BDPW

Imo this is so overrated, the biggest difference is that children have 100% exposure and almost all language they come across is tailored exactly to the right level, just for them.

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.

What would you do instead to make sure the student actually possesses the skills they are intended to have learned by the end of a program?

And especially China. And Japan.

If you had an llm that could accurately predict when a claim is uncertain it would be very popular, I think. I would pay for that kind of reliability tbh

You dont have to literally send a null token. Train it to generate text that summarizes the evidence that is there but the uncertainty of the final answer to a prompt.

Has nothing to do with size, see Japan and China.

I think they mean that a phd doesn't mean much relatively speaking, since everyone around has one so it's less impressive and you're less of an expert when everyone around you is knowledgeable in the same domain.

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)

Who are you in this comparison?

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

You're conflating coordinate and proper acceleration.

Physical classrooms don't really scale either, is that really a fundamental problem?

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?