Bojie Li

At 1:00 PM on January 12, 2025, my father called me to say that my grandfather had suddenly passed away at home that afternoon.

A Lifetime in Geology

My grandfather was a top student in his youth. In the late 1950s, he was admitted to the Beijing Institute of Geology (the predecessor of China University of Geosciences), majoring in mechanical engineering. At that time, the Beijing Institute of Geology was a prestigious university that produced many talents. Premier Wen was his junior, and “Father of Chang’e” Ouyang Ziyuan was his senior. Of course, my grandfather was far from being an outstanding alumnus of the Beijing Institute of Geology. In his junior year, the Sino-Soviet split occurred, and all Soviet experts withdrew, leaving no one to teach. In his senior year, my grandfather joined the Institute of Geography of the Chinese Academy of Sciences and became an ordinary geologist.

Although my grandfather’s position was not fieldwork, mainly conducting research in the lab, he often had to travel across the country for geological surveys. Geological surveys were not tourism; living rough was the norm. Transportation was not developed at that time, and just taking a green train to the destination could take several days. The places he went to were mostly uninhabited (places with many people didn’t need exploration), with wild mountains and waters. It was not uncommon to encounter wild animals while camping in the wild or geological disasters halfway up the mountain. There were no mobile phones or GPS back then, and if you got lost, you might end up staying in the mountains.

This article was first published in a Zhihu answer to the question “Looking back at the development of the internet, what underlying logics seem simple but will continue to be effective in the future?”

Data is the most important moat.

The Moat for Internet Companies is Data

I really like Lao Wang’s Product Class. Wang Huiwen is one of the founders of Xiaonei and Meituan. His Tsinghua product class is a classic, worth revisiting repeatedly. It talks about economies of scale, and social networks have network effects. The essence of network effects is actually data: who are my friends? How close am I to these friends?

Lao Wang’s product class mentions that replicating WeChat is difficult. Alibaba and ByteDance tried to attack WeChat but failed. However, if one day there is a Prophet app that knows all of a person’s real-life friendships and automatically generates friend relationships based on this, it could potentially compete with WeChat. This is the value of WeChat’s control over friend relationship data.

But this Prophet app doesn’t have WeChat’s chat history or Moments history, so something is still missing. This is the value of conversation history data. If the Prophet app goes further and knows what everyone says and does every day, then even WeChat might not be its match.

This article is reposted from the WeChat public account of Woke Advanced Alliance: “Dialogue | Interview with Huawei ‘Genius Youth’ Li Bojie (Part 2): Giving Up a Million-Yuan Salary to Start a Business, the Persistence and Reinvention of a USTC Alumnus”

Long article alert, this article contains 11221 words, estimated reading time 29 minutes

“Dialogue” is a series of in-depth interview columns launched by the Woke Advanced Alliance. We invite and interview outstanding alumni from USTC who have experienced detours, tasted setbacks, and achieved accomplishments during their university life at USTC. We hope to showcase their various life experiences and personal choices through in-depth dialogues, hoping that the experiences of these predecessors can illuminate more paths for the younger generation at USTC.

In this issue of the dialogue column, we invited Senior Brother Li Bojie (personal homepage: 01.me/), a USTC 1000 alumnus, USTC MSRA joint training PhD, one of the first Huawei “Genius Youth” awardees, AI entrepreneur, and co-founder of the USTC course evaluation community. He was an assistant scientist and deputy chief expert at Huawei’s Computer Network and Protocol Laboratory. He has published multiple papers at top conferences such as SIGCOMM, SOSP, NSDI, and ATC, and has won the ACM China Outstanding Doctoral Dissertation Award and the “Microsoft Scholar” scholarship.

This article is original by Woke Advanced Alliance. Do not reprint without permission.

Interview, Editing | Feng Wenjun, Chen Lei, Su Qicheng

Proofreading | Zhao Guohua

Theme Summary

Transition from University to Work Environment

How to Develop Skills to Adapt to Job Positions

Entrepreneurial Challenges and Reflections

Job Search Advice and Preparation Strategies

Employment and Self-Improvement in the AI Era

Will AI Cause Unemployment Issues

How to Embrace AI Tools to Empower Work and Study

(This article was written by the author in November 2024 at the invitation of Open Source China for the “2024 OSChina Annual AI Review”)

In 2024, large models truly began to be implemented, with most tech workers using at least one large model to enhance efficiency in their work. Many national-level applications and mobile phone manufacturers have also integrated large models. Large models are starting to diverge into two directions: professional models and personal models.

