skysight-inc/HackerNews huggingface dataset:
Ask HN: For the non compete ban, is startup equity part of executive comp?
This week there was a ban issued on non competes. But, workers making over 151k and holding a policy making position are not included. Lets say you make 150k base, and hold an equity grant on a startup whose valuation was done via a SAFE. Is the 150k + significant paper equity (whose value is probably zero), enough to push you over the 151k threshold?

Whats stopping venture backed founders from leaving their startups and bootstrapping fresh on the same idea?
Im curious if tabs are easier for non native speakers than spaces
Is it really? I'd posit this isn't even really "open source" 99% of the time.

Github is absolutely littered with hundreds of thousands of repos that nobody but their original creator has ever looked at. "Make your own project" sounds good, but in practice it almost always means "Make a personal project and make it public". You don't reach the point in which you have to handle issues, or contributions, or pull requests or anything because the vast majority of the time, projects get nowhere, it's open source only in the most literal sense.

Also I'm not sure I see the logic even if the expectation is to make a successful project. How can someone who has a hard time meaningfully contributing to a project possibly manage a whole project?
Tangential business idea: insurance against getting locked out of your Google, Apple or Microsoft account.
This is exceedingly cool use of cartridges. Just as a thought experiment I've often wondered if some of the cartridge based consoles could be expanded considerably. Along the lines of this project, would it be possible to throw an arm chip in a cart and send these as h.264? I'm not at a computer but would love to see how differently some modern codecs compress.
Reason.

LLMs mimic human language which is separate from reasoning. Tech bros are remarkably ignorant of the field of linguistics and don’t appreciate this distinction. They thus mistake the output of LLMs for reason.
I'm wondering what are you referring to when you mention NAT in the context of IPv6. I thought there is no widely adopted implementation.
that's dark apologies if asking brings up bad memories. do you have any recommendation for someone who doesn't believe in any religions?
Then companies are on the hook for validating and and remediating internal builds of CVEs.

Michaelt is right and it is becoming a major source of revenue for open-core startups (eg. Chainguard)
Are you saying you've inherited 1MLoC functional codebases, and due to their shining purity you haven't had to get familiar with them? Or haven't had to understand their "side effects", outputs / effects on the world?

Side effects are what you care about in a program. The simplest 8-bit CPU has side effects with every single instruction. It's baked into the bedrock, I don't think you can paper it over. Trying to shoehorn the complexity into nothing but function parameters and return values doesn't make the complexity go away, it just necessitates all these other weird contortions that add the complexity back twice over again.
Ancient Fashion: The Oldest Pieces of Clothing and Accessories Ever Found
I cannot understand why you wouldn’t get antibiotics. What possible risk could your doctor be imagining that would come from you taking antibiotics?

Our approach to medicine is so depressing.
> This ‘goal drift’ means that agents, or tasks done in a sequence with iteration, get less reliable. It ‘forgets’ where to focus, because its attention is not selective nor dynamic.

I don't know if I agree with this. The attention module is specifically designed to be selective and dynamic, otherwise it would not be much different than a word embedding (look up "soft" weights vs "hard" weights [1]).
I think deep learning should not be confused with deep RL. LLMs are autoregressive models which means that they are trained to predict the next token and that is all they do. The next token is not necessarily the most reasonable (this is why datasets are super important for better performance). Deep RL models on the other hand, seem to be excellent at agency and decision making (although in restricted environment), because they are trained to do so.

[1] https://en.wikipedia.org/wiki/Attention_(machine_learning)
I think that the article is correct. There are indeed things that LLMs will never be able to do, at least not consistently, however much the hardware improves or on how much more material they are trained.

How come? Note my emphasis on the 2nd 'L'. I'm not saying that there are things that AI models will never be able to do, I'm saying that there are things that Large Language Models will be unable to do.

Training LLMs is often argued to be analogous to human learning, most often as a defence against claims of copyright infringement by arguing that human creativity is also based on training from copyrighted materials. However, that is a red herring.

