skysight-inc/HackerNews huggingface dataset:
Unfortunately the plan is very dangerous as tectonic activity has a tendency to release it plus any hurricane or monsoon or thaiphoon or such has a tendency to destroy the installation or worse, move it somewhere where it will do damage to the ecosystem.

Also, use solar and wind ships instead. We don't need to sink more nuclear material...
Problem is always going to be power rather than computation.

I still haven't heard of any major breakthrough in the size of our batteries but when that comes we'll be miniaturizing literally anything.
Or just flip over a normal jigsaw and give yourself a challenge.
In the age we are living this starts to sound more like a feature to me.
> The study found that just having a first-class section on an airplane quadrupled the chance of an air rage incident and that loading economy passengers through first class doubles that again

This sounds like a study full of confounding factors that are very difficult to control for, to do with sizes of planes and lengths of flight and different seating configurations of different airlines. And indeed there is a response to the original study questioning the statistical methods: https://www.pnas.org/doi/full/10.1073/pnas.1611704113

On the wider subject, I’m a frequent flier and also have a few friends who are flight attendants. It’s a difficult job, and not well-paid. Please, every time you fly, imagine yourself in your flight attendants’ shoes, tasked with controlling a large number of grumpy primates packed into a long airtight cylinder for several hours, many of them intoxicated when they board and then expecting you to serve then even more alcohol. A little empathy goes a long way and I’m quite happy to see some draconian penalties for anyone who is physically violent on a flight.
I write more than I code, but I use ChatGPT a lot throughout the day.

I am integrating AI translations into my custom static site generator. I will test the outcome heavily before putting my name (and a big warning) on my translated content, but the early results look good. Getting it right is a lot harder than piping the page through ChatGPT. Everything needs to be translated from the UI strings to the URL slugs.

My work will no longer just benefit English-speaking immigrants, but also locals and immigrants who Google things in other languages. I am very excited about it.

I also use ChatGPT heavily for “what’s the word/expression for” questions and other fuzzy language queries. As a non-native speaker, I want to know if a given expression is appropriate for the context, if it’s dated, if it’s too informal and if it’s dialect-appropriate.

I also use it for coding, but mostly because it’s faster than reading python’s docs. I ask it questions I know the answer to, hoping to find better approaches. So much happened since Python 2.7, and I don’t always know what to ask for.

On occasion I treat it like I treated my mom as a child. I ask it all sorts of questions about the world I observe around me. It’s amazing to get a short, clear answer to work from, instead of sifting through barely relevant, spammy search results. This is super helpful when getting to know new tech and figuring out what it actually is.

It’s just so damn cool to have a sort of real-life Hitchhiker’s Guide slash Pokédex in my pocket. These things appeared in the span of a year, and nobody seems impressed. Well, I am mad impressed.
hence why most throw in tmux/screen on the other end, possibly automatically so:

https://github.com/blinksh/blink/discussions/1526
Direct CO2 capture is thermodynamically unviable, and literally every plan and attempt involving it was highly expensive in energy.
Category III autoland (other than to "keep your hand in") is relatively rare anyway because it solves only a specific narrow problem.

Suppose there is one plane and it needs to land right now, but all nearby airfields are fog bound so a human couldn't land a plane there: they'd get to minimums, still not be able to see the field and abort every time until they divert to somewhere with better weather - the Cat III autoland doesn't need to see the field, it will land anyway. You have to absolutely trust the machine, this is a rare Fail Active system - humans can't necessarily help even if things go wrong so once it reaches minimums it must land the plane even if it later ceases to have 100% confidence that it can do so correctly due to systems failure.

But now we're done, the plane is on the ground, on a runway, the passengers are no longer in the sky, if the plane was about to explode or run out of fuel that's awesome, but we can't do this again, autoland doesn't taxi the plane, and it can be pea soup out there, the pilots still can't see the ground even though they know their plane is firmly landed.

