Category: Synthetic Minds
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Prompting Architectures for Large Language Models: Evolving the Art of Reasoning
Modern prompting strategies reflect an evolving understanding of how large language models (LLMs) can be guided to think, reason, and solve problems more like humans. The shift from static question-answering to dynamic multi-step reasoning is more than a technical innovation — it represents a new layer of cognitive engineering. This article explores a variety of…
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Prompt Architecture in LLMs
Prompt architecture refers to the structured design of multi-step, modular interactions with large language models (LLMs), where each component or phase contributes to a broader reasoning process or task objective. It represents a shift from the traditional practice of prompt engineering—which focuses on crafting a single, effective input—to building systems of prompts that function together…
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A Look at Tree-of-Thought Prompting
How do you get an AI to think slowly? Not instinctively, but deliberately — like solving a logic puzzle instead of guessing an answer? This question touches on a fundamental difference in how decisions are made: quickly vs. carefully. Psychologist Daniel Kahneman called these two modes System 1 (fast, automatic) and System 2 (slow, effortful).…
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The Mind and Machine: An Introduction to Artificial Intelligence: Exploring the Intersection of Artificial Intelligence, Human Cognition, Psychology and Robotics
Enter Fullscreen Mode Summary While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested…
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Machine Learning with Python: A Comprehensive Guide to Algorithms, Tools, and Best Practices
Enter Fullscreen Mode Summary The purpose of this book is to guide you step by step through the entire process of working with various machine learning algorithms. First you will learn the basics of working with Python in order to acquire the basic knowledge needed to understand machine learning. In each chapter you will learn…
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Artificial Intelligence Basics: A Self-Teaching Introduction
Enter Fullscreen Mode Summary Designed as a self-teaching introduction to the fundamental concepts of artificial intelligence, the book begins with its history, the Turing test, and early applications. Later chapters cover the basics of searching, game playing, and knowledge representation. Expert systems and machine learning are covered in detail, followed by separate programming chapters on…
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Introduction to Artificial Intelligence
Enter Fullscreen Mode Summary This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully…
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AI – Limits and Prospects of Artificial Intelligence
Enter Fullscreen Mode Summary The emergence of artificial intelligence has triggered enthusiasm and promise of boundless opportunities as much as uncertainty about its limits. The contributions to this volume explore the limits of AI, describe the necessary conditions for its functionality, reveal its attendant technical and social problems, and present some existing and potential solutions.…
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The Ultimate Data and AI Guide: 150 FAQs About Artificial Intelligence, Machine Learning and Data
Enter Fullscreen Mode Summary Are you lost in the buzzword jungle around artificial intelligence, machine learning and big data? This book is here to help. The Ultimate Data and AI Guide provides you with a complete overview and solid understanding of the most important concepts around data, machine learning and AI. It is the result…
