What did a 17-year-old Chinese high school student do? Even Musk couldn't help but give a thumbs up 👍
Recently, the name of a Chinese high school student has been trending in the AI community
A paper from China was just published, and Musk publicly commented on Twitter: "Impressive work from Kimi."
What shocked the global AI community is that a genius in the Chinese AI field is emerging from universities!
📌 Here’s the story
This student is named Chen Guangyu, and his team is the company Moonshot AI, which developed Kimi
Chen Guangyu is the first author of the paper "Attention Residuals: Rethinking depth-wise aggregation"
The paper proposed a new method for aggregating information between model layers: using the softmax attention mechanism instead of traditional fixed residual connections
Moreover, this method has led to significant improvements across multiple mainstream testing benchmarks
The core reason Chen Feiyu has garnered attention is that many AI researchers have to go through:
Undergraduate → Graduate → Doctorate → Laboratory
Whereas he directly entered the model development team
From the first encounter with large models to publishing research results and gaining global attention, it only took about a year.
Recently, the name of a Chinese high school student has been trending in the AI community
A paper from China was just published, and Musk publicly commented on Twitter: "Impressive work from Kimi."
What shocked the global AI community is that a genius in the Chinese AI field is emerging from universities!
📌 Here’s the story
This student is named Chen Guangyu, and his team is the company Moonshot AI, which developed Kimi
Chen Guangyu is the first author of the paper "Attention Residuals: Rethinking depth-wise aggregation"
The paper proposed a new method for aggregating information between model layers: using the softmax attention mechanism instead of traditional fixed residual connections
Moreover, this method has led to significant improvements across multiple mainstream testing benchmarks
The core reason Chen Feiyu has garnered attention is that many AI researchers have to go through:
Undergraduate → Graduate → Doctorate → Laboratory
Whereas he directly entered the model development team
From the first encounter with large models to publishing research results and gaining global attention, it only took about a year.