I use CC regularly for editing large text files (especially turning interview transcripts into something readable) and have found it works much better than web chat interfaces because of filesystem access and ability to work with large files.
That’s great to know. I’ve come to the same conclusion. I’ve found that things work best when they happen right where I’m already working. Uploading files or recreating context in a web service adds friction, especially when everything is already available locally.
Hey HN! I built Partycles because I needed lightweight celebration animations for a React project and couldn't find anything that wasn't bloated with dependencies.
It's just one hook - useReward() - that gives you 11 different particle effects: confetti, fireworks, sparkles, hearts, stars, bubbles, snow, emoji, coins, lightning, and flower petals. The whole thing is under 10KB gzipped with zero dependencies.
The library is MIT licensed and on GitHub. Would love contributions - especially new animation types or performance improvements. The codebase is pretty straightforward, each animation is its own module.
I'm using it in production for success notifications and user achievements. Works great on mobile too.
Tech: TypeScript, React 16.8+, rollup for bundling. No canvas - just DOM elements with CSS transforms, which keeps it simple and performant.
An amazing women with some... strange?... romantic preferences:
"In 1895, Bly married millionaire manufacturer Robert Seaman. Bly was 31 and Seaman was 73 when they married. Due to her husband's failing health, she left journalism and succeeded her husband as head of the Iron Clad Manufacturing Co., which made steel containers such as milk cans and boilers. Seaman died in 1904."
Not that on-topic, yet the direct access page for the book [1] looks really rough style wise yet has fantastically annotated HTML. An inspect-element on the title and author block shows a ton of itemprop attributes and itemtype schema definitions for stuff as specific as alternative title information and author details including birth date and split first and last names. Downright aspirational levels of tagging, I wish that quality of care about metadata were everywhere on the web.
False start with car rental companies, only three, not four. Hertz has to be a unit then, making the first group hertz, second, mole, and volt.
Similarly, enterprise must be in the business sense. Enterprise, project, venture, endeavor.
Tiger, Ray, National, Twin are all singular versions of baseball teams?
Curb, silicon, boardwalk, and game are left. Boardwalk is the most valuable monopoly property, silicon is the modern equivalent? No clue, maybe I’m missing a cultural reference? What if curb is a verb? Curb your enthusiasm, first word of tv shows? Silicon Valley, game of thrones, maybe there is a show that starts with boardwalk? Seems tenuous.
Edit: yes, there is. Boardwalk Empire. Never watched any of them, but some googling tends me they’re all hbo shows - I knew that about Thrones. That seems slightly more realistic a connection than just first word of tv shows.
Seems like exactly the kind of thing AI would/could theoretically best humans in.
Seems like a very American riddle, three-quarters of these are based on assuming US-centric associations to the words. Not very surprising that a non-US-based model doesn't get there as easily as a US-based one.
This guy was one of the greats. A deepness in the sky (the sequel) is one of my favourite sci fi books of all time, and even better than Fire upon the deep imo.
A Deepness in the Sky was perhaps the first "hard sci-fi" novel I ever read (this was before I knew of Greg Egan). The concept of spiders and the onOff planet was just awe-inspiring.
While Egan's idea-density is off the charts, I found Deepness in the Sky to be the most complete and entertaining hard-scifi novel. It has a lot of novel science but ensures that the reader is never overwhelmed (Egan will have you overwhelmed within the first paragraph of the first page). Highly entertaining and interesting.
I wonder what Vinge thought of LLMs. If you've read the book, Vinge had literal human LMs in the novel to decode the Spider language. Maybe he just didn't anticipate that computers could do what they do today.
> Vinge had literal human LMs in the novel to decode the Spider language.
Could you elaborate on this? It's been a while since I read the novel. I remember the use of Focus to create obsessive problem-solvers, but not sure how it relates to generative models or LLMs.
Thinking about it, I'm not sure how useful LLMs can be for translating entirely new languages. As I understand it they rely on statistical correlations harvested from training data which would not include any existing translations by definition.
I do not recall the exact details but I remember that some of the focused individuals were kept in a grid or matrix of some sort. The aim of these grids were to translate the spider-talk and achieve some form of conversation with the spiders on the planet. It is also mentioned that the focused individuals have their own invented language with which they communicate to other focused individuals, which is faster and more efficient than human languages.
I may be misremembering certain details, but the similarity to neural networks and their use in machine translation was quite apparent.
The zipheads were crippled with a weaponized virus that turned them all into autistic savants. The virus was somewhat magnetic, and using MRI like technologies, they could target specific parts of the brain to be affected to lesser or greater degrees. It's been awhile since I've re-read it, but "focused" was the propaganda label for it from the monstrous tyrannical regime that used it to turn people into zombies, no?
Not zombies, but loving slaves. People able to apply all of their creativity and problem–solving skills to any task given to them, but without much capacity for reflection or any kind of personal ambitions or desires.
> If you've read the book, Vinge had literal human LMs in the novel to decode the Spider language. Maybe he just didn't anticipate that computers could do what they do today.
