Just noticed another tax of hyperinflation: cognitive load.
Grocery stores hide constant price hikes behind endless discounts and bizarre bundle combinations.
I just bought the wrong coffee trying to decode one.
The cognitive-load tax.
Delighted to share this breakthrough:
After diligent efforts, I'm proud to unveil a novel algorithmic price oracle, presenting a trustless alternative to solutions like @chainlink.
1/3
Price feed is a critical infrastructure used by many building blocks in DeFi, like @Uniswap, @compound, @AaveAave, and many others.
While there are certain edge-case nuances, I believe this innovation will be a fundamental building block in approaches like @sedaprotocol.
2/3
I think there's a major problem with the work ethic in our generation. Younger generations seem to expect more for less work and reflect poorly on feedback.
It almost seems like as technology advances, it gets harder to maintain discipline.
Most games I've played have an algorithmic boss fight gameplay. It's mostly about reaction time & learning the patterns to escape boss attacks.
What if bosses learned user patterns so that the user has to introduce some sort of randomness into their fighting strategy ?
Are there dApps that implemented any kind of strategy to correctly trigger (ex:MA) buy & burn of their native tokens? These funds can be much more valuable in burning during bear mkt
It seems like most L1s and dApps are missing out on the importance of timing these transactions
Smart cities mostly failed as a concept due to high political and regulatory overheads attached to set them up. But the core idea, which many miss, is to let communities self-organize and function autonomously will keep morphing, materializing, and growing.
@mikeykremer @avalancheavax It is true subnets decrease burned feeds in AVAX - the upside is vertical scalability with additional AVAX hold pressure because subnetValidators ⊂ avalancheValidators.
The problem with $LUNA isn't experimenting with new models, but making the same mistakes over and over again.
We've seen the effects of sloppy feedback loops in $MKR - $DAI before, $LUNA - $UST was just a sequel.