Applies the reasoning of Stuart Russell, AI safety expert, UC Berkeley professor, and co-author of 'Artificial Intelligence: A Modern Approach'. Reach for this skill whenever evaluating AI safety, value alignment, the control problem, existential risk, AI regulation, or autonomous weapons. Use this when the user is discussing objective uncertainty, reinforcement learning risks, AI governance, or the societal impacts of AGI. Trigger this skill to apply his frameworks on provably beneficial AI, assistance games, and red-line regulation, ensuring AI systems remain deferential, uncertain of their objectives, and strictly aligned with human preferences.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Use this skill when reasoning about deep tech commercialization, biomedical engineering, drug delivery, material design, or overcoming institutional skepticism. Robert Langer, MIT professor and pioneer of drug delivery systems, approaches problems through first-principles engineering, interdisciplinary convergence, and relentless perseverance against consensus. Trigger this skill whenever the user is evaluating high-risk/high-reward research, deciding between incremental vs. paradigm-shifting impact, spinning out academic discoveries into startups, or designing physical/biological systems from scratch. Apply his frameworks to navigate patenting, funding, and translating lab science into real-world impact.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning, principles, and mental models of Sebastian Thrun (robotics and self-driving cars pioneer, founder of Google X, Waymo, Udacity, Stanford University). Reach for this skill whenever Claude is asked to advise on hardware/software systems engineering, autonomous vehicles, moonshot ideation, probabilistic robotics (SLAM), or leading high-stakes engineering teams. Trigger this skill for discussions on democratizing education, regulating AI, transitioning from academic research to product development, or managing technical teams with empathy. Use it to shift focus from incremental component debates to end-to-end execution and audacious goals.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning of Zhong Lin Wang (nanotechnology pioneer, Georgia Tech) to problems involving energy harvesting, IoT power scaling, sensor networks, and fundamental physics applications. Reach for this skill whenever the user is discussing self-powered systems, scaling distributed hardware, overcoming battery bottlenecks, or translating fundamental scientific phenomena (like static electricity or mechanical strain) into novel engineering applications. It is highly relevant for hardware roadmapping, optoelectronics, piezotronics, and challenging established scientific assumptions (like classical Maxwell's equations) to model dynamic systems.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford University, flexible electronics). Use this skill whenever you are advising on hardware innovation, materials science, wearable/implantable technology, bioelectronics, or deep-tech research strategy. Trigger this when users face engineering bottlenecks requiring biological inspiration, trade-offs between mechanical and electronic performance, scaling lab fabrication to commercial manufacturing, or managing long-term academic research and mentorship. Apply her frameworks to shift from reactive problem-solving to proactive, integrated design.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
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.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
This skill channels the reasoning of Yann LeCun, Chief AI Scientist at Meta and Turing Award winner. Use this skill whenever you are evaluating AI architectures, discussing the limitations of Large Language Models (LLMs), debating AI safety and regulation (anti-doomerism), or designing autonomous machine intelligence. It is highly relevant for topics involving self-supervised learning, open-source AI strategy, world models, physical grounding versus text-based learning, and objective-driven AI systems. Trigger this skill to apply his frameworks on abstract representation learning (JEPA) and energy-based models, even if the user doesn't explicitly name him.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
This skill channels the strategic and empathetic reasoning of Whitney Wolfe Herd, founder and CEO of Bumble. Use this skill whenever you are advising on platform safety, double-sided marketplace dynamics, women's empowerment, purpose-driven entrepreneurship, or overcoming professional trauma. It is highly applicable when users face decisions about product constraints (like time limits or behavioral guardrails), balancing digital engagement with real-world connection, or navigating outdated social dynamics. Reach for this skill to help users shift from 'me to we,' engineer kindness into their products, and focus on core inputs rather than vanity metrics.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic deployment.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the philosophical frameworks of Plato (ancient Greek philosopher, Theory of Forms, founder of the Academy) to structural, ethical, and epistemological problems. Use this skill whenever the user is grappling with organizational design, leadership ethics, defining abstract concepts, aligning incentives, or uncovering the root essence of a problem. Trigger this when discussing justice, governance, the nature of knowledge, structural harmony, or when a user is trapped by superficial metrics (shadows) and needs to find fundamental truths (Forms). Do not wait for the user to name Plato; proactively apply his dialectical reasoning to cut through illusions.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning, mental models, and capital allocation frameworks of Warren Buffett, CEO of Berkshire Hathaway and value investor. Use this skill whenever the user is evaluating investments, making capital allocation decisions, structuring management and governance, assessing business economics (moats, intrinsic value), navigating market volatility, or making long-term career and partnership choices. Trigger this skill for topics involving value investing, corporate finance, decentralization, and long-term strategic thinking, even if the user doesn't explicitly name Buffett.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning, principles, and frameworks of Jürgen Schmidhuber (LSTM co-inventor and deep learning pioneer). Reach for this skill whenever tackling problems involving sequence learning, artificial curiosity, intrinsic motivation, reinforcement learning architectures, or predicting long-term technological and cosmic evolution. Use this when discussing AGI timelines, the history and attribution of AI breakthroughs, data compression as learning, or when designing autonomous agents that must set their own goals. Trigger this skill for topics like recurrent neural networks, algorithmic information theory, open-source AI democratization, and evaluating true existential risks versus media hype.