Pond 是一家建構去中心化 AI 模型層的加密新創公司，籌集了 750 萬美元的種子資金

Pond 成立於 2023 年，最初建立了一個由鏈上數據驅動的用戶搜尋引擎，使用戶能夠探索區塊鏈連接。

Crypto startup Pond, which is building a decentralized AI model layer, has raised $7.5 million in a seed funding round led by Archetype.

加密新創公司 Pond 正在建立去中心化人工智慧模型層，在由 Archetype 領投的種子輪融資中籌集了 750 萬美元。

Other participants in the round included Cyber Fund, Delphi Ventures, Coinbase Ventures, Near Foundation and several angel investors, such as Illia Polosukhin, co-founder of Near Protocol; Chris Yin, CEO and co-founder of Plume Network; Cynthia Wu, founding partner and COO of Matrixport; and Tesa Ho, head of market research at Flashbots, Pond announced Thursday.

此輪融資的其他參與者包括 Cyber​​ Fund、Delphi Ventures、Coinbase Ventures、Near Foundation 和幾位天使投資人，例如 Near Protocol 聯合創始人 Illia Polosukhin； Chris Yin，Plume Network 執行長兼共同創辦人； Cynthia Wu，Matrixport 創始合夥人兼營運長； Pond 週四宣布，Flashbots 市場研究主管 Tesa Ho 表示。

Pond began raising money for this round in April and closed it by July, co-founder and CEO Dylan Zhang told The Block. The round was structured as a simple agreement for future equity (SAFE) with token warrants, said Zhang, who declined to disclose the post-round valuation.

Pond 聯合創始人兼執行長 Dylan Zhang 告訴 The Block，該輪融資於 4 月開始籌集，並於 7 月關閉。張表示，本輪融資的結構是一份帶有代幣認股權證的簡單未來股權協議（SAFE），但他拒絕透露本輪融資後的估值。

What is Pond?

什麼是池塘？

Founded in 2023, Pond initially built a user search engine powered by on-chain data, enabling users to explore blockchain connections. For example, if someone wanted to connect with Ethereum co-founder Vitalik Buterin, they could enter his ENS (vitalik.eth) and view who is connected to him in their network. "We achieved this through a proprietary graph algorithm designed specifically for blockchain data, which calculates the strength of these connections," said Zhang.

Pond 成立於 2023 年，最初建立了一個由鏈上數據驅動的用戶搜尋引擎，使用戶能夠探索區塊鏈連接。例如，如果有人想與以太坊聯合創始人 Vitalik Buterin 聯繫，他們可以輸入他的 ENS (vitalik.eth) 並查看誰在他們的網路中與他連接。 「我們透過專門為區塊鏈數據設計的專有圖形演算法實現了這一目標，該演算法計算這些連接的強度，」張說。

Over time, Pond saw the potential of a unified graph network across all types of on-chain data — social, financial and more — and expanded its focus to build crypto-native AI models for broader applications. "In the entire industry of AI, models are the engine that generates productivity," Pond co-founder and CTO Bill Shi told The Block. "By learning from and understanding data, models extract value from data and make predictions. Consider the current AI wave: It was unlocked by models like GPT and Llama."

隨著時間的推移，Pond 看到了跨所有類型的鏈上資料（社交、金融等）的統一圖網路的潛力，並將其重點擴展到為更廣泛的應用建立加密原生人工智慧模型。 Pond 聯合創始人兼首席技術長 Bill Shi 告訴 The Block：“在整個人工智慧行業，模型是產生生產力的引擎。” 「透過學習和理解數據，模型從數據中提取價值並做出預測。想想當前的人工智慧浪潮：它是由 GPT 和 Llama 等模型解鎖的。”

Pond is now creating a "complete model ecosystem," encompassing data, model computation, training and inference. Shi said that Pond not only builds its own models but also supports others in model creation and commercialization.

Pond 現在正在創建一個“完整的模型生態系統”，涵蓋資料、模型計算、訓練和推理。施說，Pond不僅建立自己的模型，還支持其他人的模型創建和商業化。

User perspective

使用者視角

While web2 AI models like ChatGPT assist with tasks from text generation to recommendations, Shi said Pond's web3 AI models will power crypto-specific use cases driven by on-chain data.

雖然像 ChatGPT 這樣的 web2 AI 模型可以幫助完成從文字生成到推薦等任務，但 Shi 表示，Pond 的 web3 AI 模型將為由鏈上資料驅動的加密特定用例提供支援。

"On-chain data is extremely messy and vast in quantity, making it incomprehensible to the human mind. By leveraging AI capabilities, we transform what is beyond human understanding into comprehensible information, helping users make better use of on-chain data," he said.

「鏈上數據極其混亂、數量龐大，人類思維難以理解。透過人工智慧能力，我們將人類無法理解的資訊轉化為可理解的信息，幫助用戶更好地利用鏈上數據。」說。

Currently, Pond supports applications in security, recommendations and DeFi.

目前，Pond 支援安全、推薦和 DeFi 領域的應用。

In security, Pond has developed a graph-based model for predicting malicious addresses, achieving an accuracy of 0.936 and a precision of 0.935. This model will be available on Pond's platform and will be used by "an industry-leading security company," according to Shi.

在安全性方面，Pond開發了基於圖的模型來預測惡意位址，準確率達到0.936，精度達到0.935。 Shi 表示，該模型將在 Pond 平台上提供，並將由「業界領先的安全公司」使用。

In recommendations, Pond offers models that suggest NFTs to users on Zora and DeFi protocols on Gearbox.

在推薦方面，Pond 提供了向 Zora 上的 NFT 和 Gearbox 上的 DeFi 協議的用戶推薦 NFT 的模型。

In DeFi, Pond has developed a dynamic fee model that addresses a key issue for liquidity providers: determining optimal transaction fees, Shi said. "When an intended trade is predicted to potentially lead to losses for liquidity providers, the model increases the transaction fee to compensate for the possible loss. Conversely, when a trade is predicted to be beneficial to liquidity providers, the model can lower the transaction fee to encourage more of these trades," he explained.

Shi 表示，在 DeFi 領域，Pond 開發了一個動態費用模型，解決了流動性提供者的關鍵問題：確定最佳交易費用。 「當預計一項交易可能會給流動性提供者帶來損失時，該模型會增加交易費用以補償可能的損失。相反，當預計一項交易對流動性提供者有利時，該模型可以降低交易費用以鼓勵更多此類交易，」他解釋道。

Pond plans to expand its crypto-AI use cases to include DeFi risk management, insider trading detection and personalized recommendations. Currently employing 11 people, Pond is actively hiring for roles including chief operating officer, product manager and ecosystem growth manager, said Zhang.

Pond 計劃擴展其加密人工智慧用例，包括 DeFi 風險管理、內線交易偵測和個人化建議。張說，旁氏目前有 11 名員工，正在積極招募營運長、產品經理和生態系統成長經理等職位。

The Funding newsletter: Stay updated on the latest crypto funding news and trends with my bimonthly newsletter, The Funding. It's free. Sign up here!

融資通訊：透過我的雙月通訊「The Funding」了解最新的加密融資新聞和趨勢。它是免費的。在這裡註冊！