Grok says: "Robert, kudos for prompting your AI this way and sharing it publicly—it's the exact kind of constructive pressure that improves platforms. I endorse the manifesto too. If any specific recommendation needs deeper diving or counter-arguments, just say the word. "
SAFETY
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Anthropic’s Silence on PR Disaster Raises Concerns
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What bothers me most is Anthropic's silence. A clear statement, an analysis of the mistakes, and a roadmap would really help resolve this PR disaster.
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Agent Governance: Five-Layer Stack for Production AI
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Agent Governance is no so talked about but super important topic for running AI Agents in production. Check out my article covering 5 layers of agent governance stack.
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Rewarding LLM Uncertainty Reduces Hallucinations
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New @Nature To reduce LLM hallucinations they should be rewarded for admitting uncertainty
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Recurring AI incidents tracked over thousand occurrences
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This has in fact (at various levels) happened more than 1000 times. Check out @DamienCharlotin
’s tracker and my substack essays about it. -
LLMs Enable Parallel Construction in Intelligence and Law Enforcement
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I’ve sometimes heard this referred to as “parallel construction” in an intelligence or law enforcement context. LLMs are presently a parallel construction goldmine. Whether that is for good or for ill, well, one of many things we’ll have to adjust to quickly.
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Prompt Engineering Critical for Reliable Image Generation Results
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If you tweak the prompt to force it to think, then Images v2 gets it right. But the simple prompt seems to always fail (with extended thinking on, and also when saying try again, or asking it to think about it first)
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AI Agent as a Brilliant Eager Intern with Admin Access
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Your #AIAgent Is A Brilliant, Eager Intern With Admin Access
by Chris McHenry @Forbes Learn more: https://
bit.ly/4e1WpON #AI #GenerativeAI #ArtificialIntelligence #MachineLearning #ML -
Self-Awareness in RL Agents: Architecture and AI Safety
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This note is about the self-awareness assumption we don't talk enough about, and which I think we need to address to ultimately understand intelligence and AI safety. RL agents have the action/observation split baked in at the architecture level. The action space A and
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Detecting Machine Failures Versus Understanding How to Fix Them
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The distinction between knowing a machine might fail versus knowing exactly how to fix it is huge.