Because when enough people start using a technical term incorrectly, that mistake becomes the "official, most correct" usage of the term in the natural language.

Examples:

CPU - you know, the big beige computer box under your desk, as opposed to the "monitor". Luckily somehow English has escaped from that misuse that was common in the 1990s and 2000s.

"I could care less" - This now means "I couldn't care less" which actually made literal sense.

"Meme" - you know, those silly viral images or animations passed around on socials or the Interweb: Example "Grumpy Cat"
                                As opposed to its intended scientific meaning as "a unit of information with the property that it can induce its hosts to replicate it and thus carry it forward in time." Examples: the holy books of a religion.

And now we have "AGI" which if we're not careful will come to mean "Agentic AI" or even, an ARM chip used for AI, as opposed to "Artificial General Intelligence".

 

Stop all the alternatives to fossil fuels and then start a war carefully calculated (lol) to raise oil and gas prices through the roof. I guess we know which industry his shell companies, relatives, and cronies are all invested in.

Seriously though, can we just exile Trump and his fossil fuel CEO buddies to a large iceberg that just broke off a formerly stable ice shelf somewhere. Poetic justice. They'll be fine, because global heating is fake news.

Can you please put me through to Claude?

It's Trump and Hegseth's Pentagon that constitutes the risk to national security these days.

Am I right?
Check back in a couple of months after the US government-initiated Iranian asymmetric attack on the US homeland or ordinary citizens.

as far as any international sales going forward.

BYD and a few similar Chinese companies are going to eat them for lunch, or force them to just relabel Chinese cars as theirs, as Volkswagen, Volvo, Nissan, Honda, Toyota, and Mazda are doing.

Picked the wrong time to stop rapidly innovating their EV technology. Oops.

after this, I bet. Thank you for your service waking them out of complacency.

Our innate then cultivated morality enables trust and reciprocity necessary for the creation and maintenance of stable market trading and economic growth.

Morality is a meme which enables lower economic friction (lower waste of energy in petty squabbles, etc), overall having the effect of banishing social friction to the boundaries of larger and larger in-groups and enabling co-operation (whether market based or not) within the co-operating in-group. It also allows the size of the in-group to be increased by growing trust and co-operation with neighbours. Morality is a natural consequence of the max-entropy rule of non-equilibrium thermodynamics; it is a spontaneously evolution-discoverable feature of stable complex systems, allowing them to configure for more energy efficiency in activities and structure that builds toward increased survival probability.

Edit: VAT reduction for companies retaining more human workforce.... is what I meant.in the third sentence.

Hey slashdot, I know you probably can't afford innovation, but 5 minutes of editing power on a post would be amazing.

I think AI will continue changing rapidly (to substantially self-directed multi-agent Agentic, among other changes) so a tax on input token use or something like that is probably not feasible.

So instead, probably an increased value-added tax (VAT) is the way to go, but where companies are given VAT credit for their human labor force size measured in both wages and number of people, and excluding senior executives.

So higher VAT rate is charged.to low or zero human-workforce companies that to companies that have fewer human workers.

Can anyone think of a better way to tax the automated economy for wealth redistribution?

Bigger question. Assuming very low human employment, is there even any VAT or profit taxation rate that is sufficient to keep a wide-participation economy working? Or is it always more expensive to buy end-product/service stuff than the average universal basic income recipient can afford?

I get that AI+automation reduces end-product/service prices, but if VAT/profit tax revenue is always just a fraction of that, it won't be sufficient to support everyone to biuy those products/services to subsist, will it?

Maybe we also need to have higher VAT on non-subsistence products/services (not housing, not food, not basic energy amounts, etc) than on essential products/services.

Is there another technical model of AI+automation wealth distribution that works better? Ideas?

Fair enough. Thanks for the numbers.

Worth noting that the radiative forcing factor (global heating energy) of excess greenhouse gases is estimated at about 0.003 to 0.004 of the solar radiation incoming. (Source: leading answer sourced and/or calculated by Google Gemini lol).

So yeah, an order of magnitude or two difference in heating, if all human energy would be supplied this way.

Ok I'll take your word for it that you've done the (at least back of envelope, remember envelopes?) math. Just saying it's important to think and analyse at the system level, and define a sufficiently large system boundary.

Too lazy to calculate final answer myself: Showing work:

e.g. degrees C atmospheric heating (eventually settled atmospheric surface temperature delta after accounting for temp buffered by oceanic heat capacity) per GWh energy added to Earth system at surface, assuming otherwise in equilibrium at current average surface temperature.

+ heating from embedded and direct emissions of production and launch of space based solar power system.

vs
How many tCO2-eq / GWh for coal, for gas, times 0.00000000045 degrees C per tonne of CO2 added to atmosphere.

Would have to make an adjustment on each side to account for efficiency of converting the energy beamed (and energy burned) to usable energy across the range of uses, because the fair comparison is the global heating per amount of usable energy in each case.

Is it worth noting that such a system is (at least sometimes) capturing solar energy that would otherwise have missed the earth and beaming it onto Earth.

That is a positive global heating factor.

Someone needs to do the math to show that the fossil fuel GHG emissions avoided by using this system for energy outweighs the direct heating of Earth by this system.

exists?

If not I guess I would have a keyboard plugged into my keyboard.

It's not an SUV unless it can comfortably go up an old logging road with exposed rocks embedded in the road and many potholes, on a mountain.

A Pathfinder was an SUV, as was a Forerunner, or a Range Rover.

These new "SUVs" (grocery getters, kid soccer transporters) are a marketing joke that we all seem to have accepted. Those are cars. with a slightly more upright seating position.

The transformers used by LLMs discover and encode the relationships between words IN HUMAN THOUGHT EXPRESSIONS. The multi-layer nature of the deep neural net into which the transformers encode these relationships results in increasing levels of abstraction of the relationships being encoded in different layers of the neural net, along with the ways and strength that each more abstract relationship-aspect is involved in each more particular relationship. By focus on contextual relationships that humans attend to in their communications, and by having the ability to capture abstract aspects of the relationships, the LLM is effectively learning a semantic network of the concepts that words and word sequences utttered by humans represent. The carefully hierarchically organized and represented statistical properties of human syntax (when averaged over many many uttereances so as to ignore accidental, non-essential differences in expression) ultimately result in a usable (cheaply associatively tourable) representation of the semantics (MEANING) behind human communications. i.e. a general and specific knowledge base has been represented in the deep neural net.

It is then possible to design and implement various query-driven and goal-directed associative touring algorithms to visit the concepts in the knowledge base in appropriate touring orders (nearby concepts are nearby in the neural net representation, more general ones are "above", more specific ones are "below") so that we could say these algorithms are thinking abouit the queries and appropriate answers to them.