Professional Models

Professional models are designed to enhance productivity, such as AI-assisted programming, writing, design, consulting, education, etc. Once the model’s capabilities reach a threshold, professional models will bring high added value. In 2024, professional models have already been implemented in many fields. For example, AI-assisted programming can more than double development efficiency, with API call or IDE subscription costs of just tens of dollars per month, equivalent to engineers costing tens of thousands of dollars per month. AI-generated images, podcasts, live broadcasts, etc., can increase the work efficiency of artists, voice actors, and hosts by hundreds of times. AI consulting services in psychology, law, and medical fields can reach the level of junior professionals, with hourly charges significantly higher than the model costs. AI virtual foreign teachers can already rival real foreign teachers, and due to standard pronunciation, the effect even surpasses most domestic English teachers. In the future, AI-assisted teaching will change the traditional one-to-many teaching model, making one-on-one AI teaching possible and significantly improving the efficiency and quality of human teachers’ content preparation.

This article is reposted from the WeChat public account of Woke Advanced Alliance: “Dialogue | Interview with Huawei ‘Genius Youth’ Li Bojie (Part 1): Giving Up a Million-Dollar Salary to Start a Business, the Persistence and Reinvention of a USTC Alumnus”

Long article warning, this article contains 10016 words, estimated reading time 27 minutes

“Dialogue” is a series of in-depth interviews launched by the Woke Advanced Alliance. We invite and interview outstanding alumni from USTC who have experienced setbacks, tasted failures, and achieved success during their university life at USTC. Through in-depth conversations, we hope to showcase their life journeys and personal choices, hoping that their experiences can illuminate more paths for future USTC students.

In this issue of the Dialogue column, we invited Senior Brother Li Bojie (personal homepage: 01.me), a USTC 1000 alumnus, USTC-MSRA joint PhD, one of the first Huawei “Genius Youth” awardees, AI entrepreneur, and co-founder of the USTC course evaluation community. He was an assistant scientist and deputy chief expert at Huawei’s Computer Network and Protocol Laboratory. He has published multiple papers at top conferences such as SIGCOMM, SOSP, NSDI, and ATC, and has received the ACM China Outstanding Doctoral Dissertation Award and the “Microsoft Scholar” scholarship.

This article is original by Woke Advanced Alliance. Do not repost without permission.

Interview, Editing | Feng Wenjun, Chen Lei

Proofreading | Zhao Guohua

Theme Summary

Learning and Practice Experience During University

How to View Mathematical Foundations

Development History of the Course Evaluation Community

How to Transition to AI Research

Academic Planning and Career Choices

Misconceptions and Suggestions for Choosing a PhD

This article was first published in a Zhihu answer to “What do you think of OpenAI’s latest o3 model? How powerful is it?“

When o1 first came out, many people doubted that it had not yet reached AGI (Artificial General Intelligence). The programming and mathematical capabilities demonstrated by o3 not only meet the threshold for AGI but even touch the edges of ASI (Artificial Superintelligence).

o3 further validates the value of RL and test-time scaling, providing a path to continue enhancing model intelligence and solving more difficult problems through post-training and increased inference time when high-quality pre-training data is nearly exhausted and model capabilities hit a “wall.”

Many have seen the specific performance metrics of o3, so I won’t repeat them. Here’s a summary:

• o3 defeated 99.9% of programmers in Codeforces programming competitions, ranking 175th among 168,076 programmers. Even the authors of o3 couldn’t beat it.
• o3 also shows significant improvement over o1 in meeting real-world programming needs. In the SWE-Bench software development test, the previously released o1-preview scored 41.3%, while o3 scored 71.7%. This means o3 can directly meet 70% of real-world needs and pass unit tests, leaving only 30% of the work for human programmers, which AI can also help significantly improve efficiency.
• It scored 96.7% on the AIME 2024 math test, equivalent to only missing one question in the American Mathematics Olympiad.
• In the GPQA Diamond test for PhD-level scientific questions, it exceeded o1 by 10 percentage points, while o1 was already at the average level of human PhD students.
• In graphical logic reasoning ARC-AGI, after fine-tuning, o3 reached 87.5%, surpassing the human average (85%).

On the evening of November 15, 2024, at the Zhihu Academic Bar, I, along with prominent figures like Kai-Fu Lee, Zhiyuan Liu, and Guohao Dai, participated in an open mic sharing session.

Question:

“Vulnerabilities & Bugs—What moment made you feel like the world had a bug?”

On Zhihu, there are several highly upvoted questions about bugs, such as “What moment made you feel like the world had a bug?” and “What are some bugs that left you dumbfounded?”

However, it’s not scary when the world has a bug; what’s scary is when AI discovers a bug.

Recently, did AI discover a major security vulnerability in the real world for the first time? A vulnerability in SQLite was fortunately discovered by Google’s AI Agent, and after being fixed, it caused no damage. Could it be that with further evolution, AI could permanently prevent global blue screen incidents like those from Microsoft? This possibility is exciting.

