我们很高兴宣布投资 io.net。 是领先的人工智能工作负载分布式计算市场。 我们引领种子轮，并参加了 A 轮融资。 io.net 总共从 Multicoin、Hack VC、6th Man Ventures、Modular Capital 以及一个由深度关联的天使投资者组成的财团筹集了 3000 万美元，以使按需、生产就绪的计算市场成为现实。
2023 年 4 月，我在 Austin Solana Hacker House 首次见到 io.net 的创始人 Ahmad Shadid， 而他专注于实现机器学习工作负载的计算资源访问民主化，立刻吸引了我。
从那时起，io.net 团队以光速按照论文执行。 如今，该网络已聚合了数万个分布式 GPU，并帮助人工智能企业获得了超过 57,000 个计算小时。 我们很高兴与他们合作，因为他们推动了未来十年的人工智能复兴。
全球计算短缺
对人工智能计算的需求正以惊人的速度增长；需求永无止境。 2023 年，人工智能工作负载的数据中心收入突破了 1000 亿美元，但即使是最保守的情况下，人工智能的需求也超过了芯片供应。
新的数据中心若能容纳这种等级的硬件，则需要在高利率和资本稀缺时期，开展大规模的前期投资。 问题的症结在于对先进芯片（如 NVidia A100 和 H100）的生产限制。 尽管 GPU 性能提高且成本稳步下降，但实际制造工艺的速度不够快；原材料、零部件和产能的短缺限制了增长速度。
尽管人工智能前景光明，但其物理足迹日益扩大，对空间、电力和尖端设备的需求日益增加，而这些设备使得全球各地的预算捉襟见肘。io.net 为这样一个世界铺平了道路，在这个世界里，我们努力加速，但不会受制于当前供应链。
io.net 是 DePIN论文的经典具体表现：使用代币激励，从结构上降低获取和保留供应方资源的成本，最终降低终端消费者的成本。 该网络将大量异构 GPU 供应整合到一个共享池中，供人工智能开发人员和公司利用。如今，该网络依托于数据中心、采矿场和消费级设备的成百上千个 GPU。
尽管聚合这些资源很有价值，但人工智能工作负载不会自动从集中式、企业级硬件扩展到分布式网络。 在加密货币的历史上，曾有数次尝试构建分布式计算网络，其中能够产生有意义的需求方体量者，可谓少之又少。
在各种异构硬件（具有不同的内存、带宽和存储配置）中编排和调度工作负载，并不容易。 我们相信，io.net 团队拥有当今市场上最实用的解决方案，能够使这种硬件聚合用于终端客户，并且经济上富有成效。
利用集群，铺平前进的道路
在计算的历史中，软件框架和设计模式围绕着市场上可用的硬件配置而自我成型。 大多数用于人工智能开发的框架和库严重依赖集中式硬件资源，但过去十年，在地理位置分布式硬件的离散实例中分配这些工作负载方面取得了重大进展。
io.net 采用世界上已有的潜在硬件，并在其上部署定制网络和编排层，然后将其带到网上，创建一个超级可扩展的 GPU 互联网。 该网络利用 Ray、Ludwig、Kubernetes 及各种其他开源、分布式计算框架，以便机器学习工程和运营团队能够以最小调整的方式，在 GPU 网络中扩展其工作负载。
ML 团队能够启动按需集群，利用这些库来处理编排、调度、容错和扩展，从而在 io.net GPU 中实现工作负载并行化。 例如，如果一组运动图形设计师将他们的家庭 GPU 贡献到网络中，io.net 可以构建一个集群，让全球任意地方的图像扩散式模型开发人员都能访问集体计算资源。
BC8.ai 是一个精调版的 Stable Diffusion（完全在 io.net 硬件上训练），就是这方面的一个例证。 io.net explorer 会显示实时推理，以及向网络贡献者付款。
提示：地理分布式人工智能超级计算机
每个推理都会记录在链上上，以提供出处。 针对此特定图像生成的付款支付给了 6 个 RTX 4090 集群，它们是游戏的消费级 GPU。
如今，网络上有数十万台设备，遍布采矿农场、未充分利用的数据中心及 Render Network 消费者节点。 io.net 除了创建净新 GPU 供应之外，还能够在成本上与传统云提供商相竞争，通常提供更便宜的资源。
他们将 GPU 协调和间接费用外包给协议，从而实现了成本节约。 另一方面，云提供商则会承担加成基础设施成本，因为他们有员工支出、硬件维护和数据中心的间接费用。 消费卡集群和采矿农场的机会成本大大低于超大规模云服务商愿意接受的成本，因此存在结构套利，即 io.net 上资源的动态价格低于不断增长的云费率。
构建 GPU 互联网
io.net 的独特优势在于既能保持资产轻量化，将服务特定客户的边际成本降低到几乎为零，又能拥有与市场供需双方的直接关系。他们处于有利地位，能够服务于数十万新企业——他们为了打造富有竞争力的产品而需要访问 GPU，而总有一天人人都会使用他们的产品。
我们很高兴与Ahmad及团队其他成员合作，在 世界各地构建和加速人工智能的发展。 如果您正在构建计算密集型应用程序，您可以立即在此处 注册，从 io.net 访问资源。 如果您拥有潜在 GPU，也可以立即向io.net Worker，由此赚取积分。
该团队正在招聘优秀的销售、工程和设计职位。 请联系：careers@io.net。
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