机器人操作系统：区块链和智能合约提供了这一新兴行业蓬勃发展所需的重要基础设施。

医疗保健、教育和国防领域的好处将是显而易见的。

The integration of thinking machines into human society poses unique challenges. Existing systems are designed for humans and assume characteristics like fingerprints, parents, and birthdates, which are irrelevant for machines. Moreover, there is uncertainty about how to regulate thinking machines, with some advocating for outlawing them, pausing their development, or limiting their ability to synthesize human-intelligible emotions (as proposed in the European Union).

将思维机器融入人类社会带来了独特的挑战。现有系统是为人类设计的，并假定指纹、父母和出生日期等特征，而这些特征与机器无关。此外，如何监管思维机器还存在不确定性，一些人主张取缔思维机器，暂停其发展，或限制其合成人类可理解的情感的能力（如欧盟的提议）。

Determining which regional laws apply to a 200B parameter LLM running on a computer in low earth orbit that controls the actions of a trading bot or a physical robot in the New York SEC office on Pearl Street also presents difficulties.

确定哪些地区法律适用于在近地轨道计算机上运行的 200B 参数 LLM，该计算机控制纽约 SEC 位于珍珠街办公室的交易机器人或物理机器人的行为，这也存在困难。

To address these challenges, we need a global system that supports financial transactions, enables humans and computers to collaborate in voting and setting rules, and is immutable, public, and resilient.

为了应对这些挑战，我们需要一个支持金融交易的全球系统，使人类和计算机能够协作投票和制定规则，并且是不可变的、公开的和有弹性的。

Fortuitously, thousands of innovators and developers have spent the last 16 years building precisely that - a parallel framework for decentralized governance and finance. From the outset, the aim was to support “non-geographic communities experimenting with new economic paradigms” by creating a system that “doesn't much care who it talks to” (Satoshi 2/13/09).

幸运的是，在过去 16 年里，数以千计的创新者和开发人员一直在构建这一目标——一个用于去中心化治理和金融的并行框架。从一开始，其目标就是通过创建一个“不太关心与谁交谈”的系统来支持“尝试新经济范式的非地理社区”（Satoshi 2/13/09）。

It's now becoming clearer what that meant - in contrast to the rest of the human-focused tech, financial, and regulatory stack, blockchains and smart contracts don’t much care if they are being used by humans or thinking machines, and gracefully accommodate all of us. For this reason, decentralized crypto networks offer the vital infrastructure that's needed to allow this burgeoning sector to flourish. The benefits will be tangible across healthcare, education and defense.

现在，这意味着什么变得更加清晰——与其他以人为中心的技术、金融和监管堆栈相比，区块链和智能合约不太关心它们是被人类还是思维机器使用，并且优雅地容纳了所有人我们。因此，去中心化的加密网络提供了使这个新兴行业蓬勃发展所需的重要基础设施。医疗保健、教育和国防领域的好处将是显而易见的。

Several hurdles will need to be overcome. Seamless human<>machine and machine<>machine collaboration is essential — especially in high-stakes environments such as transportation, manufacturing, and logistics. Smart contracts enable autonomous machines to discover one another, communicate securely, and form teams to complete complex tasks. Presumably, low latency data exchange (e.g. among robot taxis) will happen off chain, for example in virtual private networks, but the steps leading up to that, such as discovering humans and robots able to drive you to the airport, are well suited for decentralized markets and actions. Scaling solutions such as Optimism will be critical to accommodate these transactions and traffic.

需要克服几个障碍。无缝的人<>机器与机器<>机器协作至关重要——尤其是在运输、制造和物流等高风险环境中。智能合约使自主机器能够相互发现、安全通信并组建团队来完成复杂的任务。据推测，低延迟数据交换（例如机器人出租车之间）将发生在链外，例如在虚拟专用网络中，但实现这一点的步骤，例如发现能够开车送你去机场的人类和机器人，非常适合去中心化的市场和行动。乐观等扩展解决方案对于适应这些交易和流量至关重要。

The fragmented regulations around the world is another factor slowing innovation. While some jurisdictions such as Ontario are ahead of the curve when it comes to autonomous robotics, most are not. Decentralized governance tackles this by establishing programmable, blockchain-based rule sets that deliver much-needed uniformity. Creating global standards for safety, ethics and operations is critical for ensuring that autonomous robots can be rolled out across borders at scale, without compromising safety or compliance.