Answer:

Original podcast content: Six Forks Podcast “R&D Positions Must Embrace AI, Then Spend the Remaining Time Doing Experiments—A Conversation with Huawei’s First Batch of Genius Youth Li Bojie”

The following content is approximately 35,000 words, organized by the author using AI based on the podcast content. Thanks to Hunter Leslie for the wonderful interview and post-production, the 2-hour session was a blast without any retakes. Also, thanks to AI for allowing me to organize 30,000 words of content in an afternoon and supplement it with previously written materials.

Core Points Summary:

• Sci-fi movies like “Her” and “Black Mirror” involving AI scenarios have already been realized or are close to realization, turning sci-fi into reality will undoubtedly have immense value.
• Model capabilities are rapidly increasing, and small AI companies should make friends with foundational model companies rather than embellishing or wrapping models.
• The success rate of “20% projects” is relatively high; start with interest projects based on daily work and life needs during spare time, and if there is a generalized need, expand into commercial projects for a higher success rate.
• Many performance issues in AI applications are not model problems but should be solved with system optimization based on first principles.
• A lot of work in the AI industry has not been published or open-sourced, creating a huge information gap.
• The information gap in modern society is enormous; AI interacting more with users can understand everyone’s knowledge boundaries, greatly improving recommendation efficiency and helping to bridge the information gap.
• OpenAI o1’s strong reasoning ability is crucial for the reliability of model applications in serious scenarios.
• For most users’ daily life needs, the most capable models are already sufficient; the focus is on reducing costs. AGI might be very expensive, mainly used to solve the most important problems in human science.
• Limited energy and chip manufacturing capabilities are major challenges for AGI.
• Startups need to recruit people with solid computer science knowledge, strong learning ability, and strong self-drive.
• AI-assisted programming can significantly enhance programmers’ work efficiency, freeing up time for exploring “20% projects” or achieving a better work-life balance.
• After AI improves efficiency, it will bring more demand, turning more needs into reality, and even independent developers can complete work that previously required a team.
• A person’s career is composed of a series of projects, and it’s important that each project has an impact. Different projects are suitable for different approaches, including startups, small and beautiful companies, communities, academic projects, etc.

Full Text:

Q: What is the one product you most want to share from the past year?

A: I previously mentioned a saying, “AI in a day, human in a year.” There have been many exciting products in the past year. If I had to choose one, I would pick OpenAI o1, which, simply put, taught AI to think. This thinking is most evident in mathematics and programming. We shouldn’t understand mathematics and programming narrowly, as they are the biggest challenges for current large models in commercial applications.

In mathematics, most large models currently can’t calculate accurately, such as not distinguishing between 3.8 and 3.11, leading to low accuracy and making them unreliable in serious scenarios, like booking a flight or calculating expenses. What if they make a mistake? Now that models can calculate accurately, they can be used in many serious scenarios.

Programming isn’t just for programmers. We’ve observed an important trend in AI applications: the generated content is not just text but a multimodal content with images and text, or even interactive mini-games or mini-programs, like Claude Artifacts, OpenAI Canvas, Google NotebookLM generating podcasts, and Perplexity generating illustrated wikis. These contents are essentially a piece of code generated by large models and then dynamically rendered. This kind of multimodal content tests the programming ability of large models.

Before starting my business, my wife bought me “Xiaomi’s Entrepreneurial Thinking,” but I never read it. Recently, I had some time to go through it and found it very rewarding. I used to dislike such books, thinking these experiences were processed and beautified, and some advice might not be applicable. However, after having personal entrepreneurial experience, reading books by industry leaders makes a lot of sense.

The essence of “Xiaomi’s Entrepreneurial Thinking” is in Chapter Six, “The Seven-Word Formula for the Internet,” which is Focus, Extreme, Reputation, Speed.

The development approach of MIUI fully embodies the “Focus, Extreme, Reputation, Speed” seven-word formula for the internet:

• Focus: Initially, only four functions were developed (phone, SMS, contacts, and desktop), with extreme restraint.
• Extreme: With customizable lock screens and themes, it could simulate any phone, pursuing an extreme experience.
• Reputation: The entire company communicated with users on forums, making friends with them. It was very popular on the XDA forum and became a hit abroad, with its earliest internationalization starting from MIUI.
• Speed: Weekly iterations, adopting an internet development model.

Focus

Focus is the most important of the seven-word formula for the internet and applies to all companies and products.

Companies Need Focus

Lei Jun shared his first entrepreneurial failure experience. Lei Jun was technically strong, completing four years of credits by his sophomore year. In his junior year, he wrote the antivirus software “Immunity 90,” which sold for a million yuan—a significant amount in the 1990s. So, in his senior year, he founded the Tricolor Company with two tech experts, Li Ruxiong and Wang Quanguo (both of whom are very successful now), but this venture quickly ended in failure.