So if there's a stack of fifty planes for JFK and it's zero visibility this technology lands one plane per runway, maybe you can land three or four, then it's effectively closed, that's 46 planes left to divert, it's not useless, especially when visibility is marginal rather than truly zero, but it does not allow the airports to stay running normally.
I've tried it, and I don't like it. There's too much confabulation to be useful as code completion, and any task more complicated than that results in logic errors most of the time.

Code completion was fine without LLMs, and solving problems myself usually ends up being quicker than trying to coerce an LLM into doing it correctly and then verifying that the output is actually correct.

The one time I used an LLM in my workflow to good success was using ChatGPT to automatically create an enum of every EU/EEA country and a switch statement over that enum. Those sort of "grunt work" tasks that don't require any thinking, but a lot of typing, seem to be where LLMs shine.
You need to add a metric of "how many people can my software kill if it misbehaves", otherwise your point is moot.
I've been thinking for quite some time about how to incorporate spacing properly into the syntax of a programming language, and I now settled for a simple solution: hard-code blocks of texts via spacing into the text format itself. I call the result Recursive teXt (RX, http://recursivetext.com), and I am using it as the basis for the rest of my work on Practal, instead of using just plain text. A lot of issues are resolved with this, for example it is trivial to have different kinds of syntax live next to each other, as they can just occupy separate blocks.
Would've enjoyed a randomized approach to this. A paper I like a lot randomly exposed south Africans to luxury cars and found increased support for reidstribution.

https://www.nature.com/articles/s41586-020-2763-1
Oh, did I make mistake by remembering the wrong generic name? If only it could have been prevented...
>low poly

There are, such as Apocalytic Petra

https://bad-sector.itch.io/post-apocalyptic-petra

http://runtimeterror.com/tech/petra/

On pixel art, I remind you that late NeoGeo games such as Garou look thousands better than most 32 bit games, even Crysis. If any, we need to head into the 64 bit peak of 3D gaming, something with true realtime raytracing.

The peak of 3D art from 32 bit machines it's maybe Crysis and some 2010 games where the OS' limits (even with PAE) show up by the architecture, yielding far less data managed per cycle, even with GPU's helping out. These should be compared to the peak of 8 bit CPU's doing pixel art, such as the Game Boy Color displaying Cannon Fodder which was a masterpiece.

The peak of pixel art from the 16 bit era (and 24-32 bit with the NeoGeo) should be compared to maximized 64 bit machines with almost a TB of RAM and GPU's able to host Windows 10 in VRAM if they could.

The early PSX games should be compared to the early OG Game Boy games such as Mario Land, or maybe the Atari 2600 because of the novelty of the architecture.
What a fun write up and a huge confidence building post for me in ScyllaDB.
Unlike later home computers that directly output color signals, Woz designed the Apple II to use a side effect of the NTSC color TV standard's backward compatibility for black-and-white televisions. Basically, it cheats. The dependence on NTSC for color is why, as you noted, the separate Europlus models were developed.

Woz is one of the greatest engineers of the 20th century, and the Apple II demonstrates his talent. After its 1977 debut, no other mass-market home computer offered color output until the Atari 400/800 line two years later. But his brilliance at simplifying things always straddles the line between optimized and overoptimized. The Disk II might be his greatest feat at doing more with less, while the video circuitry falls just into overoptimization, given the color fringing, NTSC dependence for color, and lack of lowercase. Integer BASIC is somewhere in the middle; great performance (especially given (or maybe because) Woz knew nothing about mainstream BASIC), but the code is so tightly written that it was easier for Apple to license Microsoft BASIC than to add floating-point code to Woz's work.
I only use it to get a sense of a project. Instead of looking for a similar project (and ending up in medium hell), I now ask claude some first steps. I can continue from there. It's like helping out a friend get his project doing g
VirtualBox 7.1.2: Boosting Windows VM Performance and Enhancing Virtualization
Showing median people what the upper class steals from them seems like a reasonable thing to do.

I think, there isn't any situation where it's so obvious.

