Deeptech: Revolutionising the Future of Technology

What’s in today’s article?

• Introduction
• Key Characteristics of Deeptech
• Present Challenges Facing Deeptech
• Future of Deepteach
• National Deeptech Startup Policy
• Objectives of the Policy
• Key Features of the Policy
• News Summary

Introduction

• Deeptech, or deep technology, refers to cutting-edge innovations rooted in scientific and engineering breakthroughs.
• Unlike traditional tech companies that often focus on software or app development, deeptech ventures delve into complex technologies that have the potential to disrupt industries and address significant global challenges.
• These technologies include artificial intelligence (AI), robotics, quantum computing, biotechnology, blockchain, advanced materials, and more.

Key Characteristics of Deeptech

• Scientific and Engineering Foundations: Deeptech is built on scientific research, engineering advancements, and sophisticated algorithms. It often involves long-term research and development (R&D) and requires a deep understanding of the underlying science.
• High Entry Barriers: Deeptech ventures typically have high entry barriers due to the need for specialized knowledge, substantial capital investment, and complex development processes.
• Significant Impact Potential: Deeptech solutions aim to solve critical problems in various sectors such as healthcare, energy, manufacturing, and agriculture. They have the potential to create substantial economic value and drive societal change.
• Extended Development Timelines: Unlike typical tech startups that can scale rapidly, deeptech companies often face extended timelines due to the need for rigorous testing, prototyping, and validation before reaching the market.

Present Challenges Facing Deeptech

• High R&D Costs: The development of deeptech solutions requires significant investment in research, infrastructure, and talent, making it difficult for startups to secure funding.
• Commercialization Barriers: Converting deeptech innovations into market-ready products involves overcoming technical, regulatory, and market acceptance hurdles.
• Talent Shortage: There is a growing need for specialized talent in fields such as quantum computing, AI, and biotechnology, but the supply of skilled professionals is limited.
• Long Time-to-Market: The extended timelines for development and regulatory approval can deter investors looking for quicker returns.

Future of Deeptech

• The future of deeptech is promising, with increasing investment and support from governments, academia, and private sectors.
• As deeptech continues to evolve, it will play a pivotal role in shaping industries and enhancing human life.
• Governments and private investors are recognizing the importance of supporting deeptech ventures through funding, incubators, and policy frameworks.

National Deeptech Startup Policy

• India's National Deeptech Startup Policy is a strategic initiative aimed at fostering the growth of deep technology startups in the country.
• Deeptech startups, which are rooted in advanced scientific and engineering innovations, play a critical role in driving India’s technological leadership and addressing complex challenges in sectors such as healthcare, agriculture, energy, and manufacturing.

Objectives of the Policy

• Promoting Innovation: Encourage the development of cutting-edge technologies through R&D support, grants, and innovation hubs.
• Facilitating Access to Capital: Provide financial assistance and incentives, including venture capital, government grants, and tax benefits to startups in the deeptech domain.
• Building Infrastructure: Establish dedicated incubators, accelerators, and test beds for deeptech innovations to bridge the gap between research and commercialization.
• Developing Skilled Talent: Strengthen educational programs and skill development initiatives to create a robust talent pool in advanced technological fields.
• Streamlining Regulations: Simplify regulatory frameworks to enable faster approvals and reduce barriers for deeptech startups, including intellectual property rights (IPR) protection and export controls.

Key Features of the Policy

• Funding Support: Creation of funds like the Startup India Seed Fund Scheme and deeptech-specific funds to provide initial and growth-stage funding to startups.
• Collaboration with Academia and Industry: Promote partnerships between academic institutions, research labs, and industry to accelerate innovation and technology transfer.
• Incentives for R&D: Offer incentives such as reduced taxes, grants, and subsidies to encourage R&D activities in deeptech fields.
• Ease of Doing Business: Simplify compliance procedures and provide a single-window clearance system for deeptech startups.

News Summary

• The Defence Research and Development Organisation (DRDO) is set to launch a pioneering initiative to advance research in emerging military technologies, backed by a₹1 lakh crore corpus announced in the interim Budget.
• The initiative aims to indigenize defence products and promote deep tech innovations in areas such as quantum computing, blockchain, and artificial intelligence.
• The DRDO has identified five high-value projects, each with a funding cap of ₹50 crore, to reduce reliance on imports and foster self-reliance in defence technology.
• Inspired by the US DARPA model, the programme seeks to push futuristic and disruptive technologies that could revolutionize defence systems.
• Defence Minister Rajnath Singh has approved the funding, which will be managed through the DRDO’s Technology Development Fund (TDF).
• The fund focuses on engaging private industry, MSMEs, and startups in the development of military hardware and software.
• The DRDO will soon publish project details and invite proposals, with successful bidders potentially receiving up to 90% of the project funding in tranches, subject to rigorous evaluations by a panel of experts.

Q1. What is LLM in simple terms?

A large language model (LLM) is a type of artificial intelligence (AI) program that can recognize and generate text, among other tasks. LLMs are trained on huge sets of data — hence the name "large." LLMs are built on machine learning: specifically, a type of neural network called a transformer model.

Q2. What do you mean by Machine Learning?

Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

Source: DRDO to fund first-of-its-kind deep tech research for military use

Gov.in