The responses from ever more powerful LLMs are indeed impressive, and beyond what an overwhelming majority of us believed possible just 5 years ago. They are nearing and sometimes surpassing the performance of educated humans in certain areas, so how come I can argue they are limited? Consider it from the other side: how come an educated human can create something as good as an LLM can when said human's brain has been "trained" on an infinitesimal fraction of the material which was used to train even the 1st release of ChatGPT?

That is because LLMs do not learn nor reason like humans: they do not have opinions, do not have intentions, do not have doubts, do not have curiosity, do not have values, do not have a model of mind — they have tokens and probabilities.

For an AI model to be able to do certain things that humans can do it needs to have many of those human characteristics that allow us to do impressive mental feats having absorbed barely any training material (compared to LLMs) and being virtually unable to even remember most of it, let alone verbatim. Such an AI model is surely possible, but it needs a completely different paradigm from straightforward LLMs. That's not to say however that a Language Model will almost certainly be an necessary module of such an AI, but it will not be sufficient.
1.5g-3g a day is fine. Powder form comes with little dosing spoon.. just do a little reading its very accessible.
Ipv6 is a lot like a bios update - best avoided unless absolutely necessary. Potential mess with no upsides for end users.
I worked on this project in college and went to the South Pole in 2009. Happy to see it is still making discoveries!
Saudi Arabia Spends Big to Become an A.I. Superpower
Was wondering the same thing, this could be really disruptive to early stage tech
previous discussion https://news.ycombinator.com/item?id=40157111

168 points, 158 comments
China's first Sora-level text-to-video large model Vidu unveiled
https://archive.ph/RRkrR
I understand your concern, but what about an open-source form builder that gives you control over what’s on your site?

https://news.ycombinator.com/item?id=39895960
This is supposed to be the sane way? Certainly not!
You guys know that you can use "mailto:" as form action, yes?
No backend stuff needed.
If your not a native English speaker, why are you even expecting the LLM to understand even 80% of the time?

Just ask it in your own native language.
Keeping track of directories using pushd and pop
I’d rather work on something I believe to be good at a big decentralized company like McKinsey than something like what many / most large tech companies do. There’s basically no relationship to the other parts of the firm
Fantastic news! So, in British Columbia, may I enjoy one next to someone who is doing heroin, and is allowed to? (Getting tired of clarifying my unanswered question.)
Happened to me while on holiday in Costa Rica. Was able to reset PW this morning, thank goodness.
>X has security issues.

And Wayland is just a protocol, I would rather trust some old X11 code that was shared by entire Desktop Linux then GNOME devs code, this is my personal opinion and I will not bring forward sourced/evidence why I do not trust GNOME devs and designers.
I couldn't understand the original wording either, but after reading one of the sibling comments that explains it, it suddenly made sense.

I think you left out a few words that most English writers would include. So instead of:

> "ensure that numbers from one to ten as written as words and numbers greater ten as digits in the given text",

something like the following might be better for most people:

> "ensure that the numbers from one to ten are written as words, and the numbers greater ten are written using numerical digits in the given text"

There are multiple ways to write this, so other people may have better versions.

I'm not an English grammar expert, so I cannot explain to you why the addition of those extra words helps with the clarity of that sentence.
An article that says almost nothing. Here's the key bit:

> Zuckerberg has a new pitch: “Creator AIs”, personalised chatbots and agents that he hopes will provide a much more engaging way to reach customers.
The idea of chatbots is hardly new — Facebook has tried them before without success. But what was new this week was the depth of Zuckerberg’s enthusiasm for the idea, and the extent to which he is swinging his company’s resources behind the new wave of generative AI.

Sounds like another advertiser/influencer-focused, walled-garden venture.
Because even if we assume the labor costs are zero in the developing countries, that means the platform is only earning a couple dollars per order.