I mean, I don't think LLMs have been notably useful in decoding unknown languages, have they?
All currently-unknown real languages that an LLM might decode are languages that are unknown because of a lack of data, due the civilization being dead. An LLM won't necessarily be able to overcome that.
In the book the characters had access to effectively unbounded input since it was a live civilization generating the data, plus they had reference to at least some video, and... something else that would be very useful for decoding language but would constitute probably a medium-grade spoiler if I shared, so there's another relevant difference.
Still, it should also be said it wasn't literally LLMs, it was humans, merely, "affected" in a way that they are basically all idiot savants on the particular topic of language acquisition.
Oh, yeah; I'm just not convinced there's any particular reason to think that LLMs would be useful for decoding languages.
(That said it would be an interesting _experiment_, if a little hard to set up; you'd need a live language which hadn't made it into the LLM's training set at all, so you'd probably need to purpose-train an LLM...)
LLMs are.. not bad at finding some semantic relationships between some arbitrary data. Sure, if you dump an unknown language into LLM then you can only receive a semantically correct sentences of unknown meaning, but as you start to decode the language itself it would be way easier to find the relationships there, if not just outright replacing the terms with a translated ones.
> Not evil for the sake of evil, but rather reasoned decisions with terrible prices
The Emergents and their system are pretty clearly just evil, and there's never any indication given that they actually care about those terrible prices, or even reflect on them for long. Vinge is very good at channeling the Orwellian language that regimes like these use, but I didn't find his intent at all ambiguous.
The really compelling and ambiguous character in that book is [redacted spoiler], who really does grapple with the moral implications of his decisions, but ultimately chooses the not-evil path. Personally I think this also highlight's Vinge's biggest flaw as an author for me, which is that in all of his books, the most fully realized and believable protagonist is a scheming megalomaniac, with second place going to the abusive misanthrope of Rainbows End, and third to the prickly settlement leader in Marooned in Realtime. All of the more sympathetic characters feel like empty vessels that just react to the plot.
I think Greg Egan in one of his novels has a line that goes like "Humans cannot be universe conquerors if they don't overcome their bug like tendencies to invade and destroy". Nah, it is this very tendency that makes them universe conquerors. Nothing to beat good old fashioned greed and discontent.
IIRC wasn't it the chamber/ship of someone he worked with, that he tolerated? Read it like six or seven years ago, so the details are fuzzy. The impression I kept was that he did a lot of evil stuff not because he relished the suffering he created in others, but because he didn't mind it.
It's both. On one hand, he is aware that one of his valued subordinates "needs" to regularly murder people, and doesn't consider it an issue so long as that subordinate remains productive and is kept in check to avoid "wasting resources".
But there's also a record of him personally torturing and raping one of the captives for the sake of it - which he keeps around, presumably to rewatch every now and then.
I second that. Re-read it multiple times and enjoyed every minute and every page. The creative concepts making up this book such as localizers/smart dust or the Focus captivated by their plausibility, and the unsolved mystery of the onOff bothered me as much as it did Pham Nuwen.
R.I.P. dear friend, you will be missed and remembered.
For those who might not know, this is the difference between "percentage" and "percentage points". It is not 6% higher, it is 6 percentage points higher.
This really matters for things with a very low probability.
A percentage always reflects a ratio between a quantity and another reference quantity. When you say a value is 6 percent higher, you are saying it went from X to (X + X*(6/100)) = (X*106/100) = 106% of the value you had before (whatever it was).
When you say it is 6 percentage points higher it means you had a percentage Y% and it is now (Y+6)%, a value which cannot be determined unless you know Y, never mind the reference absolute value it relates to.
In this particular case you can say it went from 7% to 13.2%, so if you ignore "%" as the unit the actual change is from 7 to 13.2; a ((13.2-7)/7) ≈ 0.8857 = 88% change. Had the original percentage been say 67%, a 6.2 p.p. change would have increased the percentage to 73.2%; a much smaller ((73.2-67)/67) ≈ 0.0925 = 9% change.
Had the change been "six percent of seven percent", the new value would be 7+7*(6/100) = 7.42 (percent).
"Per cent means one hundredth of something. Percentage point is used when comparing percentages to one another. For example, when inflation drops from three to two per cent, inflation decreases by one percentage point and 33.3 per cent."
This is a nice simple explanation of it. It's also why stock holders use "points" instead of "dollars." A stock share going up $1.50 is amazing if it was a penny stock, and absolutely not worth mentioning if it was say, Tesla. But the points have the same meaning for either stock - one is just a lot higher of a point than the other, even though the dollar change was the same.
Airbnb used to be my go-to, but I've since mostly returned to more conventional hotel booking sites.
Have had numerous experiences where hosts have had to 'sneak' me in because their building banned short term rentals. None of this was disclosed in advance, and no doubt it's in Airbnb's best interests to look the other way.
As others have mentioned, there's often not much of a price differential anymore, and hotels typically have their shit together way more than the average Airbnb host.
