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This episode unpacks large event models—AI that can understand, represent, and forecast real-world event sequences over time, not just generate text. We explore how LEMs extract underlying rules with schema induction, marry neural nets with symbolic planners for safety, and use sparse attention to manage massive timelines. We discuss real-world uses in public safety and healthcare, the safety nets that keep predictions grounded in reality, and imagine how a personal LEM could optimize your day.
Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.
Sponsored by Embersilk LLC
By Mike BreaultThis episode unpacks large event models—AI that can understand, represent, and forecast real-world event sequences over time, not just generate text. We explore how LEMs extract underlying rules with schema induction, marry neural nets with symbolic planners for safety, and use sparse attention to manage massive timelines. We discuss real-world uses in public safety and healthcare, the safety nets that keep predictions grounded in reality, and imagine how a personal LEM could optimize your day.
Note: This podcast was AI-generated, and sometimes AI can make mistakes. Please double-check any critical information.
Sponsored by Embersilk LLC