When I’m driving, it’s actually unsafe for my car to be operated in that way

being able to consistently and reliably operate the thing without taking your eyes off the road

Considering they’d just spent the previous few questions discussing the visual-first aspect of touchscreens and accessibility issues for the visually impaired, I think that’s exactly what they were talking about.

The generalizations are about completely different devices. They talk about CT machines & automatic defibrillators later.

Another Deezer user in the wild! Been a subscriber to it for years now.

Thanks for the link, it was a very interesting read. While it is disappointing that it’s not actually a collective (assuming this blog post is accurate), having a platform run and owned by 6 creators is still better than YouTube’s governance structure, and still has the advantage in having both the capacity and desire to invest in creators.

An advantage of funding things via a collective like Nebula as opposed to each individual creator managing their own patrons is that new creators can start making bigger, more expensive projects quicker. Even established creators have this advantage, they can take bigger risks on bigger projects with the safety net of a share of the nebula pie.

I don’t think a project like The Prince would exist without Nebula, for example.

Ublock origin isn’t the only ad blocker out there. If you like Ublock origin, use Ublock origin lite. It’s fully V3 compliant.

So basically the Lemmy version of Subreddit Simulator, but allowing users as well?

Yes, absolutely. That is a concern that I too share, fellow meat being. We should be vigilant against superior, more capable, and really friendly artificial intelligences.

Even the question of “who” is a fascinating deep dive in and of itself. Consciousness as an emergent property implies that your gut microbiome is part of the “who” doing the thinking in the first place :))

So, first of all, thank you for the cogent attempt at responding. We may disagree, but I sincerely respect the effort you put into the comment.

The specific part that I thought seemed like a pretty big claim was that human brains are “simply” more complex neural networks and that the outputs are based strictly on training data.

Is it not well established that animals learn and use reward circuitry like the role of dopamine in neuromodulation?

While true, this is way too reductive to be a one to one comparison with LLMs. Humans have genetic instinct and body-mind connection that isn’t cleanly mappable onto a neural network. For example, biologists are only just now scraping the surface of the link between the brain and the gut microbiome, which plays a much larger role on cognition than previously thought.

Another example where the brain = neural network model breaks down is the fact that the two hemispheres are much more separated than previously thought. So much so that some neuroscientists are saying that each person has, in effect, 2 different brains with 2 different personalities that communicate via the corpus callosum.

There’s many more examples I could bring up, but my core point is that the analogy of neural network = brain is just that, a simplistic analogy, on the same level as thinking about gravity only as “the force that pushes you downwards”.

To say that we fully understand the brain, to the point where we can even make a model of a mosquito’s brain (220,000 neurons), I think is mistaken. I’m not saying we’ll never understand the brain enough to attempt such a thing, I’m just saying that drawing a casual equivalence between mammalian brains and neural networks is woefully inadequate.

That’s a strong claim. Got an academic paper to back that up?

This is why I strictly refer to these things as LLMs. That’s what they are.

I’m happy with the Oxford definition: “the ability to acquire and apply knowledge and skills”.

LLMs don’t have knowledge as they don’t actually understand anything. They are algorithmic response generators that apply scores to tokens, and spit out the highest scoring token considering all previous tokens.

If asked to answer 10*5, they can’t reason through the math. They can only recognize 10, * and 5 as tokens in the training data that is usually followed by the 50 token. Thus, 50 is the highest scoring token, and is the answer it will choose. Things get more interesting when you ask questions that aren’t in the training data. If it has nothing more direct to copy from, it will regurgitate a sequence of tokens that sounds as close as possible to something in the training data: thus a hallucination.

Ah, I misunderstood then, sorry. But still, even with all the investment in the world, LLM is a bubble waiting to burst. I have a hunch we will see truly world-altering technology in the next ~20 years (the kind that’d put huge swathes of people out of work, as you describe), but this ain’t it.

There’s an upper ceiling on capability though, and we’re pretty close to it with LLMs. True artificial intelligence would change the world drastically, but LLMs aren’t the path to it.

Actually, that’s not the real reason patents are public. The reason is to allow everyone to freely use the patent after the expiry.

The tradeoff is supposed to be the inventor gets exclusive use for a decade in exchange for detailing exactly how the thing works for everyone else.

For the families who can afford it, daycare is the replacement.

“It takes a village to raise a child” is an old expression for a reason. Historically (EDIT: And today in most of the world), parents wouldn’t take care of their kids 24/7. They would have parents, siblings, neighbours and friends to help share the load.

The idea that parents and parents alone do 100% of everything to raise a child is a very modern western thing.

I don’t know the details of this app, but if it’s specifically US streets and notes on households there, then GDPR does not apply, as they’re not mapping EU households. GDPR is only invoked if the personal information of Europeans is at risk.