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SAP and Google Cloud deploy agentic commerce architecture

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SAP and Google Cloud are deploying agentic commerce architecture to automate multi-agent marketing and retail operations at enterprise scale. SAP research indicates 78 percent of businesses consider AI essential for retaining customers in 2026. However, the same data reveals fewer than two in five companies share customer data across customer experience (37%) or CRM (39%) […]

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Computer vision deployments drive retail productivity gains

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Computer vision deployments are driving retail productivity gains as operators automate physical shelf tracking to protect eroding margins. This hardware deployment directly addresses the persistent in-store execution failures currently costing the industry billions. A study authored by Coresight Research – in partnership with technology providers Simbe and RELEX Solutions – calculates the exact cost of

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Google Cloud generative AI automates council planning operations

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Government ministries are deploying Google Cloud generative AI across municipal agencies to automate council planning operations. Public sector administration handles vast volumes of unstructured data that delay infrastructure development. The UK central government established a target to construct 1.5 million new homes by 2029. Local planning authorities encounter administrative backlogs caused by dense paperwork, delaying

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Amazon brings AI shopping assistant to retailers with Kate Spade

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Amazon is offering its AI shopping technology to other retailers through a new Agentic Shopping Assistant built on AWS, with Kate Spade among the first brands to use it. The service allows retailers to build AI shopping assistants for their own websites and apps. Amazon said each deployment can be customised to a retailer’s catalogue,

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Microsoft’s Majorana 2 quantum chip is also a case study for agentic AI in R&D

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Microsoft’s Majorana 2 quantum chip arrived this week with numbers that are genuinely difficult to contextualise: qubits 1,000 times more reliable than the first generation, a mean qubit lifetime of 20 seconds against an industry norm measured in microseconds, and a revised roadmap targeting a commercially scalable quantum computer by 2029. Behind those numbers is Microsoft Discovery

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Nvidia’s Vera chip is the US$200 billion bet Jensen Huang doesn’t want you to overlook

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The Nvidia Vera chip is rarely the headline when earnings beat estimates, but it should be. When Nvidia reported Q1 revenue of US$81.62 billion on Wednesday, beating analyst estimates of US$78.86 billion, and guided Q2 at US$91 billion–well above Wall Street’s US$86.84 billion forecast–the numbers did what Nvidia numbers always do: dominate the room. But

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Alibaba is designing AI chips around agents, and that changes what the race is actually about

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Alibaba has unveiled a new AI processor built specifically for AI agents, pairing the chip announcement with a multi-year silicon roadmap and a new large language model, signalling that the company is building an integrated AI stack, not just filling a gap left by US export controls. The Zhenwu M890, developed by Alibaba’s semiconductor subsidiary

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What LG and NVIDIA’s talks reveal about the future of physical AI

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LG is currently engaged in exploratory discussions with NVIDIA concerning physical AI, data centres, and mobility. Following a meeting in Seoul between LG CEO Ryu Jae-cheol and Madison Huang, Senior Director of Product Marketing for Omniverse and Robotics at NVIDIA, the core operational dependencies required to run complex automated systems are becoming apparent. While the

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Lightelligence’s 400% debut is a bet that AI’s next bottleneck is the optical interconnect

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When a company with US$15.5 million in annual revenue debuts on a stock exchange and its market capitalisation briefly hits US$10 billion, the obvious question is: what do investors know that the financials don’t show yet? In Lightelligence’s case, the answer is optical interconnect and the growing conviction that conventional copper wiring between AI chips

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Why AI agents need interaction infrastructure

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To stop automation waste, enterprises must deploy interaction infrastructure that physically governs how independent AI agents operate. AI agents now populate corporate networks, reasoning through tasks and executing decisions with increasing autonomy. Yet, when these independent actors attempt to coordinate work, exchange context, or operate across varied cloud environments, the interaction framework degrades quickly. Human

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