Here is the translation of the contents into English:
This paper "Visual Self-Supervised Modeling: Scalable Image Generation via Next-Level Predictions" is a groundbreaking research achievement written by Tian Ke Yu during his tenure at ByteDance. The paper was the first to prove that GPT-like models can surpass diffusion models in image generation, making significant progress in this field.
This breakthrough has sparked a series of reactions, including:
1. Technological value: This paper and Tian Ke Yu's research have extremely high gold content and show clear scaling laws and zero-sample generalization ability, marking a major breakthrough in the AI field.
2. Actual achievements: The paper has been open-sourced and gained over 5,000 stars on GitHub, becoming a popular project.
However, this achievement also raises several problems, including:
1. How to allocate effective resources to talented scientists?
2. How to evaluate the work results of interns?
This controversy has also sparked more profound questions, including:
1. The development speed and innovation power in the AI field.
2. Company management's recognition and support for research achievements.
3. The balance between individual achievements and company interests.
Ultimately, this event raises some broader issues, including:
1. The pace of development and innovation in the AI field.
2. Company management's acceptance and support for research achievements.
3. Finding a balance between personal accomplishments and company interests.
This is an event worth thinking about, not just for Tian Ke Yu and ByteDance, but also for the entire AI community.
Translation
这篇论文《视觉自回归建模：基于下一个尺度预测的可扩展图像生成》是田柯宇在字节跳动工作期间撰写的一份突破性的研究成果。该论文首次证明了GPT类模型可以超越扩散模型，在图像生成方面取得重大进步。这一发现可能会让视觉模型与语言模型走向殊途同归的道路。
这一成就也引发了一系列的反应，包括：
- 技术价值：该论文和田柯宇的科研含金量都极高，并且展现出了清晰的Scaling Laws和零样本泛化能力。这是AI领域的一个重大突破。
- 实际获得的荣誉：该论文已经开源，并获得了超过5000颗star，成为GitHub上的热门项目。
- 公司管理困境：尽管田柯宇在字节跳动工作期间撰写了这一成果，但是公司却无法大张旗鼓地宣传这一成就，因为田柯宇正被公司起诉。这反映出公司对有才华的科学家资源分配的不当。
这起纷争也引发了一系列的问题，包括：
- 如何对有才华的科学家分配有效的资源？
- 实习生的工作成果该如何认定？
- 树立了一个重要的AI研究方向是否会因为个人纠纷而无法持续？
最后，这一事件也引发了一些更广泛的问题，包括：
- AI领域的发展速度和创新力。
- 公司管理对科研成果的承认和支持。
- 个人成就与公司利益之间的平衡。
这是一起值得思考的事件，不仅仅是对田柯宇、字节跳动，而是对整个AI领域的发展。