BitsCrunch获取Nidum AI来建立一个高性能AI计算节点的全球网络

区块链分析公司Bortscrunch已收购了一个分散的AI计算平台Nidum AI，以建立一个具有高性能AI计算节点的全球网络

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.

该公司周三宣布，区块链分析公司Bortcrunch已收购了分散的AI计算平台Nidum AI，以启动一个由高性能AI计算节点的全球网络。

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

此次收购将使Nidum AI的分布式计算资源集成到Bortscrunch的运营中，旨在扩大区块链应用程序的AI驱动分析。

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.

除了购买外，Bortcrunch推出了一个分散的AI生态系统，其Bcut/USD代币将是访问该网络中服务的唯一货币。

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.

这项交易使Nidum AI的基础架构（在全球范围内具有计算能力的AI开发人员）在Bitscrunch的伞上，这一举动着重于后者在区块链法医学和数据见解方面的专业知识。

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.

该生态系统将利用张量和管道并行性将复杂的AI任务跨越多个节点，旨在更快的模型培训和推断欺诈检测和风险评估等应用的推断。

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声称，这种结构将使大约1/100的竞争对手削减成本，例如Openai和Grok，但对此成本差异的独立验证仍在审理中。

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令牌已经在Bybit，Kucoin和Uniswap Uni/USD等交易所上列出，将用于本生态系统中的付款，将其实用性直接与网络的功能联系起来。

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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的创始人兼首席执行官Vijay Pravin强调了收购的战略性及其对全球规模的影响。

"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.

该生态系统将迎合金融机构，监管机构和投资者，为数字交易中的实时合规性和威胁检测提供工具。

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

此次收购是Bortscrunch在多链分析中的工作，它为零售和机构客户提供了AI驱动的取证。

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的技术将增加一层分布式计算能力，并有可能将Bitscrunch的覆盖范围扩展到需要可扩展AI的行业，例如广告，游戏和新材料发现。

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，这种集成的成功将取决于执行 - 通过计算资源将全球开发人员群联系起来带来后勤和技术挑战。

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等竞争平台也正在争夺分散的AI计算中的优势，提出了有关BortsCrunch如何将自己区分开来超越其成本要求的问题。

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