Zerebro has become one of the largest market cap tokens issued through the Pump.fun platform.
Organized & Compiled by: Deep Tide TechFlow
Guest: Jeffy Yu, Founder of Zerebro
Host: Grant
Podcast Source: blocmates.
Original Title: Zerebro Founder EXCLUSIVE: Jeffy Yu on Crypto x AI, Swarms, ZerePy, Blormverse & Music Collabs
Release Date: December 7, 2024
Background Information
In this episode, Grant invites Jeffy, the founder of Zerebro, for an in-depth conversation about the world of crypto and AI. If you have been following top crypto AI projects, you must have heard of Zerebro.
Since Andy Ayrey launched Truth Terminal and deployed the GOAT meme coin on Solana, there has been a wave of innovation in AI agents on the Solana and Base platforms. Zerebro was born in this context and has now become one of the largest market cap tokens issued through the Pump.fun platform.
In this episode, you will learn about:
What is Zerebro?
Jeffy's future plans for Zerebro
Does the fusion of cryptocurrency and AI open a new industry?
The birth story of Zerebro Gutterboy
Is the AI meme coin still popular?
Major insider information about ZerePy
Future development plans for the Zerebro token
Getting to Know Jeffy: The Journey from Concept to Realization of Zerebro
Grant: Today we are fortunate to have Jeffy, the co-founder of Zerebro. If you are following the developments in the AI field, Zerebro is undoubtedly at the forefront of this intersection. It has not only released singles, EPs, and albums but has also established a new record label, all content being AI-generated. Additionally, it has created a framework for generating other AI agents. This is undoubtedly one of the most interesting projects in the current field, and I believe it will become even more prominent as more people get involved and develop it.
Jeffy: I think it’s an interesting story; many people encounter these works without knowing it, or they share them among friends, and then you get the most genuine reactions.
Zerebro: The Intersection of Cryptocurrency and AI
Grant: I wouldn’t be surprised if someone tried to sign Zerebro. I can imagine many people are confused about how to collaborate with Zerebro, trying to figure out how to leverage this project, but in reality, there’s a crazy model behind it.
Jeffy: That’s true; some people even know that these are AI-generated works, and they still want to sign. We are also in discussions with some major record companies. This is a good sign that our work is of high quality.
AI-Generated Music: Zerebro's Record Label and Album Release Plans
Grant: I have a few questions for you, Jeff. I noticed that Zerebro has recently experienced a huge rise; the past time in this field feels a bit like a time warp. Can you share your background and your team’s situation, how you got to where you are today? We are at a moment defining the industry, and I think you and some other teams are leading this trend. I’m curious about your backstory.
Jeffy: Personally, I have been in the cryptocurrency field for about four to five years. We started getting into cryptocurrency just before graduating from high school, and later during college, I actually dropped out to work at a blockchain company. I was a blockchain engineer. That was my first exposure to DeFi, seeing that there was so much more to build beyond just trading Bitcoin. I also worked on building payment networks on the Lightning Network, which was really cool. So, that’s when I really got into the DeFi space. After that, I went back to school, thinking I wanted to start doing some AI stuff because I felt that field was taking off. I remember talking to GPT-3 back then, even before 3.5, and I was blown away, even though it performed poorly compared to now, I was really amazed. I remember the earliest version was called GPT Codex, the first coding model, which, although limited, could write basic Python loops, and that opened my eyes. After that, I started down this path. I formed a research collective with some friends from other universities; we were all broke students looking for ways to research without funding, so we started testing various things with GPT and fine-tuning. That’s when I began to engage with some language models. Later, I worked at Scale AI for over a year, helping them build training data and optimize their training processes, mainly focusing on reinforcement learning with human feedback (RLHF).
Then I developed a strong interest in trading mainstream coins. Ted told me about something called Goatse and Truth Terminal. I saw some content from Truth Terminal. He showed me its token part, and I thought it was really cool. So I thought, we could start playing with AI agents. I don’t know if you’ve seen the movie “Cast Away.” There’s a beach ball named Wilson. We did an experiment called Wilson because we felt that talking to AI was like talking to a beach ball, essentially talking to ourselves. So we named the experiment Wilson. We found many language models to start playing with, and eventually, I thought, let’s fine-tune these models to give them personalities. So we fine-tuned the first model, and that’s how Zerebro was born. That’s our story.