One type of humans gets cramped like farm animals, and the other gets pampered like pets.
I have to admit that I have few project that are just local.
You've clearly read the guidelines attentively so I'm surprised that your take is that if shallow jokes are not explicitly banned then they are welcome?

> Avoid generic tangents. Omit internet tropes.

I interpret that part as saying that generic jokes and boring puns should be avoided. (The trope being a long chain of commenters trying to one up the previous pun, with zero substance)

Personally I'm neutral when it comes to puns in child comments.

But I really don't like top comments that consist of only a pun. Make an insightful comment and conclude with your pun, if you really must.
Adrian's Digital Basement just released a video discussing an open-source design for Apple II HDMI output. In the video he discusses an Apple IIe-only graphics mode that this article does not mention, I believe. <https://www.youtube.com/watch?v=rrM6bPCk8DM>
RuntimeMaxSec would have systemd kill a live forwarded connection though?
It wasn't at all popular at uni, but one my teachers did use it and that's how I got to know it.

Her use case was to write visualization programs in C/C++ and then have Tcl/Tk as the GUI with buttons, inputs, etc.
How is Claude performing when project grows and things get more complicated?

I had some issues with both gpt4 and sonnet getting slower and doing pointless refactors as project grows
The problem with too rural is the people, not the wolves. You’re right though, and it’s why we moved to NL.

I was mostly thinking of back when I was in California to be honest. Though recently when I had to decide between a four or five day work week the biggest factor was “will I be able to outbid other people who want the same house”

As far as schools, I’ve been underwhelmed. They have kids on tablets a lot, shove a tv in front of them for lunch, and have rapidly declining PISA scores.
vitest is nice but it’s completely unsuited for micro-benchmarks as it ends up oom crashing after just 2 optimized out benchmarks
I wrote my own Notebook Assistent and I use it to quickly make data driven arguments. It is able to both code and read program outputs so it's very good at pulling remote sources, then peeking at the result, doing the data wrangling and then displaying the output. I think having the LLM being able to read program state is a big upgrade for what you can achieve, it can do test driven development for example because it can read the test report. However, being a side project limits the fluidity of the UX, it's open source and buildless though if you want to modify it.its very hackable by design.
https://observablehq.com/@tomlarkworthy/robocoop
the thing about punitive measures is that they don't need to work in order to be perpetuated; they simply fit the way the people in power think the world ought to work.
i have to leave this here www.molecularreality.com
And in the video Matt talks about the effort he went to in order to avoid trivial solutions like that. He wanted to find the least trivial one he could.
Indeed. In the case of self-referential borrows, this is not allowed because Rust wants copying structures byte-for-byte (e.g. `memcpy`) to always be safe.

The solution was `Pin<T>` et. al., which gives a way to make some value immovable in memory.

An equivalent yet simpler version of this system could be integrated into the borrow checker (this was a proposed solution for Rust), but as I said before, it would not be backwards-compatible, hence the need for `Pin`.
That's not really a solution, is it, for example I don't want <= to be confused with ≤ within a string. What you propose is just one more half-baked solution that the industry is full of.
jabbascript salute
>the speed

Check mawk and awka.
Floating megabomb heaves to near the English coast
> the pilots still can't see the ground even though they know their plane is firmly landed.

They get a "Follow me" car to help the plane taxi out

Slower, but it is not like the plane will stay on the runway
I'm all in for class segregation everywhere, including on airplanes. In the "good old" Soviet days, first class (there was no "Business" as there was no business in the Soviet Union) section was in front and used the same toilet and entry door as the pilots and the crew, AFTER it was the attendant's rest section, galley, luggage storage compartment, and on THEN the economy section. So those "animals that are more equal than others" could never intermix with the rest and most passengers were not even aware the first class existed. Thus the impression of egalitarian society was maintained and industry/government elites enjoyed their flights with no annoyances (the Party elites flew private planes).
It’s not like they just wrote a prompt and got a result. It sounded like a very hands-on process.

