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Trends — Artificial Intelligence Report (2025)

Syllabus:

GS3: Science and Technology- developments and their applications and effects in everyday life.

Context: 

Trends — Artificial Intelligence Report (2025 highlights India as a major player in AI adoption

More on the News

  • Venture capitalist Mary Meeker, known as the 'Queen of the Internet,' has released her first major trends report since 2019.
  • The report, titled ‘Trends — Artificial Intelligence,’ highlights the unprecedented pace and scope of AI development and adoption.
  • Meeker describes AI's evolution as "unprecedented", particularly in terms of declining usage costs and an adoption curve unlike any previous technology disruption.

Key Highlights of the Report

• AI adoption has outpaced previous tech revolutions:

  • Key global social media platforms took 2–4 years to reach 100 million users.
  • ChatGPT achieved the same milestone in less than 3 months.

• Based on Morgan Stanley data:

  • It took 6–12 years for 50% of US households to adopt mobile/desktop internet.
  • It is projected to take only 3 years for the same share of households to adopt AI platforms.

• Despite high user growth, revenue per user remains low, with a median of $23.

•The report flags major concerns in AI development:

  • Hallucinations
  • Biases
  • Misinformation
  • Slow regulatory progress

India’s Role in the Global AI Landscape

  • India’s large digital population and mobile-first internet habits have helped it become a crucial consumer market for global AI platforms.
  • Due to its large population and high internet penetration, India has become a crucial market for AI adoption.
  • India is the largest market for ChatGPT, contributing: 13.5% of mobile app users, ahead of the US (8.9%) and Germany (3%).

India also ranks:

  • Third-largest user base (6.9%) for DeepSeek, a Chinese AI platform.
  • Despite DeepSeek’s rivals like ChatGPT being banned in China and Russia, India contributes significantly to both Western and Chinese AI platforms.

Closed vs. Open Source AI Models

Aspect

Closed-Source AI Models

Open Source AI Models

Approach

This model, often referred to as closed-source or proprietary AI, is are AI system where the underlying code, algorithms, and often the training data are kept private by its developers.

Open-source AI models are pre-trained machine learning algorithms that are publicly accessible for use, modification, and distribution. 

Examples

OpenAI’s GPT-4, Anthropic’s Claude

Meta’s Llama, Mistral’s Mixtral (via Hugging Face)

Training Data

Proprietary datasets

Often transparent or community-contributed datasets

Resource Requirements

Extensive compute resources; high cost

Lower resource threshold; accessible to smaller players

Adoption Preference

Enterprises, consumers, governments

Startups, researchers, governments

Transparency

Low (no access to model weights, data, or tuning methods)

High (access to weights, customization, and fine-tuning possible)

The Dual AI Development Path

Meeker highlights a philosophical split in AI development:

  • Open Source: Represents freedom, speed, openness, and community-led innovation.
  • Closed Source: Emphasizes control, safety, optimization, and corporate/government adoption.

This divergence is shaping:

  • The future of AI architecture
  • Who has access to powerful AI tools
  • The direction of global innovation and regulation

UPSC Mains Practice Question 

Q. Discuss the key trends highlighted in the ‘Trends — Artificial Intelligence’ report (2025) with reference to India’s role in global AI adoption. How does the open-source vs. closed-source AI development model impact the future of innovation and regulation?

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