Z Potentials | Akool, an AI video tool created by Jiajun Lv, has rapidly gained popularity in North America, reaching an annual recurring revenue (ARR) of $40 million in just two years
Z Potentials invited the creator of Akool, Jiajun Lv, to give a talk.
In an era of rapid AI development, the boundaries of technology iteration and application are continuously expanding, especially in the field of video production and editing. AI's power is gradually rewriting the industry's rules, bringing unprecedented efficiency and possibilities to creators and businesses. Akool, a company dedicated to next-generation enterprise-level AI video production solutions, is redefining this space with its technological innovation and deep differentiation.
Akool's founder, Jiajun Lv, has over a decade of top-tier technical expertise and practical experience, starting from the CAD & CG Laboratory at Zhejiang University to further studies at UIUC, followed by product development roles at Apple and Google. From machine learning to generative AI, he has consistently explored how to drive innovation in content creation and production efficiency through technology. In 2022, he chose to transition from working at major tech companies to entrepreneurship. Driven by his unwavering pursuit of the vision of creating "the best commercial video production platform," he led Akool to quickly establish a presence in the global market. As of now, the company has achieved nearly 40 million USD in invoiced ARR.
In this interview, Jiajun Lv shares in detail how Akool achieved product-market fit (PMF) by leveraging differentiated technological products, transitioning from its initial startup positioning to product transformation. He also discusses how the company continues to expand its feature matrix around human-centric video generation, ultimately providing deep services to enterprise clients and content creators. Lü explores the profound impact of technological development on the future of the industry and envisions Akool’s long-term goal of competing with Adobe to become the leader in the video production field. Let’s dive into Akool’s story. Enjoy!
“Elon Musk’s goal is to enable humanity to survive across planets, whereas I am more focused on how technology can transform humanity itself, making us wiser and stronger in the future. This might sound a bit like science fiction, but for me, I still want to do something that has a real impact... Although I’ve been involved in two entrepreneurial ventures before, I realized that if I want to drive the things that truly interest and excite me, the best way is to strike out on my own.”
"First, it was the technological shift that caught my attention, such as models like Stable Diffusion starting to truly work and becoming more mature. This marked a huge difference. Of course, the fastest evolution has been in Language Models, but at the same time, we also see the trend expanding towards images and videos... This shift was also driven by the fact that we noticed data for these functionalities on the platform had started to rise, so we decided to go all-in in this direction."
"The signal for reaching PMF (Product-Market Fit) is incredibly strong——it feels unstoppable. When we pivoted to video generation, our servers were on the verge of collapsing; no matter how many machines we added, it was never enough. If you're unsure whether you've reached PMF, there's a high likelihood that you haven’t actually reached it yet."
"Our differentiated advantage lies in our deep focus on the Enterprise market. Unlike competitors who focus on the Prosumer market, we believe the enterprise market has a higher ceiling, deeper barriers to entry, and stronger customer retention. Video production/editing is also more of a systemic engineering problem. On one hand, it's about how to implement the solution in more scenarios, which requires extensive engineering development. On the other hand, it's about refining the product experience, which demands significant product polishing. Whether it's engineering or product refinement, these are areas where our team excels."
"In the early stages, one of the key reasons our product was well-liked by users was because our technology was superior. Looking at the medium to long term, we still believe that technology is crucial to user experience. We’ve maintained a tech-first mindset and have continuously pushed for breakthroughs and advancements in technology. We’ve made groundbreaking progress in foundational large model frameworks, high-precision 3D modeling, and neural network rendering."
01 From Apple/Google to Independent Entrepreneurship: Always Committed to Doing Things with Long-Term Impact
ZP: Welcome, Jiajun! Could you please introduce yourself to everyone?
Jiajun: Hello everyone, I’m Jiajun Lv, the founder of Akool. I was born in 1990. From high school onwards, I was very passionate about physics and mathematics. However, in high school, I read a book called The Great Failure by Wu Xiaobo, which sparked my interest in business. So, I chose computer science as my major in university, thinking it was the best combination of physics, mathematics, and business. In 2009, I started studying computer graphics at Zhejiang University’s CAD&CG Lab, one of the top computer graphics labs in the world. My main focus at the time was 3D modeling and how to use AI to improve 3D modeling. Although AI back then was still based on machine learning and used a method called "Divide and Conquer," it was also when I first came into contact with AIGC. Over the past decade, I have continued to explore the fields of graphics, CG, and visual generation.
