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OpenAI aligns safety practices with EU AI Act’s GPAI Code

OpenAI has outlined how it aligns safety, security, and transparency work with the EU AI Act’s GPAI Code as enforcement approaches. The company has contributed to and endorsed the EU’s General-Purpose AI (GPAI) Code of Practice and the Code of Practice on Transparency of AI-Generated Content. Both emerged from multi-stakeholder processes. The GPAI Code sets […]

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Zuckerberg details Meta’s personal AI superintelligence strategy

Mark Zuckerberg has published a WSJ op-ed that argues superintelligence must reach individuals, not just a handful of institutions. The Meta chief published the piece as a statement of company philosophy rather than a product announcement. It contains no release dates, no benchmark figures, no named models. What it does contain is an argument that

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Why AI Will Humble Regulators

Illinois has chosen to move before Washington. Gov. JB Pritzker signed the Artificial Intelligence Safety Measures Act on July 6, 2026, adding transparency, accountability and audit requirements for the largest artificial intelligence developers. The law applies to companies generating more […] The post Why AI Will Humble Regulators appeared first on TechSpective.

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Meta, Microsoft, Nvidia, IBM, and others back open-weight AI

Two dozen companies and organisations signed an open letter urging US policymakers to protect open-weight AI models. The letter, published today (PDF), carries signatures from a list that spans direct commercial rivals and organisations with little obvious overlap in business model: Meta, Microsoft, Nvidia, IBM, Dell Technologies, CrowdStrike, Palantir, ServiceNow, Hugging Face, Perplexity, Mistral, Andreessen

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Anthropic deploys Claude Sonnet 5, Fable and Mythos restored

Anthropic has launched Claude Sonnet 5 and restored access to its Fable and Mythos frontier models following a federal export control review. The decision marks the conclusion of an eighteen-day operational pause triggered by a US government export control directive on June 12, which forced the temporary suspension of Anthropic’s highest-capability systems. Government officials enacted

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Scaling safe enterprise AI with OpenAI governance frameworks

OpenAI’s latest governance frameworks offer enterprise leaders a structured blueprint for scaling safe and compliant AI deployments globally. The adoption of large language models has steadily progressed towards requiring sustainable, commercial-grade architecture. OpenAI has released its Frontier Governance Framework (FGF), documenting how the organisation addresses systemic risk assessment and mitigation. The framework maps directly to

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IDC: How EMEA CIOs can jumpstart AI rollouts

Getting stalled enterprise AI rollouts in the EMEA region moving again will require CIOs to aggressively audit their systems. Over the past 18 months, AI deployments across Europe advanced far beyond initial testing. Companies poured capital into large language models and machine learning, expecting heavy operational upgrades. IDC research reveals that boards are slowing down,

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Strengthening enterprise governance for rising edge AI workloads

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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Agentic AI’s governance challenges under the EU AI Act in 2026

AI agents hold the promise of automatically moving data between systems and triggering decisions, but in some cases, they can act without a clear record of what, when, and why they undertook their tasks. That has the potential to create a governance problem, for which IT leaders are ultimately responsible. If an organisation can’t trace

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Secure governance accelerates financial AI revenue growth

Financial institutions are learning to deploy compliant AI solutions for greater revenue growth and market advantage. For the better part of ten years, financial institutions viewed AI primarily as a mechanism for pure efficiency gains. During that era, quantitative teams programmed systems designed to discover ledger discrepancies or eliminate milliseconds from automated trading execution times.

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