YUNGRØC

05/07/2026

OLODO UPRISING.

IYKYK

01/07/2026

30/06/2026

Need your mix to sound finished, not just loud?
I handle mixing, mastering, and beats. Years of studio experience, work done remotely, fast turnaround.
If your track sounds muddy, weak, or unfinished, that's what I fix. Send me the stems and I'll show you what's possible.
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27/06/2026

No comments Oluremmy

25/06/2026

🎉 Facebook recognized me as a consistent post creator this week!

22/06/2026

A lot of musicians are using AI music tools without realizing the legal battle happening behind the scenes.

One of the largest music datasets linked to AI training is LAION-DISCO-12M, a collection containing over 12 million YouTube music links and metadata. LAION, a German nonprofit known for building open AI research datasets, says the dataset contains links and metadata only, not the actual audio files themselves.

However, during ongoing copyright lawsuits involving Suno, record labels used audio fingerprinting technology on training data and claimed they found millions of copyrighted recordings belonging to Sony and Universal Music Group. Court filings state that more than 61,000 identified recordings may be added to the lawsuit, with the labels describing them as only a small fraction of the total matches discovered.

The artists involved aren’t just global superstars. Reports suggest the datasets contain music from artists such as Taylor Swift, Billie Eilish, Nirvana, and The Beatles, alongside thousands of independent musicians.

The major question now is whether training AI models on copyrighted music without permission is copyright infringement, or whether it qualifies as “transformative use” under fair use law. A key hearing in the Sony vs. Suno case is scheduled for July 2026, and the outcome could influence how AI music companies operate for years to come.

No matter where you stand on AI, one thing is clear:

The music used to train these systems came from somewhere.

As producers, engineers, songwriters, and artists, we should understand how these tools are built, what rights creators have, and what precedents are being set for the future of music.

Your music may be helping train the next generation of AI. Make sure you know what’s happening with it.

YUNGRØC

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20/06/2026

Most new artists are making a costly mistake.

They're using AI to create music but forgetting that fans connect with people, not prompts.

Here are 10 reasons a new artist should never rely on AI music to build an audience:

1. People follow stories, not software. Fans want to know who you are, what you've been through, and why you create.

2. AI can generate songs but it cannot live your experiences. Your struggles, wins, heartbreaks and dreams are what make music relatable.

3. If everyone uses the same tools, everyone starts sounding the same. Originality becomes rare.

4. Audiences eventually figure out what's real and what isn't. Trust is hard to earn and easy to lose.

5. Great artists develop skills. AI dependency kills growth in songwriting, arranging, production and performance.

6. A prompt cannot replace personality. Personality is what turns listeners into loyal supporters.

7. Live performance still matters. AI cannot stand on stage and create a genuine connection with a crowd.

8. Trends come and go. Real talent survives market shifts.

9. The music industry rewards creators who consistently bring value, not just generate content.

10. When your audience loves your music, you should know you earned it through creativity, effort and authenticity.

AI is a tool.

It should never become your identity.

The artists who will last are the ones using technology to enhance their creativity, not replace it.

What's the point of a million streams if nobody knows what you actually bring to the table?

YUNGRØC™

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17/06/2026

Whats up Dear Artist.