After completing my undergraduate degree, I went on to pursue a PhD at UIUC, where I worked under a professor who is highly influential in the field of computer vision. His research covered everything from basic vision to advanced vision that integrates machine learning and deep learning. I participated in several projects related to image/video editing and generation, as well as real-time sensor processing. I also worked on some cross-disciplinary research with computer graphics. Later, I joined a researcher program at Stanford, focusing on animation generation, such as transforming comic books into animated films. These projects were all fascinating and closely aligned with my interests, which kept me highly motivated and passionate about my work. During my PhD, I also co-founded a startup called "小嘿科技" (now rebranded as "今日水印相机"). We developed a dating app called "Double Date," aimed at creating a new form of social interaction by organizing activities for two men and two women. I thought this direction was really interesting at the time.
After graduating in 2018, I joined Apple, where I worked on the development of Face ID, particularly focusing on how to achieve facial recognition while wearing a mask. In 2020, I moved to Google Cloud, where I specialized in video processing and human action recognition, such as counting people, analyzing human movements, and structuring video data to make video content more efficiently searchable and analyzable. During that time, I also worked part-time as an adviser at Xreal for a year, where I helped build their AI/ML team and contributed to the development of AI/ML applications. One of the key areas we worked on was gesture recognition, which was used for hand gesture control in AR glasses.
ZP: In 2022, you left the major tech companies and decided to start your own business. What was the reason and motivation behind that decision?
Jiajun: Actually, entrepreneurship has always been something I wanted to pursue. From reading Xiaobo Wu’s book to being influenced by the stories of Bill Gates and Elon Musk, I’ve always wanted to do something impactful. I even wrote a book called Enhancing Humanity, which discusses how technology can drive human development. It covers topics like the integration of humans and machines, memory uploading, and even discussions about immortality. I’m very interested in these cutting-edge fields, and this is one of the main reasons why I’m focused on the virtual human space now. Musk's goal is to enable humanity to survive across planets, while I am more focused on how technology can change humanity itself, making us smarter and stronger in the future. It might sound a bit like science fiction, but for me, I still want to do something that has impact—on a smaller scale, for myself and my company, and on a larger scale, for the development of humanity. That’s why I felt that staying at a big company didn’t really align with what I wanted to do. I also attended a program at Harvard Business School, called PLD, which really encouraged us to make a change. Although I had participated in two entrepreneurial ventures before, I realized that if I truly wanted to push the things that excite and inspire me, the best way was to strike out on my own.
ZP: How have your past experiences at major tech companies and in your entrepreneurial ventures influenced and helped you in this new startup?
Jiajun: I think resilience is extremely important in the entrepreneurial journey, as well as being able to ride the wave and seize the opportunities of the times. Working at big tech companies allowed me to accumulate a lot of systematic methodologies, such as understanding the complete development process, how to build infrastructure, and how to construct organizational structures. At Apple, what left the deepest impression on me was the focus on refining the product—pushing the product experience to perfection, to the point where it could even be called "extreme." At Google, I saw the cutting-edge developments in technology and learned how to apply those technologies across many fields to create a significant impact.
ZP: I noticed that Akool is headquartered in the U.S., and the founding team has a very strong international background. Could you share how the founding team came together?
Jiajun: From day one, I wanted to build an international company, and that definitely required an international team. Especially since we are targeting the B2B market, we needed to have a team with enough international experience and seniority in business, otherwise, we wouldn't even be able to get through the door of enterprise clients. In the early stages, the team was mostly made up of friends or people we were introduced to. I met Deepa Sureka in the entrepreneurial community before starting Akool, and we spent time convincing each other to join our respective projects. After she joined Akool, she brought in a lot of colleagues with diverse, international backgrounds. Gradually, we started hiring more externally, using platforms like LinkedIn to recruit talent.
02 Benchmarking Adobe: Positioning as the Next-Generation AI Video Production Suite and Finding PMF Around Initial Customer Needs
ZP: What was Akool's initial positioning when it was founded, and how has it evolved over time?
