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New enterprise research shows most AI agents fail with total confidence rather than visible doubt - and that automated testing is not catching it before deployment. For operators running AI agents alongside private networks in manufacturing, mining, ports, airports and utilities, that combination changes how agent-based tools should be evaluated and rolled out.
A new alliance between SK Telecom (SKT), Arm, and Rebellions targets the fast-growing AI inference market with a server platform designed for sovereign AI and telecom-grade data centers. SKT will validate a new AI server that combines Arm’s AGI CPU—its first Arm-designed data center processor, based on Neoverse CSS V3—with Rebellions’ RebelCard inference accelerator in live AI data center environments. The partners will co-develop the full software stack, from firmware up, and test telco-specific models and large-scale workloads, including SKT’s proprietary foundation model, A.X K1. Industry focus is shifting from training to inference at scale, where energy, latency, and total cost of ownership (TCO) are decisive.
Anthropic has introduced Claude Code Security, an AI capability that reviews codebases, flags complex vulnerabilities, and proposes patches with human oversight, and its early results should change how security leaders plan for AI on both offense and defense. Anthropic reports that its latest Claude Opus 4.6 model helped uncover more than 500 vulnerabilities in production open-source projects, including issues that had persisted for years. The product centers on high-signal findings, structured triage, and human-in-the-loop remediation so it can slot into existing DevSecOps workflows.
A new partnership between Infosys and Anthropic brings agentic AI into regulated, process-heavy industries, with telecom squarely in scope. Infosys will integrate Anthropic’s Claude models and Claude Code with its Topaz portfolio to build and operate enterprise-grade AI solutions across telecom, financial services, manufacturing, and software engineering. The collaboration emphasizes agentic AI—systems that can plan, call tools, and execute multi-step workflows with oversight—delivered with the controls, auditability, and policy enforcement that regulated sectors demand. Pairing Infosys’s domain depth with Claude’s reasoning and long-context capabilities gives operators a path to pragmatic automation that respects regulatory, safety, and transparency requirements.
India’s AI agenda increasingly spans silicon, data platforms, models, and applications, with an intent to catalyze domestic innovation and contribute to global ecosystems. For telecom leaders, the message is clear: AI is not a bolt-on capability but a system-level transformation that touches RAN, core, transport, cloud, and the enterprise edge. The AI economy runs on connectivity—low-latency access to data, assured bandwidth, location-aware processing, and programmable control. The operators that can fuse connectivity, compute, and data into a cohesive platform will set the pace for India’s next wave of digital growth.
The UK government signalled a rapid escalation of online safety measures that will bring AI chatbots squarely under the Online Safety Act and could introduce an under‑16 social media ban as early as this year. Ministers plan to amend the Online Safety Act 2023 so one‑to‑one interactions with AI systems fall within scope of illegal and harmful content controls. The government wants providers of large language model (LLM) assistants and agentic chatbots to implement safety‑by‑design, including stronger filtering, red‑teaming, abuse detection, and rapid takedown procedures for sexualised or otherwise illegal outputs.
Cognizant is expanding its partnership with Google Cloud around Gemini Enterprise and Google Workspace, and it is putting real skin in the game by rolling out this stack internally to boost productivity and delivery velocity. The company is forming a dedicated Gemini Enterprise Center of Excellence and codifying repeatable delivery with an Agent Development Lifecycle that embeds AI across design, build, validation, and production. It is also packaging accelerators—Cognizant Ignition for discovery and data readiness and Cognizant Agent Foundry for no-code, pre-configured agents targeting use cases like AI-powered contact centers and intelligent order management.
Microsoft’s AI QuickStart, backed by IMDA and UOB, aims to turn generative AI intent into production outcomes in weeks, not years. AI QuickStart targets “Digital Leaders” in Singapore—SMEs and larger non-ICT enterprises that have already built basic digital capabilities and can fund transformation—by offering a fast, structured path to deploy enterprise AI. Each engagement is designed to finish within three months with a cost cap of up to S$20,000 per project, covering cloud, compute, and professional services, which directly addresses executive concerns over unpredictable pilot spend and elongated proofs-of-concept.
Positron closed a $230 million Series B at a reported $1 billion valuation, co-led by Arena Private Wealth, Jump Trading, and Unless, with strategic capital from Qatar Investment Authority (QIA). Positron is focused on inference silicon rather than training, aligning with a market shift from building ever-larger foundation models to deploying them at scale. Its first-generation Atlas chip, manufactured in Arizona, is designed around high-speed memory throughput and is claimed to match Nvidia H100-class performance at under one-third the power for select inference workloads.
Amdocs is launching aOS, an agentic operating system for telecom, to move CSPs from AI pilots to production-scale, cross-domain automation. Amdocs’ aOS targets that gap with a multi-agent architecture that automates complex workflows while keeping humans in the loop for policy and final decisions. At the foundation is a “Cognitive Core” that manages telco-specific knowledge, agent libraries, and guardrails. aOS pricing will lean on outcome-based SLAs, tying spend to measurable business impact such as resolution rates, handle-time reductions, activation velocity, or assurance KPIs. aOS is Amdocs’ bid to make agentic AI the connective tissue of telco operations.
Nvidia used NeurIPS to expand an open toolkit for digital and physical AI, with a flagship reasoning model for autonomous driving and a broader stack that targets speech, safety, and reinforcement learning. Nvidia introduced DRIVE Alpamayo-R1 (AR1), an open vision-language-action model that fuses multimodal perception with chain-of-thought reasoning and path planning, aiming to push toward Level 4 autonomy in constrained domains. To lower adoption friction, Nvidia published the Cosmos Cookbook with step-by-step recipes for data curation, synthetic data generation, inference, and post-training workflows, enabling customization for diverse physical AI use cases.

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