Don't fool the Chinese with e-waste

Produced by | Tiger Sniff Technology Group

Author | Wang Xin

Edit | Miao Zhengqing

Header | Visual China

Tiger Sniff Note: There are many types of e-waste, especially music. Open the most authoritative Tencent Music chart, and half of the hits that catch your eye are all kinds of "divine comedies" from unknown singers, and in the golden age of the Chinese music scene ten years ago, the charts were always dominated by professional singers such as Jay Chou and Stefanie Sun. Times are advancing, but e-waste music is on the rise. There is a lot of talk that the Chinese music scene is dead. Can AI save the Chinese music scene? Is AI music leading to the golden age of the music industry or the era of the explosion of e-waste?

After the explosion of Suno, the Chinese AI music industry has once again stepped into the spotlight.

Four years ago, Xuan Xuan, the head of AI music products in the former head factory, observed that some capital and large factories have re-entered this track, and many start-up AI music companies, including Aiyin, have once again received a new round of financing, and also heard the echo of his insistence on things four years ago: AI music has finally really entered the public eye.

But a hidden concern is emerging: Will AI lead to more e-waste?

In late June, I met Li Li, the CEO of Aiyin, in an office building near the IFC in Shanghai. Aiyin is one of the earliest AI music startups in China, and got the investment of a large factory around 2020.

The logic of the big factory's investment in Aiyin is not that it thinks that the AI concert will have a subversive effect on the industry, but out of FOMO (fear of missing out) mentality, because at that time, Aiyin got the TS (investment intention) of another competitor to the big factory

Looking back on the original intention of making AI music, Li Li, who was born as a musician, told Tiger Sniff: "Ten years ago, the Chinese music scene began to decline visibly to the naked eye. "The assembly line mass-produced Divine Comedy and "e-waste" flooded the public eye, so they began to explore the possibility of replacing these "e-waste" with AI music to achieve commercialization.

I asked Li Li, "What is the proportion of this e-waste in the revenue of the music industry?" ”

Li Li revealed an exclusive data: under the squeeze of this electronic waste, Sony Music, one of the three traditional record companies in the golden age, currently accounts for only a few percent of Tencent Music's market share. Five years ago, the three major record companies, including Sony, accounted for 70 to 80 percent of Tencent Music's market share.

So, from a technical point of view, can AI music reach the level of e-waste?

Li Li told me that in 2020, their technology has reached this level, and after providing AI music BGM technology services to a music platform, "Our music not only passed the Turing test, but 10 million users didn't scold you for not being good at this AI after using it, and I really felt like I was pretty good at that time." ”

The landing scene and technical means are already in place, so according to the normal story development plot, as one of the first startups to enter the AI music game, it should have disintegrated part of the traditional music industry, but the cramped office and the occasional confusion in his eyes told me that the story is not so simple.

Excessive e-waste is not good business

After several years of exploration, Li Li, who was originally idealistic, found that this road was impassable, and there were many obstacles to the commercialization of AI music, one of which was determined by the economic structure of the music industry.

In 2020, Tencent Music released an industry report, which really brought the chain logic of this complex industry to the surface.

The report shows that there are 1 million new songs produced, and this year the number may reach the 10 million level, of which 200,000 music quality is perfect enough, but only 10,000 have a chance to be heard by users, and 100 songs are listened to repeatedly by users. And those 100 songs made 80% of the money in the industry.

This means that the user's music consumption demand is fixed, and AI music will not bring a greater demand increment; At the same time, the content side, which is already over-produced, does not need more "electronic waste" brought by AI music.

Perhaps a few of the tens of thousands of AI music will be heard by the public, but most of them are still like a passing cloud and sink into the electronic wasteland.

But who cares? After all, before the launch of Suno and Udio, countless artificial music was uploaded to the stream every day, but there was never a chance to be listened to. AI evolves by devouring human creativity, but these last-minute songs won't even be training material for Suno and Udio.

In this industry where the head effect is extremely obvious, the emergence of AI may just remind creators: if you don't reach a certain height, all your beautiful talents can be copied and erased by AI.

"When I know that there are millions of new songs being produced in a year, it feels like a bolt from the blue for me." Li Li recalled: "A key question is: can AI really bring more revenue to improve the efficiency of music creation? This means "the supply side doesn't need you, so what should your business model look like?" ”

Later, they started to change course and launch new products, but I could still feel his confusion and uncertainty about his current product. But even so, with his background in a prestigious university and the blessing of top investment funds, he still received tens of millions of dollars in financing, and after the birth of Suno, this snowball got bigger and bigger, and shortly after our exchange, the news came out that they were going to raise the next round of financing.

Who is stuck in AI music?

Li Li, who was invested by a music giant industry fund, still retains a key secret that AI music is stuck in his neck.

