Eleven Music

Existing “reverse” music AI (listening → notes)

• Several commenters note tools already exist to transcribe audio to notation/MIDI or isolate instruments: AnthemScore, ScoreCloud, Melody Scanner, Spleeter, CREPE, Moises, Google’s AudioLM, Spotify’s BasicPitch.
• Some think these use “older” ML and don’t reach expert-musician quality; others report surprisingly good results (e.g., generating decent guitar tabs via ChatGPT).
• People want deeper “understanding” tools: extracting chords/tabs, interactive idea exploration, or isolating instruments for practice.

Perceived quality and limitations of Eleven Music & peers

• Many compare Eleven to Suno and Udio; consensus is that Eleven’s v1 sounds behind: timing/pacing issues, robotic vocals, artifacts, low apparent bitrate, narrow context window, buggy UI.
• Suno and Udio are seen as more musical, with better stereo, stems, and editing, though still generic and occasionally “off.”
• Specific failures include mis‑generating Argentine tango (defaulting to ballroom “tango”) and awkward blues/rock solos that feel random and unnatural.

Use cases: from muzak to prototyping

• Widely seen as ideal for low-stakes, background uses: intros for podcasts/YouTube, generic corporate or marketing music, game placeholders.
• Some musicians see value as a prototyping tool: quickly generating drones, grooves, or bass/drum ideas to refine in a DAW; or as an “infinite sample library.”
• Others want more collaborative, stem-level, iterative tools (e.g., “add drums to this demo”) rather than one-shot song generators.

Impact on musicians’ livelihoods

• Strong worry that every use case AI can serve removes another “entry-level” or middle‑tier income stream: library music, ads, TV/film cues, session work.
• Several argue this “eats the seedcorn”: fewer paid apprenticeships → fewer future professionals and innovators.
• Counterpoint: music was already heavily industrialized and generic; AI is an accelerant, not the root cause.

Art, originality, and “soul”

• Many describe AI output as lifeless, aggressively mediocre, “McMusic” optimized for average palatability, good for “muzak” but not boundary-pushing art.
• Some argue curation, prompting, and editing can themselves be art, analogous to photography or collage; others say that’s just selecting from the model’s whims, not expressing a genuine intent.
• Ongoing debate over whether art must be difficult to produce, must “challenge,” and whether distinguishing art from entertainment is meaningful.

Ethics, copyright, and business models

• Serious concern that models are trained on music without consent, then sold back into the same market, threatening the original creators’ income—even if legally defensible as “fair use.”
• Eleven claims collaboration with labels/publishers, but commenters find details unclear and remain skeptical.
• Subscription licensing (paying a platform indefinitely to use a generated track) is seen as exploitative; some argue users should own full rights to outputs or be able to self‑host open models.
• Frustration that major players keep weights closed, slowing community experimentation and open tooling.

Automation, capitalism, and cultural worries

• Several connect this to a broader pattern: automation under capitalism increasing drudgery and precarity rather than freeing people for creative work; comparisons to the Industrial Revolution and Luddites.
• Fear that cheap, infinite AI “slop” plus platform economics (e.g., Spotify) will further crowd out distinctive human work and deepen cultural malaise.
• A minority predict a counter‑movement: renewed demand for “organic” live music, weird and experimental human art that AI can’t easily imitate.

Musicians’ emotional responses

• Hobbyists and semi‑pros express real demoralization: after years of practice, being outclassed in seconds by a model feels worse than competing with other humans.
• Others reaffirm that the real reward is the process, community, and live performance—things AI can’t replace—and expect human-made art to become more valued, if smaller in market share.