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News in Shorts: 28 October 2024

News in Shorts: 28 October 2024

95% of Land Records in Rural India Digitized

Context: Rural India is shifting to digital land records, bringing a new way to manage and own land.

  • Major Progress Since 2016: Around 95% of rural land records are now digitised, ensuring land ownership is more secure and easier to access for people in rural areas.

Digital India Land Records Modernization Programme (DILRMP)

  • Program Overview: DILRMP, formerly the National Land Record Modernization Programme.
    • It was restructured in 2016 as a Central Sector Scheme, funded by the central government.
  • Goal: Establish a transparent, real-time land information system to improve land use, support policy-making, and streamline transactions.
  • Advantages: Reduced land disputes, minimized fraudulent transactions, data sharing with other agencies, and fewer visits to physical offices.

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Key Initiatives under DILRMP

  • Unique Land Parcel Identification Number (ULPIN):
    • Each land parcel receives a 14-digit alphanumeric code based on geo-coordinates.
    • Implemented in 29 states/UTs, it aids in managing real estate, resolving disputes, and supporting disaster management.
  • National Generic Document Registration System (NGDRS):
    • Standardizes the registration process across India.
    • Facilitates online document submission, payments, appointments, and searches.
    • Adopted by 18 states/UTs, with data sharing in 12 others.
  • e-Court Integration:
    • Links land records with e-Courts for faster case resolution and fewer disputes.
    • Approved in 26 states/UTs.
  • Transliteration of Land Records:
    • Records are translated into 22 languages from the Indian Constitution to overcome language barriers.
    • Currently in use in 17 states/UTs.
  • Bhoomi Samman:
    • 168 districts across 16 states have achieved “Platinum Grading” for meeting core program requirements, including digitization of records and maps.

Importance of Digitizing Land Records

  • Reduced Disputes and Fraud: Digitization addresses long-standing issues such as fraud, disputes, and slow manual processes.
  • Easy Access to Ownership Records: With digital access, land ownership information is more transparent and helps reduce encroachments.
  • Empowerment for Marginalised Communities: Improved access to land records strengthens land rights, especially for vulnerable groups.
  • Enhanced Land Management: Integration with geospatial tools improves survey accuracy and planning.
  • Fair Compensation: During land acquisitions or natural disasters, digital records help ensure timely, fair compensation.

Meta and ‘IndiaAI’ unveiled the Centre for Generative AI, Shrijan at IIT Jodhpur

Context: IndiaAI and Meta have announced the establishment of the Center for Generative AI, Srijan (सृजन) at IIT Jodhpur, along with the launch of the “YuvAi Initiative for Skilling and Capacity Building”.

Key Initiatives

  • Centre for Generative AI, Srijan:
    • Location: IIT Jodhpur
    • Objective: Advance R&D in Generative AI (GenAI) and foster ethical, responsible AI development.
    • Focus: Promotes open science innovation in AI.
    • Impact: Empowers researchers, students, and AI practitioners with knowledge and tools for responsible AI development.
  • YuvAi Initiative for Skilling and Capacity Building:
    • Collaborators: Meta, Ministry of Electronics and Information Technology (MeitY), All India Council for Technical Education (AICTE).
    • Objective: Train 100,000 young developers and students (aged 18-30) in AI and open-source large language models (LLMs).
    • Sectors Addressed: Healthcare, education, agriculture, smart cities, and financial inclusion.
  • Skill Development and Resource Hub:
    • Components:
      • GenAI Resource Hub with courses, case studies, and open datasets.
      • “LLM for Young Developers” course by Meta.
      • Master Training Workshops on foundational AI concepts.
    • Unleash LLM Hackathons: Students propose AI solutions, with mentoring, seed grants, and market support for top ideas.
    • AI Innovation Accelerator: Supports 10 student-led startups working with open-source AI models through incubation and funding.

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Significance of the Collaboration

  • Boosts Indigenous AI Solutions: Supports development of AI tailored to India’s specific needs, enhancing tech sovereignty.
  • Strengthens AI Ecosystem: Enhances open-source AI innovation, research capabilities, and responsible deployment.
  • Bridges AI Talent Gap: Trains youth in generative AI and LLMs, preparing them to address real-world challenges and boost India’s AI workforce.
  • Promotes Sector-Specific AI Applications: Focus on critical areas like healthcare, education, and agriculture.
  • Global AI Leadership: Aims to position India as a leader in AI, contributing to the $5 trillion economy goal.

Future Directions

  • Strengthen AI Policy Framework: GenAI CoE will contribute to AI policy, standards, and ethical guidelines.
  • Drive Regional and Global AI Partnerships: Collaborative innovation with global industry leaders to enhance India’s digital transformation.
  • Sustain Open-Source AI Community: Fosters long-term open-source collaboration between academia, industry, and government.

About IndiaAI Mission

  • IndiaAI is a government-backed initiative aimed at boosting artificial intelligence (AI) research and development in India.
  • Objective of IndiaAI Mission
    • The mission, with a budget of Rs 10,370 crore, aims to establish a massive infrastructure of over 10,000 GPUs to support AI development. 
    • This includes training AI models with over 100 billion parameters on datasets that cover major Indian languages, benefiting sectors like healthcare, agriculture, and governance.

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AVAILABLE FOR DOWNLOAD SOON
UDAAN PRELIMS WALLAH
Comprehensive coverage with a concise format
Integration of PYQ within the booklet
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हिंदी में भी उपलब्ध
Quick Revise Now !
UDAAN PRELIMS WALLAH
Comprehensive coverage with a concise format
Integration of PYQ within the booklet
Designed as per recent trends of Prelims questions
हिंदी में भी उपलब्ध

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