Jiajun: In the beginning, we were looking for new opportunities in the AI field. We didn’t see a business model in the U.S. that was similar to SenseTime, so we aimed to create "the SenseTime of the U.S." From day one, we positioned ourselves as a B2B company. Initially, we partnered with the Saudi government, and our main focus was on security, such as developing facial recognition-based access control systems. We planned to focus on the Middle East and U.S. markets. However, we faced some practical issues. Government projects in the Middle East moved very slowly, often taking over six months to progress, and the security sector in the U.S. was also relatively slow to adopt new technologies.
At that time, we launched many applications. Although we focused on security, we also developed some video editing and video generation features. Around Q4 of 2022, we noticed that the video editing feature had grown significantly. The usage started to increase organically, without any advertising, with users spontaneously adopting it. That's when we realized this was the true Product-Market Fit (PMF). We then decided to dedicate more time and resources to this direction. After the launch of ChatGPT, we made a full pivot towards this area, gradually adding new features and refining the product experience.
ZP: What opportunity did you see that led to the pivot?
Jiajun: First, we saw the trend of technological changes, such as models like Stable Diffusion starting to truly work and becoming much more mature. This marked a huge difference. Of course, the fastest development has been in Language Models, but at the same time, we noticed the trend was also expanding towards images and videos. Products like Midjourney were just starting to gain popularity and were still in their early stages. We realized that the video field had barely been touched by others, which presented a significant growth opportunity. Additionally, as I mentioned earlier, we saw that the data for these features on our platform had started to pick up, so we decided to go all-in on this direction.
ZP: You mentioned that Akool’s positioning is B2B Video Cloud. What features did we initially launch, and what is the logic behind the expansion of our products today?
Jiajun: Our initial three core products were: Face Swap, 3D Generation, and Image Generation. While we made good progress on the technical side of 3D generation and image generation, the product experience wasn’t fully optimized. There were some key details that still needed refinement. At the time, image generation was similar to what Midjourney was doing, and for 3D generation, we initially aimed to target the e-commerce vertical. However, we later realized that this was a "false demand"—users didn’t have the level of interest in 3D as we had imagined. Face Swap was the first feature that was more successful. In January 2023, we secured a big client, Coca-Cola, which helped us build traction and set the foundation for growth.
The subsequent expansion was based on two main principles. First, after acquiring our initial customer base, we looked for new demands within that group. Second, we explored which technologies were similar to face-swapping and could be expanded using our existing technical capabilities. With these two strategies in mind, we developed many new features, most of which were centered around "people", such as Face Re-editing and Reanimation, and eventually even expanded to include features like Video Translation.We focused on specific customer groups and use cases, primarily in marketing, advertising, and content creation for creators. While we also launched features like image background replacement and video background replacement, we realized that most of the traction came from features related to editing and generating content involving people. Once we recognized this pattern, we shifted more of our R&D resources towards people-related video generation and editing functionalities. Overall, our approach has been to continuously iterate and expand our product matrix based on the technical similarities and needs of our customers.
ZP: Why did we choose to focus on the "people" direction?
Jiajun: First, the technology related to "people," especially facial recognition and generation, is relatively more mature. This is because face generation is a more constrained problem compared to generating arbitrary objects or random content, which makes it less complex. Even when it comes to full-body generation, the problem remains more controllable, so it’s easier to develop. Second, when focusing on human generation and editing, users tend to have higher acceptance and willingness to pay, as their overall purchasing power is stronger.
Third, generating objects is much more challenging. The biggest demand for object generation comes from e-commerce, but the objects need to be highly realistic and match actual products, which is extremely difficult. Additionally, e-commerce businesses aren’t as willing to pay for such content because in their business model, novelty in the material doesn’t necessarily drive sales. Moreover, in the U.S. e-commerce ecosystem, many companies rely on outsourced manufacturing, so they receive their materials directly from suppliers and don’t need to generate their own content. Most of these suppliers are based in Asia.
Therefore, the marketing scene is still a better fit. Customer demand and willingness to pay are higher, and when considering the difficulty of generation and the maturity of technology, the "people" domain is a more favorable track overall.
ZP: So Akool has focused on the "people" video production track. What products and features do we currently have?
Jiajun: First, we have Face Swap, including both real-time and non-real-time face-swapping features. Second, we have Talking Avatar, which can generate videos of various virtual personas and edit existing videos—such as making people in the video say different things. It also supports real-time interaction, like conversing with a customer support agent. We’ve also developed Video Translation, which allows us to translate the language in a video into multiple target languages while preserving the original natural expression. Additionally, we’ve been working on human generation with Image Generation and Image-to-Image, which can create different virtual human personas. Recently, we also launched features for 3D motion editing.