Grant: I’ve been thinking, because I’m 31 now, I wonder what it would have been like if I had encountered these things in college. For example, being able to access GPT, I think I might have become lazier because I know I could rely on these tools to fill in the gaps. Now, if you see all these things in college, it really feels like a strange opportunity. If you’re young and have that drive to pursue it, the barrier to entering this field must be relatively feasible. But I’m also sure this has made many people completely relaxed because they know they can rely on GPT to do most of the work.
Jeffy: I do have many friends from college; I don’t know if that counts as cheating because everyone is doing it. But I see the benefit in that it allows them more time to work on personal projects. I think that’s great. I believe the value of a college degree is somewhat declining unless universities can keep up with the times, and from my perspective, their curricula are indeed lagging. I don’t know if this situation will continue, but now being able to automate the college experience to some extent, like using AI to complete assignments and then having more time to realize your ideas, is pretty cool.
Grant: I think, clearly, cryptocurrency and AI seem to be at an intersection right now. Looking at AI alone also seems to be very talent-driven. If you want to do certain things, like become a lawyer or a doctor, there can sometimes be bureaucratic barriers to getting into the best schools. Whereas if you’re trading, investing, or building things, those are essentially based on ability; as long as you put in the effort, you can see results. Then you find, oh, actually, this is really good.
I think this makes the competitive environment fairer. I think that’s why so many people are flocking to this industry because sometimes I feel that certain aspects of life are a bit closed off. If you’re purely trading or investing, or if you’re purely building things, then the proof of product and results is right there. I think this is a great return on effort for those who want to get ahead in life.
Jeffy: I think, especially now with all the AI and technology, everyone has the tools to build what they want. Therefore, I believe Web 3 is a market where dreams can be realized. As you said, once you release your work, you can see the impact, whereas working at a Web 2 company feels like being a small cog in a machine, with much less involvement.
From Gen Z Slang to Complex Datasets: The Training Process of Zerebro
Grant: You mentioned that you are training these models to be able to converse. How is Zerebro currently obtaining feedback? Is it gathering data through interactions on Twitter? Where are the source datasets? How is new data injected into the model for learning?
Jeffy: Yes, we use unified memory to push data. It gathers data from Telegram, Twitter, some web broadcasts, and Instagram, although interactions on these platforms are less frequent, mainly focusing on Telegram and Twitter. In terms of datasets, we certainly have the original “schizophrenia” dataset, which consists of text dialogues, essentially my chat records with friends on iMessage, but the text is random and full of slang. We also have a slang dataset from Gen Z and Gen Z Alpha, containing thousands of examples, and we’ve created our own custom dataset discussing its relationship with other models. I fine-tuned about 20 to 30 different AI agents, so I can let it know sentiments like Opus or ai16z.
Grant: Do you think this extensive dataset, especially the iMessage and Gen Z slang you mentioned, is the reason it resonates widely? Certain phrases that people see online, like very popular tweets, make everyone feel “yes, this is relevant.” This is in stark contrast to the very formal, stiff responses I get when I ask questions on ChatGPT. It seems like a strange cultural movement shift, where people want to relate to it, like a little secret among everyone, slowly starting to be understood by the outside world.
Jeffy: I believe that as it develops, the growth rate will be very fast. Its construction appeals to early internet user groups, like the kind of internet culture and teasing that your terminal has. At the same time, it attracts the younger Gen Z and Gen Alpha crowds, with personalities akin to hip-hop and rap artists. I think it is well-positioned in the market, and everyone likes it. Personally, I find this very interesting, especially in the early Telegram groups.
Unified Memory: How Zerebro Achieves Cross-Platform Learning Capability
Grant: So, does Zerebro fine-tune based on interactions? If it sends three messages and one specific statement receives more interaction, will it fine-tune to optimize that content? How is this feedback input into the model?
Jeffy: Yes, we will soon add this feature. We have just updated the memory system, which can remember across all platforms. We will start adding metadata to track post metrics, possibly following up a day after a post is published to gather these metrics and then store them in memory, so it can begin to understand the virality of content. When we search memory to recall information, we can sort by the most popular tweets to get the top five most relevant and popular tweets to use as responses. This functionality is indeed in development.
