you know, I’m not sure you can have an uncountably infinite number of people. so whatever that abomination is I’ll send the trolley down its way. it’s probably an SCP.

Trump rounds trans people up into death camps

“another attempt to distract us from the Epstein files!”

we have to find ways to restore the other side’s empathy. it’s the only thing that’s worked for me.

I’m trans. I spent months talking with TERFs, long ago. it was horrible. but, I managed to make a connection with one of them. I described my experiences, my life, the feelings of dysphoria, the hurt from the hate… she listened, and came to care about me, and left their hateful cult.

I repeated this with conservatives I met. taught myself to keep my cool, to be honest, to answer mocking with sincerity. I didn’t try to be “one of the good ones,” I didn’t throw my sisters under the bus, I made it clear that most of us were like me - just wanting to live happy, fulfilling lives.

we need to make friends with enemies. even when they betray us and hurt us. it’s dangerous but I can see no better way forward.

I’m pretty sure the Epstein files are the distraction from sending the military to conquer our own cities.

aren’t we all hermaphrodites in that analogy?

I’d actually love a series of 1-hour lectures and a series of textbooks, but I’m a massive nerd.

leader/follower for things like Paxos and RAID arrays works okay.

wait, like bears, or bear bears? are bear bears like bears?

what the fuck is with Windows App? it takes gigs and it’s literally just an RDP wrapper.

exactly everything I need and nothing more. doesn’t need X. reasonably lightweight. no fiddly configuration needed. nice support for tiling alongside floating.

also, very buggy (at least as of alpha.7), somewhat fickle (at least on my hardware), and I can’t remap keyboard shortcuts.

the SG teams embody American ideals, while the NID embodies American history. specifically, the NID acts like '60s CIA.

it pleases me that the actress who played Carter cared about science like the character.

HOG and Hough transforms bring me back. honestly glad that I don’t have to mess with them anymore though.

I always found SVMs a little shady because you had to pick a kernel. we spent time talking about the different kernels you could pick but they were all pretty small and/or contrived. I guess with NNs you pick the architecture/activation functions but there didn’t seem to be an analogue in SVM land for “stack more layers and fatten the embeddings.” though I was only an undergrad.

do you really think NNs won purely because of large datasets and GPU acceleration? I feel like those could have applied to SVMs too. I thought the real win was solving vanishing gradients with ReLU and expanding the number of layers, rather than throwing everything into a 3 or 5-layer MLP, preventing overfitting, making the gradient landscape less prone to local maxima and enabling hierarchical feature extraction to be learned organically.

pff, you call using an operating system bare metal? I run my apps as unikernels on a grid of Elbrus chips I bought off a dockworker in Kamchatka.

and even that’s overkill. I prefer synthesizing my web apps into VHDL and running them directly on FPGAs.

until my ASIC shuttle arrives from Taipei, naturally, then I bond them directly onto Ethernet sockets.

/uj not really but that’d be sick as hell.

for work I have a cloud dev VM, in which I run WSL2. so there’s at least two levels of VMs happening, maybe three honestly.

I recently told my mother that I’m probably the most intelligent person she will ever meet

and so humble, too! seriously though, this is a major red flag. I rarely find smart people to brag about how smart they are.

also, telling someone that their beliefs are wrong because they’re dumb, and that your beliefs are right because you’re smarter than them, has literally never worked. it will just make them resent you, your beliefs, and anyone they meet in the future who believes what you do. this kind of smugness has been the Achilles heel of Dems for years.

I was taught that serious academics favored Support Vector Machines over Neural Networks, which industry only loved because they didn’t have proper education. oops…

also, Computer Vision was considered “AI-complete” and likely decades away. ImageNet dropped a couple years I graduated. though I guess it ended up being “AI-complete” in a way…

is that the Network State that Peter Thiel is trying to build?

and make MAGA Place pay for it?

it’s weird that he uses those juvenile nicknames even in private(?) conversation.