No, that is not L5. There may be some cities like that, especially ones designed from scratch, but that’s not L5. And it won’t help eg in NYC. Certainly possible in principle to be safer than humans, fully automated, and it probably will happen, I just doubt it will be soon.
SAFETY
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Autonomous Vehicle Safety Evaluation and Independent Agency Oversight
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Most commutes, around the globe, really? I am willing to bracket regulatory issues and pulled over vehicles if we can agree on a way to evaluate safety that is some kind of independent agency that has access to data.
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L5 AGI Safety Betting: Can We Achieve It by 2030?
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You want to put money on (safe as humans) L5 by end of decade? @metaculus @MatthewJBar https://
x.com/realGeorgeHotz
/realGeorgeHotz/status/1591567145032368129
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Innate Priors Shape AI Learning: Evolution Over Minimalism
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– you still need some prior to organize that infinite data and decide how to generalize from it
– the choice to minimize is an aesthetic choice, not a scientific one; evolution has clearly endowed many animals with significant priors (eg baby ibex climbing down a mountain). -
Balancing AI Risks and Benefits: A Regulatory Approach
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Correct. The risks outweigh the benefits. I don’t think it should be illegal but it should be approached as a drug or a loaded weapon.
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Strong innate priors in machine learning systems
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that’s learning that the set of relevant cases is empty; it’s still a strong innate prior
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Controlled Perturbation: Function Application as Risk Factor
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But in reality you may fail when you try to do f(X), so doing it is effectively just another perturbation, albeit under your control.
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Re-impressionism Challenges AI Censorship of NSFW Content
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The themes chosen by Re-impressionists were also in challenge to the #AI-based censorship, exploring so-called NSFW themes that would be aggressively censored by cloud services which monopolized terra- and peta-byte generative models. "Not Safe For Who?"
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Pixel patterns cause image blur for corporations using uncurated datasets
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The use of these pixel patterns resulted in increasingly blurred images throughout the 2020s for corporations still using uncurated and infringing web-scale datasets — as opposed to the industry standard datasets based on opt-in consent.
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Adversarial Pixel Patterns Outside Natural Image Manifold
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In particular, the pixel patterns used were specifically not on the "manifold" of natural images — thus making it difficult for algorithms such as Latent Diffusion to generate good results. Ironically, optimization techniques were used to find these adversarial pixel patterns!