Tag: artificial intelligence
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Infrastructure as Intelligence: Huang and Fink on AI’s Platform Shift, the Energy–Compute Stack, and the Political Economy of Broad Participation
Convened at the World Economic Forum in Davos, the conversation stages a highly legible problem-space: how a set of technical claims about artificial intelligence, computational architecture, and industrial capacity can be translated into a public account of economic development that remains intelligible to non-specialists while still functioning as a justification for an immense redirection of…
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Scaling the Candle: Engineering Optimism, Energy Constraint, and the Public Justification of Abundance in the Davos Musk–Fink Dialogue
The Davos conversation between Laurence D. Fink and Elon Musk is structured as a public exercise in justified optimism under institutional conditions that demand legibility, investability, and procedural civility. Its central problem-space concerns the possibility of presenting a single, integrated orientation toward “AI, robotics, energy, and space” as a coherent engineering project and, simultaneously, as…
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AI as a Truth-Procedure: Davos, Alex Karp, and the Exposure of Institutional Reality
The recorded exchange at the World Economic Forum Annual Meeting 2026 in Davos, framed as a “conversation” between Laurence D. Fink and Alex Karp, stages artificial intelligence as a problem of institutional judgment rather than a mere problem of computational capability. Across a compact sequence of prompts and answers, the event concentrates on how sovereign…
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Artificial Intelligence and Symbolic Computation | 9 Volumes
The Artificial Intelligence and Symbolic Computation series represents a look through the evolving landscape of computational intelligence and symbolic reasoning over the course of several decades. This collection of nine volumes encapsulates the proceedings of nine international conferences, each serving as a milestone in the convergence of artificial intelligence (AI) and symbolic mathematical computation. The…
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Explainable and Transparent AI and Multi-Agent Systems | 3 Volumes
The anthology Explainable and Transparent AI and Multi-Agent Systems is a monumental compilation that encapsulates the forefront of research and philosophical inquiry into the realms of explainable artificial intelligence (XAI) and multi-agent systems (MAS). Spanning three significant international workshops—EXTRAAMAS 2021, held virtually due to the global pandemic; EXTRAAMAS 2022, also conducted virtually; and EXTRAAMAS 2023…
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Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning
Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning by Uday Kamath and John Liu is a seminal work in the evolving landscape of artificial intelligence, particularly in the critical domain of explainable AI (XAI). As AI systems become increasingly integrated into the fabric of society, influencing decisions in healthcare, finance, justice, and beyond, the…
Simon Gros 