Danny argudin (13 Ergebnisse)
Sprache: Englisch
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Sprache: Englisch
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
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Sprache: Englisch
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Sprache: Englisch
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Sprache: Englisch
Verlag: Independently published, 2026
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Sprache: Englisch
Verlag: Independently Published Mai 2026, 2026
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Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - What does it mean to call something artificial When you sit down with an AI system and produce something-a decision, a document, a design, a strategy-after guiding its output, applying your judgment, redirecting when it goes wrong, and taking responsibility for what comes out the other end: w…hat, exactly, is artificial about that That is the question at the center of this book.The label 'artificial intelligence' may be the most consequential naming decision in the history of technology. It shapes how we regulate AI, how we govern it, how we use it, and most importantly, how we understand what we are doing when we work with it. And it may be getting the most important thing wrong.Danny Argudin argues that the word 'artificial' points at the wrong part of the system. Language models are not artificial thinkers. They are compressed patterns drawn from the full corpus of human thought-encoded mathematics, not invented sentience. What they produce when guided by a skilled human collaborator is not an artificial substitute for intelligence. It is intelligence extended.At the heart of the book is a distinction that changes everything: resident vs. non-resident intelligence.The resident intelligence is you. You have stakes. You will face consequences. You can be held accountable. You bring judgment that costs something when it is wrong.The non-resident intelligence is the AI. It has no skin in the game. It cannot be hurt by a bad decision. It processes without consequence.This is not a limitation to overcome. It is the design. And once you see the distinction clearly, the question answers itself.A composer who uses an orchestra is not producing artificial music. A designer who uses tools is not producing artificial design. A thinker who uses an AI is not producing artificial thought.The orchestra plays. The tools shape. The AI processes. And the human-present, accountable, directing, deciding-is the intelligence that makes all of it mean something.What You'll Find in This Book- Where the term 'artificial intelligence' came from-and what it was never meant to describe- What large language models actually are at a level that changes how you use them- Why the human-as-operator model is the wrong frame for AI collaboration- The resident vs. non-resident distinction and why it matters for accountability, governance, and daily practice- A new vocabulary for human-AI partnership: cognitive extension, not automation- What the future looks like when we get the framing rightWhat's So Artificial About AI is not a technical guide and not a hype manifesto. It is a reframing-careful, argued, grounded in the actual experience of working with these systems every day. By the end, the word 'artificial' will look different to you. And so will the partnership you're building.
Sprache: Englisch
Verlag: Independently Published Mai 2026, 2026
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Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - Your logs read clean. Your traces show successful execution. Every agent ran. Every call returned. The outputs are still wrong.This is the most common and least diagnosable class of failure in agentic AI systems: emergent, interaction-dependent, history-driven failures that do not show up in…any instrument designed for deterministic software. The pipeline is working. The chemistry is wrong.The Chemistry of Agentic Systems applies five chemical principles to multi-agent AI development, giving practitioners a diagnostic vocabulary for the class of failures that standard debugging cannot address.The five principles: Limiting Reagent: Every pipeline has a constraining resource. Adding more AI capacity cannot improve throughput beyond what that resource allows. Finding it - and it is rarely where the slowdown appears - is the first diagnostic step.Retrosynthesis: Most architecture failures are discovered three weeks into building. Planning backwards from the required final output, rather than forward from available tools, makes hidden gaps visible before they become reconstruction projects.Kinetic and Thermodynamic Control: The same pipeline, at different points in its life, requires different optimization modes. Applying sprint speed to architectural decisions produces fragile structure. Applying architectural caution to sprint deliverables produces missed windows. Knowing which mode is correct - and when the switch must happen - is a diagnostic skill.Assay and Purification: Threshold checks are proxies for quality measurement, not quality measurement itself. A pipeline that passes outputs forward without assaying their identity, concentration, contamination, stability, and traceability is a pipeline that propagates plausible garbage downstream. The five-dimension Purity Checklist makes assay practical.Autocatalysis: Agentic systems that capture and reuse their own outputs can improve their own performance over time. They can also degrade their own performance over time, when the feedback loop runs on contaminated products. Understanding which direction the loop is running - and why - determines whether the system is a compounding asset or a compounding liability.The book includes the Chemistry Diagnostic Sequence for reading failing systems, the Conflict Resolution Matrix for when the five principles point in different directions, the Repair Classification Guide for distinguishing chemistry-level repairs from patches that compound, and the Portfolio Chemistry Map for practitioners maintaining multiple systems simultaneously.Written for engineers, technical leads, and AI operations practitioners who already have systems running and need vocabulary precise enough to name what is going wrong, explain it to colleagues, and choose the intervention that addresses the cause rather than the symptom.
Sprache: Englisch
Verlag: Independently Published Mai 2026, 2026
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - What if the best model for understanding AI is already inside your head The brain does not think in straight lines. It fires in parallel, prunes what it does not use, and rewires itself based on what it practices. Multi-agent AI systems work the same way - and once you see it, you cannot unse…e it.In The Synaptic Theory of Agentic Systems, Danny Argudin maps ten neuroscience principles onto the mechanics of running agentic workflows: working memory, Hebbian learning, synaptic pruning, predictive coding, myelination, and more. Each chapter takes a mechanism the brain already uses and shows exactly how it appears - and fails - in a live AI operating system.This is not a theoretical book. It was written inside a real agentic OS, with real agents contributing to the chapters, real failures informing the lessons, and real parallels discovered through operation rather than imagination.You will walk away with: - A neuroscience vocabulary that makes agentic system behavior legible- Practical models for managing context windows, agent specialization, and memory degradation- A new way of thinking about coherence, drift, and recovery in multi-session AI programs- The specific parallel between myelinated neural pathways and optimized agent routingWhether you run one AI assistant or a galaxy of specialized agents, the synaptic model will change how you design, observe, and tune your systems.Part of the Danny Argudin non-fiction library on agentic AI systems.