ZP: Looking back, how did Akool gradually find PMF?
Jiajun: First, regarding the "P" (product), as I mentioned earlier, we launched many features. We based our decisions on market observations around core video features and the team’s previous experiences to understand user needs. Face Swap turned out to be a high-frequency feature, so we focused on it and, using new technologies, launched our product around that.
Then, looking at "M" (Market), the first group to approach us were virtual human companies. I clearly remember one Canadian virtual human company reaching out to us. They were quite established and kept recommending, "Your face-swapping technology is so good, why don’t you go ahead and make virtual humans? This market is very profitable." By Q2/Q3 of 2022, we had a bunch of virtual human companies approaching us, asking us to develop lip-syncing technology. That’s when we realized this trend was gaining momentum, so we decided to jump in.Next, we started looking for potential use cases. At the time, we brainstormed various scenarios and shared them on forums and communities. Many users came to try out the product. By January 2023, we had signed Coca-Cola as a client. We used that client to approach others and employed marketing tools to find every possible customer who could benefit from our product, sending them emails. Eventually, we narrowed our focus to the marketing scene.
ZP: How did we determine that we had achieved PMF?
Jiajun: The signal for achieving PMF is very strong—it’s the feeling that it’s unstoppable. After we pivoted to video production, our servers were almost overwhelmed. No matter how many machines we added, it still wasn’t enough. If you’re not sure whether you’ve reached PMF, then chances are, you probably haven’t.
ZP: Seeing that many players in this space mainly focus on ToP (Prosumer), why did Akool choose the ToB (Business) business model?
Jiajun: On one hand, we analyzed the productivity software market in the U.S. ToP products are lighter, with shorter decision cycles, so they typically scale quickly in the early stages. On the other hand, ToB products are heavier, with longer development cycles, but they have stronger customer loyalty and a higher ceiling. Almost all productivity software worth billions of dollars is ToB. On the other hand, our team has a stronger ToB DNA and a better understanding of the needs of B2B enterprises. Of course, we’ve also seen more traction in the B2B space. From the beginning, our website and overall tone have always been ToB. Whether we were starting with a U.S. version of SenseTime, focusing on security, developing cloud-based AI services, or offering marketing services, we’ve maintained a ToB branding throughout the entire process, despite some changes along the way.
However, we are now considering creating a new landing page to separate ToB and ToP, with a specific branding direction for Prosumer customers. Currently, over 60% of our customers are business clients, and 40% are Prosumer clients. We haven't adopted any special marketing strategies for Prosumer customers yet, but we believe there's still a lot of growth potential in that segment. Our current benchmark is Adobe. We've analyzed Adobe’s user base, which includes both Prosumer and Business clients, and they have different landing pages for each group. So, we may also need to create separate landing pages to align more closely with Adobe’s approach.
ZP: How do you view the long-term competition with Adobe?
Jiajun: We’re starting with the "human" aspect, which Adobe has done less in. At the same time, we’re also providing products and services to Adobe. Overall, our experience working with them shows that their progress in the "human" space is slow. They have many concerns and ideas, which present an opportunity for us. Currently, their strategy in this area is to integrate third-party solutions, so overall, they aren’t moving as quickly as startup companies.
ZP: What new products does Akool plan to launch in the next 2-3 years? What is the main logic behind expanding your product line?
Jiajun: From a functional perspective, first, we will launch more features around "human" video production, including image, voice, motion, and even expanding to clothes, glasses, and other elements. The second area is more generic video generation, but this will depend on how technology develops. We might also expand into generic video editing, but we will approach that more cautiously.
From a business perspective, if we look at Adobe, it has several key components: Creative Cloud, Marketing Cloud, and Content IP. For us, we will focus on three pillars. The first is a vertical Marketing Cloud that is more deeply integrated with video. The second is Content IP, and the third is Creative Cloud. The difference from Adobe is that we will focus more on web-based experiences and cloud processing. While some features have already been moved to desktop, overall, we will continue to prioritize the cloud, including collaboration experiences, API interactions, and focusing more on video AI editing and generation.
ZP: Could you introduce the current tech stack of the company? What models and algorithms has Akool developed in-house?
