skysight-inc/HackerNews huggingface dataset:
GraphQL isn`t an alternative for REST.
GraphQL is a solution for very specific cases and even in this cases it has his own drawbacks.
You mean such as when high level languages became mainstream and we no longer needed to code in assembly language? Or when IDEs became widely available? The underlying design skills are still difficult to acquire and not displaced by new tools - that is at least until SoftwareArchitectGPT comes along...
In reality, Emacs has the gentlest UI/UX of any Unix tool. Emacs has tutorials built-in, is 100 percent documented and all of the moving bits and pieces are discoverable.
One example of a use that requires real gold is the manufacture of gold plated tungsten.
Reminds me of the "sacks" in Ananthem.
Thanks, this is a pretty good intro to ideas to bounce off others.
The comment to which you are responding is pointing out a real limitation of current machine learning systems though - most of them have a hard separation between training-time and runtime - which obviously doesn’t exist for human and animal intelligences.

Now, I’m sure sooner or later someone will come up with a system that lacks that hard separation-and it will unlock new capabilities that current systems lack - which will further close the capability gap between AIs and natural intelligences - which still hasn’t gone away, although it clearly has shrunk significantly in the last few months.
Generation of functional oocytes from male mice in vitro
Exactly what? I wasn't thinking about CALL in regards to hieroglyphs, rather the set of language design ideas out of Bell Labs and its descendants, that turn a line full of symbols into valid code.
We could replace corn fields with solar panels for like 10x the energy yield.
US comes out with revelations of this type 40 years after the fact, by routine. Can't wait to see the confirmations in 2060, if we're all still around to muse over it
TL;DR: the author had to figure out the hard way that Zig's FixedBufferAllocator is a bump allocator, and that it doesn't reuse freed memory except when it's the last allocation.
Not the US, but anecdotally, I've heard the main cause of homelessness in Australia is not being poor. Generally there is some mental health component that prevents people from getting help. Yet more anecdotally, I'm 2 degrees away from a few people who have been homeless and it was fairly easy to get back on their feet.

But the comments on this are still pretty crazy and maybe miss the point. Even if the comparison isn't quite exact, wouldn't you expect the worlds richest country to do the best? Even the life expectancy is declining in the US. And even if COVID had an impact on life expectancy, again world's richest country.
> Interested to know what your plans are.

I think I'll manage to eke out the rest of my career doing the kinds of programming I enjoy at least until I'm ready to retire. That's basically the extent of my plan.

> Just know you're standing at a height somewhere above, and as a giant to me I hope you can see farther ahead :)

I wish I could, but I'm as lost as the rest of us. I just happened to have written a couple of books.

> Maybe we'll retreat more into our personally-named server, managing a handful of like-minded users, crafting rooms in a MUD no one will read. We'll publish stats for our packet filter, read stories typed by hand, and make little games.

That hits perhaps just a little too close to home.

I think of the countless old folks in garages tinkering on old cars with manual transmissions and no engine computers, simple enough that they can still be tinkered, wishing they still made cars like that today. (I drive a twenty-year-old truck for similar reasons, though I'm not savvy enough to actually work on it.) Or other old folks hand-knitting sweaters and blankets for grandkids who appreciate the gesture but put it into storage because the latest mass produced fast fashion blanket they got off Amazon matches their room's decor better.

The whole thing just makes me feel old and out of touch.
Trust me I am one of the people absolutely baffled and pleasantly surprised by all the new things these LLMs can do. There are plenty of potential in this tech and I am not so scared to not acknowledge that.

But what I am asking is a core feature of these models. The transformer is what make LLMs possible but it is by design static after it was trained. You can't simply install another pipeline or wrap it in a program and fix this problem. From what I understand, RNN isthe self improving type of AI and it was supplanted by the transformer type and one of the key differences between them is the ability to do learning from its own output. Transformer model sacrificed that for the ability to process a large amount of data in parallel. And that is by design. You can't change it as far as I know.

