How AI is changing the face of music

Music is one of the oldest and most universal forms of human expression, transcending cultures, languages, and time. Music can evoke emotions, convey messages, and inspire creativity. But music is also a product of human intelligence, skill, and creativity. How does artificial intelligence (AI) fit into this picture?

One of the domains that has been profoundly influenced by AI is music. AI can help musicians and music lovers in various ways, such as:

• Composition: AI can help musicians to create original and diverse music by generating melodies, harmonies, rhythms, lyrics, and styles. For example, OpenAI’s Jukebox is a neural network that can produce music in any genre and style, using lyrics and artists as inputs. Jukebox can also remix existing songs or create mashups of different songs.
• Performance: AI can help musicians to improve their skills and techniques by providing feedback, guidance, and training. For example, Yousician is an app that can teach users how to play various instruments, such as guitar, piano, ukulele, and bass. Yousician can also monitor the user’s progress and adjust the difficulty level accordingly.
• Production: AI can help musicians to enhance the quality and efficiency of their music production by providing tools for editing, mixing, mastering, and distribution. For example, LANDR is an online platform that can automatically master any audio track using AI algorithms. LANDR can also help users to distribute their music to various streaming platforms and online stores.
• Discovery: AI can help music lovers to discover new and relevant music by providing recommendations, playlists, and radio stations. For example, Spotify is a popular music streaming service that uses AI to analyze the user’s listening habits and preferences and provide personalized suggestions. Spotify also uses AI to create dynamic playlists based on the user’s mood, activity, or context.

AI can also create new forms of musical expression and interaction that challenge the conventional boundaries of music. For example:

• Interactive music: Interactive music is music that responds to the user’s input or environment in real time. Interactive music can create immersive and engaging experiences for the user. For example, Incredibox is a web app that allows users to create their own beatbox music by dragging and dropping different sounds and effects onto animated characters. Incredibox can also generate random combinations of sounds based on the user’s choices.
• Generative music: Generative music is music that is created by a system that follows a set of rules or algorithms. Generative music can produce infinite variations of music that are never repeated or predictable. For example, Endel is an app that creates personalized soundscapes based on the user’s location, weather, time of day, and biometric data. Endel can also sync with the user’s heartbeat and circadian rhythm to optimize their relaxation or focus.
• Collaborative music: Collaborative music is music that is created by multiple agents or participants who interact with each other. Collaborative music can foster social connection and creativity among the participants. For example, Google’s NSynth Super is a hardware device that allows users to create new sounds by blending different sounds from a large database of musical instruments. NSynth Super can also be connected with other devices or users to create collaborative musical performances.

AI is undoubtedly a powerful and innovative tool for music. It can enable new levels of creativity, diversity, and quality for both musicians and music lovers. However, it also poses some challenges and risks for the music industry. One of the main concerns is the ethical and social impact of AI on the rights,