orpheansodality

did you mean Pentiment, led by Josh Sawyer at Obsidian?

for other folks currently in an incident trying to resolve the chaos this caused, the first commit we've found with issues in our repo is from ~10:30am pacific this morning

seems to have gone up for a few minutes before going back down again

My partner and I have played dozens of games of Spirit Island, far and away our most-played board game

Magic Maze is a great one!

https://boardgamegeek.com/boardgame/209778/magic-maze

I am also confused by this goal, I've started a discussion in the repo to get some clarity on intent and direction there: https://github.com/biomejs/biome/discussions/1642

I've appended `; tput bel` to the end of long-running scripts to get the same effect.

Fun fact: the `bell` control character is part of the ascii standard (and before that the baudot telegraph encoding!) and was originally there to ring a literal bell on a recipient's telegraph or teletype machine, presumably to get their attention that they had an incoming message.

To keep backwards compatibility today's terminal emulators trigger the system alert sound instead.

Sometimes a "PR machine" is just social capital at work. If there's anything else I've learned in this saga it's that Sam has had a consistent track record of building and maintaining highly positive relationships with anyone near his orbit, this board aside, and that it consistently pays him dividends.

Isn’t that the value-prop of Apple News?

there are so many comments here that really feel like they didn't read any part of the announcement other than that there's a thing called runes.

For me personally I tried svelte in the past and bounced off because there was too much implicitly happening that I needed to have a deep understanding of to model correctly. This solves basically all those problems for me.

I thought your video[1] especially did a great job walking through the pros this change brings. Thanks for all your great work on this!

1. Link for the curious: https://www.youtube.com/watch?v=RVnxF3j3N8U&t=6s

pairing is taking stories, it’s two people working on one task together.

it's anecdata but I drive this this on the regular and don't have any issues! May be some regional differences

if you think about the speeds involved, a single additional car in front of you on the freeway (or even any additional cars) adds pretty miniscule time to the total commute.

Let's compare a few situations. In the baseline you're tailing the car in front of you with a focus on not letting anyone cheat and get in front of you, let's say 50 feet away. Your commute is 30 miles, and in this frictionless sphere of traffic you're going 60mph the whole time. You get to work in 30 minutes flat.

In the second scenario you're following the 3-second rule[0]. This would put you ~285 feet behind the car in front of you. Let's say over the course of your commute 20 cars move in front of you. If the average car length is 15 feet, and they all are 50 feet away from each other, when all 20 cars are in place you're a net -(20 * 65) feet away from the original car, or 1300 feet total. At 60 mph that adds ~15 seconds to your total commute time.

Well worth having an easier time avoiding a potential crash IMO! Also has the benefit of helping prevent traffic to begin with[1]

0: https://driversed.com/trending/what-safe-following-distance.

1: https://www.youtube.com/watch?v=iHzzSao6ypE

why is it being applied to a tesla whistleblower post though

GPT-4 is a fine-tuned model (likely first fine-tuned for code, then for chat on top of that like gpt-3.5-turbo was[0]), while PaLM2 as reported is a foundational model without any additional fine-tuning applied yet. I would expect its performance to improve on this if it were fine-tuned, though I don't have a great sense of what the cap would be.

[0] https://platform.openai.com/docs/model-index-for-researchers

the paper says llama:

We develop a large multimodal model (LMM), by connecting the open-set visual encoder of CLIP [36] with the language decoder LLaMA, and fine-tuning them end-to-end on our generated instructional vision-language data

afaik sentence embeddings via sbert are still considered a pretty viable path. This may be what you were already looking at, but there's more info here: https://www.sbert.net/index.html

The Pile already does!

Part of its contents come from the "USPTO Backgrounds" dataset. From The Pile's paper:

USPTO Backgrounds is a dataset of background sections from patents granted by the United States Patent and Trademark Office, derived from its published bulk archives. A typical patent background lays out the general context of the invention, gives an overview of the technical field, and sets up the framing of the problem space. We included USPTO Backgrounds because it contains a large volume of technical writing on applied subjects, aimed at a non-technical audience.

More details in the paper: https://arxiv.org/pdf/2101.00027.pdf

The Pile: https://pile.eleuther.ai/

this is a parody account. The poster actually works at carbon health https://www.crunchbase.com/person/alexander-cohen

whoops decimals mixup, will edit:

784 / 815,201 = 0.00096 = 0.1%

For twitter, here are the actual number for the bay area, according to state filings[0]

* SF: 784

* San Jose: 106

Still high numbers IMO but SF for example has ~800k residents, so this only represents ~0.1% of the total population. Not super convinced yet that it's going to have any immediate impact on housing in the city unless this triggers a much larger avalanche of firings that don't have an associated swarm of smaller companies waiting in the wings to pick good employees up at a discount.

[0] https://www.sfchronicle.com/bayarea/article/Here-s-how-many-...

wow - how is this not the default? It's always the behavior that I expect to happen, and I'm pretty much always surprised and disappointed when it does a global search instead.

I also have a 10g card and saw the same thing - to get it working I had to pass in "--n_samples 1" to the command, which limits the number of generated images to 2 in any given run. This has been working fine for me

*they - it’s right there in their twitter description

compared to white students with similar test scores

(guessing JTR == John The Ripper? https://www.openwall.com/john/ )

That one is based on real data (I worked there for a bit), but I generally agree this pattern is exploitative

Check out Foundry VTT[0] -- I've been using it since release and so far it has been a much better experience than Roll20. Plus it has a pay-once-and-own-the-product-forever model, and you can easily self-host your own server.

[0] https://foundryvtt.com/

Just based on what I've seen and the women I've talked to - a lot of women in tech are encouraged to move into management because (for a variety of societal reasons) they've just upskilled more in EQ than many of their male peers.

See also: the pressure to be glue [1]

1: https://noidea.dog/glue

Care to point to these studies?