But the original article suggests that Door Dash is making over $10 an order (after labor costs), which is 5x over the best case scenario for the developing countries' apps.
There's also a First Citizens and Citizens First bank. And Citizens bank.

Also two First Banks.

https://localfirstbank.com/about-us/

https://www.firstbankonline.com/about-2/

I like the giant yellow header on this bank's website:

https://www.republicbank.com

>REPUBLIC BANK & TRUST
COMPANY - HEADQUARTERED IN
LOUISVILLE, KY - IS NOT RELATED
TO REPUBLIC FIRST BANK.
We are not affiliated in any way with Philadelphia-based
Republic First Bank, which does business as Republic
Bank.
It is interesting that all the examples I noticed in this article have a geometric aspect (even wordle - I model it as a grid with geometric rules when playing it). I think that the "first grader" comment is actually somewhat illuminating - it takes several years of learning how to navigate in a spatial world before this stuff becomes trivially easy.

The underlying point this article might be that LLMs don't understand the non-textual aspects of a grid. Which is a fair point, they model language, not space. I wouldn't expect text corpuses to explain space either, since possibly literally everyone who can read and write already knows a lot about spatial layouts.
You and I think like this, because we worked on/for the Internet. Unfortunately, other people who use these tools don't think like that.
Interesting. I only butted heads with Golang in the second phase of use. This is when we were fed the mantra of "you're not doing it right" and "the go way" (which turned out to be true.) This was an unusual experience for me in terms of programming. Rust (never tried beyond reading the spec :) per comments over the years also has that feature but unlike Go it is not something you can just pick up in a day. I released the initial working cut of an OSS driver for a DB 3 days after Go was released. I doubt I could do the same with Rust.
LLMs are fine-tuned with RL too. They are NOT simply next token predictors. RLHF uses whole answers at once to generate gradients, so it is looking further into the future. This might not be perfect but it is clearly more than focusing just 1 token ahead.

In the future the RL part of LLM training will increase a lot. Why am I saying this? There are two sources for learning - the past and the present. Training on human text is using past data, that is off-policy. But training on interactive data is on-policy. There is nothing we know that doesn't come from the environment. What is not written in any books must be learned from outside.

That is why I think supervised pre-training from human text is just half the story and RL based agent learning, interactivity in other words, is the next step. The two feed on which intelligence stands are language (past experience) and environment (present experience). We can't get ahead without both of them.

AlphaZero showed what an agent can learn from an environment alone, and LLMs show what they can learn from humans. But the world is big, there are plenty of environments that can provide learning signal, in other words feedback to LLMs.
Sorry to disappoint dear downvoters.

But i speak both from experience (personal and some brilliant friends lost to drugs) and common sense.

And this should be reflected somehow in legal and social norms.
I don't understand the outrage by some people. The Sandy Bridge has popcnt and SSE4.2. If you're using anything older than that, you owe it to yourself to come out from under that rock and treat yourself to a Sandy Bridge or newer. It can't be understated how underpowered and obsolete these CPU's or how outdated these platforms are in regards to connectivity or featureset. You'd also be doing your electricity bill a favor.

I've tried Windows 10/11 on a Pentium M and Core Duo and Core 2 Duo. It's abysmal performance-wise and honestly in every other way too.
I feel the use of the word "parrot" is unintentionally apt, given that parrots were long thought to be mere mimics but were ultimately shown to have (at least the capacity for) real linguistic understanding.
NanoGL: Framework for low-level WebGL developers
Have you seen the movie "mean girls"?

People of all genders do this all the time, group up and rat-fuck the reputation of someone they don't like for all sorts of reasons, not all of them particularly good.

