Category: AI / Machine Learning
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The content explores the paradox of artificial intelligence’s progress, highlighting the limitations of current models that simulate language without understanding. It contrasts human cognition, which is emotional and adaptive, with machine intelligence that relies on sheer volume and predicts without intent. The future calls for a focus on structured, experience-driven systems that cultivate genuine understanding…
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We often treat words like “life,” “intelligence,” or “consciousness” as if they were mysterious substances. The same now happens with AGI. But these concepts are not sparks, they are emergent bundles of processes. Understanding them as architectures of interaction, rather than hidden essences, changes how we think about minds: human, animal, and artificial.
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Alle reden von AGI, doch kaum jemand weiß, was sich hinter dem Begriff verbirgt. Dieses Essay zeigt, warum „Allgemeine Künstliche Intelligenz“ kein Funke ist, sondern ein emergentes Zusammenspiel vieler Systeme. Von Sprache über Erfahrung bis Simulation: Erst ihr Zusammenwirken macht Intelligenz und Bewusstsein greifbar. AXIS ist ein Versuch, diese Blaupause sichtbar zu machen.
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The Transformer, introduced in 2017, redefined sequence modeling by using self-attention instead of recurrence. This architecture processes the full input simultaneously, enabling each token to interact freely. The model consists of an encoder and decoder, each building contextual representations. Variants like BERT and GPT emerged, focusing on understanding or generating text, showcasing its adaptability across…
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A seasoned software architect reflects on building an Agentic AI system and why LLM-powered agents often collapse in deterministic domains. From false delegation to fragile reasoning, this post explores where Agentic AI breaks down, where it adds value, and how to design systems that balance clarity, correctness, and language-based augmentation. No hype. Just patterns.