世界各地分散的监管是阻碍创新的另一个因素。虽然安大略省等一些司法管辖区在自主机器人技术方面处于领先地位，但大多数司法管辖区却并非如此。去中心化治理通过建立可编程的、基于区块链的规则集来解决这个问题，这些规则集提供了急需的一致性。制定安全、道德和运营的全球标准对于确保自主机器人能够在不影响安全性或合规性的情况下大规模跨境推广至关重要。

Decentralized autonomous organizations, otherwise known as DAOs, help accelerate research and development in robotics and AI. Traditional sources of funding are both slow and siloed, holding the industry back. Token-based models such as DeSci DAO platform remove these bottlenecks, while giving everyday investors potential incentives to get involved. Likewise, some of the developing business models for AI involve micropayments and sharing of revenue with data- or model- providers, which can be accommodated with smart contracts.

去中心化自治组织（也称为 DAO）有助于加速机器人和人工智能的研究和开发。传统的资金来源既缓慢又孤立，阻碍了该行业的发展。 DeSci DAO 平台等基于代币的模型消除了这些瓶颈，同时为日常投资者提供了参与的潜在激励。同样，一些正在开发的人工智能商业模式涉及小额支付以及与数据或模型提供商分享收入，这些都可以通过智能合约来适应。

Combined, these advantages will help fast-track the development of autonomous robots, with a plethora of compelling use cases.

结合起来，这些优势将有助于快速跟踪自主机器人的开发，并拥有大量引人注目的用例。

A new paradigm for robotics and thinking machines

机器人和思维机器的新范例

It’s easy to fear that cognition is a zero sum game, and that the broad availability of smart machines will directly compete with humans. But the reality is that there are severe shortages of well educated humans in education, healthcare, and many other sectors.

人们很容易担心认知是一场零和游戏，智能机器的广泛可用性将直接与人类竞争。但现实是，教育、医疗保健和许多其他领域受过良好教育的人才严重短缺。

Research by UNESCO recently revealed a worldwide teacher shortage that there's an "urgent need for 44 million primary and secondary teachers worldwide by 2030" — and that's before you consider the assistants who offer one-on-one support in classrooms and help struggling students to keep up with their peers. Autonomous robots can deliver huge advantages here, tackling significant shortages across the education sector. Imagine a child being able to learn about a complicated concept with a robot sitting next to them, to walk them through a new concept of skill — reinforcing their understanding about a subject while enhancing their social skills. We are used to humans teaching robots, and this being a one way street, but that is changing.

联合国教科文组织最近的研究显示，全球范围内教师短缺，“到 2030 年，全球急需 4400 万中小学教师”——而这还没有考虑在课堂上提供一对一支持并帮助有困难的学生继续学习的助理。与同龄人并驾齐驱。自主机器人可以在这里发挥巨大的优势，解决整个教育领域的严重短缺问题。想象一下，一个孩子能够学习一个复杂的概念，旁边有一个机器人，引导他们了解新的技能概念——增强他们对某个主题的理解，同时提高他们的社交技能。我们已经习惯了人类教导机器人，这是一条单行道，但这种情况正在改变。

Meanwhile, the WHO has warned of a "health workforce crisis." There's a total shortfall of 7.2 million professionals across 100 countries — and given the world faces an aging population, this gap is expected to accelerate to 12.9 million by 2035. The industry is facing shortages in critical areas like nursing, primary care, and allied health. This crisis is affecting the quality of care patients receive and threatening the ability of healthcare professionals to do their jobs. From monitoring patients with chronic diseases, assisting surgical procedures, to offering companionship for the elderly, autonomous robots can play a crucial role in alleviating the workloads of nurses and doctors. Without being prompted, they can monitor

与此同时，世界卫生组织警告称，存在“卫生人力危机”。 100 个国家总共短缺 720 万名专业人员，鉴于世界面临人口老龄化，这一缺口预计到 2035 年将加速至 1290 万人。该行业在护理、初级保健和专职医疗等关键领域面临短缺。这场危机正在影响患者接受的护理质量，并威胁到医疗保健专业人员的工作能力。从监测慢性病患者、协助外科手术到为老年人提供陪伴，自主机器人可以在减轻护士和医生的工作量方面发挥至关重要的作用。无需提示，他们就可以监控