Nobody is mentioning that one of the biggest NFT payoffs happened yesterday. Over $500m was paid to thousands of people who previously minted (or registered) a domain name on the Ethereum Name Service ($ENS). coindesk.com/business/2021/…
This is an early glimpse as to how producers can benefit when their platforms seek the securitization of their governance.
The problem with platforms such as marketplaces (uber, airbnb) and social networks is that they fail to properly compensate their producers. The majority of the gains trickle up to the administrators of the platform and not its individual producers. medium.com/intuitionmachi…
If we look closer at DeFi platform like Uniswap and Compound we begin to see the makings of the future of decentralized platforms. Compound is a lending platform where individuals can supply their assets for lending. Uniswap is one where one supplies 'liquidity'.
In both platforms, the 'NFTs' created by the producers are also incentivized through airdrops or mining of governance tokens. Think of it like how a credit card gives you reward tokens for using their card.
NFTs can be of any complexity such that the rewards are calculated to incentivize behavior that best improves the overall growth and utility of the entire platform. What we are seeing today is the primordial form of decentralized production entities.
The problem with blockchain systems is their inaccessibility to the real world. But this is where it gets really interesting! A lot of focus has been on virtual things like finance (DeFi) and digital artifacts (NFTs and Games).
Bridging the physical and virtual worlds is very difficult. The only trillion dollar marketcap company that has done so is Amazon. Almost every other company resides in the virtual space. But what will be the Amazon for in the cryptocurrency economy?
Perhaps it's related to the lightest inert substance on earth.
Meta-conceptual frameworks like category theory, constructor theory, Peircian speculative grammar are emerging all ways to formalize complex adaptive systems at the boundaries.
They are like most formal models, at best a descriptive model of reality. However they sufficiently abstract to appeal to human capable reasoning and thus aid in setting the boundary conditions on where computational systems can take over.
A useful analogy to make here is in constraint solvers where the 'programmer' sets up the constraints for an algorithm to crunch away to find a solution. A meta-conceptual framework aids one in defining the useful constraints that a complex system should conform to.
It's insanity that the primary tool we have for controlling the economy is through the manipulation of interest rates. This has led to the utter bonehead idea that if you lower the interest rates for buying homes and paying for college that you make both more affordable.
Homes and higher education become more affordable when through become more efficient in their creation. Yet here we are, we have yet to demolish government institutions like Fannie Mae, Freddie Mac, and Sallie Mae.
If you just look around you, we have all kinds of financial instruments that were invented in the 1950s that promise all kinds of payoffs that they cannot possibly deliver. It should be obvious to anyone that you cannot fundamentally change something by changing its looks.
The form of language (i.e. its syntax) does not tell you anything about its meaning. An ancient human language cannot be deciphered without a corresponding Rosetta Stone.
That's because languages are just frozen social habits of communication by their users. Social habits become norms via information propagation and replication. Not unlike a virus propagating its RNA.
This however implies that within human languages there are commonalities as a consequence of the common interactions with humans and their neighbors.
A ton of talks on crypto infrastructure stuff going in Lisbon. @solana@SolanaConf#solanabreakpoint#breakpointlisbon Technology is moving at breakneck speed that it's really tough to keep current! Even more difficult to be involved in the action early.
@solana@SolanaConf There is always an ongoing tension between innovation and usability. Innovation thrives in permissionless and decentralized environments. Unfortunately, this free-for-all makes usability difficult because usability involves building facades that hide useful abstractions.
The conventional approach is to continue to layer technology on top of each other, thus creating a user experience accessible to the majority. Present-day complexity in cryptocurrency is a consequence of exponential innovation.
The innovation found in biology is a consequence of a development process that is absent of a centralized mind. This has benefits in that it leverages massively parallel processes. It can explore possibilities beyond that what a sequential mind can do.
However, the lack of a centralized mind also has its own downsides. Biology isn't able to consolidate its discoveries as efficiently as that of an integrated mind. A good analogy to explain this is refactoring found in software development.
In software development, rapid development eventually leads to the accumulation of what is known as technical debt. As technical debt increases, the developers refactor the code so as to reduce the debt. There is a mindful method of creation and destruction.
@pmddomingos It's also the same ignorance that leads to wild expectations when the algorithm games the results. Ignorance like naivety is a two-sided blade.
@pmddomingos The progress we make in deep learning is a consequence of our overall ignorance about general intelligence. There are many alternative ideas on cognition developed by other fields. But these were done without the benefit of computational models.
@pmddomingos It is the combination of empirical AI (i.e. Deep Learning) and theoretical formulation (i.e. Cognitive science, biology, complexity science etc) that lends us a more systematic strategy towards discovery.