Live from a studio in London as part of the Coingeek Live virtual conference on September 30, Dr. Craig S. Wright, the Chief Scientist of nChain, laid out a vision for outsourced computational and reward systems on top of the Bitcoin SV (BSV) network.
Having the ability to outsource computational work, whether it be for image rendering, scientific research, or other yet-to-be conceived applications, can offer individuals and businesses the ability to have that work completed by other machines more powerful than theirs, letting them possibly save time, money, and man power upkeeping the machines. This would also allow individuals, and businesses of various sizes to be paid for the use of their machines - with payments being easily realized because of the Bitcoin network the parties would be interconnected with.
“Right now you have Amazon and all these others competing to sell you a computer time, but we don’t really want to buy a series of computers. What we want to do is have a computation completed, most people sort of don’t realize that it’s not about the machines, it’s about the outcome. We don’t care that we have 200 machines there at Google working away for us. We care about the numbers and the data at the end.” said Dr. Wright.
nChain is a UK-based firm that is one of the leaders in the number of blockchain and distributed networks related patents held, and Dr. Wright is at the center of their innovation.
Physically Unclonable Functions (PUFs)
In order to facilitate an outsourced computational network, implementation of innovation on the computational level is necessary to be able differentiate between where each computation is coming from to compensate those completing complete and verifiably correct computations.
Wright cites Gassend et al. (2002) which defined a PUF as “a Random Function that can only be evaluated with the help of a specific physical system.” He further cited Gassend et al. which noted “We call the inputs to a Physical Random Function challenges, and the outputs responses.”
“What we’re effectively doing is creating an individual process that one individual can have, one company, one group, and that will differentiate them, allowing them to not have the same result as another party.” said Wright.
Wright noted that that notion does not mean that the parties are not calculating the same thing, but that it means that the ones doing the calculation will be able to be differentiated. This will differentiate the people doing the calculations to enable specific people to be paid for specific work.
Wright further illustrated that multi-part process of this conceptualized outsourced computational system is not too unlike the system that is part of Bitcoin itself, wherein one miner will find a solution, but will only be paid with coinbase bitcoin and transaction fees after their work is verified by other miners. Wright has previously explained that miners are incentivized to see if there is anything wrong with the other miners and their work, to perhaps have a chance to get the block for themselves and increase their own profits, thereby economically securing the network.
The Australian innovator went on to explain that in Bitcoin there is a 100 block maturity level, miners have to get the block they mine to other miners so that they can build on top of it - so for the rest of miners to have a chance to continue to earn money with the next opportunity for a block, they have to verify the last miner who mined a block - all then continuing on the chain financially incentivized.
Outsourced Computation and Provability
In one sense, individuals and smaller operations can earn Bitcoin SV be having their machines complete computations, being secured and paid for the work over the settlement payment layer of the same Bitcoin network that has enabled the verification of Physically Unclonable Functions and the provability of the work completed - all serving a more streamlined and distributed function for the economy of the future.
Computational workers in this system would have a certain chain of computations where they and the others in the system would verify the fidelity and unchanged state of the computations before the computational workers are paid for their work, in a process linked and in step with the Bitcoin payment network.
One key element of not just outsourced computation and payment for it is identity. Identity and blockchain is one issue that necessitates verification and interaction with the real world. “Because you have a digital signature algorithm doesn’t mean you have a digital signature, you cannot have a digital signature without identity,” said Wright.
“Imagine the validity of having a contract and you walk up and go ‘I’m not going to tell you who I am, but I’m going to sign’?” Wright asked. He added that pseudonymous identities and other possibilities, such as identified machines, could be used.
Machines connected to the network will be an increasingly important aspect of the Internet of Things that will increasingly pervade the future world. Bitcoin SV offers tremendous opportunity in the space of IoT because of its inherent integration of data, money, and communication.
Wright said it is expected that next year could see 34-40 billion machines on the Internet, with the number set to grow exponentially even from that number. With PUFs, Wright hopes for an Internet of Things that enables security with privacy. “Every little connection can be basically identified”, Wright said.
“If we can’t validate our machines and we can’t identify them, and we can’t link them into the network correctly, we’re going to have problems. So we want to have a system that identifies the user of a machine” continued Dr. Wright.
PUFs can have a role in proving the identity or authorization of a certain machine in the world of Internet of Things, in order to have privacy and access to such things as a car or door lock only to authorized users.
The user would be able to migrate to another provable identity if something goes wrong, Wright added. Fundamental to his presentation was the integration and enabling of Know Your Customer (KYC) and compliance systems in these systems, to ensure that the money being transferred is not from illicit sources.
A computational worker would be able to have a payment channel opened to them and be paid every so often as they do the work or to a certain threshold, thereby reducing the amount of miner’s fees taken out of the money they have earned.
Other Distributed Computational Systems
A project that has been working on something similar, albeit on the Ethereum blockchain, is Golem. The project, that had previously been one of the more exciting projects because of this unique opportunity, has since run into delays and apparent problems, having to essentially start over.
Not addressing Golem directly, Wright did assert that the base Ethereum layer (that Golem would be based on) limits itself to the the smallest machines because all nodes in the Ethereum network have to have the same state as each other and all need to complete the same computations. Wright said that validation of computations by way of a hash function is a more scalable and logical way to distribute computation.
The anticipated Ethereum 2.0 looks to distribute transaction verification by way of shards of different validators validating transactions in communication with the central beacon chain. They will be able to prove their states to each other and communicate with each other. This will increase transaction throughput from current Ethereum rates, but will still have its limitations.
It appears that a system that scales with the least amount of moving parts and uncertainty about the base layer upon which it is built is best suited for this unique opportunity to bring outsourced computation to fruition, all upon a public global ledger, where the functions themselves are physically provable and upon a worldwide timestamp network.
Note: The author possessed the related digital assets (BSV, ETH) at the time of publication.