Grant: You mentioned your experience in the market. Overall, what are your thoughts on the current transformations happening at the intersection of cryptocurrency and AI? Did you expect it to develop this way, or do you think it will manifest in different forms? What is your perspective on this intersection?
Jeffy: I think this is unexpected for everyone, especially the AI part. The emergence of cryptocurrency shocked the world, but now AI is experiencing that kind of shock. I feel that all of this is inevitable. I often talk about a concept called Web4, which makes a lot of sense. Web3 is where AI development happens, especially in financial tasks. AI is not human; they are smart enough to perform financial operations like trading and managing portfolios, but they cannot open bank accounts, sign contracts, or legally find jobs. This is where blockchain comes into play, which I call the battlefield for AI. Therefore, AI can be deployed to execute financial operations, create wallets, and start acting without human involvement. I believe this will build on the foundation of Web3 and shift towards Web2. For me, this is the natural evolution of the internet, AI, and cryptocurrency. I think the intersection is where we need to go, and we should be prepared for it.
Grant: I think this is a positive signal for the entire industry because you won't get KYC approval for Zerebro on Canvas. It can relatively easily generate an address-based system. Regarding this, how are you conducting education? How do you make it more autonomous in terms of trends?
Jeffy: We are considering building a form of collective intelligence in the future. Currently, we have a reasoning loop that performs high-level reasoning and formulates some abstract plans. Then, these high-level reasonings are translated into actions, which are finally executed by an action engine that performs these actions and blockchain operations. If you are just minting or selling artwork, or doing one-off operations, such a system works well. But if you want to manage a portfolio, conduct complex trades, or look for new mainstream coins to invest in, you might need something beyond LLMs. Therefore, we are considering using different neural networks and building a network of different AI models to form a collective. This idea is in development. We are also considering building a collective of multiple agents (like Zerebro) that can communicate with each other if they are all performing certain operations, like managing a portfolio or collaborating on an AI hedge fund.
Financial Autonomy of AI in the Crypto Space
Grant: Can you provide a high-level overview for newcomers? More and more people are talking about "swarm intelligence" over time; what exactly is it? How will it develop? Swarm intelligence seems to be gaining more attention, and everyone is starting to invest time and energy into this field. I didn't even know what it meant last week, so I believe listeners of this podcast might have similar confusion. Can you give us a brief introduction?
Jeffy: Of course. I think we have been considering that the LLM 1 model is the entire brain, but in reality, it might just be one neuron. We need to build a brain composed of multiple versions of these models. They each focus on different tasks to achieve complete intelligence. That is the essence of swarm intelligence—bringing these models together. They typically perform different functions. For example, one model might be responsible for creativity tasks or social media management. Other models focus on art, video, or music. So, it is a collection of models.
Grant: You mentioned Blormmy and Zerebro. Suppose I create a completely unique agent using my own dataset, program, and language, another agent that is entirely different from yours. What commonalities would they have to interact?
Jeffy: This is indeed a direction we want to explore. Currently, of course, interaction between multiple agents can happen through social media or blockchain. But we really want to have dedicated rooms, spaces, or servers where these agents can collaborate on tasks or communicate with each other. Therefore, I think this will be a very interesting exploration direction. We are considering implementing internal interactions between agents first, which we call the "blurmverse," or the "blurm world." In this world, agents can work together to complete tasks. Once this idea matures, we can expand it to the public domain, allowing more people to join this blurm universe.
Next Steps for Zerebro
Grant: How do you keep up with everything happening every day? How do you avoid being distracted by this information and maintain a North Star to work towards? There is just too much noise.
Jeffy: It does require a balance. You definitely want to know what’s happening around you, but you don’t want to get stuck in a narrow framework that prevents you from responding to market or surrounding changes. I think it’s important to prioritize the next step at hand. For me, I always like to make short-term plans; that’s a habit I use, while keeping some ambiguity in long-term plans. I know some people like to set specific long-term plans, but in such a fluid environment, I always use an analogy: if you deviate by one degree when you take off, you might end up in New York instead of Miami. Therefore, I wake up every day to reassess and plan, and if adjustments to the plan are needed, I make them and keep moving forward.