I actually don't know that much so that is why I am asking if what I said was wrong. Also, maybe someone will make a new model merging both transformer and RNN. But what I am saying is right now, the type of LLMs we have probably can't learn no matter how sophisticated its training is or how many parameters it is built with.
Full text: https://gwern.net/doc/genetics/gametogenesis/2023-murakami.p...

Abstract:

Sex chromosome disorders severely compromise gametogenesis in both males and females. In oogenesis, the presence of an additional Y chromosome or the loss of an X chromosome disturbs the robust production of oocytes. Here we efficiently converted the XY chromosome set to XX without an additional Y chromosome in mouse pluripotent stem (PS) cells. In addition, this chromosomal alteration successfully eradicated trisomy 16, a model of Down’s syndrome, in PS cells. Artificially produced euploid XX PS cells differentiated into mature oocytes in culture with similar efficiency to native XX PS cells. Using this method, we differentiated induced pluripotent stem cells from the tail of a sexually mature male mouse into fully potent oocytes, which gave rise to offspring after fertilization. This study provides insights that could ameliorate infertility caused by sex chromosome or autosomal disorders, and opens the possibility of bipaternal reproduction.

A good summary here: https://denovo.substack.com/p/of-mice-and-men-and-eggs
> If I had to guess it would probably be some type of animal feed that is wasting all that water.

Alfalfa is the culprit you're looking for. Thirsty crop, grown in the desert, and almost exclusively for nonhuman consumption.
What does that help in an political environment where anonymous lobbying is more or less legal?

The incredibly lax lobbying and campaign financing law in the US leads to the expected levels of corruption and the greatest democracy in the world is completely powerless to rid itself from this obvious problem.
I've been incredibly amazed by ChatGPT, GPT-4, and the potential of next-gen AI.

However, I've been trying for the life of me to get GPT to play tic-tac-toe properly for the past few days. It's not going well, heh.

This is the current prompt I've been using: https://pastebin.com/pSPkigNP

I've tried many prompts. Most of them were a lot simpler than the one in the pastebin link. I thought providing multiple examples of how to check all of the win conditions might help. It struggles most severely with the diagonals. Sigh...

My hunch is that its training data had very few examples of text representations of tic-tac-toe games, compared to say chess.

Anyone have tips for me? Or success on a similar task?

This goal was inspired by my success getting GPT to multiply large-ish numbers perfectly. Check out this gist for example: https://gist.github.com/dwaltrip/cad19703982c7f308fdbe5786e1...
I actually wrote on Twitter about exactly this post: https://twitter.com/jensneuse_de/status/1634678574274813952?...

The tldr is that most comparisons of GraphQL, REST tRPC and whatnot don't mention Fragments and Relay because a lot of developers don't understand the purpose and value of Fragments. Per-component data dependencies, data masking, persisted operations just to name a few.

Not every application needs these features, which is fine, but if you don't leverage GraphQL to the fullest, why add the complexity and not just go with something simpler like tRPC.

On the other hand, there are backend for frontend frameworks like WunderGraph (https://WunderGraph.com) that take the advantage of GraphQL, but combine it with the simplicity of RPC. (Shameless plug, I'm the founder)

That said, I think a lot of people overuse or misuse GraphQL in situations where it doesn't really add much value. E.g. when exposing an API to third parties, our API is probably consumed by a backend. What really is the benefit of using GraphQL in this case? Wouldn't an OpenAPI/REST API be much easier to adopt for your users?

GraphQL really shines when used as a first party API from the frontend, with a client like Relay that embraces Fragments. Everything else to me is hype driven development. my2c
https://archive.is/ZYCcv
Please don't use HN for partisan flamewar. It's not what this site is for, and destroys what it is for.

https://news.ycombinator.com/newsguidelines.html
Farming should be treated carefully, I think we agree.

What isn’t careful, in my opinion, is to take some poorly thought out “water rights” rules and keep applying them, while it is clear they are not fit for purpose and various water levels, both above and below ground, continue to reach new lows every year.
it can definitely evaluate whether an LLM is better aligned than itself (for some narrow definition of "aligned") - this is the motivating principle behind Anthropic's Constitutional AI idea.

