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101011

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101011
·4 か月前·議論
how do you define system completeness? what if you ship one really big feature vs three really small ones?

I would posit that you need extra context to obtain meaning from those metrics, which inherently makes them less visible
101011
·8 か月前·議論
> You can either seek understanding or seek blame, but not both at once.

This is the first I've heard this statement (not necessarily the idea), but I found it incredibly beautiful in it's simplicity - thanks for sharing!

Are there origins to this that you're aware of? With some searching I found some adjacent thread lines to stoicism and Buddhism, but nothing quite the same.
101011
·10 か月前·議論
I think it's fair to call out a dark pattern for account deletion (which, for better or worse, is common practice) - but the data training and data retention thing can both be disabled...I was much more surprised that they DIDN'T train on data as long as they did, when every other LLM provider was sucking in as much data as they could (OpenAI, Google, Meta, and xAI - although Meta gets a pass for providing the open-weight models in my head).

Anthropic has made AI safety a central pillar of their ethos and have shared a lot of information about what they're doing to responsibly train models...personally I found a lot of corporate-speak on this topic from OpenAI, but very little information.
101011
·5 年前·議論
Don't most IDEs handle this already?