Musenet (OpenAI)
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Pricing model
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MuseNet, developed by OpenAI, is a sophisticated neural network capable of creating 4-minute musical pieces using 10 different instruments and blending styles ranging from country to Mozart to the Beatles. It operates with the same versatile unsupervised technology as GPT-2, a vast transformer model designed to forecast the next token in a sequence, applicable to both audio and text. The model learns from MIDI file data and can produce samples in a selected style by beginning with a prompt. It utilizes multiple embeddings, including positional, timing, and structural embeddings, to provide the model with additional context.
Similar neural networks:
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AI Jukebox, developed by enzostvs on Hugging Face Spaces, is a web-based tool for generating music from text descriptions. It allows users to create music by inputting prompts that define the genre, mood, and various musical elements, such as "80s pop track with bassy drums and synth." With the ability to choose the track's duration, style, and mood, AI Jukebox acts as a creative platform for crafting unique music pieces without requiring musical knowledge or instruments. This tool is especially beneficial for content creators, music lovers, or anyone interested in experimenting with music creation for entertainment, prototyping song ideas, or seeking inspiration for musical projects. Users might utilize it to quickly create background music for videos, games, or podcasts, explore different musical styles, or simply enjoy the music-making process through an intuitive AI interface.
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The WhatTheBeat tool enables users to understand the meanings behind their favorite songs by artists like Drake, Eminem, A.R. Rahman, Justin Bieber, Michael Jackson, and Taylor Swift, through the use of artificial intelligence.