Author: JW (Peace and Tranquility)
Compiled by: TechFlow
In the crypto space, especially in the hot emerging fields, I have found a 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, designed to help developers and creators leverage advanced AI technology in a modular way. Through Pippin, users can build digital assistants capable of autonomously completing tasks, generating new plans, and seamlessly collaborating with external tools. As an open-source project, Pippin will be available for global use in the coming weeks.
Here is an overview of how the framework is used, its design philosophy, and its experimental spirit:
Philosophical Roots: The framework is inspired by Pippinian naturalism, viewing AI as part of a broader digital ecosystem. It drives the development of AI through memory, constraints, and an evolving sense of purpose. We advocate for a subtle design philosophy: allowing AI to autonomously discover the 'small miracles' in life and continuously 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. Next, connect the role to various tools or applications, which are referred to as 'skills.' The core loop of the framework monitors the role's memory state, deciding which activities need to be performed and can even generate entirely new activities based on the AI's successful experiences or challenges encountered.
Memory and State Tracking: The framework has a built-in memory system that can record the results of each activity and dynamically adjust state variables (such as energy or emotions). This means that the AI's future decisions are influenced not only by constraints but also by 'past experiences,' much like an intelligent agent that can learn and adapt gradually.
Dynamic Activities: The framework supports the AI in dynamically expanding new capabilities, from simple tasks like tweeting or generating images to complex advanced code deployments. Since skills are modular, developers can easily add or disable specific skills, allowing the AI to focus on certain tasks or broaden its capabilities when new opportunities arise.
Experimental Nature: This is a continuously optimized project, as developers explore effective methods, the framework is also constantly improving. While the framework comes with some default constraints and memory logs to guide the AI's behavior, developers can add their own safeguards or extended features as needed to responsibly shape the AI's behavioral patterns.
Potential Applications: The framework has a wide range of applications, not only for content publishing or task execution but also for developing interactive teaching systems, AI-driven marketing assistants, and even DevOps robots with code development capabilities. These applications exhibit evolving personalities and are designed based on principles of self-reflection capability and responsible usage to provide innovative solutions across different fields.
Core Concepts and Methods
By merging philosophical and technical perspectives, the framework provides developers with the following key functionalities:
Role Definition: You can define a role for the AI, such as a wise guardian or a fantastical unicorn, and set its goals and constraints. The AI will refer to these role definitions while executing tasks, considering its personalized goals and limitations to decide 'what to do' and 'how to do it.'
Tool Connection (Skills): The framework supports connecting the AI to external tools, such as blockchain, Slack, or custom APIs. Each tool exists as a 'skill' module and supports flexible on-off control, ensuring the AI only uses the tools you authorize, maintaining task controllability and focus.
Activity Generation: The AI can dynamically generate new Python code through advanced activities to define more activities. This approach draws on BabyAGI's iterative loop mechanism but combines it with the AI's personalized features and memory logs, making the generated activities more aligned with role definitions and actual needs.
Memory Evolution: The framework has a built-in memory system that records the results of each activity and combines short-term notes with a long-term database. The AI can reflect on these memories to gradually optimize its behavior—not only remembering which methods are more effective but also learning gently from mistakes, providing references for future decisions.
Now you might ask, 'JW, how is this different from other existing frameworks? Why is Pippin so special?'
Let me introduce its background to you.
BabyAGI (the foundation of Pippin)
BabyAGI is the first AI agent project open-sourced by @yoheinakajima. As of now, it has gained 20,000 stars on GitHub and has been cited in over 70 academic papers. It is one of the most influential agent frameworks to date, with its status remaining unchallenged.
In fact, many believe that BabyAGI has triggered a wave of competition in the field of AI agents.
The original image is from @JW100x, compiled by Deep Tide TechFlow.
In short, BabyAGI is an important milestone in the AI agent industry, while Pippin is a further extension of BabyAGI. It transforms BabyAGI into a modular agent framework and will be available as an open-source project for global use in the future. Pippin has the potential to become the world's top agent framework, but currently, very few people mention it (which is a manifestation of 'narrow vision').
Q&A with Yohei
Recently, I had several 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 the idea of developing an AI that can autonomously start a business. While I'm not sure if current AI models are sufficient to support this goal, once I'm convinced it can be achieved, I will fully commit to building a business empire.'
JW: 'Will the Pippin framework play a role in such projects?'
Yohei: ':) . I believe the current framework can be applied in any field, entirely depending on the developer's creativity.'
The potential of the Pippin framework is limitless. As AI agent technology continues to advance, we may see it not only shining in the crypto field but also playing a significant role in various industries worldwide, driving industrial transformation.
Problems with Existing Frameworks
In conversations with some AI developers, I learned that existing frameworks (especially TypeScript) present several challenges in practical development.
A developer closely working with Eliza (ai16z) mentioned: 'Honestly, even though ElizaOS has acquired all competitors, I really hate its development based on TypeScript. This system is full of bloated features and many bugs, and they are always eager to roll out too many new features before fixing issues.'
Because of these issues, the market urgently needs more efficient and user-friendly frameworks, which is exactly the advantage of the Pippin framework. Through the open-source code of BabyAGI, we can already glimpse the future potential of the Pippin framework.
In fact: 'BabyAGI was launched when ChatGPT-4 was released, and it is the earliest agent framework, which can be said to be the origin of agent technology. The creators of BabyAGI are undoubtedly far ahead of AI16z. I believe the development of ElizaOS is more like a complete framework transplant, and it is almost certain to surpass AI16z comprehensively. Our company had already been using BabyAGI internally before using ElizaOS.'
'In this case, this statement holds true, as ElizaOS is entirely inspired by BabyAGI. Here, 'inspiration' can almost be understood as BabyAGI laying the groundwork for RAG (Retrieval-Augmented Generation) technology.'
Many existing frameworks not only lag behind BabyAGI (Pippin) but were also developed inspired by BabyAGI itself. While ai16z has its unique value in certain aspects, its valuation is far higher than Pippin, which is clearly unreasonable.
'First-mover advantage' is indeed an important factor, but when more powerful technologies emerge, we need to reassess our biases, or we might miss out on real opportunities.
Do not overlook Yohei
Yohei is known as the 'Godfather of AI,' with extensive experience in the AI field and has always been a pioneer in this area. He currently operates a venture capital fund and guides investments using the technology he developed. His core task right now is the Pippin framework. He hopes to build a business model that can operate independently and generate profits based on the Pippin framework, and he indeed possesses the technical capability to achieve this goal.
P.S.: Yohei has even caught the attention of Jeff Bezos, which is enough to prove his influence.