they have a blog hinting at some answers as to "why": https://turso.tech/blog/introducing-limbo-a-complete-rewrite...

if you have trusted processes for review and aren't always rushing out changes without triple checking your work (plus a review from another set of eyes), then I think you catch a lot of the subtler bugs that are emitted from an LLM.

there are a million million subcultures with pretty stark differences in taste/aesthetics that you can dig up on the internet. looking at what's grossing in mega-dense populations of millions of people then yeah, perhaps in aggregate at large N, things their individuality -- surprise?

there are parts of every major city that feel the same, but if you're willing to take a train out 45 minutes in any direction without google maps, i'm willing to bet you get into spaces that are incredibly local!

If you really wanted to codegolf the repo, I'm sure you can make it literally <1024 lines.

Comments URL: https://news.ycombinator.com/item?id=41766293

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# Comments: 334

Perhaps we're in an early stage of Ted Chiang's story "The Evolution of Human Science", where AIs have largely taken over scientific research and a field of "meta-science" developed where humans translate AI research into more human-interpretable artifacts.

Comments URL: https://news.ycombinator.com/item?id=39510632

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But I find it a little ungenerous to interpret that young women are dating men who are cheating. I think it's more likely the case that single women who are in their 20s are willing to date men in their 30s, and so if you have to choose between a 23 year old who just graduated or a 33 year old well established in their career...

Just my guess. And copium.

> This last reason is hard for me to admit, because it’s so close to my heart. Ever since I learned to program as a kid, I felt there was something magical about languages. When I first tapped out BASIC programs one key at a time I couldn’t conceive how BASIC itself was made.

> Later, the mixture of awe and terror on my college friends’ faces when talking about their compilers class was enough to convince me language hackers were a different breed of human—some sort of wizards granted privileged access to arcane arts.

> It’s a charming image, but it has a darker side. I didn’t feel like a wizard, so I was left thinking I lacked some inborn quality necessary to join the cabal. Though I’ve been fascinated by languages ever since I doodled made-up keywords in my school notebook, it took me decades to muster the courage to try to really learn them. That “magical” quality, that sense of exclusivity, excluded me.

> And its practitioners don’t hesitate to play up this image. Two of the seminal texts on programming languages feature a dragon and a wizard on their covers.

> When I did finally start cobbling together my own little interpreters, I quickly learned that, of course, there is no magic at all. It’s just code, and the people who hack on languages are just people.

> There are a few techniques you don’t often encounter outside of languages, and some parts are a little difficult. But not more difficult than other obstacles you’ve overcome. My hope is that if you’ve felt intimidated by languages and this book helps you overcome that fear, maybe I’ll leave you just a tiny bit braver than you were before.

1: https://craftinginterpreters.com/

Comments URL: https://news.ycombinator.com/item?id=38042721

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But it seems like a bulk of the stats collected are things that I would find really useful. I've probably asked myself, "how many words are in this book" on 10+ separate occasions, both as a reader and as a writer.

It also seems like there were also counts of things like adjectives, verbs, adverbs, passive verbs, etc -- stats that I might want to know about a novel.

The bulk of the service seems rather "boring" and non-AI. Unfortunate that the whole thing was taken down because of a few features. Hopefully it'll come back.

About 2% of people in the US work in agriculture/forestry/animal handling/etc. If you include transportation workers, that's still about 5% of US workers. And if you include wholesale workers and utilities workers -- that's still < 10% of the US population.

All of this work is critical and necessary (to your point). But I think the BLS data is evidence toward OP's point that we've automated and optimized a lot of the work necessary for subsistence.

Not too many interesting technical or SWE related posts though. I mostly use it as a scratchpad for ideas and non-tech things I'm thinking about (probably write enough about technical topics at work!)

Base on what I can gather from my friends who work in the space (DRW, Citadel) it's just more stressful and has more politics than my current role (ML Engineer @ a retail company). Trading income for work-life balance and stress, and maybe OP is hinting that as you progress down that track the WL balance and stress only increase.

Just my 2 cents and why I didn't choose to pursue that path.

Both only cover the math as it becomes relevant. I am working through fast.ai's book right now and find its pragmatic approach to DL pretty agreeable to just getting models hosted and out the door. I watched the lectures before hand, and there are several Jupyter notebooks and examples on how to get models deployed ASAP with clunky interfaces, which also might be of interest to you.

> We stress that this estimate carries some uncertainty but gives us a reasonable idea of the impact of ICT. Across studies, roughly 23% of ICT's [information and communication technologies] total footprint is from embodied emissions, yet the share of embodied emissions for user devices specifically is ca. 50%. This is because, unlike networks and data centers, user devices are only used for parts of the day and use less electricity, but are exchanged often, especially in the case of smartphones.

"embodied emissions" being emissions generated from manufacturing.

older blog discussing data from older devices and electronics:

https://www.lowtechmagazine.com/2009/06/embodied-energy-of-d...