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Strengthening enterprise governance for rising edge AI workloads

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Models like Google Gemma 4 are increasing enterprise AI governance challenges for CISOs as they scramble to secure edge workloads. Security chiefs have built massive digital walls around the cloud; deploying advanced cloud access security brokers and routing every piece of traffic heading to external large language models through monitored corporate gateways. The logic was […]

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Microsoft open-source toolkit secures AI agents at runtime

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Business Strategy, Artificial Intelligence, automation, Compliance, cybersecurity, Enterprise AI, Featured News, Features, governance, Governance, Regulation & Policy, How It Works, infrastructure, Inside AI, LLM, Microsoft, Open Source, Open-Source & Democratised AI, prompt injection, runtime security, token management

A new open-source toolkit from Microsoft focuses on runtime security to force strict governance onto enterprise AI agents. The release tackles a growing anxiety: autonomous language models are now executing code and hitting corporate networks way faster than traditional policy controls can keep up. AI integration used to mean conversational interfaces and advisory copilots. Those

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KiloClaw targets shadow AI with autonomous agent governance

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With the launch of KiloClaw, enterprises now have a tool to enforce governance over autonomous agents and manage shadow AI. While businesses spent the last year securing large language models and formalising vendor agreements, developers and knowledge workers started moving on their own. Employees are bypassing official procurement, deploying autonomous agents on personal infrastructure to

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KPMG: Inside the AI agent playbook driving enterprise margin gains

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Global AI investment is accelerating, yet KPMG data shows the gap between enterprise AI spend and measurable business value is widening fast. The headline figure from KPMG’s first quarterly Global AI Pulse survey is blunt: despite global organisations planning to spend a weighted average of $186 million on AI over the next 12 months, only

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SAP and ANYbotics drive industrial adoption of physical AI

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Heavy industry relies on people to inspect hazardous, dirty facilities. It’s expensive, and putting humans in these zones carries obvious safety risks. Swiss robot maker ANYbotics and software company SAP are trying to change that. ANYbotics’ four-legged autonomous robots will be connected straight into SAP’s backend enterprise resource planning software. Instead of treating a robot

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Automating complex finance workflows with multimodal AI

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Finance leaders are automating their complex workflows by actively adopting powerful new multimodal AI frameworks. Extracting text from unstructured documents presents a frequent headache for developers. Historically, standard optical character recognition systems failed to accurately digitise complex layouts, frequently converting multi-column files, pictures, and layered datasets into an unreadable mess of plain text. The varied

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Mastercard keeps tabs on fraud with new foundation model

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Mastercard has developed a large tabular model (an LTM as opposed to an LLM) that’s trained on transaction data rather than text or images to help it address security and authenticity issues in digital payments. The company has trained a foundation model on billions of card transactions, with the intention of expanding to hundreds of

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How multi-agent AI economics influence business automation

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Managing the economics of multi-agent AI now dictates the financial viability of modern business automation workflows. Organisations progressing past standard chat interfaces into multi-agent applications face two primary constraints. The first issue is the thinking tax; complex autonomous agents need to reason at each stage, making the reliance on massive architectures for every subtask too

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Ai2: Building physical AI with virtual simulation data

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Virtual simulation data is driving the development of physical AI across corporate environments, led by initiatives like Ai2’s MolmoBot. Instructing hardware to interact with the real world has historically relied on highly expensive and manually-collected demonstrations. Technology providers building generalist manipulation agents typically frame extensive real-world training as the basis for these systems. For some

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How physical AI integration accelerates vehicle innovation

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The integration of physical AI into vehicles remains a primary objective for automakers looking to accelerate innovation. A technical collaboration between Qualcomm and Wayve offers a framework for how hardware and software providers can consolidate their efforts to supply production-ready advanced driver assistance systems to manufacturers worldwide. The partnership combines Wayve’s AI driving layer with

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