機器人作業系統：區塊鏈和智慧合約提供了這個新興產業蓬勃發展所需的重要基礎設施。

醫療保健、教育和國防領域的好處將是顯而易見的。

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).

將思維機器融入人類社會帶來了獨特的挑戰。現有系統是為人類設計的，並假定指紋、父母和出生日期等特徵，而這些特徵與機器無關。此外，如何監管思維機器還存在不確定性，有些人主張取締思維機器，暫停其發展，或限制其合成人類可理解的情感的能力（如歐盟的提議）。

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.

確定哪些地區法律適用於在近地軌道計算機上運行的 200B 參數 LLM，該計算機控制著位於珍珠街的紐約 SEC 辦公室的交易機器人或物理機器人的行為，這也存在困難。

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.

為了應對這些挑戰，我們需要一個支持金融交易、使人類和電腦能夠協作投票和製定規則、並且不可變、公開且有彈性的全球系統。

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).

幸運的是，在過去 16 年裡，數以千計的創新者和開發人員一直在建構這一目標——一個用於去中心化治理和金融的平行框架。從一開始，其目標就是透過創建一個「不太關心與誰交談」的系統來支持「嘗試新經濟範式的非地理社區」（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.

現在，這意味著什麼已經變得越來越清楚了——與其他以人為本的技術、金融和監管堆疊相比，區塊鏈和智能合約不太關心它們是被人類還是思維機器使用，並且優雅地容納了所有人我們。因此，去中心化的加密網路提供了使這個新興產業蓬勃發展所需的重要基礎設施。醫療保健、教育和國防領域的好處將是顯而易見的。

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.

需要克服幾個障礙。無縫的人<>機器與機器<>機器協作至關重要—尤其是在運輸、製造和物流等高風險環境中。智慧合約使自主機器能夠相互發現、安全地通訊並組建團隊來完成複雜的任務。據推測，低延遲資料交換（例如機器人計程車之間）將發生在鏈外，例如在虛擬專用網路中，但實現這一點的步驟，例如發現能夠開車送你去機場的人類和機器人，非常適合去中心化的市場和行動。樂觀等擴展解決方案對於適應這些交易和流量至關重要。

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.

世界各地分散的監管是阻礙創新的另一個因素。雖然安大略省等一些司法管轄區在自主機器人技術方面處於領先地位，但大多數司法管轄區卻並非如此。去中心化治理透過建立可編程的、基於區塊鏈的規則集來解決這個問題，這些規則集提供了急需的一致性。制定安全、道德和營運方面的全球標準對於確保自主機器人能夠在不影響安全性或合規性的情況下大規模跨境推廣至關重要。

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.

去中心化自治組織（也稱為 DAO）有助於加速機器人和人工智慧的研究和開發。傳統的資金來源既緩慢又孤立，阻礙了該行業的發展。 DeSci DAO 平台等基於代幣的模型消除了這些瓶頸，同時為日常投資者提供了參與的潛在激勵。同樣，一些正在開發的人工智慧商業模式涉及小額支付以及與數據或模型提供者分享收入，這些收入都可以透過智慧合約來適應。

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

結合起來，這些優勢將有助於快速追蹤自主機器人的開發，並擁有大量引人注目的用例。

A new paradigm for robotics and thinking machines

機器人和思維機器的新範例

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.

人們很容易擔心認知是一場零和遊戲，智慧機器的廣泛可用性將直接與人類競爭。但現實是，教育、醫療保健和許多其他領域受過良好教育的人才嚴重短缺。

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.

聯合國教科文組織最近的研究顯示，全球範圍內教師短缺，「到2030 年，全球急需4,400 萬名中小學教師」——而這還沒有考慮在課堂上提供一對一支持並幫助有困難的學生繼續學習的助理。自主機器人可以在這裡發揮巨大的優勢，解決整個教育領域的嚴重短缺。想像一下，一個孩子能夠學習一個複雜的概念，旁邊有一個機器人，引導他們了解新的技能概念——增強他們對某個主題的理解，同時提高他們的社交技能。我們已經習慣了人類教導機器人，這是一條單行道，但這種情況正在改變。

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

同時，世界衛生組織警告稱，存在「衛生人力危機」。 100 個國家總共短缺 720 萬名專業人員，鑑於世界面臨人口老化，這一缺口預計到 2035 年將加速至 1,290 萬人。這場危機正在影響患者所接受的照護質量，並威脅到醫療保健專業人員的工作能力。從監測慢性病患者、協助外科手術到為老年人提供陪伴，自主機器人可以在減輕護理師和醫生的工作量方面發揮至關重要的作用。無需提示，他們就可以監控