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Alibaba Qwen is challenging proprietary AI model economics

ai, AI (Artificial Intelligence), AI and Us, AI Business Strategy, Alibaba, Artificial Intelligence, china, democratisation, Economics, Features, governance, Governance, Regulation & Policy, Inside AI, Models, Open Source, Open-Source & Democratised AI, Opinion, qwen, strategy

The release of Alibaba’s latest Qwen model challenges proprietary AI model economics with comparable performance on commodity hardware. While US-based labs have historically held the performance advantage, open-source alternatives like the Qwen 3.5 series are closing the gap with frontier models. This offers enterprises a potential reduction in inference costs and increased flexibility in deployment […]

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Agentic AI drives finance ROI in accounts payable automation

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Finance leaders are driving ROI using agentic AI for accounts payable automation, turning manual tasks into autonomous workflows. While general AI projects saw return on investment rise to 67 percent last year, autonomous agents delivered an average ROI of 80 percent by handling complex processes without human intervention. This performance gap demands a change in

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How e& is using HR to bring AI into enterprise operations

ai, AI (Artificial Intelligence), AI Business Strategy, AI in Action, Artificial Intelligence, cloud, Features, hr, Oracle, telecom, Workforce & HR AI, World of Work

For many enterprises, the first real test of AI is not customer-facing products or flashy automation demos. It is the quiet machinery that runs the organisation itself. Human resources, with its mix of routine workflows, compliance needs, and large volumes of structured data, is emerging as one of the earliest areas where companies are pushing

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We let Chrome’s Auto Browse agent surf the web for us—here’s what happened

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We are now a few years into the AI revolution, and talk has shifted from who has the best chatbot to whose AI agent can do the most things on your behalf. Unfortunately, AI agents are still rough around the edges, so tasking them with anything important is not a great idea. OpenAI launched its

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How insurance leaders use agentic AI to cut operational costs

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Agentic AI offers insurance leaders a path to scalable efficiency as the sector confronts a tough digital transformation. Insurers hold deep data reserves and employ a workforce skilled in analytic decision-making. Despite these advantages, the industry has largely failed to advance beyond pilot programmes. Research suggests only seven percent of insurers have scaled these initiatives

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Agentic AI in healthcare: How Life Sciences marketing could achieve US$450bn in value by 2028

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Agentic AI in healthcare is graduating from answering prompts to autonomously executing complex marketing tasks—and life sciences companies are betting their commercial strategies on it. According to a recent report cited by Capgemini Invent, AI agents could generate up to US$450 billion in economic value through revenue uplift and cost savings globally by 2028, with 69% of

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Exclusive: Why are Chinese AI models dominating open-source as Western labs step back?

ai, AI (Artificial Intelligence), AI and Us, AI in Action, Artificial Intelligence, Deep Dives, Features, Inside AI, Open Source, Open-Source & Democratised AI

Because Western AI labs won’t—or can’t—anymore. As OpenAI, Anthropic, and Google face mounting pressure to restrict their most powerful models, Chinese developers have filled the open-source void with AI explicitly built for what operators need: powerful models that run on commodity hardware. A new security study reveals just how thoroughly Chinese AI has captured this space. Research published by SentinelOne

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Goldman Sachs tests autonomous AI agents for process-heavy work

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Goldman Sachs is pushing deeper into real use of artificial intelligence inside its operations, moving to systems that can carry out complex tasks on their own. The Wall Street bank is working with AI startup Anthropic to create autonomous AI agents powered by Anthropic’s Claude model that can handle work that used to require large

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How separating logic and search boosts AI agent scalability

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Separating logic from inference improves AI agent scalability by decoupling core workflows from execution strategies. The transition from generative AI prototypes to production-grade agents introduces a specific engineering hurdle: reliability. LLMs are stochastic by nature. A prompt that works once may fail on the second attempt. To mitigate this, development teams often wrap core business

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Why Darren Aronofsky thought an AI-generated historical docudrama was a good idea

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Last week, filmmaker Darren Aronofsky’s AI studio Primordial Soup and Time magazine released the first two episodes of On This Day… 1776. The year-long series of short-form videos features short vignettes describing what happened on that day of the American Revolution 250 years ago, but it does so using “a variety of AI tools” to

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