Throw in a bit of bandwagoning during the height of #metoo when we decided that having a bad date where the wrong kind of wine was ordered with Asis Ansari or having a jokey boob photo from 30 years ago with Al Franken was somehow worthy of Thou Shalt Never Work Again, and I can totally understand how all this went down.
>will not change it from being a language model into something else,

This is a pretty empty claim when we don't know what the limits of language modelling are. Of course it will never not be a language model. But the question is what are the limits of capability of this class of computing device?
Reminds me of the all-time classic (now) HN discussion on Dropbox https://news.ycombinator.com/item?id=8863 as I got older I realized that, you can never ever hope to choose what will be successful or important, and that is true down to the most seemingly small action you can make. The world is simply too complex and interdependent for that.
A lot of people are incapable of realizing other people are different from them.

If you could give the entire population each their own “happy button” a significant portion would be hitting it all day long, ignoring everything else in their life. Those on HN are largely not the same type of people.
Java: portable bugs.

I forgot about 10bit. I should have said indexed-mode or non-true-color. I meant anything below RGB888.

Linear for processing would be nice where that conversion can be done efficiently, and where the display driver can make a passable representation.

The system I worked on only had black, light grey, dark grey, and white. What was nice about X was that the driver could express its limitations to clients, so that the client could make smart rendering decisions and handle dithering vs not dithering appropriately, rather than doing it at the display driver layer.
Thanks for pointing that out, will post in the appropriate thread in the future
>Another assumption is that it’s because of tokenisation issues. But that can’t be true either.

It's definitely a tokenizer issue, if GPT-4 was trained on singular characters I'm pretty sure it would be able to play Wordle much better. GPT-4 as they are trained today have quite lossy knowledge about the characters inside a specific token, probably a fix would be to embed the knowledge inside the embeddings.
Roughly half the doctors are below average and probably more than half of GPs are below average...
Penny Arcade had this comic, a few days ago (about the CyberTruck): https://www.penny-arcade.com/comic/2024/04/22/cyberyuck
Oh I followed the C++ standardization process quite closely for about 15 years up until around C++14 and still follow it from the sidelines (having mostly switched back to C since then), and I'm fully aware of the fact that C++ has designed itself into a complexity corner where it is very hard to add new language features (after all, C++ has added more new problems that had then to be fixed in later standards than it inherited from C in the first place).

I still think the C++ committee should mainly be concerned about the language instead of shoehorning stuff into the stdlib, even if fixing the language is the harder problem.

And I can't be alone in this frustration, otherwise Carbon, Circle and Herb Sutter's cppfront wouldn't have happened.
Apple doesn’t really “let”, the law demands.
Yeah but this is using 3 different backend services just to automate self hosted forms.

Pretty sure you can do this without 3 different services.
Extractive vs. Abstractive Summarization for the Enterprise
Microsoft is rewriting quite a bit of their C# to Rust for performance reasons. Especially within their business line products. Rust have also become rather massive in the underlying tech in the telecommunications infra structure in several countries.

So I’m not sure that your take is really so on point. Especially as far as comparing it with Go goes (heehee), at least not in terms of 3rd party libraries where most of the Go ecosystems seems to be either maintained by one or two people or abandoned as those two people got new jobs. I think Go is cool by the way, but there is a massive difference in the maturity of the sort of libraries we looked into using during our PoCs.

Anyway. A lot of Rust adoption is a little quiet, and well, rather boring. So maybe that’s why you don’t hear too much about it.
5-10% of my typical orders. $10-15 a day is a good wage for unskilled labor there.
Some more things to consider: Sugary things like marinades and rubs will stick more as they caramelize compared to just salt & spices. This is great if you're making a pan sauce, as there's more to deglaze. But I've had my pan act so non-stick in some cases that I couldn't build a fond.

Also if the surface of the food is wet, it can cool the pan a LOT on contact, as well as cause other reactions that promote sticking. This is especially true with too little oil.
I still see people getting nailed by CP1251.

