Transformative Power of DeepTech AI to real-world GeoEconomics

By Maya Kannan, President & Chief Client Advisor, Sonicorn

The major challenge of Innovation-driven solutions is their longevity in R&D. Most of the time, AI based solutions face such challenges and fail to reach or ScaleUp up to the market. But, when they are rightly adopted, go through state transformations, and are aligned with the market at a scale of economies, they succeed exponentially. The Deep-Tech AI provides such a transformational framework, and State-Machine that adjusts itself dynamically to the market ecosystem. It is a time-tested fact that Innovation often fails to translate into mass commercialization and adoption. It might work within some special interest blocks that consume “Innovation as an Input”, but fails at a larger block of economies, such as a region or a nation-state or union of nations, etc. Innovation needs good packaging strategies for mass production and mass scale-up. Deep-Tech as a strategy can bring out the best Invention wrapped with the best Engineering and Implementations. Every deep-tech company needs to not just find the “Moat” over time, but to implant, it in the early stage of the company by applying the best mix of tech engineering, business engineering, and financial engineering, what I call “Three Leg(3L) Engineering”. Such a Moat can only be created by making sure it’s difficult or impossible to copy and reproduce. This is the reason, the Chinese, despite inventing the Printing press 500 years before Europeans, kept it as a Protected Innovation. Now in the 21st century, they are applying a reverse strategy, making copy-cat technologies to help local companies and the economies to benefit. It is hard and counterproductive to use Protectionism to gain a competitive advantage in the current Global Economy with complex and inter-dependent supply chains driven by treaties and other geopolitical mechanisms and frameworks. But, deep Tech itself provides the solutions for such a Packaging, i.e., embedding the Intelligence and just-In-Time transformative intelligence through the Deep-Learning networks such as the ‘karma Capsule network’. There is a huge difference in the way every power around the world looks at “AI.” Some people look at AI as 40 years of work in progress and see nothing innovative about it, but some look at AI as one of the Innovations of the past, like Electricity and the Internet. Those nations and their entrepreneurs look at AI as a “Wonder” like a child looking at everything around them as magical and will take it forward to a greater extent to Implement it at scale, create fantastic use cases and transform the economies to a larger extend. And they are going to create a Moat when they do it.

Unlike electricity or the Internet, the best-in-breed AI networks can create millions of moats as they become catalysts and inputs for other related industries within the GeoEconomic region. They will become impossible to catch up or copy or recreate, provided the three legs of the Engineering(3LE) are individually designed well, collectively aligned, and implemented the best way. While AI has many perceptions, the right one is – “AI is Distributed Intelligence.” It was called AI during the initial days of computer and network evolution. Those initial contributors to AI goals were achieved through computing. But the later day AI is an entirely new breed of technology with different rules of development, adoption, and Implementation. While many algorithm-driven computer systems claim themselves as an AI(i don’t dispute it), the purest form of AI is the one driven by Artificial Neural Networks. That means intelligence requires a network to exist, expand and transform. One such network is my invention called karmaCapsuleNetwork( https://github.com/karmaCapsuleNetwork/KCN1.0/blob/master/KarmaCapsuleNetworkV1.1.pdf ). I don’t call ANN the purest form of AI as an egoistic scientific inventor. My statement comes in my capacity as an Engineering Architect who has developed in developing many solutions, systems, and AI throughout my career as a Tech Entrepreneur and as an Enterprise Architect. I insist on this fact because most failures in the Market implementation of AI are due to this poor adoption of AI. At Sonicorn, we make sure that the AI Use-Cases go through a rigorous ideation process where we make all these corrections at an early stage of the project so that it gets the “Moat” embedded in it. This factor alone will make the company a Unicorn as the use case and the product around it matures through acceleration and ScaleUp Processes.

Another aspect of AI is the human who designs the AI trying to control it through programming it. Instead, AI’s development should be driven by autonomy, self-thinking, self-analysis, and guidance by looking into the past, present, and future. The basic mistake we humans make is that we want to create a Robot (an AI System) that wants to be our subordinate instead of our master. Any smart & successful entrepreneur would know that S/he should hire an ‘A’ instead of a ‘B’ because when you hire an ‘A’, he/she will hire either A or B; but when you hire a ‘B’, he/she will never hire an ‘A. Similar logic should be applied in developing AI Systems. You make an AI that can advise you to do things and derive conclusions, whether a business decision, trade decision, or a GeoPolitical Decision. That requires a Series of Doubts(logic) not arranged in a Linear form but as a non-linear “State-Machine.” These “Doubts” create “Conflicts,” and those conflicts create a new “Change of Events,” which in turn influence the market either positively or negatively. Real-world GeoEconomics is a complex mixture of market sentiments, government policies, rules, and Decisions, within an EcoSystem, whether within an Enterprise or a Nation, or an Economic Zone. So, if you want to be a winner through implementing AI, then you have to make it a Deep-Tech Ai-driven engagement. Such an AI should be able to dynamically go back to the sequence of Past events, reinforce it with the present events, and then apply the Intuition from the Market ecosystems. When you build such an AI Solution, it will automatically create multiple Moats and ScaleUp exponentially to be a Unicorn.

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Author Bio – Maya Kannan is a futuristic entrepreneur and a Strategic Consultant in the Deep-Tech Space with Specific Focus on Geo-Economics. He liberates Brands, Institutions, Leaders, and Nations from systemic failures and help in accelerating the Geo-Economic transformation. He plays key role in developing Successful “GeoEconomic Ecosystems” using Deep-Tech models, frameworks and Methodologies. He is the Inventor of the karma Capsule Network, a Deep-Tech System. His clients span Brands, Institutions, State-National Governments, and social organizations through four models: #MayaNom-ics, #MayaLogical, #MayaNess, and #MayaNation.