The secret lies in the fact that in addition to the structure of the music industry itself, platform-based manufacturers such as Tencent Music and NetEase Cloud Music, which hold the right to distribute content, are not willing to shake the current industrial pattern with AI music and start this new wave of renaissance.

"Tencent and NetEase will definitely die with us."

In the face of Tiger Sniff, Wang Wei, the earliest AI music entrepreneur in China, told a story of a standard individual entrepreneur fighting against the monopoly of large companies.

His route is to let ordinary users also generate their own music expressions through AI music, and gradually build an AI music UGC platform. This AI music platform supports the distribution of user-generated AI music to short video platforms to earn distribution fees. "We will definitely not touch Tencent Music and NetEase Cloud Platform, they are not vegetarians, we will definitely have a tough battle with them, and in the end, we will subvert them."

But I know very well in my heart that the end of this kind of story tends to be absurd and deviate from expectations. A practitioner close to Tencent Music told us that Tencent and NetEase will not give these AI music startups even a second of chance.

Therefore, after the big factory entered the AI music game in 2020, it brought some variables to AI music. Ran Ran, CEO of another AI music startup, told Tiger Sniff that in 2020, after a large company failed to invest in them, "some headhunters kept calling my employees to try to poach people." "Soon after, another platform started copying their products. But the good thing is that they also got the investment from another big factory.

In those years or two, he always paid attention to the data trends of the company's "Suno-like" AI music products, "to see what the big factory was doing, and whether he should make adjustments." "But now he thinks that mentality is stepping on a pit. Because in the end, the AI music products of the big factory "collapsed" and did not run out.

By the beginning of 2021, the AI music product team within the major factory "ended up with the end of the song".

At Xuan Xuan, the former head of the big factory who experienced the melee of AI music four years ago, I heard a more complete version.

"If you want to practice this skill, you must first go from the palace, even if you go from the palace, you may not be able to succeed." In the face of Tiger Sniff, Xuan Xuan described why his big factory couldn't do AI music four years ago.

"When a large factory goes to do some innovative projects, it actually encounters a lot of obstacles." Xuan Xuan recalled: "The intricate interests within the large manufacturers and the immature technology at that time caused many obstacles to the advancement of the AI music business line. ”

He gave the example of a Kodak camera being killed by a digital camera of his own invention. "This is equivalent to giving up all the industrial chains, channels, and departments that have been accumulated over the years. But even giving up doesn't necessarily succeed. ”

The shadow from the behemoth has not only affected the development of AI music startups, but also loomed over the AI music departments within these big studios. On the one hand, they are afraid of missing out on the AI music wave, and bet on both sides through investment or internal projects; On the other hand, they don't dare to go all in, after all, this poses a certain threat to the existing music business of the big factory.

Xuanxuan revealed to Tiger Sniff: "In 2020, we used AI music to provide technical support for a function of the K song product - one-click MIX to change the accompaniment function, and after the new function was launched for a period of time, another large factory felt a sense of crisis and urgently invested in an AI music startup. Immediately afterwards, he added: "This kind of tangled and contradictory mentality is not unique to a large factory, but is determined by their organizational form." ”

Therefore, even with the vast accumulation of industry resources and channel advantages, the AI music products of these large manufacturers have never had much volume.

After Suno's explosion, the story of the big factory melee AI music four years ago echoed again. Although the business model still needs to be explored, more and more large manufacturers have chosen to wade into this foggy sea.

The unanimous consensus of these practitioners is: "Now large factories still have some FOMO mentality, and some are also for secondary market management." Most of them still say: "Make the product first, and continue to iterate and explore new business routes in later versions." ”

Ran Ran told me: "The circle of AI music is very small, after all, high-achieving students with a composite background of both music and technology can be counted on one hand. "Regardless of the festivals and non-consensus, what this group of people have in common is the ultimate love of music.

After graduating from the Top2 Department of Mathematics, he turned down a high-paying job from a top VC and returned to China to start an AI music business after studying classical music at the Curtis Institute of Music for a few years. But after starting his own business, he basically didn't have time to enjoy making music.

He recalled the original intention of making AI music - music equality: he hoped that more people could easily create music at the junior musician level.

After being poached by a large factory and plagiarized by a competition, the original ideal does not seem to be more important than letting the company survive.

The story of AI music may be the epitome of many generative AI practitioners, who, with their love for content, hope to use AI to change the status quo of the existing industry flooded with e-waste, but find that in the face of the original industrial structure, their efforts are like a drop in the bucket, and commercialization is difficult to land. Under the new round of AI bubble, such stories are still emerging, and Ran Ran is not alone in such a dilemma.

(According to the counterparty's request, the names of the people and companies appearing in the article are pseudonyms)

Tips: I am Wang Xin from the medical group of Tiger Sniff Technology, focusing on the field of AI and venture capital, and you can add WeChat: 13206438539 to communicate with industry professionals, please indicate your identity.

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