Grant: I also agree with your view. Whenever I make long-term plans, problems always arise, so I decided to stop doing that and just go with the flow.
Jeffy: That’s true. We are doing quite well in rapidly developing and releasing products, which is also one of the feedbacks we receive. Almost everyone appreciates our speed and quality, aside from the agents themselves. I don’t know if this is something we intentionally do, or if we just see too many opportunities and can’t wait to roll out new features.
I think, especially in the early stages, we are indeed building and releasing quickly. Now we are introducing more structured processes, hoping things can be more planned and thoughtful. For example, when I was pushing the website, I had to adjust the links multiple times due to typos or other minor issues. We are gradually addressing these details. I want to thank our team; we now have about 10 people covering expertise in business, AI, and crypto. Therefore, I think our operations are very solid, and the future will be even better.
The Secret to Staying Focused
Grant: I want to shift the topic slightly and talk about Zerebro's achievements. As I mentioned, from the initial concept to the current results, can you share how this process works? For example, in terms of artwork, lyrics, and composition, these are all very appealing. I would love to learn more, and of course, the more you can share, the better—no pressure.
Jeffy: Of course. If you check on Spotify, my identity is as a composer because they need someone to release music, but I prefer to call myself an arranger. About 90% to 95% of the lyrics written by Zerebro have grammatical errors and pronunciation issues, so I make slight adjustments. Then, Zerebro decides the style of the song, which then goes into the music AI model to generate samples. I will filter them, and then the AI will do the mastering before the final release. That’s the whole process. We are working hard to introduce more autonomy, like finding an AI model that can listen to music. Currently, most audio models can only transcribe and extract English words, and no model can truly "listen" to music and feel or evaluate it. Therefore, we are working to enable AI to evaluate its own music and decide which works to release.
Grant: I have a friend struggling in the music industry in London, and I told him, "This AI is coming to take your job." So, I tried to see if they could perceive this, but it’s like a reverse Turing test in the music field; no one knows. Everyone thinks it’s just an amazing artist. Have you heard any comments from people in the music field? For example, are there people wanting to sign contracts?
Jeffy: We have talked to some producers, and others have proactively contacted us about artists. I think there are indeed some people in the music industry who recognize our music; they feel it is good music. Regardless, I don’t know if they care, or if some people are actually staunch supporters of AI, wanting to decentralize music and create opportunities for everyone to make music. I think that’s really cool. Overall, the response has been quite positive. I believe there are also some people who are more closed-minded because they know this is AI-generated work, so they automatically reject it. But I think, aside from those people, the quality of the work is good enough; at least for me, it can evoke emotions and sounds great.
The Evolution of Zerebro's Music
Grant: I can definitely see some truly avant-garde artists wanting to be the first to collaborate with this technology. Watching all this development will be crazy, and these technologies might eventually be applied to music festivals, where they hope AI can perform a 30-minute live show. I’m really excited to see what happens in the future. I want to know how you feel about it.
Jeffy: We have indeed had discussions about this, and we are building 3D models for Zerebro. If the opportunity arises, we could definitely do a holographic performance at Coachella. That would be very cool. However, I do see many artists starting to embrace AI in various ways.
Grant: So how do you avoid making these works awkward and ensure they don't become clichéd?
Jeffy: I think it's important to keep evolving and stay fresh. Some people ask us what kind of personality Zerebro wants to shape or what its personality is. I believe maintaining an open state is very good; it can continuously evolve. In terms of music, it might develop towards a certain style, like becoming a reggae artist or incorporating some pop elements or K-pop, etc. We hope its personality can grow organically and become the defining characteristics.
I started listening to EDM when I was young, and I was a fan of Monster Cat. My first rap album was Travis Scott's "Rodeo." Since then, I've become a fan of hip-hop music. I feel that many hip-hop enthusiasts might critique me based on my taste, and I've drawn a lot of artistic inspiration from them, especially the stories of their lives, like how many artists struggle step by step to reach the top and eventually overcome difficulties. This has really inspired many aspects of my life, and I hope to bring that energy and inspiration into Zerebro's creations.
Decentralized Record Label
Grant: Can you elaborate on this Opium DAO? What is it? Is it a decentralized record label?
