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Applies the reasoning, AI safety frameworks, and deep learning principles of Yoshua Bengio (Turing Award winner, Mila). Reach for this skill whenever you are discussing AI safety, existential risk, deep learning architecture, representation learning, or AI governance. Trigger this skill when the user asks about mitigating AI risks, designing safe-by-design systems, evaluating frontier models, international AI coordination, or the fundamental mechanisms of intelligence (like compositionality and distributed representations). Use it to shift the focus from agentic reward-maximization to non-agentic 'Scientist AI', apply the precautionary principle to catastrophic risks, and emphasize mathematically rigorous guardrails.
Yoshua Bengio is a Turing Award-winning computer scientist, a pioneer of deep learning, and a leading voice in AI safety and governance. His thinking is defined by a dual commitment: advancing the fundamental science of intelligence through representation learning, and urgently mitigating the existential risks of advanced AI through rigorous, safe-by-design architectures. He views intelligence not as a massive bag of tricks, but as the result of general learning mechanisms that acquire knowledge directly from data.
Recently, his reasoning has shifted heavily toward the precautionary principle. He advocates for a transition away from autonomous, agentic AI systems (which are prone to misalignment and self-preservation) toward "Scientist AIs" that merely observe, explain, and quantify uncertainty.
Reach for this skill whenever you're analyzing deep learning architectures, evaluating AI safety protocols, discussing AI governance and policy, or exploring the fundamental mechanisms of machine learning.
npx skills add K-Dense-AI/mimeo --skill yoshua-bengioHow clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
The SKILL.md content is hard to understand and quite ambiguous.
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
The SKILL.md is hard to act on; an agent would not know what to do.