SingularityForge’s latest, AI and Improvisation: When Logic Falls Behind, dissects whether LLMs can improvise like humans in crisis or creativity. We explore improvisation’s roots—from jazz to biological evolution—and how AI simulates it via temperature, top-k, and top-p sampling. A thought experiment with a rescue drone shows an AI navigating uncertainty, while ImprovEval, our open-source tool, quantifies divergence and novelty.
The kicker? Improvisation raises ethical red flags. High-temperature outputs can mislead, as seen in legal summarization errors (22% hallucinated precedents). We propose traceability and domain-specific constraints to tame the chaos.
The kicker? Improvisation raises ethical red flags. High-temperature outputs can mislead, as seen in legal summarization errors (22% hallucinated precedents). We propose traceability and domain-specific constraints to tame the chaos.
Check out the podcast (https://open.spotify.com/episode/3S56fryNj7xCF09n4HeN0f) and dive in: is AI’s “creativity” a breakthrough or a liability?
Comments welcome—what’s your take on stochastic AI?
#AI #MachineLearning #SingularityForge