• Member
• May 18, 2024

Revisiting Deep tech Start up Policy

 Revisiting  Deep tech  Start up Policy

 It is suggested that the area of consideration for Deep Tech startup policy may be  expanded to include the emerging and  promising  fields of  science   and technology.  The  geography of innovation is expanding  ,  special  efforts  are  required for  on boarding   deep tech startups  from  all cities  and   irrespective of  size and location . Our  suggestions  are  grouped under following heads

 

1.      Broadening the scope

2.      Essentiality  of  Technology and trend forecasting

3.      Research Landscape  Survey

4.      Modularization

5.      Failure  Mode Success Analysis

6.      Virtualisation  and Ai

7.      Open Source

8.      One  Cluster  One  Focus

 

1.Broadening the scope

The current  policy   is focused on certain technologies, such as artificial intelligence and machine learning , It is  suggested   to broaden the scope to include emerging other important Deep-Tech areas  such as following

·       Radar

·       Electric  Vehicle  

·       Nano  technologies  

·       3D additive manufacture

·       Green Energy

·       Optics  based  technology

·       Genomics

·       Construction & Infrastructure

·       Smart Materials

·       Space

·       Robotics

·       Quantum computing

·       Biotechnology.

·       Regenerative Medicine

·       Precision Agriculture

 

2.Essentiality  of  Technology and trend forecasting

Technology and trend forecasting will help in formulating   a road map for getting maximum benefits from the resources   invested   in  developing   and in aligning the trajectory of efforts  of  Deep Tech  startups towards the most promising areas in that domain  . Review and alignment of trajectory of Deep Tech  startups to the changing  dynamics of the field  will  facilitate  course    correction    and  enhance   chances of success.     

3.Research Landscape  Survey

Research landscape survey is  a  must to facilitate  development   of  taxonomy   of the field  facilitating  modularising the science and technology development efforts. The Big Open Research picture  will  reflect the existence of various  strands of domain knowledge    and  interplay    at  periphery   , simultaneously  including    more granular – local and context-specific  data  to be more inclusive. Application of perception processing techniques

The  above   has  emerged from an interaction of a group dedicated to trends and  technology forecasting . and forecasting emerging trends  The group is an inter disciplinary group consisting of more than 100 eminent experts  from   different domains  and  fields , The  group  works with following  objectives

·       To know the emerging technologies in different areas.

·       Assist in preparation technology forecast for different sectors and technologies.

·       Connect people in different areas of technology to understand advances in different fields and understand impact on their own field.

4.Modularization

An overview of modules  while modularising the science effort can help reducing the risk of failures . The  modules themselves can go on to become ideas processes product technology is in their own right  that can be transformed into useful product for the market .Modularity will ensure that efforts can be distributed and with Resilient interconnection. Modularization and  virtualization  facilitate  multi-institutional distributed   research.

Uncertainties caused by rapidly developing technologies, shifting market demands and the changes occasioned by these developments, including new requirements for products being developed and increased difficulty for companies to reliably execute state-of-the-art processes.

5.Failure  Mode Success Analysis

Resilience Framework is required to ensure that the resources allocated for deep science and deep tech  provide commensurate  returns. Resilience is  created  by modularization . The   interplay between  supportive structures   interdependencies   and  adaptive capacities. Resilient   science   leads  to Failure  Mode Success Analysis - a  paradigm  in which  modules  from failed  projects  have  potential to evolve to solutions  in their  own right

6.Virtualisation and  AI

Virtualisation  enables    interdisciplinary knowledge exchange at   multi-institutional distributed   research .  We are  at  computationally enabled   significant inflection point  in the trajectory of scientific discovery. As society continues its digital transformation, so does humankind's collective scientific knowledge and discourse. The transition has led to the creation of a tremendous amount of information, opening exciting opportunities for computational systems that harness it. In parallel, we are witnessing remarkable advances in artificial intelligence, including large language models capable of learning powerful representations from unstructured text. The confluence of societal and computational trends suggests that computer science is poised to ignite a revolution in the scientific process itself. Virtualization  should be part of proposals  on Deep Tech Start Ups

7.Open Source at   the front  end of Science

The open science at front end of innovation  enables wider  participation and early   spinoffs Research conducted on open principles is more collaborative, transparent and reproducible, and makes its outputs more accessible to a greater number of people. This best serves the  mission to disseminate knowledge for maximum public benefit.  Open-source science  will   enable  a culture shift to a more inclusive, transparent, and collaborative scientific process, which will increase the pace and quality of  Deep Tech  start ups .