Jiajun: Our team is quite technical, so before we start, we generally evaluate whether we can handle it ourselves and what method would be the most cost-effective. If we can do it well, we’ll build it ourselves; if the ROI for doing it in-house is low, then we’ll use open-source tools or integrate third-party APIs. For example, we use a third-party API for our voice model.
So, it really depends on our actual situation to determine whether the team can handle it. Of course, the core algorithms must be developed in-house, as it's difficult to meet our requirements without them. There is still plenty of room for optimization in this area. The key algorithms for generating and modeling various "human" elements——such as faces and bodies——will all be developed in-house going forward. For other areas, it will depend on whether our resources allow us to handle it internally.
ZP: Why does Akool place such a strong emphasis on cutting-edge technology research and academic collaboration? Could you share some key technological breakthroughs?
Jiajun: Most of our team is focused on technology, and I myself come from a technical background. I believe that technology can change the world. My PhD advisor, David Forsyth, is a leader in this field, so we have always maintained strong academic connections. In the early stages, one of the main reasons our products were well received by users was because our technology was better. Looking at the medium to long term, we still believe that technology is crucial to user experience. We maintain a technology-first mindset and have been pushing for technological breakthroughs and development. We have made significant advancements in foundational large model frameworks, high-precision 3D modeling, and neural network rendering. Our Akool Research Team also collaborates on cutting-edge research projects with institutions such as Google DeepMind, Salesforce Research, and UCLA, and we have co-published several papers.
ZP: As the CEO of the company, what do you think are the three most important things in the next two to three years?
Jiajun: The first thing is to secure more resources for the company, no matter what kind of resources they are. The second thing is to set a clear direction for the company, so that it can move forward in that direction for the long term. The third thing is to build the team and motivate them. Setting the direction involves both extending the direction and determining various priorities. There are so many things we could do, but our resources are limited. So, the most important thing is to set priorities and decide what to do first and what to do later.
ZP: What is Akool's long-term vision?
Jiajun: In the long run, we still want to build a company similar to Adobe. Our goal for the next few years is to become the best commercial video production platform, empowering various business application scenarios, including advertising, marketing, film production, and more.
03 Targeting the Enterprise Market with Higher Potential and Stronger Barriers, Solving System Engineering Challenges in Video Production
ZP: How do you view the current competitors in the industry? What is our differentiation advantage?
Jiajun: We believe that the current competitors in the industry include Synthesia, HeyGen, Runway, Captions, and others, all of which have performed well in the startup space. However, in the long term, the real challengers could be industry giants like Adobe and Canva, especially if Google Cloud enters the video generation business in the future, as they would also become significant competitors.
Our differentiation advantage lies in our deep focus on the enterprise market. Unlike competitors that focus on the prosumer market, we believe the enterprise market has a higher ceiling, stronger barriers to entry, and greater customer loyalty. The needs of enterprise customers are often more complex and diverse. At this stage, we focus on specific verticals, providing feature differentiation. Our team also has a strong advantage in the enterprise sector, enabling us to better understand and meet the video production needs of enterprise clients.
Additionally, video production/editing is more of a systemic engineering problem. On one hand, it's about how to implement it in more scenarios, which requires extensive engineering development. On the other hand, it's about how to refine the product experience, which requires significant product iteration. Whether it's engineering or product refinement, these are areas where our team excels.
ZP: The company has already achieved great success in commercialization. How do you plan to maintain your first-mover advantage going forward?
Jiajun: As of now, our ARR has reached $20 million. We did start quite early, and I believe the accumulated advantages are twofold: one is our customer base, and the other is the data. We’ve built a network effect with our customers, as we’ve established a group/workspace with a lot of customer cases, and we’ve refined many aspects of the product experience, which can only be done through customer feedback. We’re also working on more initiatives that leverage network effects. The first is seen in our workspace and collaboration features, and the second is in the data we’ve accumulated. Additionally, we’ve innovated more around IP and have formed more exclusive partnerships to help us further expand our IP.
ZP Note: In private discussions, I also learned that, according to industry standards and competitors' metrics, the invoiced ARR has already reached $40 million. However, due to issues like failed credit card payments (mainly in Southeast Asia), the founder prefers to use the financial reporting metric, as it aligns better with the commercial nature of the business.
ZP: What key changes and breakthroughs have occurred in the technology of video production/generation and editing over the past few years?
