Name: Hyperspace: A Peer-to-Peer Artificial Intelligence Network
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Hyperspace: A Peer-to-Peer Artificial Intelligence Network

“Hyperspace: A Peer-to-Peer Artificial Intelligence Network” is an open standard protocol designed for distributed model inference, developed in response to stringent regulations imposed on large language models and the broader realm of artificial intelligence (AI) in the US. This protocol is a part of the initiative by HyperspaceAI to advocate for decentralization and to ensure the widespread availability and democratization of AI, without the constraints of the regulatory landscape.

Description

Hyperspace: P2Peer Artificial Intelligence Network

Key aspects of Hyperspace include:

Distributed Hash Tables (DHTs): These are foundational components in decentralized systems, enabling storage and retrieval of data across a distributed set of nodes without a central authority. This includes implementations like Kademlia DHT, S/Kademlia, and Suzaku and Kirin, each offering unique features for efficiency, security, and resiliency against various types of network attacks.
Equilibrium of Computation Exchange: The protocol is designed to incentivize network participants to share and exchange their computational power, akin to BitTorrent’s approach of “tit-for-tat”.
Hyperspace Protocol Design:
- Identity: Involves address assignment and message signing, using cryptographic techniques to mitigate attacks and ensure identity authenticity in a decentralized environment.
- Model: Covers aspects like threshold signature, hash functions, and the roles of Hyperspace community servers and Hyperspace inference nodes. It also includes mechanisms for fraud proof and a challenge model to maintain network integrity.
- Economics: The economic structure and incentivization mechanism drive entities to operate with integrity. This includes utilizing cryptoeconomic protections, possibly in collaboration with systems like Ethereum, to ensure network security.
Response to Regulatory Challenges: HyperspaceAI was created as a response to US policies that regulate AI, particularly large language models. These policies were seen as a threat to innovation and were especially challenging for open-source projects and smaller entities in the AI field.

HyperspaceAI represents an innovative approach to maintaining the functionality and growth of AI technologies in a regulatory environment that could potentially stifle innovation and centralize AI power in the hands of a few large entities. Through its decentralized nature, HyperspaceAI aims to keep AI accessible and robust, leveraging peer-to-peer network principles.