Original title: Pippillions
Original author: JW (Peace and Tranquility)
Original translation: TechFlow
In the crypto space, especially in those hot emerging fields, I have found a very common phenomenon: many people tend to become too focused and ignore other possibilities after finding a "good project" and seeing it rise quickly. Although this may bring benefits in the short term, when the external environment changes, if you cannot adjust in time, problems may arise.
I think it is naive to think that the current leader in an emerging field that has only been around for 4 months can maintain its lead for long term, especially when better developers and technologies are constantly emerging.
Pippin Framework
Pippin is an AI agent framework developed by @yoheinakajima that aims to help developers and creators leverage advanced AI technologies in a modular way. With Pippin, users can build digital assistants that can complete tasks autonomously, generate new plans, and work seamlessly with external tools. As an open source project, Pippin will be available to the world in the coming weeks.
The following is an overview of the framework’s usage, design philosophy, and experimental spirit:
Philosophical roots: The framework is inspired by Pippinian naturalism and views AI as part of a broader digital ecosystem. It drives AI development through memory, constraints, and an evolving sense of purpose. We advocate a delicate design philosophy: let AI discover the "little miracles" in life on its own and learn and grow through success and failure.
· Usage process: When using the framework, you first need to define a role, including its personality, goals, and constraints. Then, connect the role to various tools or applications, which are called "skills." The core loop of the framework monitors the role's memory state, determines which activities need to be performed, and can even generate new activities based on the AI's successful experiences or challenges.
Memory and state tracking: The framework has a built-in memory system that records the results of each activity and dynamically adjusts state variables (such as energy or emotions). This means that the AI's future decisions are not only determined by constraints, but also influenced by "past experience", just like an intelligent agent that can gradually learn and adapt.
Dynamic Activities: The framework enables AI to dynamically expand new capabilities, from simple tweets or image generation to complex advanced code deployments. Because skills are modular, developers can easily add or disable specific skills, allowing AI to focus on certain tasks or expand its capabilities when new opportunities arise.
Experimental: This is an ongoing project, and the framework is constantly improving as developers continue to explore effective methods. Although the framework has some default constraints and memory logs built in to guide the behavior of AI, developers can add their own protection mechanisms or extend functions as needed to shape the behavior of AI responsibly.
Potential applications: The application scope of this framework is very wide. In addition to publishing content or performing tasks, it can also be used to develop interactive teaching systems, AI-driven marketing assistants, and even DevOps robots with code development capabilities. These applications have evolving personalities and provide innovative solutions for different fields based on the design principles of autonomous reflection and responsible use.
Core concepts and methods
By combining philosophical and technical perspectives, the framework provides developers with the following key features:
Role definition: You can define a role for the AI, such as a wise guardian or a fantasy unicorn, and set its goals and constraints. The AI will refer to its personalized goals and constraints when performing tasks based on these role settings, thus deciding "what to do" and "how to do it".
· Tool connection (skills): The framework supports connecting AI to external tools, such as blockchain, Slack, or custom APIs. Each tool exists as a "skill" module and supports flexible switch control to ensure that AI only uses the tools you authorize, keeping the task controllable and focused.
Activity generation: AI can dynamically generate new Python code from high-level activities to define more activities. This approach draws on the iterative loop mechanism of BabyAGI, but combines AI’s personalized features and memory logs to make the generated activities more in line with role settings and actual needs.
Memory Evolution: A memory system is built into the framework that records the results of each activity and combines short-term notes with a long-term database. AI can reflect on these memories and gradually optimize its behavior - not only remembering which methods are more effective, but also gently learning from mistakes to provide reference for future decisions.
Now you might be asking: “JW, how is this different from other existing frameworks? Why is Pippin so special?”
Let me give you some background on it.
BabyAGI (the basis of Pippin)
BabyAGI is the first AI agent project that @yoheinakajima has open-sourced. So far, it has received 20,000 stars on GitHub and has been cited in more than 70 academic papers. It is one of the most influential agent frameworks, and its status remains unshakable.
In fact, many believe that BabyAGI sparked a wave of competition in the field of AI agents.
The original image is from @JW100x and compiled by TechFlow.
In short, BabyAGI is an important milestone in the AI agent industry, and Pippin is a further extension of BabyAGI. It transforms BabyAGI into a modular agent framework and will be open sourced for global use in the future. Pippin has the potential to become the world's top agent framework, but few people are talking about it yet (this is a manifestation of "narrow vision").
Q&A with Yohei
I recently had some interesting exchanges with @yoheinakajima. He allowed me to share some of the questions and answers:
Yohei: “For the past two years, I have been exploring an idea to develop an AI that can start its own business. Although I am not sure whether the current AI model is good enough to support this goal, once I am sure it can be achieved, I will go all out to build a business empire.”
JW: “Will the Pippin framework play a role in a project like this?”
Yohei: “:). I think the current framework can be applied to any field. It all depends on the creativity of the developers.”
The potential of the Pippin framework is limitless. As AI agents continue to advance, we may see it emerge not only in the crypto space, but also in a variety of industries around the world, playing an important role in driving industrial change.
Problems with existing frameworks
In my communication with some AI developers, I learned that existing frameworks (especially TypeScript) have many difficulties in actual development.
A developer who works closely with Eliza (ai16z) mentioned: "To be honest, even though ElizaOS has acquired all its competitors, I really hate that it is based on TypeScript. The system is full of bloated features and a lot of bugs, and they are always eager to launch too many new features before fixing the problems."
Because of these problems, the market urgently needs a more efficient and easier-to-use framework, and this is where the Pippin framework comes in. Through BabyAGI's open source code, we can already get a glimpse of the future potential of the Pippin framework.
In fact: “BabyAGI was launched when ChatGPT-4 was released. It is the earliest intelligent agent framework and can be said to be the origin of intelligent agent technology. The creators of BabyAGI are undoubtedly far ahead of AI16z. I think the development of ElizaOS is more like a thorough framework transplant, and it will almost certainly surpass AI16z in all aspects. Our company has used BabyAGI internally before using ElizaOS.”
“In this case, that statement is true, because ElizaOS is completely inspired by BabyAGI. The “inspiration” here can almost be understood as BabyAGI actually laid the foundation for RAG (Retrieval-Augmented Generation) technology.”
Many existing frameworks are not only inferior to BabyAGI (Pippin), but are even inspired by BabyAGI. Although ai16z has its own unique value in some aspects, its valuation is much higher than Pippin, which is obviously unreasonable.
“First-mover advantage” is indeed an important factor, but when more powerful technologies emerge, we need to re-examine our biases, otherwise we may miss real opportunities.
Don't Ignore Yohei
Yohei is known as the "Godfather of AI". He has extensive experience in the field of AI and has been a pioneer in this field. He currently runs a venture capital fund and uses the technology he developed to guide investments. At present, his core task is the Pippin framework. He hopes to build a business model based on the Pippin framework that can operate independently and continue to make profits, and he does have the technical ability to achieve this goal.
P.S.: Yohei even got the attention of Jeff Bezos, which is enough to prove his influence.
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