The Terrifying Recommendation Algorithm

"He's gone crazy, this Lin Feng is utterly insane."

"I'm so disappointed. A measly algorithm is worth 20% of Bilibili's shares? More valuable than the plan that turned Bilibili profitable?"

"Exactly, it's just a 10-year license for an algorithm, and they claim it's worth 20% of Bilibili's shares. It's laughable."

"Lin Feng is practically stomping on our intelligence with his feet." ...

Many discordant comments appeared in the live stream. Through these comments, Lin Feng knew they were from jealous individuals or Bilibili content creators.

And these comments did have an effect. Over 2.5 million netizens on Bilibili couldn't help but show doubt after seeing the barrage of comments.

"It seems everyone doesn't understand the significance of a recommendation algorithm? In your opinion, what's most important for business success?"

In response to Lin Feng's sudden question, a flood of comments surged.

These comments primarily fell into categories like 'Core technology is most important,' 'Maintaining good relationships with superiors is most important,' 'Marketing genius is most important,' 'Luck is most important,' 'Service is most important,' 'A complete development plan is most important,' and so on.

Facing so many opinions, Lin Feng shook his head and then said with a smile:

"Among the answers you've given, each one is a factor influencing business success.

But in my view, the most crucial element for business success is the ability to sell tangible and intangible goods to consumers. Otherwise, it's all in vain.

Unless you don't want to make money and just want to play around or gain a reputation, the ultimate goal is always to sell tangible and intangible goods to consumers.

Other elements like core technology, development plans, and marketing talent are merely means to achieve that ultimate goal. It is within this context that my recommendation algorithm arises.

Its most terrifying aspect lies in its ability to analyze user data such as personality, preferences, and behavioral patterns through big data.

It can directly push news, novels, videos, movies, TV shows, food, travel, and merchandise – any tangible or intangible product information that the user is interested in.

Theoretically, once this recommendation algorithm is completed, it will influence the entire global commercial landscape and change everyone.

Because from then on, mobile and computer users worldwide will find that the news, novels, videos, movies, TV shows, food, travel, and merchandise they see every day are all things they are interested in.

And now I am giving Bilibili a 10-year usage license for such an algorithm. This will undoubtedly bring Bilibili immense competitive potential.

Because once Bilibili uses the recommendation algorithm I developed, users will find that the videos or live streams promoted on Bilibili are always what they are interested in.

Naturally, people will enjoy browsing Bilibili more. With increased user engagement and retention on Bilibili, it will naturally attract more UP Masters to upload videos there.

With more and richer videos, combined with the precise recommendations of the algorithm, users will naturally be unable to stop once they open Bilibili.

Through this mutual interaction, Bilibili will grow stronger over time, while other websites without a recommendation algorithm will become weaker. This is the importance of a recommendation algorithm."

Hearing Lin Feng's words, the over 2.5 million netizens finally understood what he meant and the significance of the recommendation algorithm.

If the recommendation algorithm developed by Lin Feng could truly achieve what he claimed, then Bilibili might indeed become stronger and stronger.

No wonder Lin Feng said the profit development plan was worth 10% of the shares, and the 10-year usage license for the recommendation algorithm was worth 20%.

This was because the profit development plan only addressed its own operational issues, whereas the recommendation algorithm could give Bilibili powerful competitiveness and a stronger development momentum, allowing it to defeat competitors.

"Amazing, I can already foresee the terrifying implications of such an algorithm's creation."

"Indeed, everything you see on your phone is what you like, things that have been curated for you. Such a world is a bit frightening to think about."

"I just don't know if Lin Feng can actually pull it off. Don't just make empty promises."

"Why are you all so full of malicious speculation? Regardless, I feel that if such an algorithm can be created, it would be a good thing."

"Yeah, it's too troublesome to find videos now. If it can automatically recommend videos I like, I'd be very supportive." ...

A polarization occurred in the comments.

Some felt that the emergence of such a recommendation algorithm would not be a good thing for humanity, as people would lose their freedom.

Others believed that the creation of such a recommendation algorithm was a good thing, as it would save them the time wasted searching for good videos amidst a sea of content.

However, among the 2.5 million people present, there were many with keen business acumen, and they began asking Lin Feng in the comments if he was looking for investment.

Although there was no concrete evidence that Lin Feng was proficient in algorithm development, his confidence suggested that he could definitely create such a recommendation algorithm.

Even if it couldn't achieve the exact effects Lin Feng described, just performing at one-fifth of that level would be impressive, which is why they were eager to invest in Lin Feng's research.

Lin Feng naturally wouldn't give them the opportunity to invest. After all, if they could keenly perceive the potential of this recommendation algorithm, how could he, a transmigrator developing it, not know?

In the following time, Lin Feng chatted with netizens for another ten minutes. Then, Lin Feng announced that he needed to go and develop the recommendation algorithm and would be unable to answer further questions from netizens.

The camera feed would then switch to an overhead view of his workspace, allowing remote observation of his work.

Only background music would accompany viewers, who could watch him work from a distance. If they found the view boring, they could do other things.

The netizens in the live stream naturally nodded in understanding and then went about their own business.

Soon, the millions of viewers in the live stream gradually dispersed.

Some went to watch videos, others watched other streamers poached from Bilibili, and finally, only about 200,000 remained, curious to see how Lin Feng worked.

By 11 PM, when Lin Feng ended the stream, he discovered that a total of 2.81 million people had visited the live stream.

This number was lower than his expected three to four million, but higher than his lowest estimate of over two million, making it a decent result.

The income from live stream donations was also not low, reaching 520,000 yuan. After deducting his non-exclusive highest 70/30 split contract with the Bilibili live streaming platform, Lin Feng earned a pre-tax income of 360,000 yuan.

Overall, being an internet celebrity is indeed profitable. A single live stream can bring in hundreds of thousands of yuan. If he could earn this much every day, it would be more profitable than selling handwriting robots.

But Lin Feng knew this was impossible. The reason he could earn so much from this one live stream was that many teachers, grateful for his work, had given him donations upon seeing him.

This was evident from the large number of people who tipped, yet the average tip was no more than 100 yuan.

So, earning 10,000 yuan before tax each day would already be considered pretty good in the future.

After all, his livestreams weren't really that interesting; they just featured non-repeating background music and a panoramic view overlooking the entire room.

If Lin Feng didn't occasionally take some time to chat with his viewers, the number of people watching the stream simultaneously would be lucky to reach 1,000.

However, just as Lin Feng thought time would slowly tick by, and he would quietly research until he created a groundbreaking recommendation algorithm, a public opinion crisis quietly loomed.