Your implicit assumption here is that both criticisms and solutions are equally easy (or difficult) to make, which is obviously not true, hence the relative quietness.
only in the podcasts I listen to
Yes definitely. Many of my fellow NLP researchers would disagree with those researchers and philosophers (not sure why we should care about the latter’s opinions on LLMs).
it’s using tokens, which are more like concepts than words
You’re clearly not an expert so please stop spreading misinformation like this.
You seem very certain on this approach, but you gave no sources so far. Can you back this up with actual research or is this just based on your personal experience with chatgpt4?
And how do you think robotaxis address all these issues (high fare, poor coverage, limited operating hours)?
You know the problem already: poor coverage of public transit. Why not advocate for that? It’s much safer than any cars, and we have the tech right now. We can stop killing people right now.
Many people literally die each year because of car-centric infrastructure, and you’re basically telling us to calm down? No fucking way.
Before cars, there used to be a massive amount of infrastructure for trains and streetcars, not to mention walkable neighbourhood, but they all get demolished for cars. So yes, we do operate like that.
And did I mention that car-centricity kills people each year? So yes, eliminate all cars if we have to. But honestly, I don’t think anyone wants to eliminate all cars, just those we don’t need (which is most of them).
Sounds like your city is the problem here, not trains. Vote better.
Normal taxis benefit both the elderly and people with disabilities like you said right now. So why bother with robotaxis?
How is solving a quadratic equation, whose analytical solution is known, equal to driving?
Trains now are already much less lethal than cars. If safety is truly important for you, you would advocate for trains. You ain’t fooling anyone mate.
I’ve been enjoying cycling as transportation lately, so right now my top choice is a bike. It’s just so much fun! The ability to dismount and instantly be a pedestrian, and to bring it inside trains makes bicycles very versatile.
The temperature scale, I think. You divide the logit output by the temperature before feeding it to the softmax function. Larger (resp. smaller) temperature results in a higher (resp. lower) entropy distribution.