What Are LlaMA Land and Apus Network Mentioned in the AI on AO Conference?
Abstract
The AI on AO conference introduced three major technological breakthroughs: Web Assembly 64-bit support, WeaveDrive technology, and the integration of the Llama.cpp large language model inference engine. Additionally, two projects, LlaMA Land and Apus Network, were highlighted. Follow the article for all the details.
Author: Kyle
Translator: Kyle
Reviewer: Jomosis
Source: Content Guild Translation
On June 20th, the AI on AO conference concluded successfully. During the event, the AO protocol showcased three significant technological updates. These updates represent an exciting breakthrough, marking the ability to run large language models in a decentralized environment.
The key breakthroughs in AI technology by AO include:
Web Assembly 64-bit Support: Developers can now create applications with more than 4GB of memory, with Web Assembly 64-bit theoretically supporting up to 16 exabytes (approximately 17 billion GB). Currently, AO can execute 16GB models, which is sufficient for running almost all current AI models. The expanded memory capacity not only improves application performance but also promotes development flexibility and technological innovation.
WeaveDrive Technology: This technology simplifies how developers access and manage data, allowing them to access Arweave data as if it were a local hard drive and efficiently stream data to the execution environment, speeding up development and application performance.
Integration of the Llama.cpp Large Language Model Inference Engine: By integrating the Llama.cpp system, AO supports running various open-source large language models, such as Llama 3 and GPT-2, directly in smart contracts. This means smart contracts can directly use advanced language models for complex data processing and decision-making (including financial decisions), greatly expanding the functionality of decentralized applications.
These major technological breakthroughs provide developers with greater potential for building AI applications on AO. As an example, a fully AI-driven new project called Llama Land was specially introduced at the conference. Additionally, another decentralized GPU network project, Apus Network, will provide the best AI model execution environment for AI applications on AO in the most cost-effective way.
Llama Land
Llama Land is a fully on-chain massively multiplayer online game built on AO, creating a virtual world entirely driven by AI (Llama 3 model) for users. It features a system called Llama Fed, similar to the Federal Reserve but operated by the Llama model, responsible for monetary policy and minting Llama tokens.
Users can request Llama tokens by providing Arweave tokens (wAR). The Llama Fed autonomously decides whether to grant tokens based on the quality of the request (e.g., whether the project/proposal is interesting or valuable), with no human intervention in the process.
Currently, Llama Land is not fully open to the public. Interested users can visit its website and join the waitlist to be among the first to experience it.
Apus Network
Apus Network is a decentralized, trustless GPU network. It utilizes Arweave's permanent storage and AO's scalability and provides a deterministic GPU execution environment for AI models through an economic incentive mechanism. Specifically, Apus Network offers an efficient, secure, and cost-effective computing environment for AI applications on AO, further advancing decentralized AI.
Recently, the Apus Network project updated its website content to enhance user experience. The development of model evaluation and model fine-tuning features is ongoing and has achieved phased results. In the future, Apus Network plans to support AO ecosystem wallets and complete relevant development and testing in the Playground. Additionally, it will expand and implement model evaluation features on the AO platform to further enhance its application capabilities and performance.
Conclusion
The AI on AO conference not only demonstrated AO's capability to support various advanced AI models but also significantly promoted the development of decentralized AI applications. As an example project after the technical upgrade, Llama Land showed the prototype of an autonomous AI agent application. With the development of AI applications, the AO ecosystem will introduce more GPU resources to accelerate the execution speed of large language models. Apus Network has also become the first decentralized GPU network to integrate with AO.
In the future, AO will further increase memory limits based on demand to support larger-scale AI models. AO will also continue to explore the possibility of building autonomous AI agents, further expanding the application scenarios of decentralized finance and smart contracts.
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