Along with all the technical breakthroughs that Bitcoin (BSV) has enabled, the economic innovation of using a self-incentivized proof-of work system to reward infrastructure providers via transaction fees, is actually a brilliant, self-tuning economic “anchor/gauge/regulator.”
We are about to have a potentially explosive early November event coming in Bitcoin, and it involves the oft worshipped anthropomorphized anti-hero of Bitcoin himself, Satoshi Nakamoto, Jerry Chan writes.
One of the key features of Bitcoin SV which allows it to adapt and thrive without the need for administrators is the fact that it doesn’t try to do anything besides the basic task of being a public traceable indelible record keeper.
With CDBCs and useful tokens on BSV out of the way, Jerry Chan addresses the elephant in the room—non-fungible tokens, or more specifically, the economic viability of the speculative NFT market.
When at first the market discovered cryptocurrencies, people took to inventing new blockchains with new tokens to raise money and cash out at the expense of new adopters buying into their projects filled with high promise.
There has been some active discussions about the mining infrastructure and ecosystem of BSV hashrate adjustments and how it pertains to projects that wish to deploy on BSV, and what they should expect.
Jerry Chan explores some more technical aspects behind Bitcoin BSV, and the lessor known under-the-hood components that are more of an interest to students of computer science.
Bitcoin is not an investment product; it is simply a technology. To be fair, it isn’t exactly the same as technology products in the past, where paying for its use was completely separate from the platform itself.
This week, Jerry Chan takes a break from the hard computer science aspects of BSV to one which has more appeal to general society—the problem of agreeing on the timing or sequencing of events or actions.
By looking at BSV from a network engineering perspective, Bitcoin can be seen as something more than just a token system, but a global network with a dynamic and customizable topology, Jerry Chan writes.
A Turing machine—or an unbounded number of them—can be built on top of the public infinite tape, and any number of parallel computations can be calculated.
A common feature of computer languages which generally make them Turing complete is the ability for the language to allow for structured control flow of a program, either through loops or jumps.
