uhhh... Is that "confirmed"? Seems to say "Trump still won't commit" which is substantially different from "Trump won't do it"
bignate31
joined 1 year ago
Yeah, I grew up in Fahren-wasteland, but have lived in Celsi-heaven for 7 years. I embraced it, and now when someone says "40 FUCKING DEGREES!!" I know exactly what they're talking about. It's hot. You probably don't have an air con. It's misery.
I love my ThinkPad, but that's mostly because of the TrackPoint
oh nice! I found the same labyrinth after 4-5 taps.
this is so exciting! I imagine in the next few days I might be able to get to the content!!!
I just had a seizure ~~reading~~ trying to read this "article". what do I even click to escape??
"If you sing at the table you'll cry before you go to bed." I thought it was super common until I said it to my kid and my partner thought I was crazy.
"We will continue to charge you penalties until you can afford to pay us back"
Well actually you can't die either, that's illegal. Let me know if you find any other options and I'll make sure they get illegal'd as well!
oooh. design intricate sandwiches! sounds like a lovely holiday!!
Favourite part of the whole article:
A spokesperson for Truth Social said, “It’s hard to believe that Reuters, once a respected news service, has fallen so low as to publish such a manipulative, false, defamatory and transparently stupid article as this one purely out of political spite.”
"You never saw what you thought you saw. And even if you did, it was entirely justified and your interpretation was extreme."
Yeah, the problem is how to sanitise effectively. You've gotta be able to find a way to automatically strip out "bad" things from your training data (via an "oracle"). But if you already had that oracle, you could just slap it on your final product (e.g. Search) and make all the "bad" things disappear before they hit the user (via some sort of filter).
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Another great example (from DeepMind) is AlphaFold. Because there's relatively little amounts of data on protein structures (only 175k in the PDB), you can't really build a model that requires millions or billions of structures. Coupled with the fact that getting the structure of a new protein in the lab is really hard, and that most proteins are highly synonymous (you share about 60% of your genes with a banana).
So the researchers generated a bunch of "plausible yet never seen in nature" protein structures (that their model thought were high quality) and used them for training.
Granted, even though AlphaFold has made incredible progress, it still hasn't been able to show any biological breakthroughs (e.g. 80% accuracy is much better than the 60% accuracy we were at 10 years ago, but still not nearly where we really need to be).
Image models, on the other hand, are quite sophisticated, and many of them can "beat" humans or look "more natural" than an actual photograph. Trying to eek the final 0.01% out of a 99.9% accurate model is when the model collapse happens--the model starts to learn from the "nearly accurate to the human eye but containing unseen flaws" images.