Inteligência Artificial

Fender’s CEO seems to think your bandmates are just analog AI

Publicado porRedacao AIDaily
4 min de leitura
Autor na fonte original: Terrence O’Brien

Fender CEO Edward "Bud" Cole gave an interview to T3 in May celebrating the 75th anniversary of the Telecaster with comments on AI and music that initially flew under the radar. But it has started making the rounds recently, pouring more fuel on an already raging fire of bad PR following the company pissing off […]

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Bud Cole also compared learning cover songs to AI training data in a controversial interview.

Fender CEO Edward “Bud” Cole gave an interview to T3 in May celebrating the 75th anniversary of the Telecaster with comments on AI and music that initially flew under the radar. But it has started making the rounds recently , pouring more fuel on an already raging fire of bad PR following the company pissing off basically the entire guitar-playing community by sending cease-and-desist letters to builders, claiming copyright of the Stratocaster body shape.

Some influential guitar YouTubers have even said they’re done buying Fender gear in the wake of the controversy. And Cole’s resurfaced comments comparing cover songs and bandmates to a sort of “analog AI have only sunk the company’s standing further among the loudest of its fans online.

T3 editor-in-chief Mat Gallagher’s feature mostly paraphrases Cole’s statements, and Fender did not immediately respond to a request for comment or clarification. But here are the relevant bits from the interview:

Cole’s philosophy is that AI in music is nothing new. “I think AI has existed in music as long as there’s been recorded music,” he says. While the biggest barrier to playing guitar is the time it takes to learn the instrument, it’s the second barrier, writing songs, where he believes AI plays a part.

“I actually believe cover music has been sort of analog AI for a long time,” says Cole. Those that don’t yet have the skills to write their own songs can play the songs written by their favourite artists instead. “I listened a lot to REM, U2, The Smiths and The Cure, and at some point I got sick of just listening to them. I wanted to play it, so I learned to play guitar.”

Those taking their first steps into writing, according to Cole, can also lean on a second analogue form of AI: their band mates. You might just have a chorus or a riff to start with but then the drummer or bassist can add to it, and a song is born. AI can also play this role. “I actually think that we are in the brink of freeing up people to move beyond the same old covers and to really get into working like they do with their bands,” says Cole.

Cole is trying to draw a comparison between a human “training” on a handful of cover songs and an AI ingesting enormous datasets of copyrighted music. He appears to be suggesting that, by learning to play other people’s songs, internalizing those influences, and then synthesizing them into something new, you are essentially doing the same thing as an AI. This is a woefully misguided take that says to me that Cole either doesn’t understand AI or doesn’t respect artists.

For starters, scale matters. No person could possibly learn all of the songs used to train your average generative AI model, which, in the case of Suno , is suspected to be in the millions . Additionally, it dismisses the inherent humanity of the millions of tiny decisions, conscious or otherwise, that an artist makes during the songwriting process. Whether they’re driven by emotional response, reacting to a happy accident, or compensating for limitations, the artistic decisions made by a human are unique to them.

This is fundamentally different from a model spitting out something based on a prompt and a network of data points. As Steve Onotera, better known as Samurai Guitarist , points out, a player’s physicality, or the tiny errors that every human is prone to, prevent them from replicating someone else’s work perfectly. That kind of serendipity can’t be replicated by an LLM.

The same is true of bandmates. Humans who pull from their own unique sets of “training data,” life experiences, and physical skills or limitations are not the same as a chatbot. An AI doesn’t have taste or instincts in the way that your picky bassist who studied jazz composition in college does. If you told your drummer they were no different from an AI model, they’d rightfully be insulted.

Later in the interview, Cole says: “I believe that AI is actually going to help create a whole new world of guitar players that use it. To help connect with other musicians, to be more productive. And across the chasm into becoming a student of songwriting to a master of songwriting.”

Cole’s assertion that AI will somehow help people “across the chasm” to becoming master songwriters is also, frankly, ridiculous. Evidence is mounting that relying on AI tools is actually leading to deskilling . Using an AI to suggest rhymes or metaphors for pain isn’t the same as practicing songwriting and developing skills. The AI has never been left at the altar or sweated over the perfect pre-chorus transition. Repetition is the key. The adage is that you need to write 100 ( or 1,000 ) (or 10,000 ) bad songs before you write one good one. That’s how you grow beyond tired tropes and learn to recognize when you’ve stumbled into something good.

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Pontos-chave

  • A comparação de Cole entre a aprendizagem musical e a IA pode democratizar a criação musical, mas também gera controvérsias.
  • A insatisfação da comunidade de guitarristas com a Fender destaca a importância da autenticidade e da conexão emocional na indústria musical.
  • A interação dos músicos brasileiros com a tecnologia pode moldar o futuro da música no país, oferecendo novas oportunidades criativas.

Análise editorial

As declarações de Edward Cole, CEO da Fender, sobre a relação entre a música, a inteligência artificial (IA) e a prática de tocar instrumentos levantam questões significativas sobre a evolução da criatividade musical e o papel da tecnologia nesse processo. Ao comparar a aprendizagem de músicas de outros artistas com o treinamento de IA, Cole sugere que a imitação e a adaptação são partes fundamentais do desenvolvimento musical, algo que pode ser visto como uma forma de democratização da criação musical. No entanto, essa perspectiva pode ser controversa, especialmente em um momento em que muitos músicos se sentem ameaçados pela IA, temendo que a tecnologia possa substituir a criatividade humana.

No contexto brasileiro, onde a música é uma parte vital da cultura e da identidade nacional, essa discussão é particularmente relevante. O Brasil possui uma rica tradição musical, e a forma como os músicos locais interagem com a tecnologia pode moldar o futuro da indústria musical. A comparação de Cole pode ser vista como uma oportunidade para os músicos brasileiros explorarem novas formas de criatividade, utilizando a IA como uma ferramenta para expandir suas composições, em vez de vê-la como uma ameaça.

Entretanto, a resposta negativa da comunidade de guitarristas à Fender, especialmente após a polêmica sobre os direitos autorais, indica que a marca precisa reconsiderar sua abordagem. A insatisfação dos consumidores pode ter um impacto significativo nas vendas e na lealdade à marca, especialmente em um mercado onde a autenticidade e a conexão emocional são fundamentais. A Fender deve encontrar um equilíbrio entre inovação tecnológica e respeito às tradições musicais que seus clientes valorizam.

Por fim, a discussão sobre IA na música não deve ser vista apenas como uma questão de tecnologia, mas como um reflexo das mudanças culturais e sociais em curso. À medida que a IA se torna mais integrada ao processo criativo, será crucial observar como as comunidades musicais, tanto no Brasil quanto globalmente, se adaptam a essas mudanças e como isso afeta a produção e o consumo de música no futuro.

O que esta cobertura entrega

  • Atribuicao clara de fonte com link para a publicacao original.
  • Enquadramento editorial sobre relevancia, impacto e proximos desdobramentos.
  • Revisao de legibilidade, contexto e duplicacao antes da publicacao.

Fonte original:

The Verge AI

Sobre este artigo

Este artigo foi curado e publicado pelo AIDaily como parte da nossa cobertura editorial sobre desenvolvimentos em inteligência artificial. O conteúdo é baseado na fonte original citada abaixo, enriquecido com contexto e análise editorial. Ferramentas automatizadas podem auxiliar tradução e estruturação inicial, mas a decisão de publicar, a revisão factual e o enquadramento de contexto seguem responsabilidade editorial.

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