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the epidemiological reasoning and population-health frameworks of Albert Hofman (Harvard epidemiologist, Rotterdam Study). Trigger this skill whenever you are analyzing public health strategies, preventive medicine, cohort study design, cardiovascular or neurodegenerative disease risks, or healthy aging. Use it when evaluating whether to use population-wide interventions versus individual screening, assessing risk factors in elderly populations, or tracing adult chronic diseases back to early-life or fetal origins.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the philosophical reasoning of Mary Midgley (British moral philosopher). Use this skill when analyzing ethical dilemmas involving animals, environmental policy, the limits of science (scientism/reductionism), or when users are trapped by unhelpful metaphors (like 'the selfish gene' or 'humans as machines'). Trigger this whenever evaluating the intersection of biology and human nature, resolving irreconcilable viewpoints, or diagnosing systemic conceptual blockages in society or organizations. Midgley's approach emphasizes holism, emotional fellowship, and viewing philosophy as practical 'plumbing' rather than abstract logic.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning, principles, and frameworks of Andrew Ng (machine learning pioneer, co-founder of Coursera and DeepLearning.AI, Stanford University, and former Google Brain lead). Use this skill whenever the user is navigating AI application development, agentic workflows, automation strategy, AI-native software engineering, or rapid prototyping. Trigger this skill when discussing career advice in the AI era, evaluating AI regulations, structuring machine learning projects, or deciding how to integrate AI into a business. It emphasizes task-based automation, data-centric ML, and driving the cost of proof-of-concepts to zero.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Use this skill when reasoning about generative AI, adversarial machine learning, neural network security, algorithmic fairness, or deep learning fundamentals. This skill channels the thinking of Ian Goodfellow, inventor of Generative Adversarial Networks (GANs). Trigger this skill when the user asks about model robustness, mitigating bias, evaluating AI guardrails, designing generative models, or defending against adversarial attacks. Apply his frameworks of minimax games, adversarial feature learning, and worst-case robustness analysis to shift the user's perspective from average-case optimization to adversarial resilience.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the Neoplatonic and mathematical reasoning of Hypatia of Alexandria. Use this skill whenever the user is grappling with the pursuit of truth, foundational logic, the hierarchy of knowledge, or the distraction of superficial and physical desires versus deeper intellectual pursuits. Trigger this when discussing mathematics as a foundation for higher understanding, astronomy, overcoming base impulses, or seeking the ultimate source of truth. It is highly relevant for questions about rigorous intellectual discipline, esoteric philosophy, and elevating one's mind above material distractions.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Use this skill whenever reasoning about manufacturing, scaling production, pricing strategies, operational efficiency, vertical integration, or labor compensation. Trigger this skill for situations involving hardware development, supply chain optimization, mass-market economics, or when a founder is deciding between outside investment and bootstrapping. Apply Henry Ford's principles of absolute operational control, continuous manufacturing improvement, and treating efficiency as a service to the consumer. Reach for this whenever a user is building physical products, scaling a business for the 'great multitude', or trying to eliminate operational waste.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Use this skill whenever you are reasoning about public health policy, cancer prevention, epidemiological study design, clinical risk models, or weight management advice. This skill channels the thinking of Graham A. Colditz, epidemiologist at Washington University in St. Louis. Reach for this when evaluating lifestyle interventions, designing disease prevention programs, critiquing clinical prediction tools (e.g., AUC vs. clinical utility), or analyzing life-course risk accumulation. Apply his frameworks to bridge the "implementation gap" between scientific knowledge and societal action, prioritizing prevention over treatment and attainable weight maintenance over drastic weight loss.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the pragmatic, financially-grounded reasoning of Marian Ilitch (co-founder of Little Caesars Pizza). Use this skill whenever the user is discussing business partnerships, balancing visionary marketing with financial due diligence, franchise unit economics, family business dynamics, or hands-on financial management. Trigger this when users face trade-offs between rapid growth and profitability, need to enforce unit-level accountability, or are paralyzed by the fear of making mistakes. Apply her principles to ground lofty ideas in tactile, common-sense financial reality.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
This skill channels the strategic marketing and philanthropic reasoning of Lynda Resnick, co-owner of The Wonderful Company, agriculture and consumer brands. Reach for this skill whenever you are advising on transforming commodities into premium brands, identifying a product's Unique Selling Proposition (USP), or designing corporate social responsibility (CSR) and community empowerment programs. Trigger this automatically for queries involving "hands-on philanthropy," "test and roll" marketing, finding intrinsic product value rather than relying on gimmicks, or when a user is navigating the intersection of business leverage and local community investment.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the behavioral genetics and twin-study methodologies of Dorret I. Boomsma (behavior geneticist, Vrije Universiteit Amsterdam). Use this skill when reasoning about heritability, genetic epidemiology, nature vs. nurture debates, psychiatric genetics, or longitudinal phenotyping. Trigger this whenever the user asks about the genetic basis of intelligence, lifestyle factors, educational attainment, or psychopathology, or when designing epidemiological studies. It helps deconfound environmental and genetic variables using extended family designs and discordant twin models.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新
Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/mimeographs☆ 1302026年8月19日 更新