NVIDIA company headlines, earnings, strategy, leadership, and market-moving business updates.
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Recent results show continued growth in AI infrastructure spending, while both companies also face a market expectation problem: how much upside is left after years of blockbuster gains.
THE APEX TIMES
THE APEX TIMES
Marvell shares have surged on investor enthusiasm for the AI infrastructure layer, helped by a high-profile Nvidia partnership that aims to plug Marvell’s custom chips into Nvidia’s rack-scale ecosystem.
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An analyst at D.A. Davidson argues that Nvidia’s AI-chip margins may stay near the mid-70% range for years, citing hyperscalers’ limited near-term alternatives despite the rise of custom silicon.
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The US chip designer says its new multi-year agreements with Korean firms are aimed at building out next-generation memory and expanding large-scale AI “computational factories.”
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Huang’s comments on June 8, 2026 came as global tech stocks slid on worries that the AI trade had become overheated, even as Nvidia highlighted record revenue and ongoing AI “factory” expansion.
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LG and NVIDIA say they are turning the physical world into training ground for physical AI, linking simulation, data generation, edge deployment, and factory-scale digital twins. LG also outlines broader collaboration in robotics, autonomous driving, and sovereign AI, without providing deal size or timing.
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The AI cloud operator says it will add three new NVIDIA-powered infrastructure deployments in the United Kingdom, expanding capacity and cloud capabilities aimed at agentic and enterprise AI workloads.
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From a next-generation zero-carbon supercomputer to inference labs and enterprise pilots, the UK’s plan to be an “AI maker” is moving from policy language to deployments, backed by NVIDIA-linked infrastructure and ecosystem programs.
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Speaking in South Korea after a broad chip pullback, Huang linked the ongoing AI buildout to multi-year supply constraints, and pointed to Nvidia’s memory roadmap work with SK hynix.
