In this engaging episode of Future of Music Podcast, hosts Ryan Withrow and Jonathan Boyd directly answer listener questions on trending music tech topics. Despite both suffering severe back pain, they soldier on to provide their trademark blend of insights, ideas, and humor around the questions.
Evaluating the Current State of VR Music Apps
The episode kicks off by discussing listener’s feedback on VR music apps. The commenter tried multiple options but couldn’t see much benefit compared to augmented reality music or multi-screen setups. Ryan and Jonathan explore why current VR music software feels gimmicky.
Most apps simply attempt adding VR on top of old music software paradigms. This “putting wheels on a horse” approach feels unnatural, like Wii music games. VR music will take off once developers build new experiences using VR capabilities as the foundation rather than bolting it onto non-VR software.
Ryan notes VR music is a learning curve. As virtual reality keeps evolving with more accessible and powerful hardware, the music experience will get closer to the seamless feeling of traditional software. Oculus Quest 3 and Apple Vision Pro may accelerate things. For now, patience and open-minded experimentation are key.
They compare it to early internet technology, which was clunky at first until infrastructure caught up. The same cycle will likely occur with VR music as headsets and software improve. Ryan tried 10 different VR music apps but only found 2 he truly enjoyed. This discovery process lets you find options aligning with your creative style.
Jonathan speculates VR music learning could overcome the limitations of traditional instruments. For example, those unable to play guitar could learn in virtual environments using natural motions. This contrasts with current apps mirroring real instruments, which feel unnatural. VR may spark more innovation applied to music once developers think beyond mimicking physical experiences.
Strategies for Monetizing AI Music Without Playing an Instrument
Next, the hosts tackle a question about earning money from AI music without traditional musical skills. Boyd suggests various ideas:
- Writing articles and monetizing the traffic through ads or products.
- Selling AI compositions on stock music marketplaces.
- Freelancing to create AI music for clients’ video and film projects.
- Creating a virtual artist brand around AI music uploaded online.
Ryan adds AI exponentially multiplies content creation by automating the recording, mixing, and mastering of songs. This capacity for speed enables maximizing views and virality potential.
Testing ideas using AI’s instant generation capabilities allows easy pivoting approaches until profitably finding an audience. Jonathan agrees to cover monetization thoroughly in a future dedicated episode.
Ryan notes major time savings using AI for creating video content and music. For example, he used to spend hours editing each video with original composed music. With AI, he can generate multiple music tracks and edit videos in a fraction of the previous time.
This efficiency frees up time for distributing content wider. AI turns the former content bottleneck into a high-speed pipeline. They both give the example of an AI music YouTube channel focused on concentration music. Generated quickly at scale, it could gain monetized viewers over time per viral video formulas.
Jonathan also highlights AI copywriting software like ChatGPT for automating written blog and social media content around music topics. Combined with AI music and video generation, businesses can scale output while testing ideas.
Demystifying AI-Generated Songs
Finally, the hosts respond to a comment doubting quality examples exist of full AI songs. Ryan explains the past year saw an explosion in viral AI music, especially using real artists’ voices. He recommends starting with “Heart on My Sleeve” by Drake AI and Kanye West AI covers of popular songs. Series like Chillhop Music already leverage AI composition. Withrow says searching “AI music” on YouTube reveals the options rapidly expanding.
While AI song quality varies, the sheer volume of experiments increases the odds of compelling material emerging. The era of AI music going mainstream has clearly arrived. Listeners should approach with an open mind. AI-generated music excels at mimicking specific artists versus creating wholly original compositions. So songs in the style of Kanye or Adele often convince listeners through vocal accuracy. Some see this as unethical. But overall exposure is breaking down stigma.
Jonathan notes communities on Reddit already share Prompt engineering knowledge for optimizing AI music. A new musical format is taking shape combining human experimentation and machine creativity. The future likely involves collaboration between AI tools and artists’ imagination and ingenuity.
Conclusion: A Dialogue With Listeners
Rather than a monologue, this episode facilitates genuine dialogue around engaging questions from the show’s community. Ryan and Jonathan demonstrate responding to listeners directly provides value on both sides. The candid back-and-forth on these forward-looking topics is educational for hosts and audiences alike.
If you want your own questions addressed in a future episode, make sure to follow the podcast online and comment on episodes. The vibrant Future of Music community awaits you!
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