BitsCrunch獲取Nidum AI來建立一個高性能AI計算節點的全球網絡

區塊鏈分析公司Bortscrunch已收購了一個分散的AI計算平台Nidum AI，以建立一個具有高性能AI計算節點的全球網絡

Blockchain analytics firm bitsCrunch has acquired decentralized AI computing platform Nidum AI to launch a global network of high-performance AI compute nodes, the company announced on Wednesday.

該公司週三宣布，區塊鏈分析公司Bortcrunch已收購了分散的AI計算平台Nidum AI，以啟動一個由高性能AI計算節點的全球網絡。

The acquisition will see Nidum AI's distributed computational resources integrated into bitsCrunch's operations, aiming to amplify AI-driven analytics for blockchain applications.

此次收購將使Nidum AI的分佈式計算資源集成到Bortscrunch的運營中，旨在擴大區塊鏈應用程序的AI驅動分析。

Along with the purchase, bitsCrunch unveiled a decentralized AI ecosystem, where its BCUT/USD token will be the sole currency for accessing services within this network.

除了購買外，Bortcrunch推出了一個分散的AI生態系統，其Bcut/USD代幣將是訪問該網絡中服務的唯一貨幣。

The deal brings Nidum AI's infrastructure—connecting AI developers with computational power throughout the world—under bitsCrunch's umbrella, a move focused on the latter's expertise in blockchain forensics and data insights.

這項交易使Nidum AI的基礎架構（在全球範圍內具有計算能力的AI開發人員）在Bitscrunch的傘上，這一舉動著重於後者在區塊鏈法醫學和數據見解方面的專業知識。

This ecosystem will utilize Tensor and Pipeline parallelism to split complex AI tasks across multiple nodes, aiming for faster model training and inference for applications like fraud detection and risk assessment.

該生態系統將利用張量和管道並行性將復雜的AI任務跨越多個節點，旨在更快的模型培訓和推斷欺詐檢測和風險評估等應用的推斷。

bitsCrunch claims this structure will cut costs to roughly 1/100th of competitors like OpenAI and Grok, but independent verification of this cost differential is still pending.

Bitscrunch聲稱，這種結構將使大約1/100的競爭對手削減成本，例如Openai和Grok，但對此成本差異的獨立驗證仍在審理中。

The $BCUT token, already listed on exchanges like ByBit, KuCoin, and Uniswap UNI/USD, will be used for payments within this ecosystem, tying its utility directly to the network's functionality.

$ bcut令牌已經在Bybit，Kucoin和Uniswap Uni/USD等交易所上列出，將用於本生態系統中的付款，將其實用性直接與網絡的功能聯繫起來。

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Vijay Pravin, Founder and CEO of bitsCrunch, highlighted the strategic nature of the acquisition and its implications on a global scale.

Bortcrunch的創始人兼首席執行官Vijay Pravin強調了收購的戰略性及其對全球規模的影響。

"This strategic acquisition showcases the magnitude of our ambition to be a leading force in decentralizing AI," he said, noting how Nidum AI will be India's answer to centralized AI giants like OpenAI."Our native $BCUT token will be the exclusive currency of a thriving, decentralized AI marketplace," he added, highlighting the token's role in linking users and developers.

"This strategic acquisition showcases the magnitude of our ambition to be a leading force in decentralizing AI," he said, noting how Nidum AI will be India's answer to centralized AI giants like OpenAI."Our native $BCUT token will be the exclusive currency of a thriving, decentralized AI marketplace," he added, highlighting the token's role in linking users and developers.

This ecosystem will cater to financial institutions, regulators, and investors, offering tools for real-time compliance and threat detection in digital transactions.

該生態系統將迎合金融機構，監管機構和投資者，為數字交易中的實時合規性和威脅檢測提供工具。

The acquisition follows bitsCrunch's work in multi-chain analytics, where it serves retail and institutional clients with AI-powered forensics.

此次收購是Bortscrunch在多鏈分析中的工作，它為零售和機構客戶提供了AI驅動的取證。

Nidum AI's technology will add a layer of distributed computing power, potentially expanding bitsCrunch's reach into industries requiring scalable AI, like advertising, gaming, and new materials discovery.

Nidum AI的技術將增加一層分佈式計算能力，並有可能將Bitscrunch的覆蓋範圍擴展到需要可擴展AI的行業，例如廣告，遊戲和新材料發現。

However, the success of this integration will depend on execution—connecting a global developer base with compute resources presents logistical and technical challenges.

但是，這種集成的成功將取決於執行 - 通過計算資源將全球開發人員群聯繫起來帶來後勤和技術挑戰。

Competing platforms like io.net IO/USD and Gaia GAIA/USD are also vying for dominance in decentralized AI computing, raising questions about how bitsCrunch will differentiate itself beyond its cost claims.

IO.NET IO/USD和GAIA GAIA/USD等競爭平台也正在爭奪分散的AI計算中的優勢，提出了有關BortsCrunch如何將自己區分開來超越其成本要求的問題。

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