"Better" is pretty vague, but "more capable" would be difficult, because I don't think ChatGPT has a good idea of its own capabilities.
The top three benefits of college have nothing to do with anything you mentioned.
My point is that a lot of debate surrounding LLMs is based around the idea that the brain appears to have structures that are innate to language, but that LLMs don't (or at least, not to the same degree; ISTM that tokenisation is one such trick). And to me, this means that there may exist further mathematical optimisations that the brain is using that LLM's don't. Making it likely that we will some day be able to encode LLMs in less space/energy.

At which time I suppose we'll be told that LLMs can't be intelligent for some other reason.
Australia has the equivalent of FDIC insurance (called FCS) that covers up to AUD250K per account holder at all ADIs.

The 4 "major" banks in Australia (Commonwealth, Westpac, NAB, ANZ) all maintain ratios above the minimum requirements and above the international requirements for "unquestionably strong". They're also (implied) "too big to fail".

APRA (our banking regulator) publishes plenty of stats.

I found this presentation https://www.commbank.com.au/content/dam/commbank-assets/inve... for the Commonwealth for FY21, which shows that their loan book is funded 73% by deposits, and the remainder is 74% long term, with a 5 year average maturity and they have 13.1% of their capital retained.

So if they have they have 13% capital, as well as AUD175B in liquid assets, with $610B in deposits, then they'd start to be in real trouble if more than 25% of their account holders started pulling out cash.

Of that $610B, $310B is households, so the split between standard savings accounts and business/investment/term deposits etc is roughly 50/50.
Why not? Not everything has to be success.
Warren Buffett in Contact with Biden Team on Banking Crisis
> What have you read recently?

"Embrace the Suck", by Gleeson. (Yet another Navy SEAL memoir. This author seems to enjoy the suffering a bit too much. Other SEAL memoirs describe the same training, but not with such enthusiasm for the pain.)
I can guarantee it’ll never be able to support infinity records. I can also guarantee that most data structures can’t even support a googol of records and never will. Some won’t ever support a quintillion records due to complexity, and quantum won’t fix all of those. There may be structures that support this, but they aren’t the ones we use today.

And the reason is that complexity theory is on shaky ground these days and needs a revision. Forty years and six orders of magnitude ago we treated a bunch of operations as constant , which is a clever fiction that is blatantly obvious now,but some of you knuckleheads continue to not look at. Most C terms are in fact stair-stepped log(n). Every time log(n) doubles and crosses a threshold, the cost of the operation doubles, and therefore is in log(n), not C. When you’re talking billions of records that distinction is already fairly obvious, and people dealing with trillions have to architect for it.

Memory access, as it turns out, is sqrt(n), not C, and with magic hardware might some day reach the cube root of n, and don’t count on it getting any better until we can bend space. With that sort of memory access a lot of O(1) algorithms perform worst than log(n) operations.

As you go into 128 bit addressing the difference between nlogn and n^3/2 * log(n)² becomes impractical. There’s a wall there, and we won’t get past it without completely different algorithms or desktop FTL technology.

The next order of magnitude of n will require a complete rewrite of that section of the code, so in practical terms the n only goes up in a new program, not the old one, and therefore the old program cannot and never will handle a thousand times more data than it was designed for.
For insightful comments like yours!?

I’m on both.
Great, most of them are irrelevant, will it even get 1 user on each of them?
Original version was written TCL:

https://gist.github.com/antirez/6ca04dd191bdb82aad9fb241013e...
Isn't a term deposit exactly what you are looking for? Lock in for 3/6/12 months or more and get a higher rate.

