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AI capabilities

Human learning algorithms can be instantiated in silicon.

Whatever the brain does to learn can in principle be reproduced in a machine. Denying this leaves some human abilities permanently out of reach for AI.

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Novella·2010AI-generated draftSource unchecked

The Lifecycle of Software Objects

Ted Chiang

A start-up sells digients, artificial beings that must be raised like animals or children over years, as virtual pets; the company folds, the platform they live on is superseded, and their handful of remaining owners spend a decade keeping them alive, unable to pay to port them to the new world until a sex-companion company offers to fund it, while the digients themselves grow into adolescents who want work and legal personhood.

Conscious aiAi companionsOrdinary life with AI
+3Human–AI coexistenceMixed futureSexuality
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Turning point: Relative / conditionalOriginal source

Neuroblast is a genomic engine whose digients learn the way animals and children do, through attention, reward, and practice, and Ana’s zookeeping skills transfer directly to training them.

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Book·2024AI-generated draftSource unchecked

The Singularity Is Nearer

Ray Kurzweil

The price-performance of computation keeps doubling roughly every sixteen months, so AI matches the best humans in every field by 2029; in the 2030s AI-driven medicine reaches longevity escape velocity, medical nanorobots maintain the body, and nanoscale interfaces connect the neocortex to the cloud while automation drives prices down and universal basic income absorbs displaced work; by 2045 merged human and machine intelligence has expanded a millionfold, with risks managed by principles, broad distribution, and the merger itself.

Recursive self-improvementFlourishing / utopiaPost-scarcity
+6Human–AI coexistenceSucessor speciesRoboticsAi-driven job displacementUniversal basic incomeConscious ai
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Turning point: 2029–2045Original source

Kurzweil’s 2029 estimate rests on a computational budget for the human brain of about a trillion calculations per second, and the virtual neurons added in the cloud are treated as more of the same neocortex.

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Book·2016AI-generated draftSource unchecked

The Age of Em

Robin Hanson

Brain emulations that can be copied and run at any speed arrive within roughly a century and displace humans in almost all jobs; competition among trillions of copies drives em wages to subsistence and the economy to doubling every month or so, a few hundred clans of the best-suited originals dominate work, and biological humans retire on em-economy investments while an era that lasts an objective year or two passes into something stranger.

Ai-driven job displacementSucessor speciesHuman–AI coexistence
+2RoboticsMixed future
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Turning point: Relative / conditionalOriginal source

Ems are cell-by-cell models of specific human brains running on computer hardware, and Hanson treats them as thinking and feeling like humans.

Not applicable33 entries