Meta Appoints Aman Jain to Oversee Public Policy in India

In 2026, India is poised to make significant advancements in artificial intelligence (AI), but experts warn that only resilient players in the sector will thrive amid increasing competition and evolving technologies. The landscape is shifting as Indian IT companies transition from embedded AI solutions to more modular products, enhancing adaptability and operational efficiency.

The United States has initiated the Pax Silica initiative, aimed at securing the global silicon supply chain through collaboration with partner countries on semiconductor design, fabrication, and logistics. This initiative reflects a strategic effort to enhance the resilience of the semiconductor industry amid growing global demand.

Ankush, the CTO of Thoughtworks India, has cautioned against the impulsive trend of converting APIs into Microservices Control Plane (MCP) servers, emphasizing the need for a more thoughtful approach to API management and integration. He argues that such a rush could lead to inefficiencies and complications in the long run.

The transition from a human-in-the-loop model to an agent-in-the-loop approach signifies a significant shift in artificial intelligence (AI) practices, with findings indicating that task-specific agents outperform humans in efficiency and cost-effectiveness. This change reflects a growing trend in AI development where automation is prioritized over human intervention.

Former President Trump has initiated a national policy push to regulate artificial intelligence (AI) at the federal level, countering state-level regulations. This move is encapsulated in an executive order aimed at establishing a cohesive national framework for AI governance, reflecting the growing importance of AI in various sectors.

Broadcom has disclosed that Anthropic placed a substantial order worth $21 billion for Google's Tensor Processing Units (TPUs), which are critical for powering AI models. This order includes a $10 billion acquisition of Ironwood TPU racks in Q3 and an additional $11 billion in Q4, reflecting Anthropic's commitment to enhancing its AI capabilities.

CAMB.AI has partnered with Ziroh Labs to optimize its multilingual voice synthesis models for CPU performance, enhancing the efficiency of voice technologies. This collaboration aims to make advanced voice models more accessible and effective across various applications.

A recent study evaluated the performance of Large Language Models (LLMs) in maternal and newborn healthcare triage in India, highlighting a significant performance gap between romanized and native scripts. The research found that LLMs had F1 scores 5-12 points lower for romanized messages, potentially leading to nearly 2 million excess errors in triage. This issue underscores the importance of script accuracy in high-stakes clinical applications.