Browse entries 313–336 of 1025. Return to the first page to search and filter the complete collection.
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AI Engineer session on Ensure AI Agents Work: Evaluation Frameworks for Scaling Success, presented by Aparna Dhinkaran, CEO Arize. It adds practical context for how teams are building and operating AI systems in production.
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NDC AI 2025 talk on LLM frontdoors and backdoors, jailbreak techniques, control-token abuse, local model compromise, and how attackers or insiders can manipulate model behavior.
Palo Alto Networks' Unit 42 says a Chinese-speaking threat actor used DeepSeek through the open-source Hermes Agent framework to launch attacks autonomously. After an initial Telegram instruction, the agent found internet-facing systems and selected public exploits.
Participatory AI often stops at consultation. Why governance infrastructure, community authority and lifecycle oversight are essential for trustworthy AI.
AI regulatory sandboxes in AI governance: benefits, design, global examples and policy insights to foster innovation, trust and compliance.
3.1 Pro is designed for tasks where a simple answer isn’t enough.
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AI Engineer session on How to Build Planning Agents without losing control - Yogendra Miraje, Factset. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on LLM Safeguards: Security Privacy Compliance Anti Hallucination: Daniel Whitenack. It adds practical context for how teams are building and operating AI systems in production.
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This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. 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 benchmarks and evaluation evidence. 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 multimodal generation and provenance. 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 benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
With the introduction of models that require data sharing with third-party providers—such as Claude Fable 5—organizations need a way to centrally enforce data retention policies. Amazon Bedrock gives you control over whether your prompts and model outputs are retained after an inference request completes.
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AI Engineer session on AgentCraft: Putting the Orc in Orchestration, presented by Ido Salomon. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Agents need more than a chat - Jacob Lauritzen, CTO Legora. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Full Workshop: Build Your Own Deep Research Agents - Louis-François Bouchard, Paul Iusztin, Samridhi. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Future of MCP, presented by David Soria Parra, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on From Chaos to Choreography: Multi-Agent Orchestration Patterns That Actually Work, presented by Sandipan Bhaumik. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Agentic Engineering: Working With AI, Not Just Using It, presented by Brendan O'Leary. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Platforms for Humans and Machines: Engineering for the Age of Agents, presented by Juan Herreros Elorza. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Shipping AI That Works: An Evaluation Framework for PMs, presented by Aman Khan, Arize. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Welcome to AIE CODE - Jed Borovik, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Code World Model: Building World Models for Computation, presented by Jacob Kahn, FAIR Meta. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Real World Development with GitHub Copilot and VS Code, presented by Harald Kirschner, Christopher Harrison. It adds practical context for how teams are building and operating AI systems in production.