Representative appearances

• DEBATE: Why Do Gen Z Women Hate Men So Much?

  A book by Mark Manson about dating and attraction.

• Context Engineering SF: Context Engineering for Engineers - Jeff Huber

  state-of-the-art models

• Ship Without Bugs - AI That Reviews Code So You Don't Have To!

  Each coming model gets better at catching issues.

• Martin Casado on Tradeoffs Between General AI and Specific Use

  And so these models will will align with those fundamental trade-offs, right? And maybe it's performance, maybe it's correctness, maybe, you know, whatever it ends up being. And so as soon as you want a specific solution for a given problem where it it hits one of those trade-offs, you're just going to need a different model because otherwise you just you just can't end up having both. And and again, because I know the coding space the best, we see this a lot, right? Which is uh uh you know, a model that's very very good for certain parts of code is just not going to be generally good at other things because those are the trade-offs made when training it. And I I think that this is kind of the the future plurality of model. Is that true? You know, I I thought somebody said something. I may be wrong about this, but I saw some counterintuitive result that said that making an AI specialized in one area makes it worse in other areas. Did you see something like that? Well, yeah. I mean, so well, this is this is a very big debate, but the debate goes as follows. Like the first wave of AI was pre-training where everything you threw into it like it just got smarter. And so that's kind of a 10 for 10 technical win, right? Just because it'll be as good as writing coding as sonnets. But as soon as you're doing RL where you're training it in a specific domain with a specific verifier, you're likely losing, you know, other areas. So you make it really really good at playing chess, it's going to be less good at, you know, something else like that, you know, like, you know, writing general scores or something. So, so, so I I think the current debate now and the current data seems to suggest that RL doesn't generalize in the same way. And so now we are in this case where you would have a plurality of models because you're always kind of robbing Peter to pay all when you make it good at a certain domain.

• What makes AI hardware design go viral? | ON AI with Jordan Noone

  These models are at their infancy. ... This is our first generation of models um that we found releasable.