Panel Discussion: Assessment of Opportunities For Skills Development in AI/ML Electronics Hardware Sector

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Industry Veterans Assessing Opportunities For Skills Development in AI/ML Electronics Hardware Sector
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  • Hosted by Electronics Sector Skills Council of India, the discussion also unveiled a report titled AI/ML in electronics hardware
  • This report highlights that the AI industry is set to grow to USD 482.8 billion by 2025
  • AI hardware industry spending is likely to double every year till 2025 to reach USD 54.6 billion
  • The report pointed out that while the AI industry will leverage India’s existing software capabilities, but hardware expertise is an emerging opportunity

AI, ML, and Data Sciences have become what IT and ITES industry were in the 1980s. The scope of opportunities is humongous. Just like the IT and ITES industry, these can dominate almost every aspect of growth and business in the coming times. However, AI hardware is in its nascent stage since semiconductor chip development has a limited presence in India.

Discussing the same, and also the opportunities and challenges, in the AI and ML hardware electronics, a panel moderated by Poornima Shenoy, CEO, Hummingbird Advisors shed light on to tap the opportunities and the way ahead. This panel discussion was hosted by the Electronics Sector Skills Council of India (ESSCI).

Esteemed panelists included NK Mohapatra, CEO, ESSCI; Ashok Mishra, VP, ASIC BU, ALTEN Calsoft Labs; Bharat Daga, Principal Engineer &Director of Engineering, Intel Corporation, and Sathya Prasad, Director, Center for Innovation & Entrepreneurship (CIE), PES University. The panel discussions included AI & ML electronics hardware from the startup and entrepreneurial perspective, deep-tech angle, formal education perspective, and skilling & upskilling angle.

Dr. BK Murthy, senior director and group coordinator R&D in IT and Digital India Corporation, MeitY was the chief guest and keynote speaker at the online event. Niju Vijayam, executive director, Avanteum Advisors LLP presented the report and was also a speaker at the event.

(Click to view report)

Questions answered

1. What are the challenges in the AI & ML electronics hardware vertical?
2. What are the opportunities in the AI & ML electronics hardware vertical?
3. What role can corporates, startups, government, and Academia can play in tapping these opportunities?
4. How big are AI and ML in electronics hardware?
5. What is the market size in India and what are the key drivers?
6. Does AI and ML electronics hardware have any opportunities for entrepreneurs?
7. How can Academia prepare students for the opportunities?
8. Who all can be the catalyst for increase AI hardware implementation?
9. How are the investments in the technology and skills sectors shaping up?
10. What’s the road ahead?

“In the early 1980s, there was a lot of promise from IT and ITES verticals. These promises have been delivered. Almost similar scales of promises are being promised by the AI, ML, and similar technologies now. Just like IT and ITES verticals in India have made their presence felt globally, we expect that AI and other emerging technologies will do the same. Now is the time we should start focusing more on AI. Even hardware engineers should start learning AI. Remember that the clients now expect a complete ecosystem of hardware, software, and emerging technologies,” noted Dr. BK Murthy in the keynote.

Points to remember
1. The development of the Aarogya Setu App is proof of how AI and ML and Data science can benefit everyone through an aggregator platform.
2. AI and Data Science are the key pillars of the present that are building the future.
3. We can come out of the COVID 19 imposed recession using these technologies in a year or two, provided we work together.
4. Total AI hardware workforce will be around 11,58,376 by 2020.
5. The amount of computing done is increasing two-three times on an average. This is the fastest ever growth.
6. India is still a nascent market in terms of AI, emerging technologies, and AI/ML electronics hardware development.
7. Just like dot com, AI is an all-encompassing technology. It will take time to mature. We need to be mature about its adoption and funds being pumped into it.
8. AI and ML of today are very different from those of yesterday.
9. Budding engineers need to focus on a specific approach to AI/ML and the electronics hardware side of it.
10. AI will be the most dominant technology in the future. More than 20 billion are being spent annually on works around AI.

