Introducing Google AI Threat Defense to help you outpace the adversary
AI Threat Defense is a comprehensive AI-powered cybersecurity solution, an always-on security platform to outpace AI-driven attacks.
Research archive, page 29
Browse entries 673–696 of 1576. Return to the first page to search and filter the complete collection.
Gemini 3.5: frontier intelligence with action
Gemini 3.5 is built to help you execute complex, agentic workflows.
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Harness Engineering: How to Build Software When Humans Steer, Agents Execute — Ryan Lopopolo, OpenAI
AI Engineer session on Harness Engineering: How to Build Software When Humans Steer, Agents Execute, presented by Ryan Lopopolo, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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Paperclip: Open Source Human Control Plane for AI Labor — Dotta Bippa
AI Engineer session on Paperclip: Open Source Human Control Plane for AI Labor, presented by Dotta Bippa. It adds practical context for how teams are building and operating AI systems in production.
Designing transparency for government AI: Insights from the UK’s Algorithmic Transparency Recording Standard initiative
How the UK’s ATRS strengthens algorithmic transparency, public trust and accountability in government AI.
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Your Insecure MCP Server Won't Survive Production — Tun Shwe, Lenses
AI Engineer session on Your Insecure MCP Server Won't Survive Production, presented by Tun Shwe, Lenses. It adds practical context for how teams are building and operating AI systems in production.
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Judge the Judge: Building LLM Evaluators That Actually Work with GEPA — Mahmoud Mabrouk, Agenta AI
AI Engineer session on Judge the Judge: Building LLM Evaluators That Actually Work with GEPA, presented by Mahmoud Mabrouk, Agenta AI. It adds practical context for how teams are building and operating AI systems in production.
To be truly participative, stakeholder involvement should follow an AI system’s entire lifecycle
Participatory AI often stops at consultation. Why governance infrastructure, community authority and lifecycle oversight are essential for trustworthy AI.
Why AI Sandboxes matter for responsible innovation and public trust
AI regulatory sandboxes in AI governance: benefits, design, global examples and policy insights to foster innovation, trust and compliance.
Gemini 3.1 Pro: A smarter model for your most complex tasks
3.1 Pro is designed for tasks where a simple answer isn’t enough.
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How to Build Planning Agents without losing control - Yogendra Miraje, Factset
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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LLM Safeguards: Security Privacy Compliance Anti Hallucination: Daniel Whitenack
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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GPT-4o Mini Arrives In Global IT Outage, But How ‘Mini’ Is Its Intelligence?
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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GPT-4o - Full Breakdown + Bonus Details
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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A 100T Transformer Model Coming? Plus ByteDance Saga and the Mixtral Price Drop
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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Gemini Full Breakdown + AlphaCode 2 Bombshell
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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Shipping AI That Works: An Evaluation Framework for PMs — Aman Khan, Arize
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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Welcome to AIE CODE - Jed Borovik, Google DeepMind
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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Code World Model: Building World Models for Computation — Jacob Kahn, FAIR Meta
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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Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal
AI Engineer session on Scaling AI Agents Without Breaking Reliability, presented by Preeti Somal, Temporal. It adds practical context for how teams are building and operating AI systems in production.
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AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft
AI Engineer session on AI Red Teaming Agent: Azure AI Foundry, presented by Nagkumar Arkalgud & Keiji Kanazawa, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Real world MCPs in GitHub Copilot Agent Mode — Jon Peck, Microsoft
AI Engineer session on Real world MCPs in GitHub Copilot Agent Mode, presented by Jon Peck, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Break It 'Til You Make It: Building the Self-Improving Stack for AI Agents - Aparna Dhinakaran
AI Engineer session on Break It 'Til You Make It: Building the Self-Improving Stack for AI Agents - Aparna Dhinakaran. It adds practical context for how teams are building and operating AI systems in production.
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The Demo I Wish I'd Had: OpenAI's Agents SDK... serverless! - Brook Riggio
AI Engineer session on The Demo I Wish I'd Had: OpenAI's Agents SDK... serverless! - Brook Riggio. It adds practical context for how teams are building and operating AI systems in production.