GSMA Warns AI Chip Demand Could Widen Mobile Internet Gap
GSMA warned (in French) that rising demand for AI infrastructure and data centers is increasing memory and chip costs, making entry level smartphones more expensive. Its State of Mobile Internet Connectivity 2026 report says this pressure could widen the global digital divide.
More than 3.4 billion people do not use mobile internet, although over 90% of them live in areas with mobile broadband coverage. Smartphone cost is the main barrier in low and middle income countries, followed by limited digital skills.
GSMA director general Vivek Badrinath called for coordinated action from policymakers, mobile operators, device makers and component suppliers to keep smartphones affordable. Its previous analysis estimated that closing the mobile internet usage gap could add $3.5 trillion to global GDP from 2023 to 2030, with more than 90% of that amount going to low and middle income countries.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like AI Policy Brief, Enterprise AI Brief or Daily AI Brief.
Also, consider following us on social media:
More from Regulation
Nov 1 East African Community adopts regional AI strategy and university training plan Nov 1 Türkiye Plans AI Scoring for Open Ended School Tests Nov 1 Sadiq Khan Calls for Cap on London Robotaxis Nov 1 SpaceX AI Loses Bid to Dismiss NAACP Air Pollution Lawsuit Oct 31 Canada Joins EuroHPC Supercomputing and Quantum NetworkMore from Enterprise
Nov 1 Mumtalakat and ARP Group Plan AI Native Wholesale Bank in Bahrain Nov 1 GO Telecom Awards $49.6 Million AI Data Center Contract to 3T Nov 1 Context Labs Launches AI Distillery for Sovereign Enterprise AI Oct 31 Orange Cyberdefense Gets Early Access to Cyber Version of Mistral Large 4 Oct 31 Ares Intelligence Raises €2.9 Million for AI Adoption PlanningAI Policy Brief
Weekly report on AI regulations, safety standards, government policies, and compliance requirements worldwide.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
IMF Warns AI Could Disrupt Jobs and Tax Revenue
DataReportal Estimates Monthly AI Use Exceeds 4.1 Billion People
Huawei Forecasts AI Agents Will Account for Over 90% of Traffic by 2035
Intel and Broadcom CEOs Warn Capital Could Limit AI Growth
Gartner Says $3.5 Trillion in AI Infrastructure Spending Faces Impairment Risk by 2030
Daily AI Brief: the AI news that matters, in your inbox.