Following US And China, India On Its Way For AI Advance Innovation Engine

AI AI

Today, Silicon Valley hosts above 15,000 top-end engineers from IITs. This shows that, our top talents (raw material) are getting supplied and buying back innovations (Google, Facebook, Amazon). This is the power of the innovation engine created in the Silicon Valley over the last 70 years and it is the leading source of tech innovation for the whole world. China could learn the innovation engine model that the Silicon Valley had prepared. Now, its economy is 5x that of India and has already exceeded that of the US in buying power equivalence. According to Accenture Research, China is poised to obtain $8 trillion gains out of the huge AI wave which is slated to distribute $16 trillion of new economic value. How could they handle to rebuild the Silicon Valley magic?

China did three things right that achieved strong results:

Making a risk-taking capital pool: As of December 2018, the Chinese government said it has gathered $1.8 trillion in state money across thousands of venture capital funds to achieve its goal of tech dominance by 2025 (Made in China initiative). Some of the companies which came out of that trial are Didi Chuxing ($56 billion), SenseTime ($4.5 billion) and ByteDance ($75 billion).

Infrastructure investments:China carried out massive infrastructure investments to bring quick job growth. The increase in service economy in both digital and physical economy guided to quick job and economic output conception, letting quick and more distributed economic growth.

‘Idea to impact’ network design:China invested around $5 billion in making a huge ‘idea to impact network’, where universities, research parks and companies worked in tandem to prepare next-generation AI tech. The Chinese government is offering hand-picked top researchers in AI, to relocate and free housing benefits, in addition to more research grants. It is fine on its way to its goal of becoming the sole AI superpower by 2030. This will permit it to lead not only technologically, but also geopolitically. As its social rating systems and AI-powered observation systems are reasonably controversial in a democratic setup, there is no denying that it is dominating the AI pack worldwide.

Currently, the new Indian government is taking the responsibility of big investments in infra to bring jobs in the short run, we should learn from China and augment it with three major steps to kick-start our innovation engine. By creating long-term value in and for India, these can drive it to not only a $5 trillion economy but also a $10 trillion economy by 2030.

Make a large domestic risk capital pool to draw ideas and talent internationally: To create more $2.5 trillion taking capital multiplier of 10, India would require $250 billion in high-return tech investments. Now, LIC is a $400 billion giant, and if it assigns 5 percent of the asset base ($20 billion, or Rs 1,30,000 crore) for investing in high-end tech like AI, it will be a game changer. We can truly connect with 6 billion people worldwide with this advance engine, because AI built for India will work everywhere, given the data diversity in India. Besides, capital flow, rolling out an attractive start-up visa programme will enable us attract the best and brilliant.

‘Idea to impact’ ecosystem sponsored with CSR: When Israel and Canada centred on ‘idea to impact’ ecosystem to begin innovation; we can do the similar for creating deep tech companies out of India. Today, CSR money (2.5 percent of the profit) goes to NGOs, which work on lessening the effect, not the cause. If we can redirect some of that towards creating CSR-grant-driven ‘idea to impact’ ecosystem for Indian problems, we can finance the creation of:

(a) Strong universities concentrated on research and not simply teaching—this implies infusing universities with research-driven faculty;

(b) Research translation parks which take authenticated research and change it into prototypes. Examples comprise Stanford Research Park (grew the core technology behind SIRI) and MILA (Canada);

(c) Foundry or venture studios which generate deep tech companies carry high risk and need high upfront capital, with high-end talent. It is not easy to start and fund these companies out of angel investments in a ‘lean model’. Internationally, smart VCs are more and more creating foundry-like structures—Playground Global started by the android creator Andy Rubin, Tandem Research (Canada), Sinnovation Labs (China)—to start such conversion of deep technology into leading product companies.

(d) Government-owned fund for start-ups: Many have not heard about In-Q-Tel, an interestingly named evergreen fund (with naming convention from Bond films) supported by the CIA. For every dollar invested by In-Q-Tel, companies get $9 investment by other investors. As India has taken the welcome step of funding start-ups through two FoF (Fund of Funds), this action would enable funding of companies for major areas in defence and nationally important technologies like AI. An interesting source of such funds can be the close to $10 billion of offset amount due from foreign companies via defence procurement.

(e) State-owned debt fund for AI and hardware companies and tax incentive: AI and robotics companies which maintain large hardware components are globally encouraged with low interest rates by state-owned debt funds and access to tax incentive policies. The IT sector raised to be a huge value-creation engine with the STPI model that formed tax-free zones. We require such a value structure for expanding these companies in India.

Easier norms for listing deep tech companies: The Toronto Stock Exchange permits for listing deep tech companies with just $5 million in revenue or investment. Deep-end tech companies take time to get to revenue, but once they do, they can quickly go beyond well-established legacy companies. We are seeing these kinds of AI-first companies in China and the US. SenseTime took just four years to hit $4.5 billion in evaluation. These types of rapid value creation should be available for public markets as well, and this will also allow these companies to tap into a different kind of capital pool for quick development.

India has innumerable new businesses and the enterprising likely to be an outstanding player internationally, yet it needs a solid progression motor to construct profound organizations of substance. The AI age will very soon see extremely huge organizations, of the request of $10-trillion or more valuations. We can be the centre structure AI for the entire world on the off chance that we make the above strides.

Not many know that, in the 1600s, when the Taj Mahal was shaped, India used to donate 26 percent of global GDP. Thus, we need a huge effort and willingness to create the necessary innovation engine from this forward-thinking government; shortcuts won’t do.