Autonomous robots may sound like a science fiction concept decades away, but large-scale language models and generative AI are enabling machines to plan, learn, and think. More than that, the same software that can win Math Olympiads and write novels can also control physical robots, allowing a single digital persona to operate across the digital and physical worlds. This means that the robots that walk around your neighborhood or work with you will have consistent opinions and actions on X/Twitter, in prediction markets, and in the real world.
But there is a big gap. How do we integrate thinking machines into human society, from schools, hospitals, and factories to homes and daily life?Most of the systems we build are for other humans, and they are designed to provide information about fingerprints, parents, dates of birth, and more. It strongly assumes that there is a day, but none of this applies to thinking machines. There is also great uncertainty about how thinking machines will be regulated. Will we outlaw thinking machines, suspend their development, or (like the European Union) seek to limit their ability to synthesize emotions that humans can understand? Which local laws apply to a 200B parameter LLM running on a computer in low Earth orbit that controls the operations of trading bots and physical robots at the New York Securities and Exchange Commission office on Pearl Street?
What is needed is an immutable, public, and resilient global system that supports financial transactions and allows humans and computers to vote and set rules together. Fortunately, thousands of innovators and developers have spent the past 16 years building just that: a parallel framework for decentralized governance and finance. The point from the beginning has been to support “non-geographical communities experimenting with new economic paradigms” by building a system that “doesn’t really care who you talk to” (Satoshi 2/13 /09). Now it’s clearer what this means. Unlike other technology, finance, and regulatory stacks that are human-centric, blockchain and smart contracts care less whether they are being used by humans or thinking machines, and gracefully accommodate all of us. . . Decentralized crypto networks therefore provide the critical infrastructure needed to enable this burgeoning sector to thrive. The benefits will be visible across health care, education and defence.
Some hurdles 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 each other, communicate securely, and form teams to complete complex tasks. Perhaps the low-latency data exchange (e.g., between robot taxis) will happen off-chain, such as in a virtual private network, but the steps to get there (e.g., finding a human or robot to drive you to the airport) are Decentralized markets and behavior. Scaling solutions like Optimism are important to accommodate these transactions and traffic.
Fragmented regulations around the world are another factor slowing innovation. While some regions, such as Ontario, are ahead of the curve in autonomous robots, most are not. Decentralized governance addresses this problem by establishing a programmable blockchain-based ruleset that provides much-needed uniformity. Creating global standards for safety, ethics, and operations is critical to ensuring that autonomous robots can be deployed at scale across borders without compromising safety or compliance.
Decentralized autonomous organizations, also known as DAOs, can help accelerate research and development in robotics and AI. Traditional funding sources are slow and siled, holding the industry back. Token-based models such as the DeSci DAO platform eliminate these bottlenecks while potentially incentivizing everyday investors to participate. Similarly, the development of AI business models includes micropayments and revenue sharing with data and model providers, which can be supported by smart contracts.
Combining these advantages can accelerate the development of autonomous robots with many attractive use cases.
A new paradigm for robotics and thinking machines
Cognition is a zero-sum game, and it’s easy to worry that if smart machines become widespread, they will compete directly with humans. However, the reality is that there is a serious shortage of well-educated personnel in education, medicine, and many other fields.
A recent study by UNESCO revealed a global teacher shortage, with an “urgent need for 44 million primary and secondary teachers worldwide by 2030”. And that’s before considering assistants who provide one-on-one support in the classroom and help students with difficulties stay in class. With friends. Autonomous robots can offer significant benefits here and address serious shortages across the education sector. Imagine being able to have a robot sit next to your child to learn about complex concepts and explain new concepts for skills. This allows you to strengthen your understanding of the subject while improving your social skills. We are used to humans teaching robots and this being a one-way street, but that is changing.
Meanwhile, the WHO warned of a “crisis for health workers.” There is a total shortage of 7.2 million professionals across 100 countries, and this gap is expected to accelerate to 12.9 million by 2035, given that the world faces an aging population. The industry is facing talent shortages in critical areas such as nursing, primary care and allied health. . This crisis is impacting the quality of care patients receive and threatening the ability of healthcare workers to do their jobs. Autonomous robots can play an important role in easing the burden on nurses and doctors, from monitoring patients with chronic diseases to assisting with surgeries and attending to the elderly. You can monitor drug and equipment supplies and order additional inventory as needed without prompting. When you take into account other use cases such as transporting medical waste, cleaning treatment rooms, and assisting with surgeries, it is clear that robotics can facilitate increased productivity and consistency when the medical sector needs it. .
Autonomous systems are already reshaping the defense sector, primarily involving swarms of unmanned vehicles and naval surface assets, but the benefits that robotics brings, namely performing tasks that are unsafe or impossible for humans, are increasing. We’ve only just scratched the surface.
From prototype to practical application
All of this may seem abstract and straight out of the 22nd century, but Ethereum is currently being used to store guardrails for AI and robot decisions and actions, as reported by Coinbase. and AI agents transact with each other using cryptocurrencies.
The open and auditable structure of decentralized cryptographic networks allows robot developers to securely share data, models, and breakthroughs. This will accelerate the transition of autonomous robots from prototype to real-world applications, enabling robots to be introduced into critical areas such as hospitals and schools faster than ever before. If you’re walking down the street with a humanoid robot and people stop and ask, “Are you scared?” you can say, “No, I’m not scared.” Because the laws governing the operation of this machine are public and cannot be changed. You can give users a link to the Ethereum contract address where these rules are stored.
Distributed ledgers also act as coordination hubs, allowing robots in disparate systems to find and coordinate with each other without a centralized intermediary. It is conceptually similar to standard defense C3 technology (command, communications, and control), except that the infrastructure is decentralized and exposed. Immutable records make all interactions and actions traceable, creating a reliable foundation for collaboration.
In robot-to-robot interactions, smart contracts streamline task assignment and resource sharing, enabling efficient coordination. In robot-human interactions, privacy-centric distributed systems can protect sensitive data such as biometrics and medical information and promote trust and accountability.
This new world may evoke fear. What does this mean for us? – But for those of you reading this article, by building the infrastructure that handles governance, teaming, communication, and coordination between humans and thinking machines, we’ve made nearly 20 We’ve been working to make that happen for years.
