Great Opportunity In AI And ML Hardware Sector

The introduction of new technologies such as artificial intelligence (AI), machine learning (ML), and data science has led to several growth opportunities in various sectors. These technologies will dominate almost every aspect of growth and business in the coming years. However, there are a few challenges that need to be addressed to tap the opportunities for maximum benefits.

Artificial intelligence (AI), machine learning (ML), and data science have become what IT and ITES industries used to be in the 1980s. The scope of opportunities is huge in these new emerging sectors. Just like IT and ITES industries, these can dominate almost every aspect of growth and business in the coming years. However, AI hardware is in its nascent stage since semiconductor chip development has a limited presence in India.

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

The imminent panel of experts included:

• N.K. Mohapatra, CEO, ESSCI
• Ashok Mishra, VP, ASIC BU, ALTEN Calsoft Labs
• Bharat Daga, principal engineer and director of engineering, Intel Corporation
• Sathya Prasad, director, Centre for Innovation & Entrepreneurship (CIE), PES University

The panel discussions focused on AI and ML electronics hardware from the startup and entrepreneurial perspective, deep-tech angle, formal education perspective, and skilling and upskilling angles.

Dr B.K. 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 a speaker at the event.

Questions answered

1. What are the challenges in AI and ML electronics hardware vertical?
2. What are the opportunities in AI and ML electronics hardware vertical?
3. What role can corporates, startups, and government 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 increased 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 were a lot of promises from IT and ITES verticals. These promises have been delivered. Almost similar scales of promises are being promised by 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 to start focusing more on AI. Even hardware engineers should start learning about AI. Remember that the clients now expect a complete ecosystem of hardware, software, and emerging technologies,” said Dr Murthy at the event.

Points to remember

1. The development of the Aarogya Setu App is proof of how AI, 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 Covid-19 imposed recession using these technologies in a year or two, provided we work together.
4. The total AI hardware workforce will be around 1.16 million by this year end.
5. The amount of computing done is increasing two to three times on 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. Budding engineers need to focus on a specific approach to AI and ML and electronics hardware side of them.
9. AI will be the most dominant technology in the future. More than twenty billion dollars are being spent annually on AI.

“In the next five years, the demand for AI electronics hardware professionals is expected to cross 0.45 million. The rate of growth will be 92 per cent during this period. Demand is expected to be across the spectrum, including manufacturing, agriculture, food tech, transportation to healthcare. It has the potential to contribute to the country’s goal of being a five trillion dollars economy,” said Poornima Shenoy.

Challenges

1. In India, there is a very low-value addition happening in terms of system integration.
2. We should not be making the same mistake we made for the Internet of Things (IoT). The ecosystem should be created for the world and we should not just 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, is still very expensive.
5. Large corporations (from India) have made lesser investment in AI electronics hardware as compared to startups and global corporations.
6. There are no courses in colleges and universities that focus entirely on AI and ML.
7. AI and ML need to be given a solution-centric approach rather than a product-centric approach.
8. Aggregator platforms are missing.
9. We do not have local R&D centres 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’s specific solutions will be in huge demand. These are further going to encourage the adoption of AI and data science.
3. Indigenous chip manufacturing and development in the domestic sector will grow in India. This segment will see a good jump in the AI hardware sector.
4. Individuals who can give guest lectures around emerging technologies will be needed. More faculties will be required.
5. India can emerge as the leader of the world in terms of design houses.
6. New labs, academia, and testing centres for electronics hardware around AI and emerging technologies will be required.
7. Sectors ranging from automation and robotics to agriculture and manufacturing will see a big boost in the adoption of AI and emerging tech.
8. 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 computing is doubling at every three and a half months. This is the fastest growth ever. We 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,” said 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. Collaboration 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 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 focused on AI. The advantage of being a startup is that it is small-sized and can experiment.
6. A fine balance between theory and practicals should be introduced. While 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.
8. AI and ML are horizontal. We need to stop fitting these into other courses and give 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 may find that the government plays a crucial role. 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.