At #GoogleIO, NVIDIA and @GoogleCloud are celebrating a milestone: More than 100,000 developers have joined our joint developer community in just one year, and the platform is expanding. In the past year, members have shipped RAG applications on GKE, built multi-agent pipelines,
AGENTS
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Using AI agents for proactive security auditing
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TL;DR: The winner won't be the loudest AI, but the team turning threat expertise into active auditing agents. 360 shows static code review is no longer enough. Full report → https://
vul.360.net/archives/750 -
AI security splits as OpenClaw finds 23 vulns via live runtime testing
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Meanwhile, 360 just found 23 vulns in OpenClaw by testing live runtime decisions. Is AI security splitting into 2 industries? Static code review is great. BUT auditing autonomous agents that read web data and trigger live actions is a TOTALLY different level of difficulty.
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Google launches Gemini 3.5 Flash, a step toward digital employees
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Google acaba de lanzar Gemini 3.5 Flash.
— Nico (@nicos_ai) 19 mai 2026
Y estamos mucho más cerca de los primeros empleados digitales reales.
→ planifica tareas complejas durante horas
→ divide el trabajo entre subagentes
→ trabaja sobre codebases enormes
→ usa herramientas y ejecuta acciones
→… https://t.co/L2qsKVSqDS pic.twitter.com/wBsqThLNTsGoogle has just launched Gemini 3.5 Flash. And we're much closer to the first truly real digital employees. → plans complex tasks for hours → divides work among subagents → works on massive codebases → uses tools and executes actions → maintains massive context
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Using Forking and Diffing for Self-Improving AI Agents
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if this works, will be great for self-improving agents because of the ability to fork and diff agent runs
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The Need for a New Continuity Layer for Long-Running AI Agents
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why we need a new continuity layer for long-running agents
— Yohei (@yoheinakajima) 19 mai 2026
(claude did this video! all except the voice which was @elevenlabs) pic.twitter.com/nTXcogkGhJwhy we need a new continuity layer for long-running agents (claude did this video! all except the voice which was @elevenlabs
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New intelligent multimodal Search powered by Gemini 3.5
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Today, we launched a brand-new intelligent Search box.
— Google AI (@GoogleAI) 19 mai 2026
Here's what that means:
An upgrade to the Search experience with our most advanced Gemini 3.5 models, bringing with them our latest agentic capabilities
You can ask across modalities (text, images, files, and videos) and… pic.twitter.com/JdSe5RQrBUToday, we launched a brand-new intelligent Search box. Here's what that means: An upgrade to the Search experience with our most advanced Gemini 3.5 models, bringing with them our latest agentic capabilities You can ask across modalities (text, images, files, and videos) and
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Neural Expressive ends the prompt-and-response era in AI interaction
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The prompt-and-response era is officially over.
— Harold Sinnott 📱 (@HaroldSinnott) 19 mai 2026
💥"Neural Expressive" isn't just a design upgrade, it's a complete rethink of how humans and AI interact.
By rebuilding the @GeminiApp experience from the ground up, @Google and @GoogleDeepMind are moving us past the era of… https://t.co/aiuovJh3xQ pic.twitter.com/k9ZzpO9AW5The prompt-and-response era is officially over. "Neural Expressive" isn't just a design upgrade, it's a complete rethink of how humans and AI interact. By rebuilding the @GeminiApp experience from the ground up, @Google and @GoogleDeepMind are moving us past the era of
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MetaCogAgent: metacognitive multi-agent task delegation paper
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NEW paper worth reading: MetaCogAgent MetaCogAgent equips a multi-agent system with metacognition so each agent decides whether it should answer or delegate. In other words, it aims for self-aware task delegation rather than fixed routing. The bottleneck in multi-agent systems
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New Research Paper Proposes Exploration Checkpoint Coverage for LLM Agents
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new longcat paper! “Look Before You Leap” LLM agents often fail because they act before they understand the environment. So this paper introduces Exploration Checkpoint Coverage, a verifiable reward for discovering key states, objects, affordances, and constraints. With