“In the next five years, the demand of AI electronics hardware professionals is expected to cross 4.53 lakhs. The rate will be growing at 92 per cent during this period. Demand is expected to be across the spectrum including manufacturing, agriculture, food tech, transportation to health care. It has the potential to contribute to the country’s goal of being a five trillion dollars economy,” pointed out Poornima Shenoy.

Challenges
1. In India, there is a very low-value addition happening in terms of system integration.
2. We should not be doing the same mistake as we did in IoT. The ecosystem should create for the world and not focus on consuming what the world creates
3. The adoption of AI is gated by the cost of the hardware involved.
4. The use and implementation of emerging technologies such as edge computing are still very expensive.
5. The number of applications that work on economical hardware are a few.
6. Large corporations (from India) have low investments made on AI Electronics Hardware in comparison to startups and global corporations.
7. There is an absence of ‘courses’ that focus on AI and ML entirely. Bits and pieces about the two are taught as a part of other engineering degrees.
8. The market forces require innovation on all the angles.
9. AI and ML need to be given the solution-centric approach rather than a product-centric approach.
10. Aggregator platforms are missing. This has shown to be of the biggest value.
11. We do not have local R&D centers to create global products.

“We have just missed the bus in IoT excitement. IoT was a big hype in the 2013-14 timeframe. What’s happening in 2020 in India is a very low-value addition in terms of system integration. Let’s not make the same mistake in the AI ecosystem. Thinking of the hardware side, there is a whole bunch of unsolved problems that are both challenges as well as opportunities. We need to become the value creators for the world,” explained Ashok Mishra.

Opportunities
1. AI and emerging technologies electronics hardware is a very big opportunity for entrepreneurs. We need to develop applications that work on economical hardware.
2. India specific solutions will be in huge demand. These are further going to encourage the adoption of AI and Data Sciences.
3. A huge growth in B2b applications have been forecast. Companies and individuals will need to be ready and skilled to tap these opportunities.
4. Indigenous chips manufacturing and development in the domestic sector will grow in India. This segment will see a good jump in the AI hardware sector.
5. Individuals who can give guest lectures around the emerging technologies will be needed. More faculty will be required as the umbrella widens.
6. India can emerge as the leader of the world in terms of design houses.
7. New labs, academia, and testing centers for electronics hardware around AI and emerging technologies will be required.
8. Sectors ranging from automation, robotics to agriculture, and manufacturing will see a big boost in adoption of AI and emerging tech. Electronic hardware around the same will become a necessity.
9. There is a big scope for multidisciplinary smart companies to emerge as the opportunity is very huge.

“The hardware requirement for AI, ML, deep learning, and other emerging technologies is growing at a phenomenal pace. The amount of compute is doubling is at every three and a half months. This is the fastest growth ever. We will need to think out of the box as the traditional methods won’t suffice. This is where the opportunity and challenges lie for everyone in the domain,” noted Bharat Daga.

What can be done?
1. We need to have a cohort of a pool of skilled people in these technologies. Academia can play a big role in the same by training individuals and budding engineers.
2. Collaborations between startups, academia, and corporate houses can work wonders as it helps approach the solution from different angles.
3. The government needs to be the catalyst for the adoption. It should be open to collaborate with the ecosystem working on the front.
4. Engineers, especially from the hardware and mechanical background need to learn more about AI. They can upskill, grow and contribute more.
5. Around 1700 startups are focussed on artificial intelligence. The beauty of the startup is the fact that they are small-sized and can experiment. These need to experiment more.
6. A fine balance between theory and practicals should be introduced. While the classes can be taught online by the industry, practicals must be hands-on in a good lab setup.
7. Corporates and startups need to take a deep dive into the AI hardware space. We need to create for the world.
8. AI and ML are horizontal. We need to stop fitting these into other courses and giving them a vertical approach.
9. We need to develop a collaborative culture to act as a catalyst. The government needs to play a big role in the same.

“If we look back at some of the startling things that have happened, we find that the role government plays is crucial. Any massive transformation has its roots in the government. It is wonderful to see ESSCI saying that we need to bring all the stakeholders together. It has to be a collaborative effort from startups, corporates, Academia, and the government,” concluded Sathya Prasad.

Reported by – Mukul Yudhveer Singh

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