A Brief Analysis of AMMO White Paper: AI Agent Narrative Needs Upgrade

The market is waiting for an innovative "singularity" to be born.

Written by: Haotian

I took a moment to carefully read the new white paper of @Ammo_AI, and I was very impressed. Here are some of the inspirations:

The market's pursuit of AI Agent essentially lies in not being satisfied with AI as just a Copilot mode query tool, where AI answers what users ask, but should be more like a Buddy mode companion growth mode, capable of understanding, thinking, actively creating value, and pushing it to people. This is a key factor for AI Agent to be elevated to a narrative height;

2. The traditional web2 AI monolithic model started with the "tool-based practical utilitarianism", which easily forms data source islands in multi-modal collaboration, making it difficult to truly break through to the level of wisdom. Although web3 has proposed the autonomous ideology of AI Agent individuals, it is still far from achieving the goal. The autonomous decision-making of AI is much more complex than imagined. Letting AI assist in automatic learning and path recommendation, and enhancing AI's autonomous learning through feedback from humans, can truly become the dominant direction of the next AI Agent in the "symbiosis mode".

3. AMMO defines an abstract space called MetaSpace, so that all the data around the AI Agent can be deployed in the form of Vector vectors in the space, just like the blockchain originally defined Hash, and then all the protocols and applications on the chain were created. This form of starting with Vector can not only serve web3, but also be a framework standard suitable for web2 multimodality, and with the MAS multimodal collaboration system on top of it, it can change the current "think tank" orientation of AI in the academic direction to a "practical" orientation to practical application scenarios such as work, games, and education.

4. How to understand it in plain language? We view MetaSpace as a large shopping center, where each functional layer belongs to a SubSpace. Each area has different knowledge bases, and the Buddies system is an intelligent shopping guide system. Goal Buddies act as professional guides to select some high-quality products for you, while User Buddies are more like personal assistants that can provide customized solutions based on your consumption habits and budget. AiPP is like a general service desk, collecting feedback and suggestions to improve service quality.

Overall, to make the AI Agent operate through essential components such as MetaSpace+Buddies+AiPP human-machine feedback system, truly accelerate the mass production and practical implementation of AI Agent;

5. The white paper further demonstrates a chain-based AI Agent multimodal collaboration framework and engineering implementation ideas, some combination chain-defined standards, including ID identity system, Memory memory system, Character feature system, Context context management, Oracle oracle system, etc. The definition of components still needs further exploration (the general standard framework of "chainization" that I often mentioned before);

Above.

Arguably, this is the most emotional and pragmatic project in terms of macro architecture, application landing, and engineering implementation in recent times. However, after reading the above, everyone may feel confused and abstract. Yes, the path to the widespread adoption and application of AI Agent is longer than imagined, but more and more excellent teams are indeed joining in, and some innovative solutions and ideas are also brewing. The market is waiting for the birth of an innovative "singularity."