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i still think about that from time to time
1/9 Introducing LOTION (Low-precision optimization via stochastic-noise smoothing), a principled alternative to Quantization-Aware Training (QAT) that explicitly smooths the quantized loss surface while preserving all global minima of the true quantized loss. Details below:
Gaza @elonmusk @realDonaldTrump @libsoftiktok @MattWalshBlog @DramaAlert @EylonALevy @MichaelRapaport @benshapiro @HenMazzig @EYakoby @MosabHasanYOSEF @Asmongold @kirawontmiss @TiffanyFong_
We’re trying to collect rare datasets of civil uprising in London in 2026
Accidentally said "foundation" instead of "wrapper" and they kicked me out of Tel Aviv
Accidentally said "random" instead of "stochastic" and they kicked me out of SF
come on GPT-image-2 daddy needs a new pair of memes
just in case you’re running a contest on who predicted nsfw chatgpt first
one of my favorite creators needed to dress up as his own dick just to get an elon reply. more than anything it really shows there will not be an end2end grok as judge pathway to get viral - you will always need a big account to “sign off” on your content.
speaking from a goon/token ratio perspective this is incredibly more efficient.
just when you think AR is going to win, DiT gets a power up
three years ago, DiT replaced the legacy unet with a transformer-based denoising backbone. we knew the bulky VAEs would be the next to go -- we just waited until we could do it right. today, we introduce Representation Autoencoders (RAE). >> Retire VAEs. Use RAEs. 👇(1/n)
are you paying attention anon
the best founders are mothers on extended maternity leave?
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