Computational creativity refers to the utilization of computer algorithms and artificial intelligence techniques to generate original and imaginative outputs in creative domains like art, music, and literature. It involves replicating human-like creative processes, such as idea formation and pattern recognition, often in collaboration with human creators. The goal is to push the boundaries of automated innovation and explore novel avenues of artistic and inventive expression.
Dr. Wilder explores the history of music as data and the limitations of traditional notation when attempting to capture the nuances of performance. He then discusses current LLM approaches, related brain research, and explores proven music-centric approaches to produce useful and meaningful results. 🎸 🎹 🎺 #MusicAI #LanguageAI #MusicNotation #SoundScience
This interview explores the factors that determine the quality and longevity of musical ideas. Greg and his new AI friend discuss the subjective nature of musical judgment, objective measures, success factors, and the evolution of musical ideas, ultimately emphasizing the importance of studying enduring musical ideas to enhance AI-generated music quality. 🤖👂🎶🎧 #AskAnAI #MusicalIdeas
Dr. Greg Wilder dives into the distinction between LLMs trained on past examples and the human creation of inspired ideas, emphasizing various challenges ahead for current language models to generate truly creative and inspired content. He suggests that future creative AI will need to discover ways to identify and apply human-like inspiration to generate lasting art. #CreativeAI #ArtGeneration 🎨 🎶 💃
How is musical quality shaped by our brains and culture? Can we draw parallels between musical evolution and Darwinian natural selection? The discussion highlights the role of cultural evolution in music and identifies certain musical elements that consistently drive value. Perhaps AI music systems should incorporate these principles to enhance musical value. 🎶🎻🥁 #MusicEvolution #MusicAI
Teaching intelligent systems to understand sonic surprise is essential to useful AI behavior. Computer analysis of musical expectation codifies the emotional journeys we experience when listening to music. Understanding these emotional arcs with analysis algorithms is an important step in aligning technology and artistry for future innovation. 👂🎶🎧 #EmotionalAI #MusicalAlgorithms
Technology and creativity often clash in music applications. Composers shape emotional experiences through patterns, and while AI excels at analysis, it struggles with artistic insight. Researchers exploring music’s emotional impact are working to bridge this gap which could lead to improved AI-generated music that captures timeless patterns. 🎤🎧🎶🎸#MusicCreativity #AIComposition