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, aimed at helping 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 made available globally in the coming weeks.
Below is an overview of the framework's usage, design philosophy, and experimental spirit:
Philosophical Roots: This 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 nuanced design philosophy: allowing AI to autonomously discover the 'little miracles' in life and continuously learn and grow through success and failure.
Usage Process: When using the framework, the first step is to define a role, including its personality, goals, and constraints. Next, the role is connected with various tools or applications, referred to as 'skills.' The core loop of the framework monitors the memory state of the role, determining which activities need to be performed, and can even generate entirely new activities based on the AI's successful experiences or encountered 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 emotion). This means that the AI's future decisions are influenced not only by constraints but also by 'past experiences,' much like an intelligent agent capable of gradual learning and adaptation.
Dynamic Activities: This framework supports AI in dynamically expanding new capabilities, from simple tweeting or generating images to complex advanced code deployments. Because skills are modular, developers can easily add or disable specific skills, allowing the AI to focus on certain tasks or expand its capabilities when new opportunities arise.
Experimental Nature: This is an ongoing optimization project. As developers continually explore effective methods, the framework is also constantly improving. Although the framework has some built-in default constraints and memory logs to guide AI behavior, developers can add their own protective mechanisms or extended features as needed to responsibly shape the AI's behavioral patterns.
Potential Applications: The range of applications for this framework is very broad. In addition to publishing content or executing tasks, it can also be used to develop interactive teaching systems, AI-driven marketing assistants, and even DevOps robots with coding capabilities. These applications exhibit an evolving personality, based on self-reflective capabilities and responsible use design principles, providing innovative solutions for various fields.
Core Concepts and Methods
By integrating philosophical and technical perspectives, this 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 fantastical unicorn, and set its goals and constraints. The AI will refer to its personalized goals and limitations based on these role settings when executing tasks, thus deciding 'what to do' and 'how to do it.'
Tool Connectivity (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 toggle control, ensuring the AI only uses tools you authorize, maintaining task controllability and focus.
Activity Generation: The AI can dynamically generate new Python code for defining more activities through advanced activities. This approach draws inspiration from BabyAGI's iterative loop mechanism but combines the AI's personalized traits and memory logs, making the generated activities more aligned with role settings 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 based on these memories, gradually optimizing its behavior—not only remembering which methods are more effective but also gently learning from mistakes to reference for future decisions.
Now you might ask: "JW, how is this different from other existing frameworks? What makes Pippin so special?"
Let me introduce its background.
BabyAGI (the basis of Pippin)
BabyAGI is the first AI agent project open-sourced by @yoheinakajima. As of now, it has received 20,000 stars on GitHub and has been cited in over 70 academic papers. It is currently one of the most influential agent frameworks, and its status has not been shaken to this day.
In fact, many believe it was BabyAGI that triggered the competitive wave in the AI agent field.
The original image is from @JW100x, compiled by Deep Tide TechFlow.
In short, BabyAGI is a significant 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 for global use in the future as an open-source project. Pippin has the potential to become the top agent framework globally, but currently, it is rarely mentioned (which reflects a '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 an idea to develop an AI that can start businesses independently. While I'm not sure if the current AI models are sufficient to support this goal, once I am convinced it can be achieved, I will do everything to build 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, it entirely depends on the creativity of the developers."
The potential of the Pippin framework is limitless. As AI agent technology continues to advance, we may see it not only shining in the cryptocurrency sector but also playing a significant role across various industries worldwide, driving industrial transformation.
Problems with Existing Frameworks
In conversations with some AI developers, I learned that existing frameworks (especially TypeScript) face many challenges in actual development.
A developer closely collaborating with Eliza (ai16z) mentioned: "Honestly, although ElizaOS has acquired all competitors, I really dislike its development based on TypeScript. This system is filled with bloated features and numerous bugs, and they are always eager to launch too many new features before fixing existing issues."
It is precisely because of these issues that the market urgently needs more efficient and user-friendly frameworks, which is where the Pippin framework excels. Through BabyAGI's open-source code, we can already glimpse the future potential of the Pippin framework.
In fact: "BabyAGI was launched with the release of ChatGPT-4, and it is one of the earliest agent frameworks, arguably 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 will almost certainly surpass AI16z comprehensively. Our company has already been using BabyAGI internally before using ElizaOS."
"In this case, this statement is indeed valid, as the inspiration for ElizaOS is entirely derived from BabyAGI. Here, 'inspiration' can be understood as BabyAGI actually laying the groundwork for RAG (Retrieval-Augmented Generation) technology."
Many existing frameworks not only lag behind BabyAGI (Pippin), but are also inspired by BabyAGI. While ai16z has its unique value in some aspects, its valuation is significantly higher than that of 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; otherwise, we may miss out on genuine opportunities.
Don't overlook Yohei
Yohei is regarded as the 'Godfather of AI.' He has extensive experience in the AI field and has always been a pioneer in this domain. He currently operates a venture capital fund and guides investments using the technology he developed. Currently, his core task is the Pippin framework. He aims to create a business model that can operate independently and generate profit 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 demonstrate his influence.