strategy on Robotics was circulated for public input in September.
Semiconductors and AI:
- The semiconductor market has, for most of the last decade, seen much of its profits tied to the smartphone and mobile device market.
- As the smartphone market begins to plateau, the semiconductor industry must find other growth opportunities.
- AI applications, especially in the big data, autonomous vehicles, and industrial robotics industries, can provide those opportunities.
- By defining and then putting together their AI strategies now, semiconductor manufacturers can position themselves to take full advantage of the spreading AI market.
How will AI affect the semiconductor market?
- AI offers semiconductor companies the chance to get the most value from the technology stack, the collection of hardware and services used to run applications.
- In the software-dependent world of PCs and mobile devices, the semiconductor industry is only able to capture 20 to 30 percent of the total value of the PC stack and as little as 10 to 20 percent of the mobile market.
- Within the AI sector, the technology stack requires more hardware, especially in the fields of memory and sensors. This may allow the semiconductor market to control 40 to 50 percent of the total value of the stack.
- In addition, many AI applications will require specialized end-to-end solutions, which will necessitate changes to the semiconductor supply chain.
How can semiconductor companies benefit from AI technology?
AI adoption holds the possibility for growth in the following areas of semiconductor manufacturing:
- Workload-specific AI accelerators
- Nonvolatile memory
- High-speed interconnected hardware
- High-bandwidth memory
- On-chip memory
- Storage
- Networking chips
Future of semiconductors and artificial intelligence
- To adapt to an industry increasingly dominated by the need for AI hardware, semiconductor manufacturers will need to provide industry-specific end-to-end solutions, innovation, and the development of new software ecosystems.
- End-to-end services will require chip makers to work with partners to develop industry-specific AI hardware.
- With the production of specialized products comes the need to develop existing ecosystems with partners and software developers.
- The goal of such ecosystems is to develop relationships in which partners rely on and prefer the semiconductor company’s hardware.
- Innovation, as always, plays a role in the future of semiconductors. In addition to the ongoing efforts to circumvent the limitations of Moore’s Law, semiconductor research and development will need to consider how sensors, memory, and microprocessors enable and support emerging AI applications. Focusing on serving the needs of AI and the equally important IoT industry will help keep chip makers at the forefront of the industry.
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Moore’s Law:
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