Tehran(Bazaar): Dr.Gopichand Katragadda is the Group Chief Technology Officer and Innovation Head for Tata Sons in interview with Bazaar News Agency said: governments should provide funding for startup and academic excellence in AI based on government requirements with commercial rights to use.
Following is the full text of the interview:
Bazaar: How does artificial intelligence affect the efficiency of industries?
Katragadda : Artificial intelligence (AI) along with Industrial Internet of Things (IIoT) promises disruptive value through improvements in yield, efficiencies, and costs. The AI strategy should at the minimum target:
a 2% factory yield improvement, or
a 25% process energy efficiency improvement, or
a 10% savings in operations and maintenance costs
Bazaar:What are the important factors in the better performance of artificial intelligence in business?
Katragadda : Data capture at the plant and analysis of the data in the cloud will not in itself unlock the power of IIoT. The arrival of mature Edge computing enables an Edge AI IIoT strategy which completes the value loop along with advanced sensors, AI, and 5G. The data collected by the sensors with a closed loop control through advanced AI inferencing right at the edge will enable IIoT to deliver on its promise.
Bazaar: What measures should governments take to facilitate the use of industrial intelligence?
Katragadda: Facilitate open data markets based on public funded research while safeguarding privacy and proprietary data.
Provide funding for startup and academic excellence in AI based on government requirements with commercial rights to use.
Bazaar:What are challenges in using AI for organizations?
Katragadda :Typical industries have operations technology (OT) teams at the plant or shopfloor, Information Technology (IT) teams located at the corporate headquarters, and corporate data science (DS) teams with an independent reporting structure. These teams are not incentivized to cooperate for long term success. Irrespective of the industry, the plants are short-term focused on production, the IT departments are optimizing costs, and the data science teams do not have domain expertise. In a typical IIoT setup, the OT teams provide challenge statements, the IT teams provide cloud servers for big data, and the data science teams crunch the data in an off-line mode. Practically, however, organizational barriers do not permit IIoT to deliver on its promise. Off-line outcomes from data science teams are rarely implemented by the plant. IT is satisfied by producing reports for the headquarters. And the headquarters wonders why the IIoT implementation is not producing results. There is very rarely a unified solutions approach to completely redesign the plant for better yield and efficiency leveraging new technology.
Bazaar:Do you have statistics on the use of artificial intelligence in the industries of the leading countries in the field of artificial intelligence in Asia?
Katragadda :Based on past few years of patent data China leads the Asian countries in deploying AI across industries.
According to WIPO, China has filed 389,571 patents in the area of AI over the past decade, accounting for 74.7 percent of the global total and ranking the first in the world.
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