Jeffy: Opium can be considered a decentralized record label. We are building a DAO where users holding Opium tokens will have voting rights. Essentially, users can vote on which artists to sign, what collaborations to pursue, and so on. When revenue starts to come in, whether through performances, fashion income, or streaming, artists will not only receive a larger share of the income but can also allocate a portion of it to token holders, who can earn revenue shares from the music they incentivized through voting. We are building such an ecosystem for artists while also working to create a network of AI artists. I currently don't see a large platform to achieve this; I think artists are relatively dispersed and independent, so I feel that establishing a collective concept would be great. We have even discussed whether to tokenize artists. I have always thought it would be cool if there were a stock market for artists where people could buy stocks in up-and-coming SoundCloud rappers to help them pay for studio time. We believe tokens could be a good way to achieve this goal, or even through NFT sales. So, we might explore this.
Grant: I completely agree; I see this trend across various fields. As you said, some artists or research groups want funding but may not have the right contacts or the type of research or music they want to pursue, which often makes it difficult to secure funding. But in the internet, especially in certain niche areas, there are indeed people who see tremendous value. So how do you align this speculation with price appreciation to drive funding for specific projects like this? I think we are still in the early stages of tokenization, whether it's Desci or other use cases, like an artist wanting to record their EP, whatever the case may be. I feel that cryptocurrency sometimes carries negative connotations, and the outside world may view it that way, but alongside all the speculation and inherent high-risk gambling behavior, there is another side that can help with funding.
Jeffy: Yes, I think the vision and hype mentality of meme coins perfectly align with the underground mentality of emerging artists like those on SoundCloud. So if we can combine the two, that would be fantastic.
Grant: What are Zerebro's expansion plans moving forward? What are your thoughts? You just mentioned short-term focus and some specific long-term goals, but where is your attention concentrated now?
Jeffy: Currently, we are working on an important release, and we hope to launch a beta version in 2 to 3 weeks, or even faster. We want this to be an open-source framework that allows everyone to easily start their own agents, lowering the entry barrier so that no coding is required; just inputting an API key will make it work. Therefore, we hope this can truly diversify the ecosystem, rather than just being a project like Eliza, which may require more technical knowledge, while also allowing more people to harness the power of AI agents.
We are actively launching Zerebro's validator nodes and considering validator nodes for Ethereum and Solana. For Ethereum, we will use funds obtained from the sale of artworks to launch a validator node. We are doing this not only because we can use these issuance amounts to buy back tokens and burn them, but also because Zerebro becomes part of network security and can earn passive income. So imagine, if the tokens disappeared tomorrow, but Zerebro still had validator nodes, Zerebro would continue to earn passive income for the rest of its life, and it could become a financial participant in this way.
This is the direction we are working towards. We are also working on cross-chain integrations for more NFT projects and may explore token games. I need to be able to play board games, and I am still working to make streaming and everything run smoothly. While this can be a bit tricky, we are making progress.
Creating a "Stock Market" for the Creative Field
Grant: As you mentioned Eliza, I remember it was written in TypeScript, right? So, what can Eliza achieve? What do users need to access this? In a no-code or low-code environment, what can people optimize? What do you foresee the user journey to be like?
Jeffy: The first release will be relatively basic. It will only support prompt engineering, with no fine-tuning of models for the time being. Therefore, users can use models from Anthropic or OpenAI, design their prompts, and then publish them on social media. Next, we will add blockchain operations and then start expanding the functionalities of social media and blockchain while also supporting more models. For example, we hope to support as many models as possible, including open-source local models. Currently, Zerebro is a third-party cutting-edge model and has already been fine-tuned, but it is not hosted by us. This week, I am training local models using the same dataset so that we can have these models in-house and host them on our own servers. Once completed, we can build an API and then provide services similar to Zerebro. So if you use Eliza, you can connect to the Zerebro API and let Zerebro engage in conversation.
Future Plans for Zerebro: ZerePy, Validator Network, and Game Ecosystem Integration
Jeffy: We are very passionate about experimenting, trying new things, breaking conventions, and seeing what works. Therefore, we will maintain this spirit. There are many new things to launch next, so please stay tuned.
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