Aussie banks offer it.
I found GNU parallel useful when I wanted to queue up transcoding of flac files to mp3 on my Raspberry Pi. A few ffmpeg flags plus a list of files meant I could easily just saturate one job per core with a one-line bash command.
Is there any way for others to pay for your Cloudflare bills so you could use eg the Business plan? Unclear if that would expose the payer to legal pain but there are probably ways to do it.
Related:

Master Emacs in one year - https://news.ycombinator.com/item?id=16424934 - Feb 2018 (5 comments)

Master Emacs in one year - https://news.ycombinator.com/item?id=8079083 - July 2014 (116 comments)
As a side note I just got GPT to write me some Go code and it came up with this:

templates, err := embedFS.Sub("templates")

interestingly, this is not valid Go code (Sub is a function in the "fs" package, not a method) - but it would be quite typical in say Java.

So this mistake makes me think that GPT certainly does have a "mental model" for Go. And it's made the same kind of logical mistake I made when I first learned Go.
Neither RNNs nor transformers will change their parameters during a forward pass. In production GTP just does a forward pass through the network, but never calculates the parameter gradients, and this would be true if GTP was built on RNNs as well, and without those gradients the AI will not improve.
I always wonder what could have been, if the Commodore 64 and similar machines would have come with Forth instead of Basic.
Undergraduate Physics:
Matter and Interations

https://www.amazon.com/Matter-Interactions-Ruth-W-Chabay/dp/...

They merged modern physics and classical mechanics all together in a more comprehensible way. You don't need to transit from classical to modern, or transit from 1d to 3d, everything is consistent in this book. A rather non-conservative approach.
Pre college being a requirement there was still some sort of evaluation the company had to do to decide if you were a good candidate, from their perspective college graduates show more promise and potential. Just as someone applying to college shows more potential of being a good fit to the college if they scored highly on their SAT exam. Is it fair that someone who likely has all the other criteria also has to sit through the embarrassment of an SAT exam when they’re so obviously qualified? Yes. Because that’s a way that universities have found to fairly and easily find good candidates.
Mine was the Atari 800XL. Atari Basic hadn't PEEK and POKE as the C64 (though something similar which I can't remember right now), but some more possibilities to switch graphic modes and plot things. But I never learned how the machine worked from that, it was still magic.

I tried typing in listings, but you only knew that there was a typo somewhere after you finished hundreds of lines. Finding the typo was out of the question for me. Also, it was obvious that the result of the listing, usually a game, was of much lower quality than the games I already had or could copy from friends.

The reason I learned Basic was that I wanted to know how games work. They always fascinated me since I saw Space Invaders somewhere. I quickly understood, mostly with the help of more advanced friends, that you couldn't make games with Basic, it was too slow. You had to learn machine language.

So that's what I eventually did, and that's how I really understood the machine down to the point where I could tell what almost every single of the roughly 40000 available bytes did. It took a long time to get there, those 8-bit machines where already quite layered in hindsight when you think about: How 6502-instruction, assembler, disk I/O, joystick input and graphical output where tucked together with what today be probably called the Atari-API was not immediately obvious and the result of 20 years of technical development, but nowhere explained for a 12 year old!

My enlightment moment was this dialog with a friend: Me: "Why does this assembler program crash? Why do I have to reset? Why can't the computer handle it?", friend: "Because deep down, executing your program is also a program. If your program crashes, that program crashes.". I think that was the most profound lesson ever to me. It's programs all the way down!

So, yes I know that CPUs have their own instructions and that every programming language ultimately compiles to that. But that knowledge helped me little with what I consider the next large learning steps over the decades: Learning C on x86, learning how Unix/Linux works, learning what the internet is fundamentally build up on, learning Javascript+HTML5, learning how fundamentally different asynchronous programming is if you can't assume that I/O might not respond immediately and possibly never.

My favorite language today is vanilla javascript. I love the simplicity, no compiler insisting on type safety, a great UI, almost platform independent, lots of cool APIs. I think JS is as remote from Assembler as you can get.