Recently, i've gotten bit by UTF16 (because somewhere along the line somewhere on a windows machine generated a file by piping it in powershell)
I interviewed at DoorDash way back when, could've been about employee #12 or something. But when I sat down to interview with a couple of the cofounders, it seemed to me they were some kind of sociopaths. I have no regrets whatsoever not calling them back. All of my friends that work in the service industry (at the actual restaurants, not delivery drivers) absolutely despise DoorDash. I refuse to use it.
In this scenario who puts the conduit there, government I guess?

Like this is a reasonable approach, but you are artificially creating a specific market, maybe there are other kinds of market we can as well.
This might be in jest, but this is a pretty good “side gig”. Doesn’t even have to be offered by the open source maintainers.

Can be offered by anybody. “Hey I can offer full SSCS-2 compliance on these open source projects. Only $10K per month!”
Fair point. This is still intentionally low quality clickbait
> So.... Sounds like memory safety is indeed a problem? Otherwise why do so many solutions exist for it?

Memory safety and memory management are different things. Scripting languages remove the burden of manual memory management; as a side effect, they also tend to be memory safe, but that hasn't been the main motivation.
It takes significant effort to get in the groove of a particular 'day-to-day' math. My job has regularly recurring parts where I spend a lot of time doing one or more of 3 basic skills: setting up integrals and differential equations, converting lots of numbers to binary or hex, and trig-based approximations.

When I spend too much time away from one, it really shows. The other day, I tried to do the trig approximations, and it was like getting up after sitting too long with legs crossed. The fluency just wasn't there.
Lies! Typical greek coverup! Justice for the oppressed Aeolians!
This is interesting because it contradicts a pattern I've been keeping my eye on for a while.

I haven't yet run into any very early / "hyperlexic" readers who learned by phonics. I'm not a teacher but I'm involved in a coop school and talk to other parents. The other thing worth knowing, I guess, is that very early reading tends to be "autism adjacent".

My observation has been that kids who learn to read very early usually just straight up sight read whole words. Practically every kid who teaches themselves to read seems to do it this way (which makes sense, phonics is a lot of extra steps and not really something a 2yo or 3yo would come up with on their own). I say "teach themselves" but of course they bootstrap by looking at words while being read to, noticing words in their environment, etc.

Phonics and letter-by-letter processing are more reliable methods for teaching kids to read - it allows for more incremental learning and measurement of progress. It's more steady, but it's also slower. The overall cognitive overhead involved seems higher since they need to segment the word, map to sounds / syllables, then play around with the sounds a bit until they recognise the word.

Generally it seemed to me that adults don't have much agency over "how" kids end up reading, if they're wired for early sight reading they will do that with only a few cues, otherwise phonics is the best way but they will tend to read a bit later, which is normal.

They can be wonderful readers and you can ignore the competitive hype from the article.

Sometimes I secretly wonder if phonics in schools is partly a social trick, though? Is it a delaying tactic, a way to make it look like progress is happening, placate anxious parents, keep kids confident, give the system milestones to measure. To help kids engage with words and get them to stare at them until their brain is actually ready to sight read, which develops later and requires more exposure in most kids? (Fluency at segmenting and sounding out new words is a plus but the early sight readers seem to pick that up on their own by some black magic I don't understand).

DISCLAIMER: I am not an educator, I don't do science in this area (and other people do), this is all anecdotal and you shouldn't take it seriously. I should read more papers.
interlopers and suspect professions are attracted to a new money source .. In a sea-change series of events that diverge actual authors from new auditors and insert paid control of the forge. In some venn-diagram described process, a few percent of actors will in fact have organic connection to the decades of disciplined work that got us here, and the rest (IMHO) will devolve into the usual suspects of low-rent security, opportunistic money handlers, corporate shills and various forms of government bureaucracies ..

multiple low-effort frat-guy startups already exist immediately.. follow-on "experienced" gambling security goons as well (in Ireland for example).

ps- it is crucial to distinguish between the NodeJS disaster zone, javascript in general, at one end.. and core *nix OS parts at the other. not the same conversation