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BDPW

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My experience has been the complete opposite, a bit of pressure goes a long way. There are many people who need to know X or Y and just dont have the maturity or innate motivation to do it properly. This comes from the experience of a Dutch school system so perhaps its different in other countries.

Nonsense, some of my friends are lawyers and they're able to give you consistent interpretations on why they think about a certain aspect of a law a certain way. The whole thing is that they work with this the entire time, so they have a really consistent 'head model' of how things work and why and how considerations should be weighted/ordered/whatever. LLMs just do not have this, there's no consistent underlying reasoning (the 'reasoning' traces in LLMs are really inconsistent)

Completely agree, I get that this is a stepping stone for future, more reliable robots but I found the demonstration underwhelming.

Its unclear how they intend to fix these fundemantal problems tbh. Things like "Automate the 'must not fail' moments with rules, APIs, and triggers." And "Use policies, templates, function calling, and explicit do/don't constraints." Make sense but if you have deterministic workflows, what do the llms still add?

Using APIs makes sense but isnt the whole point of these things that they can automate away stuff, it feels like we're building really big complicated frameworks to put these things in. Does it still have any actual benefit for stuff like this?

I hope I'm wrong but I haven't seen anything like this in practice. I would imagine we have the same problem as before where we could use it as an extra filter but the amount of shit that comes out makes the process not actually any more accurate, just faster.

Having seen from close-up how these reviews go, I get why people use tools like this unfortunately. it doesn't make me very hopeful for the near future of reviewing.

I don't know. I don't really care about the details in this case, I just don't really get the dismissive attitude that often surrounds things like this. Do you think this is not something that is worth looking into if it happens at such as large scale?

Just do be clear, I use genAI all the time for finding info and answering questions, so my browsing habits changed as well. I'm the kind of person who this case would indirectly be about. But don't you think that it's valuable to look at how do we compensate people who create content when their content is being used by genAI.

Many people seem to have the feeling of 'oh it's too late and those websites were garbage anyway (whatever that means), who cares'. Don't you think that's a bit of a silly way to go about this?

I just read the 'original affluent society' and (most of) your linked essay, I kind of agree with you. That said, the conclusions of Kaplan lead to estimates or 35-60 hours a week (excluding some depending on the group) and that surprised me a lot. That's very different from the image I got from some other comments in this thread talking about extremely long days with constant back-breaking work. Would you agree?

It's a pretty common thing that replanted forests turn into monocultures that don't have a lot of value for biodiversity. This then leads to all sorts of problems that healthy diverse forests don't have. I don't know if that's the case with the Appalachian forests but this is depressingly common. That being said, there are good steps being taken, e.g. the rewilding projects by mossy earth.

I would argue that you can consider those thoughts. But this is the difficult bit, I've had the experience before of thoughts/feelings whatever ypu want to call them where words fall short. Knowing multiple languages helps a bit but it still falls short sometimes (very rarely).

Language is very effective at this, but I don't think thought is inherently linguistic.

To me language is just a way to label, group or organise these things. So when you learn a new one you learn a new 'labeling system/taxonomy' does that sound familiar?

Having seen AstraZeneca inside, this is not the case. There's quite a lot of development going on. It is all non-fundamental though, the focus is heavily on late stage. No identification of disease mechanisms and such.