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 Enterprise AI Brief, AI Policy Brief or Daily AI Brief.
Also, consider following us on social media:
More from Enterprise
Sep 16 Crunchtime Launches Connected Restaurant Operations Suite Sep 16 Crusoe to Run Perplexity Model Training and Inference Sep 16 Siemens and Salesforce Connect Agentforce With Teamcenter Sep 16 RWS Opens Public Preview of Tridion Agentic Platform Sep 15 Lectra Launches Apogy Agentic AI Software for Fashion Product DevelopmentMore from Regulation
Sep 16 Trump calls AI safety fears a hoax during live call with NVIDIA CEO Sep 15 ADLM Calls for CLIA Rules to Cover AI in Laboratory Medicine Sep 15 Project Liberty and Partners Launch Pro-Human AI Coalition Sep 15 Conference Board Maps Four Paths for AI in US Workforce Sep 15 Ritholtz picks Hadrius to oversee firmwide Claude useAI 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
ZTE Opens 2026 Global Summit in Kuala Lumpur
GTI and China Mobile Release AI Security Framework
Global chip equipment billings rise 23% to $40.53 billion
Bain's Model Puts AI at 0.7% of Global Energy, Against 11% From Executives and 19% From Consumers
MediaTek Introduces Dimensity 9600 Pro Smartphone Chip
Daily AI Brief: the AI news that matters, in your inbox.