Startups

India and the United Kingdom have launched the Indiaโ€“UK Connectivity and Innovation Centre to accelerate secure, AI-driven, and resilient telecom technologies over the next four years. The two governments committed an initial ยฃ24 millionโ€”roughly โ‚น250โ€“โ‚น282 crore depending on exchange ratesโ€”to fund applied research, joint testbeds, field trials, and standards contributions in emerging telecom domains. The investment concentrates on three pillars: AI in telecommunications, non-terrestrial networks (NTNs) for satellite and airborne connectivity, and telecoms cybersecurity with open, interoperable systems. The multi-year window aligns to the critical runway for 5Gโ€‘Advanced and early 6G experimentation.
Telecom Secretary Neeraj Mittal underscored that AI will be central to the next generation of networks, not an add-on. The direction aligns with industry momentum: 5G-Advanced is already introducing AI-enabled RAN and core features via 3GPP, while 6G initiatives under the ITU-R IMT-2030 framework envision AI-native control loops, sensing-assisted connectivity, and tight integration of compute and communications. India expects 6G trials to begin around 2028, with commercial deployments to follow. Operators that harden their AI and automation capabilities during 5G-Advanced will enter 6G with a competitive execution advantage.
India Mobile Congress 2025 in New Delhi framed a clear ambition: scale domestic innovation, shape 6G, and turn telecom into a larger engine of GDP growth. Leaders underscored a whole-of-government approach, with multiple ministries backing IMC and the Department of Telecommunications and the Cellular Operators Association of India co-hosting. Indiaโ€™s telecom and digital sector is estimated to contribute roughly 12โ€“14% to GDP today. Leaders at IMC projected this could reach about 20% by the mid-2030s if India scales advanced connectivity, software-led services, and domestic manufacturing. Indiaโ€™s 6G push was tied to a potential GDP uplift exceeding a trillion dollars by 2035.
Qualcomm is acquiring Arduino to anchor an end-to-end developer funnel from hobbyist prototypes to commercial robots and industrial IoT systems. As part of the announcement, Arduino introduced the Uno Q, a new board priced around $45โ€“$55 featuring Qualcommโ€™s Dragonwing QRB2210 processor that runs Linux alongside Arduino tooling and supports vision workloads. By meeting developers at the prototyping bench and offering an upgrade path to production-grade SoCs and modules, Qualcomm aims to convert experimentation into long-term silicon design wins. The Arduino tie-up broadens access to Qualcomm compute for small teams while reinforcing an ecosystem play that spans on-device AI, connectivity, and lifecycle operations at the edge.
California has enacted SB 53, a first-of-its-kind AI safety law aimed at large model developers, with ripple effects for enterprises that build, buy, or operate AI at scale. SB 53 targets โ€œfrontierโ€ AI developersโ€”think OpenAI, Anthropic, Meta, and Google DeepMindโ€”requiring public transparency on how they apply national and international standards and industry best practices. It institutionalizes safety incident reporting to Californiaโ€™s Office of Emergency Services and extends protections for whistleblowers who surface material risks. The California Department of Technology will recommend updates annually, ensuring the regime evolves with the tech.
South Korea is funding a national AI stack to reduce dependence on foreign models, protect data, and tune AI to its language and industries. The government has committed โ‚ฉ530 billion (about $390 million) to five companies building large-scale foundation models: LG AI Research, SK Telecom, Naver Cloud, NC AI, and Upstage. Progress will be reviewed every six months, with underperformers cut and resources concentrated on the strongest until two leaders remain. The policy goal is clear: build world-class, Korean-first AI capability that supports national security, economic competitiveness, and data sovereignty. For telecoms and enterprise IT, this is a shift from โ€œconsume global modelsโ€ to โ€œoperate domestic AI platformsโ€ integrated with local data, compliance, and services.
Alibaba Cloud is integrating Nvidiaโ€™s Physical AI toolchain into its Cloud Platform for AI, bringing robotics-grade simulation, training, and deployment capabilities to customers. Alibaba and Nvidia unveiled a partnership that embeds Nvidiaโ€™s embodied AI development tools directly into Alibabaโ€™s machine learning platform. The integration targets robotics, autonomous driving, and โ€œconnected spacesโ€ such as warehouses and factories. Physical AI refers to software that models the real world in 3D, generates synthetic data, and trains control policies with reinforcement learning before deploying to physical systems. Developers on Alibaba Cloud gain access to toolchains for data processing, simulation-based training, and real-world reinforcement learning.
Google Labs has launched Mixboard, an AI-powered concepting board that turns text prompts and images into editable visual mood boards now available in U.S. public beta. Mixboard gives users an open canvas to generate, arrange, and iterate on visual ideas, from home decor and event themes to product inspiration and DIY projects. You can start from a text prompt or prebuilt boards, pull in your own images, create new visuals with generative AI, and refine them using natural-language edits. Mixboard signals how fast multimodal AI is moving from chat to visual ideation, with implications for search, commerce, and collaborative workflows.
OpenAI and NVIDIA unveiled a multiโ€‘year plan to deploy 10 gigawatts of NVIDIA systems, marking one of the largest single commitments to AI compute to date. The partners outlined an ambition to stand up AI โ€œfactoriesโ€ totaling roughly 10GW of power, equating to several million GPUs across multiple sites and phases as capacity and supply chains mature. NVIDIA plans to invest up to $100 billion in OpenAI, with tranches released as milestones are met; the first $10 billion aligns to completion of the initial 1GW. The first waves will use NVIDIAโ€™s nextโ€‘generation Vera Rubin systems beginning in the second half of 2026.
African AI Compute Is Moving Local. Telecom operators and digital infrastructure players are racing to stand up AI-grade capacity on the continent as demand, latency, and data-sovereignty pressures converge. MTN Group is negotiating with US and European partners to co-invest in AI-ready facilities and offer capacity to enterprises across multiple African markets. Cassava Technologies is accelerating its sovereign cloud strategy with five AI-focused facilities slated across key African markets in the next 12 months. Earlier this year, Cassava partnered with Nvidia to launch an AI data centre in South Africa powered by the chipmakerโ€™s GPUs, establishing a reference for accelerated infrastructure on the continent.
Mistral AIโ€™s new $14B valuation cements its role as a European AI powerhouse. As data sovereignty, GDPR, and the EU AI Act drive demand for open, governable AI, Mistralโ€™s multilingual models and telco-friendly deployments position it at the center of sovereign AI adoption. From edge inferencing to RAN automation, European telcos and enterprises are rethinking AI stack choices.
SK Telecom is partnering with VAST Data to power the Petasus AI Cloud, a sovereign GPUaaS built on NVIDIA accelerated computing and Supermicro systems, designed to support both training and inference at scale for government, research, and enterprise users in South Korea. By placing VAST Data’s AI Operating System at the heart of Petasus, SKT is unifying data and compute services into a single control plane, turning legacy bare-metal workflows that took days or weeks into virtualized environments that can be provisioned in minutes and operated with carrier-grade resilience.

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