There is a large number of singers, producers, and other music professionals among LALAL.AI users. They come from every walk of life, have unique experiences in the industry, and leverage the power of our service for different purposes. We want to shed light on some of the most remarkable personalities and introduce them to our audience.
For the first interview, we sat down with a co-founder and editor of the world’s largest Cuban music website, Kevin Moore. He is a prolific music writer – under his belt there are over 20 volumes of the “Beyond Salsa” series, “The Roots of Timba” multimedia book, “The Beatles By Ear” book, dozens of book-length articles, record analyses and interviews. Kevin is also the author of the popular 3-volume series “Tomás Cruz Conga Method” used as textbooks at various educational institutions.
What’s more, he’s been writing for the daily Cuban music blog La Última for a decade. Moore is truly a jack of all trades in the best possible sense – in addition to various writing pursuits he also produced and played on the record “Salsa Gitana” that reached semi-final level in the 1998 Grammy Award process. Read our conversation with this fascinating and ever-talented individual below.
🟡How Did You Get Into Music?
I played and arranged music in jazz bands in the 1970s and Latin bands in the 1980s through 2000s - during that period I worked for E-mu, Universal Audio and Avid (ProTools) as a music software tester.
In 2003 I started writing educational books – first about Cuban music, then about the Beatles and now about the whole range of rhythm section development from ragtime to hip-hop and everything in-between in both English-language pop and Spanish-language pop.
🟡How Does LALAL.AI Help Your Work?
LALAL.AI is hugely valuable to my current career as a music writer because everything I'm writing about depends on knowing precisely what each instrument plays and how each instrument's time feel sounds when you hear it alone.
So many music books rely on general statements and clichés about the music but to produce really useful research and insights, you have to be able to hear every detail of the individual instrumental and vocal part – not just the notes but the "swing", "playing behind or on top of the beat", etc. All of the clichés are based on real sounds that can only be fully understood by listening to the stems.
🟡Are There Any Artists You Draw Inspiration From?
The Beatles, James Brown, Joni Mitchell, Prince, Stevie Wonder, Holland Dozier Holland, Valerie Simpson, J Dilla, Kendrick Lamar, etc. but I'm more interested in zooming out to the relationships between genres in different periods and different geographical locations.
🟡What's the Best Thing You Get to Experience on the Job?
Listen to a given stem and have that "eureka!" moment where pieces of the puzzle fit together or I grasp the genius of a certain passage for the first time.
🟡Is There Any Downside to the Work?
Waiting for the next breakthrough that will give me a burst of acceleration. For example, the LALAL.AI update a few months back gave me a rush like that. When you implement the idea of having the AI analyze all the stems and recreate them based on what it's learned, I'm quite sure that will produce such a rush of insights.
The true "holy grail" I'm waiting for is when LALAL.AI or some other company is able to do with swing percentage what LiveBPM does with tempo – graphing the changes over the course of a track - more swing, less swing, et cetera. That will change everything in terms of really understand why the great music feels so good. So the downside is the waiting.
🟡What Was the First Set of Equipment You Ever Bought?
A reel-to-reel tape deck that enabled me to listen to music at twice the pitch/tempo or half the pitch/tempo.
🟡Tell Us About Your Experience Working with LALAL.AI. How Did You Find Out About the Service?
I was constantly monitoring YouTube for "isolated" and "stem" videos that I could download and study. Reading the comments and emailing the creators of these videos revealed some of the ways that they created them – using the MOGG files from Rock Band video games, using karaoke and EQ algorithms and so on.
Then I discovered stems that were extracted with the help of artificial intelligence. I also spent a lot of time talking to a musician/scientist who was using AI to analyze grooves in Cuban music. He was asking me about certain details I'd written about in my books.
This led to my first explorations of LALAL.AI and another site, Splitter.ai. Most of the stems weren't very useful for me but both services did a decent job with drums and vocals. After the LALAL.AI Phoenix network was released, I tried it and it was so good that I got excited and started a big project of compiling the drums and drumless stems for a wide range of music types that I'm studying and writing about.
🟡What Are the Main Advantages of LALAL.AI for You?
The current LALAL.AI version provides much better sound quality than other services I've tried. It's enough to give me a steady flow of new musical insights and it's particularly exciting that it seems to be currently going through a growth spurt with a lot of exciting new developments to look forward to.
The user interface is also much easier to work in comparison to other services. Having an efficient workflow saves me many hours when I set out to create a database of, for example, 230 The Beatles tracks with various types of splits. The ease of navigating back to the start point so that I can upload the next track, and I like the way LALAL.AI saves me time in naming each stem.
🟡What Are the Key Things You’ve Learned About Producing That Aspiring Musicians Could Take Advice From?
In terms of producing music, everything I've ever studied leads me to one major conclusion: creativity is almost always collaborative! For example, when a rapper works with a hip-hop beat producer or team, and the beat producer or producers themselves interact with the content of any samples they're using. Introducing random input – regardless of the source – jogs the creativity of each member of the creative process. Bringing this back to LALAL.AI, it's this ability to feel the groove of one musician and how it affects each of the others that produces the insights I'm looking for.