Man, Antirez and I walk in very different circles! I still feel like LLMs fall over backwards once you give them an 'unusual' or 'rare' task that isn't likely to be presented in the training data.

They have simplified it nicely, though: if you work from home you can claim a per-hour deduction so you don't have to do the math of wear-and-tear, electricity, internet etc. I think it was $0.6 per hour?

One should note that the cited study quotes the 45% from a 1992 study. These days, with gig economy and quasi-self-employment, that number is probably higher since you don't have an employer who reports your income for you.

Still, here in Australia, where we have the return-free tax system, adding what you earned from your various gig jobs isn't too hard: you add that as items to the web form: 'I made 15,123 from Uber Eats'. That just gets added to your overall return. I don't see how that's so hard compared to the US?

I forget which chapter it is, but Caro takes a detour where he describes the life of women during Johnson's childhood in the dirt-poor valley he was from: no electricity, no waterpower, everything in the house was done by women's hands, 24/7. There's a passage that stuck to me about how women in their 30s in that area looked like other area's women in their 70s, just a brutal life.

I think that's not due to algorithmic intervention of product design etc., I think people are just tired. The novelty of shouting at strangers on the internet has worn off - how many internet fights have we gotten into that did nothing in the end except waste time? It's only worse with a coin flip's chance of the other person being an LLM. We're all tired.

The difference to linkedin is that biostars has 'in-domain experts' only; the postdocs, the staff bioinformaticians, etc. those are not the people who will hire you. The people who will hire you are on linkedin.

They're mostly posts announcing new packages etc. but there seems to be more bioinformatics-y activity than, say, mastodon or bluesky. The posts definitely have a different tone than what OP decries.

I'd say I'm 50/50 Python/R for exactly this reason: I write Python code on HPC or a server to parse many, many files, then I get some kind of MB-scale summary data I analyse locally in R.

R is not good at looping over hundreds of files in the gigabytes, Python is not good at making pretty insights from the summary. A tool for every task.

Kind of how for the longest time, Google used to be best at finding solutions to programming problems and programming documentation: say, a Google built by librarians would have a totally different slant.

Perhaps that's why designers don't see it yet, no designers have built Claude's 'world-view'.

It seems like the limit and time measurement is based on the US time zone alone, not the local time zone. We're in Australia and that's the only explanation I can think of.

I'm also a huge fan of R.A. Lafferty, but his stuff his harder to find, mostly out of print.

Peter Watts' Blindsight is amazing recent-ish hard SF. (the follow-up, I did not like at all).

Anything from the Strugatsky brothers you can get your hands on!

>Amazon brain drain finally sent AWS down the spout

There's this older paper from Lex Flagel and others where they transform DNA-based text, stuff we'd normally analyse via text files, into images and then train CNNs on the images. They managed to get the CNNs to re-predict population genetics measurements we normally get from the text-based DNA alignments.

https://academic.oup.com/mbe/article/36/2/220/5229930

https://www.sciencehistory.org/stories/magazine/the-tragedy-...