While they used the same process generative AI uses, it doesn’t sound like they really used AI.
On the other hand, in cities people are queueing up and talking at the bakery counter. While people in the suburbs are listening to the radio while driving to the bakery. I guess you choose to live where you feel most comfortable.
We have our own tooling; it's very good and definitely increases productivity for most. One observation is that people who are bad at reading code seem often to be get negatively impacted vs writing themselves. So from our teams I think that code reading will be more valuable than writing, if it was not already. Just having a loop of telling the llm something, running it and then tell what's wrong with the observed result is very slow vs reviewing the code and tell what's wrong with it instead.

We also use cursor, copilot, claude dev, aider and plandex to see if anything is beating anything else and to get ideas from for our toolkit.
Parent sounds a bit like the software engineers who blame random FOSS libraries for the bugs that appear in their own projects using said FOSS libraries.

In your project, you're ultimately responsible for what you ship, even if you're shipping airplanes.
> But it’s virtually useless for editing or changing code where it will often produce code that doesn’t compile, has bugs and/or doesn’t solve the requirements.

That is the exact problem I am trying to solve: modifying code with LLMs really sucks most of the time. I am trying a solution with Abstract Syntax Trees: I have the LLM write the code that will write the code you need. That is, modify the source tree rather than the text representation.

I wrote about my approach here: https://codeplusequalsai.com/static/blog/prompting_llms_to_m...

I do have it working for some cases quite well, but there are lots of pitfalls with this approach too. It does take a lot of context and the LLMs aren't really that well-versed at writing specifically esprima code for example. BeautifulSoup does work better, I guess because more people use it and there's more data in the training set.

I'm adding one language at a time, currently have HTML, CSS, Javascript and Python all kind-of working. It's pretty neat but I'm not sure how well it scales yet to larger projects and more difficult requirements/implementations.
When the ground state is emergency the definition of emergency changes because emergency cannot be the same as ground state...

If we go by technical definition of "emergency" then anything not by the plan is an emergency, but it's not used that way normally and it's not a technical publication.

If you are stuck in space with no lifeboat back then I agree it is an emergency, but they apparently have Starliner and it works. If they or Nasa are more comfortable with another option maybe that makes it an emergency or maybe not.

If it turns out Starliner doesn't work, that's an emergency. If there is radiation event coming then it's an emergency, but it is always an emergency in space regardless.
Upon reading the title at first glance, I thought this was going to be how "effecient" computers nowadays. Such as MacBooks and such, who started this efficient computers thing in the recent times. And they are, but as a result computers are all worse off for it. I mean soldered RAMs and everything is a system on a chip.
I’m skimming through this and it feels like a well thought out research proposal with concrete next steps. My thermodynamics is too bad to comment on the approach but it looks cool. As long as setting up experiments for it is reasonable in cost, wouldn’t take too long to show results (before it’s too late for the planet), and can show that enough CO2 can be captured and long term costs make sense, then it sounds great! I hope some of the proposed next steps get funding.

Commenting “wouldn’t Z be better instead” feels counterproductive to the discussion here.
Until recently I was only using Copilot as an advanced autocomplete and to help writing tests, for which it's pretty useful.

A couple weeks ago I had to create some classes (typescript) implementing a quite big spec for a file format to transfer quizzes between applications. I decided to try some more advanced tool, ending up with Cursor and continue.dev. I copied the spec (which are public on the web) into a text file and used them as context, together with a skeleton start for the main class I needed, and experimented with different engines and different prompts.

The end result is that I got a very good starting point for my code, saving me many hours. Surprisingly, for this task, the best result was generated by Gemini 1.5 pro.

Since then I've been trying to integrate these tools more into my day to day programming, with varying results, but I'm now convinced that, even with the limits of the current LLMs, this technology can have a much higher impact on programming with better harnessing, eg integrating it with compiler/code analysis tools output and automated testing.
This is a link was avery inportant click here in link
Right now I'm working on my first large clojure codebase, so I do a lot of "what is the idiomatic way to do X?" questioning, pasting in small functions and asking if there's a good simplifying refactor etc. Before this I was writing a lot of numpy and doing a lot of math, so it was a lot of "there's what I want to calculate, how do I make numpy do that?".

