Finally! I had to set up a container with X on my headless server to get a few text files reliably synced, crazy stuff.
600 karma · joined April 13, 2015
You're supposed to do a $0 checkout for some reason and then download them
I was confused for a minute on how it's both _geostationary_ and _over Europe_ -- you can't be geostationary if your orbit is not over the equator!
Turns out[1] the MTG-S1 satellite is in fact geostationary and parked at exactly 0°00'00"N 0°00'00"E (off the coast of Ghana), 42164 km up from the center of Earth, it's just pointing at Europe at an angle.
The mindfuck angle is pretty effective though. This article wouldn't have been written otherwise.
Agreed on reliability and data transfer, that's a good point.
Out of curiosity, what do you use a 2x3090 rig for? Bulk not time-sensitive inference on down quanted models?
It is pretty sad to read people bash together the efforts to understand and control the technology better and the companies doing their usual profit maximization.
How the hell can people be so confident about this? You describe two smart people reasonably disagreeing about a complicated topic
The downside of diagrams from code is the loss of the wysiwyg aspect -- I want to be able to manipulate things visually.
Hah, that's a blast from the past. One reason it lasted as long as it did was the Knights of the Button, users who collaborated to keep it alive. I implemented the Zombie-presser, 1k+ donated accounts automatically pressing the button when no one else would. We kept it alive for a more then a month before the most embarrassing bug of my career finally killed it :D Good summary here [1].
Fun times! Thank you for the reminder :D
[1] https://www.theguardian.com/technology/2015/jun/08/reddits-m...
In the biological metaphor, that would be individual memory, in addition to the species level evolution through fine-tuning
>In contrast, for our own Entity Recognition models we can (and do) calculate probabilities that explain why a certain entity is shown.
>Hence, I think for API users of GPT3, OpenAI should return additional statistics why a certain result is returned the way it is to make it really useful and more importantly compliant.
For LLMs, you can get the same thing: the distribution of probabilities for the next token, for each token. But right now we cannot say why the probabilities are the way they are, same goes for your image recognition models.
Your comment has a new angle, but it only says how, not why. To paraphrase, layoffs are a way to fire white people in middle management in favor of women minorities. But why is that so?