I won't sugarcoat it: AI music has its fair share of problems. You might be curious or even a bit skeptical about how AI fits into the world of music. Let’s dive into the five major issues I see.

First off, time is a big challenge. Unlike visual art that can be created in a flash, music is a time-based art. It’s all about rhythm and flow, and AI often stumbles when trying to weave a story or emotion through a song.

Sure, AI can whip up a beat or melody, but can it tell a compelling story in three minutes? Not quite there yet.

And human musicians? They're not going anywhere. No matter how advanced AI gets, it can't replicate the depth and soul that real artists bring to their work. AI won't capture the heartache in a blues riff or the joy of a pop chorus. That’s all on you, the musician. AI can help experiment and save time, but it’s not the ultimate answer. Musicians, keep thriving – your skills are irreplaceable. AI's got nothing on your creative touch. 🎶👩‍🎤👨‍🎤

PROBLEM 1: AI Isn’t That Good At Songwriting

2024 Update: Things have improved! Tools like Suno and Udio can create songs without a lot of guidance.

Now, let’s talk songwriting. The truth is that AI-generated music often misses the mark. Sure, there’s some potential in genres like rap, but chart-topping hits? Not happening.

Suno.ai is a leader in this area. The tech is impressive, but it’s still a far cry from real hits. It can produce something if you provide it a genre and lyrics, but it lacks that human finesse.

And for lyrics, many folks turn to ChatGPT. It can churn out words, but when you stack those lyrics against actual hits, the difference is clear. They just don't have the same poetic depth and metaphorical flair. Handy for writing blogs like this – but not much more.

Want to see the contrast? AI's output? Generally lackluster. But mix in a human touch, and you've got a product worth selling. This gap mirrors the struggle with AI creating visuals - sure, it can start the process, but only humans can perfect it.

It’s disheartening when AI news outlets hype fully AI-generated music as the next big thing – only for it to sound terrible. Mumble rap can sound decent sometimes, but let's face it, that genre is messy at best.

Platforms like Suno may inspire ideas about how a song could sound, but if you're aiming for a quality track, you might be better off starting fresh in a DAW. Need help? Hit me up.

PROBLEM 2: The Ongoing Battle with Sample Quality

Next, let’s discuss sample quality in AI music. I’ve often used Stable Audio. It’s hit or miss. I typically use it for distinct parts like drums. But sometimes, those exported stems come with weird rattling sounds – definitely not ideal. Many new tracks use noise or lower bitrate for effect, so it’s not a deal-breaker every time.

Then there’s Jammable (formerly Voicify), or Kits, which can produce decent vocals, yet they still aren't studio quality. However, that might change soon. To be fair, many listeners couldn't even tell the difference...

Quality of input vocals matters a lot. With a half-hour of top-notch vocals, you might strike gold. But just three minutes from the ’60s? Well, let’s just say the quality might not hold up.

In short, AI has a long way to go to match the high standards we expect from professionals. For now, if you want top-tier quality, you need a human involved – at least in a supporting role. True artistry shines in collaboration between human creativity and AI's abilities.

PROBLEM 3: Unpredictability and Time Efficiency

Now, let’s tackle AI’s unpredictable side. You might think, “AI can write my melodies, right?” Not really. I’ve played around with tools like Magenta, and let me tell you, it’s not a quick fix. Setting it up, feeding MIDI files, and getting outputs? It’s a hassle. AI isn't the shortcut for music production you might think.

However, AI can be great for generating ideas. Think of it like Stable Audio – it can help you find melodies, chords, percussion, and the vibe. You can guide it with genres or styles too. But remember, AI’s based on randomness, which can either spark creativity or fall flat.

The “black box” problem is real: AI often doesn’t reveal how it works. It’s like saying, “Here’s your music, good luck.” Researchers are working to crack that code, but figuring out the million variables behind a song? Not an easy task.

PROBLEM 4: Misleading AI Claims

Let’s stroll into murky waters with AI claims. Take Soundraw.io. They tout their product as AI-based, but it often feels like it’s just pre-set layers stitched together. That’s not true AI. It’s well-crafted programming but not music-composing genius.

AI is the buzzword of the moment – think back to when “blockchain” was thrown around. Many products slap on the AI label for clout, regardless of whether they actually use real AI. So much is just pattern-based algorithms, not genuine machine learning.

Sure, companies like Soundraw may be using machine learning to enhance how their tracks fit together based on feedback. Maybe there is some AI in the mix.

But that doesn't mean all these “AI tools” are useless. We just need to look beyond the hype. Authentic AI in music is out there, but not every product claiming to be is the real deal.

PROBLEM 5: Legality and Unemployment (Weren’t Music Artists Already Unemployed?😅)

The Legal and Ethical Maze

The landscape of AI music is mired in legal and ethical issues, especially concerning AI cover songs and vocal cloning. Imagine mimicking an artist’s voice perfectly – should that even be allowed? Is it ethical without their consent?

Tech companies can scrape public work for AI training without facing many legal consequences – for now. But laws will need to catch up with technology eventually.

Even though laws are due for change, we all know it might take ages for any real action – like a decade or so.

AI may create new job opportunities, like producing high-quality AI cover songs, but it’s safe to say some jobs may disappear.

The Rise of AI Artists and the Changing Industry

Looking forward, the music industry is gearing up for a major transformation thanks to AI. Imagine companies producing automated music with an army of AI-assisted remixers and producers. Sounds sci-fi, right? But it’s moving closer to reality every day. This shift isn’t just in music – think about how Netflix is using AI for shows. Pretty wild!

We’re stepping into an era where AI personas might take over entertainment without audiences realizing it. The focus may shift from musical talent to who can engineer the best media algorithms.

This shift will redefine how we monetize music.

Conclusion & Philosophical Insights

AI in music isn’t just a passing trend; it’s changing the very essence of how we create and consume music. We’re looking at AI artists who are unknown to their fans and algorithms making entertainment decisions – it’s a new world.

Remember this: no matter how advanced AI becomes, it can’t recreate the depth of human experience. Those subtleties matter, and they make all the difference.