
Exploration de l'IA comme nouvel outil créatif pour les musiciens, révolutionnant le processus de composition et ouvrant de nouvelles possibilités artistiques. Benoit Carré partage son expérience pionnière avec l'album "Hello World".

Explore Markov chains for generative music AI, covering intuition, formalization, music modeling, pros and cons, and practical applications in melody, rhythm, and dynamics generation.

Explore algorithmic composition in live performances, blending computer-generated music with human creativity. Learn techniques for interactive generative algorithms and data representation of musicians' performances.

Implement a Python-based cellular automaton for generating unique drum patterns, exploring rules for syncopation, accenting, and mutation in algorithmic music composition.

Implement a Markov chain in Python to generate melodies, exploring the MarkovChainMelodyGenerator class, training process, and generation methods for AI-driven music creation.

Implement a genetic algorithm in Python to automatically generate melody harmonizations, exploring concepts like population initialization, parent selection, crossover, mutation, and fitness evaluation.

Explore generative grammars and Lindenmayer Systems for music creation. Learn to design effective algorithms, expand musical grammars, and apply key guidelines for AI-driven composition.

Explore algorithmic composition and music theory, learning to create unique musical pieces using code, frameworks, and data-driven techniques.

Explore generative music AI, its definition, contributing disciplines, and current challenges. Learn about creative vs. intelligent tasks and the multifaceted nature of this emerging field.

Explore parallels between code and classical music, uncovering shared attributes and compositional methodologies. Learn to translate musical principles into algorithms using Sonic Pi for innovative melody-making.

Explore innovative technologies for music creation and production, blending engineering principles with artistic expression.

Explore how AI transforms music composition, making it accessible to everyone. Learn about innovative AI-driven musical creations and their potential to augment creativity and productivity.

Explore Kolmogorov complexity in music, algorithmic composition, and program transformations. Discover implications for creation, copyright, and performance through demonstrations and examples.

Entdecken Sie SuperCollider: Ein freies Werkzeug für Audiosynthese und algorithmische Komposition. Lernen Sie die Grundlagen und erleben Sie eine Live-Demo zum Live-Coding für Sound und Musik.

Exploring C++20's safer alternative to the erase-remove idiom for element removal in collections, offering improved efficiency and eliminating common pitfalls in STL usage.

Master generative classical music techniques in Ableton Live using MIDI effects and grand piano sounds to create automated, evolving compositions.

Explore the evolution of computer-generated music, from early experiments to modern algorithmic compositions, highlighting key innovations and cultural impacts along the way.

Journey through computer music history: pioneers, video game soundtracks, algorithmic compositions, and its cultural impact. Explore vintage tech and code behind iconic sounds.

“AI 不会让所有内容变得千篇一律,而是会拉开通用与稀缺内容的差距。” 在独立探索 AI 创作的路上,赵汗青始终在揣摩:AI 能否创造出真正打动人心的内容? 三年来,他和团队经历了从跨时空对话实验,到 AI 短片,再到虚拟歌手 Yuri 出圈的全过程。Yuri 的作品在全球收获千万次播放和真实反馈,也让他从怀疑、矛盾,到慢慢相信这种创作模式。那就是,当 AI 的工业水准跨越临界点,它真的能带来全新的情感体验。 在他看来,AI 的加入将重新定义创作的本质。而这场变革势必点燃全新的可能性,开启属于创作者的黄金年代。 “AI will not make all content identic