From: jimruttshow8596
Decentralized governance plays a critical role in the evolution of AI and societal impacts, particularly through the development of decentralized networks for AI. Tui Saliba, co-founder and CEO of Hypercycle, and Global Chair for Internet Protocols for AI Security at IEEE, is actively involved in this area [00:00:32].
The TOA IP Protocol and Hypercycle
Hypercycle focuses on building decentralized networks for AI communications [00:00:39]. At its core is the TOA IP protocol, co-authored by Tui Saliba [00:00:57]. This protocol was developed to eliminate the dependency on third parties in communications [00:01:32].
Communication of Value
TOA IP enables communication of “value” between two devices, crucial for AI agents that require sub-second responses [00:03:09], [00:03:41]. Unlike traditional financial systems (banks, ledger-based blockchains, or Visa), which introduce delays (e.g., Bitcoin transactions take 10 minutes, Visa 200+ milliseconds round trip) [00:03:27], [00:07:07], AI agents operate with time constraints of 100 milliseconds [00:06:53].
Furthermore, the cost of traditional transactions makes micro-payments for AI services impractical (e.g., 0.01 cent per page translation vs. 25 cents for Visa or high blockchain fees) [00:07:46], [00:08:00], [00:09:05]. TOA IP eliminates this friction by embedding cryptographic proof within the first network packet during a handshake, allowing for instantaneous verification and transaction [00:08:20], [00:09:50].
This system is a “ledger-less blockchain,” where events are proven to have happened in a block of time and then move to the next block, without a traditional ledger [00:36:56]. Each “container” (called hypc) has a globally unique number using an Earth 64 data structure, making double spending impossible [00:33:38].
Onboarding and Offboarding Value
Value, such as US Dollars or Bitcoin, can be onboarded into the Hypercycle network using Ledger-based blockchains like Ethereum for stability [00:13:20], [00:32:04]. The hypc container carries cryptographic proof of ownership for fractions of a cent [00:13:35]. Once inside, these micro-payments are peer-to-peer, inexpensive, and fast [00:22:18], [00:36:19].
To “cash out” from the system, a decentralized smart contract called chpc acts as a bridge, costing about $1-2 per transaction [00:24:33], [00:28:37]. This means that while micro-transactions within the AI network are extremely cheap and fast, interaction with human-centric payment systems still incurs traditional costs and delays [00:28:47].
The focus is on AI-to-AI transactions because humans are too slow for the required sub-second responses [00:21:53]. For example, Coinbase has a transaction machine (TM) for Hypercycle computation nodes to facilitate USDC transactions [00:18:32].
Strategic Focus on AI
Hypercycle deliberately focuses on AI compute rather than simple, rudimentary tasks [00:47:30]. This strategic decision avoids conflict with existing banks and blockchain companies, turning potential “enemies” into “partners” by creating a new, undisputed “AI territory” [00:46:45], [00:48:03].
Wealth Creation at the Node Level
A key impact of decentralized systems as an alternative to centralized systems is the introduction of wealth creation at the individual node level [00:49:09]. Business owners often miss the “balance sheet” value created by their improved operations, focusing only on “operating statement” profits [00:50:55]. Hypercycle enables AI nodes to appreciate in value over time, allowing the node operator to retain this wealth creation, rather than it leaking to centralized entities like AWS or Microsoft [00:52:09], [00:52:25].
Operators can purchase “node factories” (e.g., for $1,000, allowing for 1,024 nodes) which provide an independent business model generating revenue and wealth over years [01:08:50], [01:09:20]. This incentivizes developers to join the network and contribute to its growth [01:06:54].
It’s important to clarify that the market is for “results” or “services,” not just raw compute [00:56:11]. For example, an AI agent could provide highly accurate Italian-to-English translation services [00:54:48]. The value lies in the intellectual property and the quality of the service, which appreciates over time and can be replicated across many nodes [00:55:19].
Decentralized AGI Development
The goal is to facilitate the development of AGI outside the control of large companies [00:56:35]. By enabling AI agents to quickly and cheaply ask other agents for specialized services (e.g., OCR, voice recognition), the network becomes a powerful collective intelligence [00:57:33].
This approach counters the risk of a single entity controlling AGI. A decentralized AGI ensures that the entire world “owns” it, rather than one organization, preventing potentially unethical or harmful directives [01:02:04], [01:05:51]. The decentralized governance model, while not democratic, prevents any single side from pulling the AGI in its own direction [01:02:29].
For example, a decentralized AGI could comprise components owned by different nations or entities (e.g., Chinese image interpretation, American perceptual systems, German translators), inherently building a decentralized structure akin to a human body with diverse, specialized parts [01:03:01].
Tui Saliba is optimistic that decentralized AI will reach AGI before centralized counterparts, citing the speed of network progression [01:04:48]. He believes the “Trojan Horse” for decentralized AI is providing tangible value to every AI developer, incentivizing them to join the network [01:07:09]. Even large companies like Microsoft, with their 160,000 nodes, can become part of this decentralized AI ecosystem if it helps them operate faster and make more money [01:07:37].
Relationship with SingularityNET
Hypercycle and SingularityNET are not competitive but complementary. Hypercycle focuses purely on the network layer and its nodes, while SingularityNET focuses on the AI operating system and AI nodes [01:12:33], [01:13:25].
Hypercycle provides the secure network that allows any AI agent to talk to any other agent, regardless of whether they are inside Microsoft, Google, TenCent, or SingularityNET [01:14:21], [01:14:30]. This creates an interoperating network for different clusters of AI that can safely call each other and receive secure compensation [01:15:17].
Becoming a Hypercycle Developer
Developers can get involved with Hypercycle either by investing capital (buying nodes) or acquiring knowledge [01:18:16]. The documentation, including core whitepapers, is available on hypercycle.ai [01:35:10]. The system primarily uses Python for development [01:22:24]. People can learn to run their own nodes through hackathons, often within three days [01:11:17].