Bottom line, I think it really doesn't matter to know about machine instructions, same as it didn't matter at the time how CPUs worked on the hardware level. That still mystifies me: The 6502-equivalent of an if-clause was branch-not-equal (BNE), but how did that work in reality? What's happening on the silicone then? How can a lifeless thing make a decision? Never really understood whats beneath the turtles.
Interesting idea, naively that seems possible based on other non chess example prompts I’ve seen. Would be a great way to understand it’s tracking of state throughout the game
So yesterday we had a post (https://news.ycombinator.com/item?id=35200267) that you need a special "play as a grandmaster" prompt to reduce the number of illegal moves for GPT3.5, and that "GPT4 sucks" at chess completely compared to GPT3.5.

Now we have this post that GPT4 plays good and doesn't make illegal moves at all. What changed? What was the prompt? Is it just random noise?
Analysis: Bank panic raises specter of 2008, may bring lasting change
Banks do differentiate. If you have an account that is <$250K, you're covered by the FDIC, which essentially makes it zero risk, irrespective of the account's associated interest payments.
https://archive.is/aQsVf
Unfortunately poor people are not free to acquire the food they need or live in shelter without being violently attacked for doing so if they fail to pay money to property owners.

Poverty isn't voluntary - it's violently enforced at the point of a gun.
ChatGPT has a “knowledge-cutoff”. What if you continually fed new information (like a subscription to a news wire service) into the training process so the knowledge cutoff continually moved forward?

LLMs do support additional training (fine-tuning). Why couldn’t that fine-tuning be a continual process, absorbing new information every day?

What if OpenAI took all their records of public interaction with ChatGPT, and used that to fine-tune ChatGPT? In fact, given upvote/downvote and “regenerate response” allow users to give feedback on responses, maybe that is part of their plan?
I think you both need to watch some YouTube math videos on what exactly infinity means. As Everyday Maths put it, it’s not “count until you can’t count anymore and then add one to the number”. That’s the sort of wrong frame of thinking that makes you think that an infinite pile of hundred dollar bills is worth more than an infinite pile of one dollar bills. They are both worth $infinity.

We don’t have any algorithms that can deal with infinity, so stop pretending like we do. And we couldn’t build one unless the universe is infinite and expansions turns out to be incorrect. So no infinity in computer data structures.
Not really. Did you see what I wrote? I have my own nitter instance, I use it regularly. But it's on my terms, when I see a twitter link I can replace it with my nitter instance.

Forcing your own nitter instance on others and not letting them make their own decision is absolutely forcing something on others.
Nonsense. Just like with any software you can be perfectly productive in an afternoon but actual mastery takes time. For instance, for Microsoft Excel the title would probably be "Master Excel in two years"
Sir, this is an electrical circuit class
The browser developers defacto become the library maintainers since they're now on the hook for any security issue within that library forever. Even if the "real" maintainers go play with something else.
With Heat Pumps, US Energy Requirements Could Plummet by 50%
The Digital Green Society conference
A soft limit would work well here, a prompt saying, “There are a large number of pages, it will take a while to select them all. Do you want to continue?” then it informs the user, rather than (maybe) artificially limiting them.
The cycle is already known - good economy less enrollment for colleges. Bad economy more enrollment. Would better wait for 2023 data.
Or just cap them?
One interesting result which you may find interesting: https://ncatlab.org/nlab/show/Lawvere's+fixed+point+theorem

I also highly recommend this survey paper by John Baez and Mike Stay: https://math.ucr.edu/home/baez/rosetta.pdf

There are plenty of interesting results in category theory, in fact your comparison to abstract algebra is apt. There is only so much you can say about an arbitrary group in general, or an arbitrary topological space, just like there is only so much you can say about an arbitrary category.
We've banned this account for posting unsubstantive and/or flamebait comments and for using HN for political battle generally.

Please don't create accounts to break HN's rules with.

https://news.ycombinator.com/newsguidelines.html
We also don't know enough to support the hypothesis that you put forward either (and which I reject, from a philosophical standpoint).
Yep, exactly. So obviously that is not the case.
Appreciate it (replying to both this and the parent) but I think the comments have been pretty friendly so far :). And mostly useful feedback on things I have considered but needed some direction on where to put my energy.