Browse entries 121–144 of 1032. Return to the first page to search and filter the complete collection.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Google’s CISO perspective on why agents need a new security paradigm and what changes when models can observe, plan, and act.
Google DeepMind and partners announce a $10M funding call for multi-agent safety research.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
OpenAI announced plans to acquire Promptfoo, highlighting automated AI security testing, red teaming, and evaluation as core enterprise requirements.
In a collaboration with researchers at Mozilla, Claude Opus 4.6 discovered 22 Firefox vulnerabilities over the course of two weeks.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Play video
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
Play video
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Microsoft summarizes lessons from red teaming more than one hundred generative AI products, emphasizing system-level testing, human expertise, and automation.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Play video
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Play video
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Play video
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Learn how better questions, trusted AI, and human judgment help security leaders make confident decisions and build resilient systems.
Join Microsoft Security at Black Hat USA 2026 for supply chain research, hands-on security experiences, expert conversations, and our reception.
Francis deSouza explains the crucial role that deep context plays in creating an AI advantage for defenders.
Microsoft’s latest Secure Future Initiative report outlines progress on secure foundations, AI-powered defense, and future-ready cybersecurity.
Read five key learnings from the Frost & Sullivan 2025 Frost Radar™ for CSPM to learn how CSPM is evolving from point-in-time compliance to continuous risk management.
Unit 42 analysis of phantom squatting: attackers register domains that LLMs may hallucinate in recommendations, code, documentation, or support answers. That turns model error into a supply-chain path, especially when users or agents follow generated links without independent validation.