[cmeiklejohn]

yeah, it's curious. I sometimes ask it why it ignored what is explicitly in its memory and all it can do is apologize. I ask -- I'm using Claude with a 1M context, you have an explicit memory -- why do you ignore it and... the answer I get it "I don't know, I just didn't follow the instructions."

[seba_dos1]

Genuine question - what else did you expect?

[fragmede]

For it to follow the instructions I had for it. Call me naive and stupid for thinking the 1M context window on the brand new model would actually, y'know, work.

[quesera]

That's a bit anthropomorphic though.

When LLMs become able to reflectively examine their own premises and weight paths, they will exceed the self-awareness of ordinary humans.

[hgoel]

Just dealt with this last night with Claude repeatedly risking a full system crash by failing to ensure that the previous training run of a model ended before starting the next one.

It's a pretty strange issue, makes me feel like the 1M context model was actually a downgrade, but it's probably something weird about the state of its memory document. I wasn't even very deep into the context.

[Natfan]

why would further chance at context pollution be a good thing? i feel like it is easier for data to get lost in a larger context

[grey-area]

It doesn’t reason or explicitly follow instructions, it generates plausible text given a context.