Why will human-machine teams work on cryptocurrency networks?

Autonomous robots may seem like science fiction concepts that are still decades away, but large language models and generative artificial intelligence now allow machines to plan, learn, and think. What’s more, the same software that can win the Math Olympiad and write novels can also control physical robots, allowing a single digital character to operate across the digital and physical worlds. So, yes, bots roaming your neighborhood, or working alongside 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 our homes and daily lives? Most of the systems we’ve built are for other humans and make strong assumptions about fingerprint, parentage, and date of birth, none of which apply to thinking machines. There is also a great deal of uncertainty about how to regulate thinking machines – should we ban them, halt their development, or try to limit their ability to synthesize comprehensible human emotions (as is the case in the EU)? What regional laws apply to a 200B LLM parameter running on a computer in low Earth orbit, which controls the actions of a trading robot, or a physical robot at the New York SEC’s Pearl Street office?

What is needed is a global system that supports financial transactions, allows humans and computers to come together to vote and set rules, is immutable, public, and is flexible. Fortunately, thousands of innovators and developers have spent the past 16 years building exactly that – a parallel framework for decentralized governance and finance. From the beginning, the goal was to supportNon-geographical societies experimenting with new economic models“By building a system”He doesn’t care much about who he talks to“(Satoshi 2/13/09). It’s now much clearer what that means – unlike the rest of the human-centered technology, finance, and regulation, blockchain and smart contracts don’t care much if they’re used by humans or thinking machines, and safely accommodate us all. For this reason, decentralized crypto networks provide the vital infrastructure needed to allow this thriving sector to flourish. The benefits will be tangible in the areas of healthcare, education and defence.

Many obstacles will have to be overcome. Seamless human<>machine<>machine<>collaboration is essential – especially in high-risk environments such as transportation, manufacturing, and logistics. Smart contracts allow autonomous machines to discover each other, communicate securely, and form teams to complete complex tasks. Low-latency data exchange (e.g. between robo-taxis) is meant to take place off-chain, for example in virtual private networks, but the steps leading up to this, such as discovering humans and robots being able to drive you to the airport, are well suited to decentralized markets and procedures. . Scaling solutions like Optimism will be critical to accommodate these transactions and traffic.

Fragmented regulations around the world are another factor slowing down innovation. While some jurisdictions Like Ontario When it comes to autonomous robots, most are not. Decentralized governance addresses this problem by creating programmable, blockchain-based rule sets that provide much-needed uniformity. Establishing global standards for safety, ethics and operations is critical to ensuring that autonomous robots can be deployed across borders at scale, without compromising safety or compliance.

Decentralized autonomous organizations, known as DAOs, help accelerate research and development in robotics and artificial intelligence. Traditional financing sources are slow and isolated, which hinders the progress of the industry. Token-based models, such as the DeSci DAO platform, remove these bottlenecks, while giving everyday investors potential incentives to participate. Likewise, some developing AI business models involve micropayments and revenue sharing with data or model providers, which can be accommodated through smart contracts.

Combined, these advantages will help accelerate the development of autonomous robots, with a large number of compelling use cases.

A new paradigm for robots and thinking machines

It is easy to fear that cognition is a zero-sum game, and that the widespread availability of intelligent machines will compete directly with humans. But the truth is that there is a severe shortage of well-educated people in education, healthcare and many other sectors.

Research by UNESCO Recently revealed Teacher shortages around the world There is an “urgent need for 44 million primary and secondary teachers worldwide by 2030” – and that’s before you consider the aides who provide one-on-one support in classrooms and help struggling students keep up with their peers. Autonomous robots can offer huge advantages here, by addressing a significant shortage in the education sector. Imagine a child being able to learn about a complex concept with a robot sitting next to them, guiding them through a new skill concept – enhancing their understanding of a topic while enhancing their social skills. We’re used to humans teaching robots, and it’s a one-way street, but that’s changing.

Meanwhile, The World Health Organization warned From the “Health Workforce Crisis.” There is a total shortage of 7.2 million professionals across 100 countries – and as the world faces an aging population, this gap is expected to accelerate to 12.9 million by 2035. The industry faces shortages in critical areas such as nursing, primary care and allied health services. . This crisis is impacting the quality of care patients receive and threatening the ability of healthcare professionals to do their jobs. From monitoring patients with chronic diseases and assisting with surgeries, to providing companionship to the elderly, autonomous robots can play a crucial role in reducing the workloads of nurses and doctors. Without being prompted, they can monitor drug and equipment supplies – and order additional stock when needed. When you take into account other use cases such as transporting medical waste, cleaning treatment rooms, and assisting with surgeries, it is clear to see that robots can lead to increased productivity – and consistency – at a time when the healthcare sector needs it most.

Autonomous systems are already reshaping the defense sector, which primarily includes swarms of drones and naval surface assets, and we’ve barely scratched the surface when it comes to the advantages that robots can bring – carrying out tasks that would be unsafe or impossible for humans.

From prototypes to practical use

This may all seem abstract and straight from the 22nd century, but today Ethereum is used to store decision and action guardrails for artificial intelligence and robotics, and as… Reported by CoinbaseAI agents use cryptocurrencies to transact among themselves.

The open, auditable architecture of decentralized crypto networks allows bot developers to securely share data, models, and discoveries. This accelerates the transition of autonomous robots from prototypes to real-world applications, allowing them to be deployed in critical areas such as hospitals and schools faster than ever before. When you’re walking down the street with a humanoid robot, and people stop and ask – “Aren’t you afraid?” You can tell them – No, you’re not afraid, because the laws governing the actions of this device are public and immutable, and then you can give them a link to the Ethereum contract address where the Ethereum contract is stored. These rules.

Decentralized ledgers can also act as coordination centers, allowing bots in heterogeneous systems to find each other and coordinate without central intermediaries. This is conceptually similar to standard defense technology C3 (command, communications, and control), except that the infrastructure is decentralized and public. Immutable records ensure that every exchange and action can be traced, creating a trusted foundation for collaboration.

For interactions between robots, smart contracts simplify the process of allocating tasks and sharing resources, enabling efficient coordination. In robot-human interactions, decentralized, privacy-focused systems can secure sensitive data, such as vital or medical information, enhancing trust and accountability.

This new world may spark fear – what does it all mean for us? But everyone reading this article has been working on it for nearly two decades, building the infrastructure that will handle management, teamwork, communication, and coordination between humans and thinking machines.