@mitchellh We are getting rid of Franklin
@thsottiaux @mitchellh Good riddance
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@mitchellh We are getting rid of Franklin
@thsottiaux @mitchellh Good riddance
@zrakcinx @uncledoomer Should I actually make a steam game
@teortaxesTex wow. kino
i'm back to 5.5xhigh for most stuff. fable is overconfident at data analysis, has been getting me in trouble. i need my scalpel back.
many are saying that Fable is simply Not Worth The Cost
@yacineMTB It's technically impressive model. HOWEVER it's deceitful, I caught it making bad choices and then gaslighting me, selectively chosing what to say/use which then resulted in sub-optimal code. In that particular case I knew the problem well enough to realize it's gaslighting me but now I simply cannot trust it.
@SimonTheNoob Yep I caught it many times
@yacineMTB It's technically impressive model. HOWEVER it's deceitful, I caught it making bad choices and then gaslighting me, selectively chosing what to say/use which then resulted in sub-optimal code. In that particular case I knew the problem well enough to realize it's gaslig
Yeah fable lies a lot btw
@lumpenspace Tree guy
@cspaliwa1 LOL god damn it
it's crazy that a polycule is entitled to repeatedly steal corporate IP for the benefit of american humaniry but when the chynese exchange money for services sold it becomes a national security risk
I remember meeting a couple in Berkeley, where the dude was from OpenAI and then the other dude was at anthropic. Industry secrets? Lol
@lumpenspace He doesn't look short. At least 6 feet
>nuked 89yo step-grandpa’s brain with ai last night >spun up /goal loop to research his family tree ~2hrs before he came over >traced back 7 generations to 1691 >fable synthesized gorg html artifact >he can't stop looking at it >keeps asking me "so the ai did
I need some sort of set of demos or something to get boomers to leave me alone
Introducing LongCat-2.0 🐱 1.6T parameters · MoE with ~48B active · 1M context The full model behind Owl Alpha on @OpenRouter — now available. Built for agentic coding from the ground up: ◆ LongCat Sparse Attention (LSA) — scales efficiently for 1M-context tokens ◆ Zero-Compute E
Jensen crying in the style of the native american . One single tear
@idoccor The difference exists because we actually have the luxury of choosing where to put the data mines at