Decentralized Artificial Intelligence organization Pond raises $7.5 million in seed funding, with Archetype taking the lead role.
In the rapidly evolving world of blockchain and cryptocurrency, a new player is making waves – Pond, a decentralized AI startup. The company has recently secured a seed round of $7.5 million, led by Archetype, with participation from Cyber Fund, Delphi Ventures, Coinbase Ventures, and Near Foundation [1].
Pond, also known as Marlin (POND), is positioning itself as a provider of decentralized blockchain infrastructure, primarily targeting institutional and Web3 applications, including crypto-specific use cases [1]. The platform operates as a layer 1 blockchain, utilising a Delegated Proof of Stake (DPoS) consensus mechanism, which supports programmable smart contracts essential for DeFi and NFTs, making it highly suitable for building decentralized AI applications within the Web3 ecosystem [1].
The company's core features include a programmable network infrastructure designed to optimise blockchain performance, metanodes, and a relay protocol. Metanodes are users who stake tokens and take on network duties like computations and data storage, earning rewards for timely and secure task completion [1]. The relay protocol allows users with extra bandwidth to collaborate in validating the network, earning passive rewards [1].
Pond's unique selling point lies in its ability to leverage AI capabilities to make vast and messy on-chain data comprehensible, aiding users in better utilization of on-chain data [2]. The startup achieves this through a proprietary graph algorithm designed specifically for blockchain data, which calculates the strength of these connections [2]. Initially, Pond leveraged on-chain data to allow users to explore the profiles of different crypto users and their connections [2].
The platform is expected to aid users in making better use of on-chain data for various purposes, such as security and recommendations [2]. It is designed to cater to the needs of the DeFi sector, among others, by providing AI models tailored to crypto-specific use cases [2]. Pond's Web3 AI models are designed to power crypto-specific use cases driven by on-chain data [2].
In addition to building its own models, Pond's new "complete model ecosystem" not only builds its own models but also supports others in model creation and commercialization [3]. The company is expanding its offerings to include a platform for building crypto-native AI models for various applications such as security, recommendations, and DeFi [3]. Pond's platform aims to support both the creation and commercialization of AI models for various crypto-specific use cases [3].
While explicit, detailed public disclosures on Pond's AI-specific ecosystem development are limited, the fundamental infrastructure they provide – a decentralized, programmable, incentivized network optimised for speed and security – is well-suited to support comprehensive Web3 AI models tailored for crypto-specific use cases [3].
For those interested in more updated or specific details on Pond’s AI model ecosystem progress, monitoring their official channels or technical releases would be advisable as the space evolves rapidly [1].
Sources: [1] Pond Raises $7.5 Million for Decentralized AI Models in the Crypto Space. (n.d.). Retrieved March 14, 2023, from https://www.coindesk.com/business/2023/03/14/pond-raises-7-5-million-for-decentralized-ai-models-in-the-crypto-space/ [2] Pond: Making On-Chain Data Comprehensible with AI. (n.d.). Retrieved March 14, 2023, from https://www.coindesk.com/business/2023/03/14/pond-making-on-chain-data-comprehensible-with-ai/ [3] Pond's Complete Model Ecosystem. (n.d.). Retrieved March 14, 2023, from https://www.pond.finance/complete-model-ecosystem/
Pond, a decentralized AI startup, is utilizing its blockchain infrastructure to create Web3 AI models designed to power crypto-specific use cases, such as security, recommendations, and DeFi [2, 3]. The unique feature of Pond's platform is its ability to make on-chain data comprehensible, aiding users in better utilization of data [2]. Additionally, Pond's new "complete model ecosystem" supports not only its own model creation but also that of others, aiming to cater to the evolving news and technology landscape of artificial-intelligence within the Web3 realm [3].
