![]() Futures Industry Association Hall of Fame. Cotton, commodities trader with global holdings. Dunavant Jr., SOE : Founder, former CEO, Dunavant Enterprises. Started company as Cates Company in 1977. George Cates, SOE: Founder, former chairman, CEO, Mid-America Apartment Communities. Karen Blockman Carrier, SOE: Founder, Another Roadside Attraction Catering, Bar DKDC, The Beauty Shop, Mollie Fontaine Lounge. ![]() Founder, Belz Museum of Asian & Judaic Art. Master Entrepreneur, SOE, Junior Achievement Lifetime Achievement Award, DMC. Jack Belz, SOE: Chairman and CEO, Belz Enterprises. We also feature a Power Player in IMB’s Tip Sheet newsletter every Friday, and we hope you’ll subscribe to this roundup of area business news. Read more about the Society’s newest additions here.īe sure to hang on to this essential reference to Memphis industry leaders. Power metal rapidcomposer pro#The organization is honoring new inductees this year: banking veteran Frank Cianciola, and grocery pro Randy Stepherson. This year we collected more than 500 Power Players, including many members of the Society of Entrepreneurs, who are designated with the marker SOE. On the following pages you’ll find the movers, the shakers, the difference makers: These are the folks who make things happen in Memphis, from top executives to specialists in a wide range of areas that keep this city and its economy healthy. As for AI generated music, I think it will be a travesty to de-value or remove humans from the music/art making process entirely, it will always likely be something derivative of human work in essence anyway, but I don't think it will ever match the depth and soul of human-generated music to people who truly know and love music, some things just can't be emulated.Welcome to the 2022 edition of Inside Memphis Business’ Power Players. I never thought it would have been possible 20 years ago when I started music. I have been able to remove uncleared vocals from fully mixed tunes that I've made so they can be released as well. It still has a ways to go (as audio quality can be spotty and incomplete), but these online services can often separate more than just vocals now, they can cut individual instruments out of music, and even create pretty good instrumentals. It ended up being the last remix made of his music before his passing, and I sent it to his manager just before, so I'd like to believe he heard it. I used it to remix one of my favorite songs ever by Biz Markie just before he passed last year. One thing that's been pretty interesting is AI vocal splitting, which has revolutionized the art of remixing music that couldn't be fully remixed before. But again - this is probably far from "settled" legally. It was trained on the entire English Spotify catalogue so all that has been digested by the model - under Fair Use. So my understanding is that the training of Jukebox is similar to Copilot. > the data is all locked up behind an impossible quagmire of copyright I tried myself for 6 months, but the processing power required for this is candidly only available for the Google/OpenAIs of the world. Wavenet (from Google) I believe was the first one to do this. This now allows the "subtle" musicalities to be discovered by models without relying on transcription. They break down audio into "blocks" using Fast Fourier Transforms, then each block is "tokenized" and then fed into transformers, similar to GPT-3 or other newer text generation models. What Jukebox (and other models) did well was work with raw audio, rather than rely on MIDI or similar transcriptions. So MIDI songs were being generated quite "early" on, even with basic text generators (LSTM models), where the "alphabet" was replaced by MIDI symbols. But again, music copyright is a pretty complex contraption. The data is all locked up behind an impossible quagmire of copyright.īut if I were a sheet music publishing company, I would be seriously considering the future of music creation with AI given my broad access to notated music & metadata (is this an original score, or a grade 1 simplification?). To me, the former feels much less like AI than the latter. Power metal rapidcomposer code#For generative music, we're still largely stuck with encoding musical rules in code rather than feeding data to a transformer. So if you want to automatically create something that sounds like mozart, you're in luck!īut this isn't really satisfying to me. If we had midi transcriptions of 100k songs (abc notation could be fine too), we could probably get really interesting stuff, but most of what is available is lossy chord transcriptions and classical music (public domain). Even something as seemingly simple as chord progressions are very difficult to annotate properly without deep training. ![]() ![]() Has anyone solved the data problem? I have taken many stabs at this over the last 10 years, and the primary problem is that music is _extremely_ subtle. ![]()
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