Signals in the Machine

Long before artificial intelligence became a product, it was a question: can thought be described, measured, and built? Signals in the Machine is a cinematic documentary series about the people, ideas, breakthroughs, disappointments, and recurring ambitions behind AI. Season one travels from mechanical calculators and symbolic logic through wartime computing, the Dartmouth workshop, AI winters, expert systems, machine learning, deep learning, transformers, and generative AI. The series avoids both hype and panic to ask a more durable question: what does the history of intelligent machines reveal about the humans building them?

Signals in the Machine is a history podcast hosted by Unknown Host, with 0 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Unknown Host hosts Signals in the Machine, a history show with 0 episodes published.

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  Episode #2

  The Wartime Mind

  Aug 17, 202621 minS1

  <p>World War II did not invent artificial intelligence, but it created the machines, institutions, and urgency that made it imaginable. At Bletchley Park, thousands of people and machines worked together to break encrypted communications. We trace Alan Turing’s role without the lone-genius mythology, examine the Bombe and Colossus, and follow Turing into his 1950 proposal for the imitation game. The war revealed that machines could perform immense chains of logical work. It also left a question no behavioural test can settle: when a machine sounds intelligent, what exactly have we learned?</p><p>Produced by Rogue Media Network. Narration wa...

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  Episode #3

  The Summer AI Was Named

  Aug 17, 202620 minS1

  <p>In 1956, a small summer workshop at Dartmouth gave artificial intelligence its name. John McCarthy, Marvin Minsky, Claude Shannon, Nathaniel Rochester, and their colleagues believed that the essential features of intelligence might be described precisely enough for a machine to simulate them. Early programs such as Logic Theorist made that confidence feel reasonable. But beneath the breakthroughs were tiny problem worlds, hand-built assumptions, and severe limits. This episode follows the birth of two rival dreams—intelligence as symbolic rules and intelligence as learned patterns—and asks why both remain alive today.</p><p>Produced by Rogue Media Network. Narration was crea...

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  Episode #4

  The First Winter

  Aug 17, 202621 minS1

  <p>The first AI boom met a problem more stubborn than chess: reality. Machine translation struggled with context and culture. Perceptrons ran into mathematical and computational limits. Robots that looked impressive inside carefully arranged laboratories proved brittle elsewhere. As public promises outran dependable results, funders lost patience and the field entered its first “AI winter.” Yet research never stopped. This episode separates the myth of AI’s death from the quieter truth—and finds an evergreen lesson the industry keeps relearning: a dazzling demonstration and a trustworthy system are not the same thing.</p><p>Produced by Rogue Media Network. Narratio...

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  Episode #5

  The Expert in a Box

  Aug 17, 202621 minS1

  <p>In the 1970s and 1980s, AI narrowed its ambition and became useful. Expert systems such as DENDRAL and MYCIN encoded specialist knowledge as chains of “if/then” rules, helping computers reason inside carefully defined domains. Businesses rushed to capture expertise and make it repeatable. Then the rule books grew, experts disagreed, conditions changed, and maintenance became overwhelming. We explore the commercial boom, the knowledge-engineering bottleneck, and the collapse that followed—along with the durable insight expert systems left behind: reliable AI depends on constraints, evaluation, and real domain knowledge.</p><p>Produced by Rogue Media Network. Narration was created with a...

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  Episode #6

  When Machines Began to Learn

  Aug 17, 202620 minS1

  <p>A handwritten number can take thousands of forms, yet people recognize it instantly. Teaching a computer to do the same helped change the direction of AI. This episode explains training data, parameters, error correction, and backpropagation without the equations, then follows neural networks through their revival in the 1980s and the data-rich world created by digitisation and the web. Deep Blue’s victory over Garry Kasparov became a cultural milestone, while biased datasets exposed a harder truth: machines learn patterns from human records, including our blind spots.</p><p>Produced by Rogue Media Network. Narration was created with an AI...

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