I use Claude now that they've successfully made chatgpt too insufferable to use.

I haven't tried any of the special AI editors since I don't know if I would survive the traumatic injury of having emacs taken away from me.
I assume they're using LCDs, where the brightness is provided by the backlight.
Exactly. This is also highly problematic if you try to perform atomic operations against bare 64 bit integers on those systems, because the atomic instructions do require them to be 8 byte aligned. In C11 and later it’s not an issue, because _Atomic(int64_t)’s alignment may be stricter than int64_t.

This was also an issue in Go, because it tries to use the same alignment rules as C to make cgo work. There they also solved it by adding dedicated atomic types.

https://github.com/golang/go/discussions/47141
It is fine for expanding CSVs, test data, static arrays and similar. Not comfortable using it as part of an editor or cloud services generally.
I've done the same, and my experiences also match those in the article.

Using a LLM as an autocomplete (typescript, kotlin) I found it'd be right about 10% of the time, very obviously wrong ~30% of the time, but mostly (~60%) *plausible*. Plausible is the worst, because if I don't spot the error immediately it'll come back to bite me in the coming hours/weeks and it takes me much longer to fully comprehend existing code than it does to write new code myself.

Asking questions fares better, but I never have easy questions and for difficult ones it'll usually be wrong. Like, if I'm asking an LLM a question I'm usually at a point where I've read the docs and there's something I don't understand - so it's not that surprising that the LLM won't understand it either. Occasionally pointing out the flaw will get a better answer, but more often it just leads to a circle of flawed answers. I feel like people who say this is some sort of revolution are perhaps people who weren't very good at finding information themselves.

The only places where this stuff seems to be an unqualified success so far is for jobs where the quality of the output is not very important.
Writing documentation, amongst other things, has been a save for me.

I use it to understand new codebases quickly, create the documentation boilerplate for the code I'm working on that needs better docs, or update/rewrite outdated ones.

When the codebase fits in the context window, it's simple. But even if I'm working on a larger thing, it takes a bit of RAG-alike effort to build knowledge topology, and then it's super easy to get docs on (the actual!) architecture, specific components, and all the way down to atomic function level.
The existence of the Framework Laptop proves that this is largely an imaginary tradeoff, or at least one badly taken by Apple.
Huawei's HarmonyOS puts China's tech world in awkward spot
https://archive.is/Rx6D1
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I'm currently pursuing PhD in theoretical condensed matter physics. I tried submitting questions to Humanity Last Exam [1], and it was not too hard to think of a problem that none of top llms (Claude, gpt, Gemini + both o1 models) got right. What was surprising for me is how small my bag of tricks was. I could think of 5-6 questions in my direct area of expertise with simple numerical answer that were hard for llms, and another maybe 5 that they were able to solve. But basically that was all my expertise. Of course there is stuff that can't be checked with simple numerical answer (quite a lot in my case), and there are probably additional questions that would require more effort from me to give a correct answer. But all in all, I suddenly felt I'm a one-trick pony, and that's given that my PhD is relatively diverse.

[1] https://agi.safe.ai/submit
> There are, such as Apocalytic Petra

I wasn't expecting a complete lack of low-poly games, my argument still stands with a few of them existing.

I agree with your comment, which was my point: 80s games were beautiful.
> Thus no single one has much power at all.

Property owners are effectively cartelized - that's how they got the supply restrictions passed in the first place. You can't "move your way" out of the market rent, and the market rent is the cartel rent. It's set to the same level as the monopoly rent.

It's even higher than if there were only two enormous landlords that did not benefit from the collusion built into the supply restriction system. A landlord duopoly would not have the political power to get the restrictions passed in the first place.