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Thomas

@aviationdoctor.eth

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Feels like Ethereum is now in this endgame race for RWA tokenization supremacy, and the runway is getting shorter. Ethereum has all the right infra and characteristics (incl. credible neutrality, decentralization, trustlessness, etc.) but the TardFi corporate decision-makers remain largely unaware or indifferent. Every ETH maxi is hoping for a major RWA adoption announcement (by BlackRock, Texas Stock Exchange, etc). Yet proprietary L1s are cutting corners with marketing dollars and being able to present a smiling suit to board rooms. For all their talk about disruption, corporates still want the reassurance of a wet ink contract and a neck to grab, and a decentralized network won’t provide that. I’m aware of Etherealize & the new EF 1T security initiative; but also of Betamax vs VHS. This is not about price btw — I just worry about a future where lesser solutions (proprietary blockchains / glorified databases with some vague crypto jargon peppered in) prevail over a universal, civilizational ledger
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It's fascinating to me that most of the 2D plots that we use in algebra are deceptively hiding the true behavior of functions, which only becomes visible once we start mapping them in 3D space, by switching from real to complex numbers. So many people's understanding of mathematical behaviors are based on a flawed and incomplete low-dimensional premise —much like seeing only the 2D shadows of 3D objects on the walls of Plato's cave. Extrapolating, it makes me wonder how much deep intuition we're missing out on by operating most commonly on the real number line (1D), or at best in the complex plane (2D), but almost never using the quaternion (4D), octonion (8D) or sedenion (16D) numbers — our puny brains probably couldn't take it anyway. This is an area where I'm hopeful that AI, being free of our low-dimensionality bias, can help us make strides. Watch just 30 seconds of https://youtu.be/92wXQYcYLMg?t=1469 to see how much depth is lost by switching back from 3D to 2D plots of familiar functions
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