Fender’s CEO seems to think your bandmates are just analog AI
Fender’s CEO seems to think your bandmates are just analog AI
Fender 首席执行官似乎认为你的乐队成员只是“模拟 AI”
Bud Cole also compared learning cover songs to AI training data in a controversial interview. 在一场充满争议的采访中，Bud Cole 还将学习翻唱歌曲比作 AI 训练数据。
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.
Fender 首席执行官 Edward “Bud” Cole 在五月份接受 T3 采访时，在庆祝 Telecaster 吉他诞生 75 周年之际，发表了一些关于 AI 和音乐的言论，起初并未引起太多关注。但最近这些言论开始流传，这无疑是火上浇油。此前，该公司因向吉他制作者发送停止侵权信（cease-and-desist letters）并声称拥有 Stratocaster 琴身形状的版权，已经激怒了整个吉他手群体，导致其公关形象跌入谷底。
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.
一些有影响力的吉他类 YouTuber 甚至表示，受此争议影响，他们将不再购买 Fender 的产品。而 Cole 重新被翻出的言论——将翻唱歌曲和乐队成员比作一种“模拟 AI”——只会让该公司在网上最活跃的粉丝群体中的声誉进一步受损。
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:
T3 主编 Mat Gallagher 的专题报道主要转述了 Cole 的观点，Fender 并未立即回应置评或澄清请求。以下是采访中的相关片段：
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.
Cole 的哲学是，音乐中的 AI 并非新鲜事。“我认为只要有录制音乐存在，AI 就一直存在于音乐中，”他说。虽然弹奏吉他最大的障碍是学习乐器所需的时间，但他认为 AI 在第二个障碍——歌曲创作——中发挥了作用。
“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.”
“我实际上认为，翻唱音乐长期以来一直是一种‘模拟 AI’，”Cole 说。那些还没有能力创作自己歌曲的人，可以转而演奏他们最喜欢的艺术家创作的歌曲。“我以前经常听 REM、U2、The Smiths 和 The Cure 的歌，后来我厌倦了只是听它们。我想亲自演奏，所以我学会了弹吉他。”
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 认为，那些刚开始尝试创作的人，还可以依靠第二种模拟形式的 AI：他们的乐队成员。你可能只有一个副歌或一段即兴重复段（riff），但鼓手或贝斯手可以为其增色，一首歌就诞生了。AI 也可以扮演这个角色。“我实际上认为，我们正处于一个转折点，人们将不再局限于翻唱老歌，而是能像与乐队合作那样真正投入到创作中去，”Cole 说。
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.
Cole 试图将人类通过学习少量翻唱歌曲进行“训练”与 AI 摄入海量受版权保护的音乐数据集进行对比。他似乎在暗示，通过学习演奏他人的歌曲、内化这些影响，然后将其合成为新作品，本质上与 AI 所做的事情是一样的。这是一种极其错误的观点，在我看来，这说明 Cole 要么是不了解 AI，要么就是不尊重艺术家。
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.
首先，规模很重要。没有人能够学会训练普通生成式 AI 模型所需的所有歌曲，以 Suno 为例，其训练数据据信高达数百万首。此外，这种观点忽视了艺术家在创作过程中所做出的数百万个微小决定（无论是有意识还是无意识的）所蕴含的人性。无论是出于情感反应、对意外惊喜的捕捉，还是对自身局限性的弥补，人类所做出的艺术决策都是独一无二的。
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.
这与模型根据提示词和数据点网络吐出内容有着本质的区别。正如以“Samurai Guitarist”闻名的 Steve Onotera 所指出的，演奏者的身体条件，或者每个人都容易犯的微小错误，使得他们无法完美地复制他人的作品。那种偶然性是大型语言模型（LLM）无法复制的。
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.
乐队成员也是如此。人类从自己独特的“训练数据”、生活经历以及身体技能或局限中汲取灵感，这与聊天机器人完全不同。AI 不具备你那位在大学学习过爵士乐作曲、对音乐挑剔的贝斯手所拥有的那种品味或直觉。如果你告诉你的鼓手他们和 AI 模型没什么区别，他们理所当然会感到被冒犯。
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.”
在采访的后半部分，Cole 说：“我相信 AI 实际上将有助于创造一个全新的吉他手世界。它能帮助人们与其他音乐人建立联系，提高生产力。并跨越鸿沟，从歌曲创作的学生成长为歌曲创作的大师。”
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.
坦率地说，Cole 声称 AI 将以某种方式帮助人们“跨越鸿沟”成为歌曲创作大师，这简直是荒谬的。越来越多的证据表明，依赖 AI 工具实际上正在导致技能退化。使用 AI 来建议押韵或痛苦的隐喻，与练习歌曲创作和培养技能完全不是一回事。AI 从未经历过被抛弃的痛苦，也从未为一段完美的副歌过渡而绞尽脑汁。重复才是关键。俗话说，你需要写出 100 首（或 1,000 首，或 10,000 首）烂歌，才能写出一首好歌。这就是你如何超越陈词滥调，并学会识别何时创作出了真正优秀作品的方法。