Jiajun: When I first started my entrepreneurial journey, the technology in the video industry was not mature. The videos generated back then were completely unusable. The companies that are now raising funds quickly weren't originally focused on AI video generation. Many of them started as web-based video editors and later pivoted to AI video generation. At that time, the industry hadn't developed yet, so companies focused purely on AI video generation were very small. The larger companies had all pivoted from AI video editing.
There are still many iterations and breakthroughs in technology, and overall, the results have improved significantly. Back then, the video quality was quite poor, and even digital humans looked very stiff, with only the mouth moving slightly. Now, digital humans are much more dynamic and it’s almost impossible to tell whether they are real or generated. From a technical standpoint, a major development in video generation has been the introduction of Vision Transformers (ViT) for overall video creation.In terms of application, back then, very few companies were using video generation, but now it has made significant breakthroughs in applications, with many companies starting to use it, and many technologies are now in production.In summary, there have been substantial changes in technology maturity, effects, application, model size, and model structure.
The breakthrough that has had the most impact on our business is the shift from algorithms mostly being based on 2D for a long time, to moving toward 3D space. Additionally, the optimization of model structures and the increase in model size have also had a corresponding impact on our business.
ZP: What new technological breakthroughs do you hope to see in the next three to five years that could have a significant impact on our business?
Jiajun: There are still many areas that can be optimized, and a lot of imperfections remain, with noticeable artifacts (unnatural or anomalous traces or flaws). Achieving high-quality video generation is actually quite difficult. For example, it's still very challenging to achieve physical simulation or adhere to physical laws. Most methods still rely on big data and memorization techniques. To truly elevate video generation and editing to a movie-level standard, following all the physical laws, there's still a long way to go.
So there are indeed many opportunities. For example, it's still quite challenging to fully replace an entire head, including the hair, during face-swapping. It requires a lot of interaction. Additionally, generating and editing under different angles and lighting conditions is also technically difficult. Let alone achieving truly generic video generation; making those use cases work well is tough. The technology hasn't yet advanced to a point where it's ready for commercial application. Right now, much of the technology is still in the entertainment stage, where the requirements aren't as strict, so even if the results are slightly off, they can still be used. However, when it comes to entering production-level applications, the demands are much higher, so there's still a lot of room for development. We've seen rapid improvements in generic video generation models, but there are still many limitations.
ZP: What were your expectations for yourself 10 years ago? Have you achieved them? Looking ahead, what kind of person do you hope to become in the next 10 years?
Jiajun: Ten years ago, I was involved in my first startup, and at that time, we aimed to build a very successful company. Now, with Akool, our goal is to turn it into a highly successful company with a significant impact and make a difference. We're still "on the way."
In 10 years, I hope Akool will be a very successful company, well-known, serving more customers, and used by many more people. If everything goes smoothly, I may explore other fields, see what else is interesting. Maybe, like Musk, I'll get into rocket manufacturing, or perhaps explore areas like social impact or even more ambitious ventures, like "creating humans."
I also wrote a book before, called "Enhancing Humanity." The book discusses how technology can drive human development, covering topics like the integration of humans and machines, memory uploading, and even the concept of immortality. I am deeply fascinated by these frontier areas, and this is one of the key reasons I'm so focused on the virtual human field right now. While Elon Musk’s goal is to enable humans to live on other planets, I’m more interested in how technology can transform humanity itself—making us smarter and stronger in the future. It may sound a bit like science fiction, but for me, I want to do something impactful—something that affects not just myself and my company on a smaller scale, but has a broader impact on the development of humanity. That's why I feel like working at a big company doesn’t align with what I really want to do.
ZP: Apart from your entrepreneurial work, what are your hobbies and interests?
Jiajun: My biggest hobby is watching videos, especially interesting ones. I also enjoy trying different foods and doing some exercise.
ZP: Who is your favorite entrepreneur?
Jiajun: My favorite entrepreneur is Elon Musk. He is doing things that are more meaningful for the development of humanity. Entrepreneurship is an endless journey—once you complete one thing, there's always the next. The most interesting part is figuring out how to make the next thing even greater. What I think about the most is how to do something that will have an impact in history and on humanity. That's really fascinating to me.
Disclaimer
The content of this interview has been edited for clarity and brevity, with approval from Jiajun Lv. It reflects only the interviewee’s personal views. We welcome your thoughts in the comments. For more information about Jiajun Lv, please visit his homepage.
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