Prager_U

I love cars way more than the next guy, but the meme clearly says "urban transportation".

Thank you President Michael B. Jordan Peterson 🇺🇸😎

Morpheus drinkin a forty in the death basket.

You're correct to identify that your position is inconsistent - (A) not wanting the innocent to be wrongly executed and (B) wanting the option to enact retributive punishment against certain offenders.

Let's analyze these two imperatives:

The benefits of (A) are quite self evident. It's bad to execute people for no reason. It's maybe the most brutal and terrifying thing the state can do to a person. And where there exists capital punishment, it happens with non-zero probability.

The benefits of (B) are that you get a nice bellyfeel that you've set the universe into karmic alignment. Since there's no evidence that capital punishment has a deterrent effect on crime (this can be proven by comparison of statistics between states/countries with capital punishment and without), this is really the ONLY benefit of position (B).

So if you want to prioritize what's best overall for reducing harm in society, then select (A). If you enjoy appointing yourself the moral arbiter of karma by enforcing who "deserves" to live and die (and killing some innocent people is a price worth paying), then select (B).

Simples!

This is orthogonal to the topic at hand. How does the chemistry of biological synapses alone result in a different type of learned model that therefore requires different types of legal treatment?

The overarching (and relevant) similarity between biological and artificial nets is the concept of connectionist distributed representations, and the projection of data onto lower dimensional manifolds. Whether the network achieves its final connectome through backpropagation or a more biologically plausible method is beside the point.

BRRRRR skibidi bop bop bop yes yes

BRRRR skibidi bop bop bop yes yes

Grab him by the bussy

You might want to configure it from scratch, with exactly the tools and utilities you want (e.g. networking utility, desktop environment). Or you might just find this process fun and interesting. Some people take issue with how Canonical is run, and decisions they make.

That is a used method for training other LLMs, I believe OpenAssistant did this.

Money ain't got no owners. Only spenders.

I can sympathize with them, as the way economic thought is portrayed in popular journalism makes it seem like ivory tower eggheads concocting overly-mathematized models to support bad policies. And I do believe there is some truth to this, with bad economists hiding shitty ideas behind the veneer of respectability that math provides. Science and technology are almost fetishized in our culture, especially by those who don't really study them academically, and I believe disingenuous economists and politicians use this fact to their advantage.

What they must realize is that whatever flaws they might identify to overhaul these bad economic models leads to... more economics! Hopefully better economics. But they're still participating in the field known as economics.

For instance, noting that the "homo economicus" doesn't exist IRL isn't really the gotcha that many people think it is. Rather, anybody doing economics properly is acutely aware of this fact, and is just exploring the limits of what such a simplifying assumption can yield. E.g. a surprisingly large mileage from the very parsimonious axioms of utility given by Von Neumann and Morgenstern. The really interesting and difficult part is thinking about how and why real life data deviates from the predictions made by the simple assumptions.