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If you're going to reason from fiction, then reason from Good fiction.

The woolly mouse is a Tribble, not a dinosaur, and David Gerrold is a better author than Michael Crichton.

Replying to Avatar Lyn Alden

When it comes to AI, philosophical people often ask "What will happen to people if they lack work? Will they find it hard to find meaning in such a world of abundance?"

But there is a darker side to the question, which people intuit more than they say aloud.

In all prior technological history, new technologies changed the nature of human work but did not displace the need for human work. The fearful rightly ask: what happens if we make robots, utterly servile, that can outperform the majority of humans at most tasks with lower costs? Suppose they displace 70% or 80% of human labor to such an extent that 70% or 80% of humans cannot find another type of economic work relative to those bots.

Now, the way I see it, it's a lot harder to replace humans than most expect. Datacenter AI is not the same as mobile AI; it takes a couple more decades of Moore's law to put a datacenter supercomputer into a low-energy local robot, or it would otherwise rely on a sketchy and limited-bandwidth connection to a datacenter. And it takes extensive physical design and programming which is harder than VC bros tend to suppose. And humans are self-repairing for the most part, which is a rather fantastic trait for a robot. A human cell outcompetes all current human technology in terms of complexity. People massively over-index what robots are capable of within a given timeframe, in my view. We're nowhere near human-level robots for all tasks, even as we're close to them for some tasks.

But, the concept is close enough to be on our radar. We can envision it in a lifetime rather than in fantasy or far-off science fiction.

So back to my prior point, the darker side of the question is to ask how humans will treat other humans if they don't need them for anything. All of our empathetic instincts were developed in a world where we needed each other; needed our tribe. And the difference between the 20% most capable and 20% least capable in a tribe wasn't that huge.

But imagine our technology makes the bottom 20% economic contributes irrelevant. And then the next 20%. And then the next 20%, slowly moving up the spectrum.

What people fear, often subconsciously rather than being able to articulate the full idea, is that humanity will reach a point where robots can replace many people in any economic sense; they can do nothing that economicall outcomes a bot and earns an income other than through charity.

And specifically, they wonder what happens at the phase when this happens regarding those who own capital vs those that rely on their labor within their lifetimes. Scarce capital remains valuable for a period of time, so long as it can be held legally or otherwise, while labor becomes demonetized within that period. And as time progresses, weak holders of capital who spend more than they consume, also diminish due to lack of labor, and many imperfect forms of capital diminish. It might even be the case that those who own the robots are themselves insufficient, but at least they might own the codes that control them.

Thus, people ultimately fear extinction, or being collected into non-economic open-air prisons and given diminishing scraps, resulting in a slow extinction. And they fear it not from the robots themselves, but from the minority of humans who wield the robots.

Again, this was discussed in Moravec's 1988 book "Mind Children."

https://en.wikipedia.org/wiki/Hans_Moravec

Replying to Avatar Lyn Alden

Gm.

The human brain runs on something like 20 watts of power. Less than a lightbulb. How many calculations it can do per second is partially unknown, but based on various estimates over the years the processing power is generally believed to be something like one exaflop per second. Some estimates are lower in the petaflops, while others are some orders of magnitude higher. Obviously “software” matters too, not just raw processing ability. The programming of the processor ensures that the processing capability is used efficiently rather than wasted.

The top superconductors crossed the exaflop level within the past few years. However, they run on like 20 megawatts of power; a million times more power than the human brain. They’re extremely large and energy intensive.

As a result, datacenter processing capability reaches something akin to the processing capability of a human brain well before that level of ability can be installed in a human-sized robot with similar energy consumption levels as a human.

Now, robots can offload some of their processing to datacenters, but still at a relatively high cost per calculation for a while, and at the general bandwidth limit of whatever the best wireless rate is in a region at any given time.

For some calculation types, of course computers passed humans long ago. A basic math calculator, for example, beats the best humans at calculating mathematical formulas. But when we talk about human brain “calculations” what it means is that the brain is taking in enormous amounts of information (all five senses at high fidelity, plus other indirect senses like acceleration/balance and other inputs), calculating it to make sense of it, calculating all sorts of things to interact with the environment, and simultaneously running the processes related to sapient thought and general problem solving.

As a result, it’s far easier to get a robot to work on an assembly line more efficiently than a human, or to calculate an insane number of protein folding tests, and things like that, than it is for a robot to be able to operate as effectively as a human in the real world with countless unexpected hazards.

For example, imagine a hypothetical robot handyman. It can drive out to your house and fix any residential electrical, plumbing, or hvac issue, or help with various miscellaneous things (fix drywall, get something out of a tree, carry stuff out of your attic, etc), and then drive back to the station. This is a shockingly hard problem. First they need extremely advanced mechanical bodies. Second they need processors strong enough and cheap enough to safely operate in 3D space with all sorts of unexpected things happening around them (compared to a highly controlled manufacturing floor), now all of these skills, and interact with language.

So, AI can start helping us offload certain types of white collar remote work and expand medical breakthroughs before it can replace human level in-field skilled physical labor. And it can start helping with specific in-field tasks that require less programming, like a robot dog or robot butler to watch your property or come with the owner around town, listen to owner commands and carry some of them out, and follow basic rules when left alone, well before it can fully replace a human for many in-field things.

Anyway, that’s a general framework or napkin math to help think through the order of impacts that AI can have as it goes up orders of magnitude in power and efficiency in the coming years.

This path is pretty well described by Hans Moravec in his 1988 book "Mind Children." I assume it's available at your local library, or at the internet archive for those interested.

Thank you for the reference.

Coinledger's business depends on knowing these details, and they seem like a good source.

Please keep reporting on your experience with strike here And on Twitter. I follow it with great interest, and consider following your example.

That's a fair point. I'll have to read the IRS directives carefully. I suggest acting as if it does, at least in tax calculations. Whether or not you apply it to the amount paid is a different story.

To Know, Dare, Will and Keep Silent.

Happy 100k.

Mr Barker has it right.

Horading stuff against possible future need is hedging,

and subject to the same analysis.

In general, if you save something because you might need it someday,

discard it now and commit to buying a future replacement.

Money stores as bits.

Stuff stores as atoms.