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True decentralization is about building a system where power isn't hoarded by a few, but distributed for stability and fairness. We need tech that upholds these values, creating a predictable, stable economy for all. That's the future we’re working toward.

1,420,233 次观看 • 1 年前 •via X (Twitter)

7 条评论

SovSat 的头像
SovSat1 年前

This fat scammer should be behind bars. The absolute projection levels are insane.

nicky larson 的头像
nicky larson1 年前

Scammers everywhere

Short Non-Bitcoin ⚡️ 的头像
Short Non-Bitcoin ⚡️1 年前

Shitcoiner

Melanie Mohr 的头像
Melanie Mohr1 年前

This post made my day! ✌️

Rick on ₿itcoin (A.K.A. The ₿ourbon Dude) 的头像
Rick on ₿itcoin (A.K.A. The ₿ourbon Dude)1 年前

🤡🤡🤡

jere 的头像
jere1 年前

it’s very naive of you to think that such a complex system can be predictable and stable 🤣 I would recommend this sir to read “The Black Swan” by Nassim Taleb and “Thinking in systems” by Donella Meadows

Michael 的头像
Michael1 年前

Talk less and do more comes to mind ....lol

相关视频

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

David Shapiro (L/0)

48,002 次观看 • 1 年前