foundational.html

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    <title>Era Details: Foundational AI</title>
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            <span class="year">1950 – 1980</span>
            <h1>Foundational & Symbolic AI</h1>
            <p class="quote">"Intelligence is the formal manipulation of symbols via logical rules."</p>
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            <h2>Chronology of Breakthroughs</h2>
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                    <h4>1950: The Turing Test (Computing Machinery and Intelligence)</h4>
                    <p>Alan Turing proposed a benchmark for machine intelligence based on the ability to exhibit behavior indistinguishable from a human.</p>
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                    <h4>1956: The Dartmouth Workshop</h4>
                    <p>The birth of the term "Artificial Intelligence." John McCarthy, Marvin Minsky, and others set the goal of simulating every aspect of intelligence.</p>
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                    <h4>1958: The Perceptron Algorithm</h4>
                    <p>Frank Rosenblatt creates the first supervised neural network model. It was the ancestor of modern Deep Learning, though limited to single layers.</p>
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                    <h4>1960s: LISP & Symbolic Programming</h4>
                    <p>John McCarthy develops Lisp, the primary language for AI research for decades, focused on processing lists of symbols.</p>
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                    <h4>1970s: The Logic Theorist & GPS</h4>
                    <p>Programs designed by Newell and Simon to mimic human problem-solving by searching through "state spaces" to find solutions to theorems.</p>
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            <h2>Core Methodologies</h2>
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                <li><strong>Search Algorithms:</strong> Using trees and graphs to find paths to a goal (e.g., A* Search).</li>
                <li><strong>Heuristics:</strong> "Rules of thumb" that allowed computers to skip irrelevant data and solve problems faster.</li>
                <li><strong>Knowledge Representation:</strong> Creating formal languages to describe objects, properties, and relationships.</li>
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