October 25, 2024
7 min read
Music production has come a long way since the days of plugging away at drum machines or meticulously cutting tape. Now, artificial intelligence is here, helping creators get those beats, melodies, and harmonies dialed in with half the hassle and double the creativity.
If you're tired of endless tweaks and are ready for AI to do some of the heavy lifting in your musical process, check out these five fantastic AI music production tools. These programs aren't just automating—they’re innovating!
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AIVA (Artificial Intelligence Virtual Artist) is your go-to AI for generating original music, specifically tailored for films, video games, and other multimedia. With a deep learning framework, AIVA specializes in classical and orchestral compositions. It’s not just generating simple tunes—it’s composing complex, layered pieces that rival professional composers. Whether you need an epic soundtrack or a gentle piano piece, AIVA’s got you covered. And yes, it’s copyright-free.
Free Version
Starting Price
✅
Free
Pros
Versatile genre selection
Professional-grade
Copyright-free music
Limited Free Plan
Better for instrumentals
Aiva AI FAQ
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Soundraw.io is an intuitive AI music generator known for its robust customization features. Unlike some AI tools that give you finished tracks, Soundraw lets you tweak everything—tempo, key, mood, and even individual instruments—giving you more creative control over your music. It’s perfect for content creators, game developers, and video editors who need background music that fits their projects like a glove.
Free Version
Starting Price
❌(Free Trial)
$19.99/month
Pros
High customization
User-friendly interface
Portrait enhancement
Cons
No free downloads
Subscription required for full functionality
Soundraw FAQ
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MuseNet, developed by OpenAI, is an AI that can create music in an impressive variety of genres. From Beethoven to The Beatles, MuseNet covers classical, pop, jazz, and more. Whether you're working on a project with a retro vibe or a futuristic score, MuseNet can whip up something that fits. The neural network can blend styles, creating mashups you wouldn't think possible.
Free Version
Starting Price
✅
Pros
Wide genre range
Free to use
Unique style blends
Cons
No real-time editing
Output can feel a bit generic
MuseNet FAQ
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Magenta Studio is part of Google’s Magenta project, which focuses on blending AI and art. This tool is less about generating mainstream hits and more about experimenting with sound and structure. If you're into avant-garde or looking to add a creative twist to your tracks, Magenta Studio’s AI tools for melody creation and audio interpolation will give you plenty of material to work with.
Free Version
Starting Price
✅
Free
Pros
Completely free
Flexible with MIDI editing
Great for experimental
Cons
Not user-friendly for beginners
Lacks genre diversity
Magenta FAQ
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The State Of AI Music Production
AI has significantly reshaped the music production landscape in 2024, with its integration becoming increasingly indispensable for both amateur and professional producers. One major trend is the growing use of AI-driven tools that enhance creativity while streamlining production processes. These tools, such as Orb Producer Suite 3, offer features like automatic melody and chord generation, allowing musicians to experiment with new patterns and styles effortlessly. Additionally, platforms like Soundraw and BandLab SongStarter help overcome creative blocks by providing instant music ideas and customized royalty-free tracks for content creators.
Another notable trend is the rise of AI-powered data analysis to influence production decisions. AI analyzes streaming data to predict emerging trends in music genres and styles, giving labels and artists insights into what’s next in the industry. Furthermore, AI’s ability to adapt music for specific moods or environments has sparked the popularity of functional music, such as focus or relaxation playlists, created by platforms like Endel.
Despite its benefits, AI in music production also presents certain challenges. A major concern revolves around the bias in AI-generated music. Since many AI systems are trained on datasets that favor popular genres like Western pop, marginalized genres often remain underrepresented, limiting creative diversity. This bias can inadvertently homogenize music production, as AI tools might not fully capture the nuances of more niche or cultural music styles.
Another challenge lies in the legal and ethical implications of AI-generated music. Questions surrounding ownership and copyright are becoming more pressing as AI takes a larger role in composition. Who owns the rights to a piece of music created by an AI platform, especially when it involves complex collaborations? These uncertainties could stifle broader adoption unless clear legal frameworks are developed.