skysight-inc/HackerNews huggingface dataset:
> nobody got buff without being pushed by those around them

This is completely contrary to my experience. The successes I’ve had were my own motivations and drive.
Depends on the domain you’re going to work in. Nobody understands all major CS domains in depth - you typically specialize and dive deep in the relevant area. It’s like any other field: no physicist knows all major areas of physics, no mathematician knows all major areas of math. Perhaps 50 years ago when the field was really new it was possible to understand all of CS, but it’s a big field now that covers a really diverse set of topics that each are relatively deep.

Even then, you often don’t need to dive deep into the math unless you’re a working researcher for the most part. I work in languages research, and to be honest, for most of the work you don’t need to dive deep into type theory or category theory (regardless of what some internet people would lead you to believe). You generally only need to dig deep into those if you find yourself working in foundations topics where they play a strong role.
Came here to post just that. Really like zen queries
Looks like FIDE is conducting an investigation. Their Fair Play Commission has recently submitted a report that has now been forwarded to the Ethics and Disciplinary Commission.

https://www.chessdom.com/fide-fair-play-commission-forwards-...
Try examining the above script. It's a lot of work. It's not just a bunch of wget's and cp's, there are a bunch of subroutines and conditionals. Too much to look at.

Also as another user pointed out, uninstallation is a problem.
What part you don't think is true?

Help engineers understand taxes: it is pretty much part of the GPT-4 demo. You can copy the tax code in it and ask questions about it. As a matter of facts, it helped me with some taxes questions I had this year, although it was ChatGPT and I didn't paste the tax document in it.

Translate some tax rules into code? I did something similar last week for a complex billing project I am working on. It didn't give me the best variable names and made up a few some functions but the formulas were correct and I reused a good chunk of it.

Fixing the logic of the code it just wrote? I think there are enough examples of that on Twitter.
Describing LLMs: "Training data: 1 to 2 trillion tokens"

Is number of tokens a good metric, given relationships between tokens is what's important?

An LLM with 100000 trillion lexically shorted tokens, given one by one, wont be able to do anything except perhaps spell checking.

I guess the idea is that tokens are given in such "regular" forms (books, posts, webpages) that their mere count is a good proxy for number of relevant relationships.
ASR systems usually have a language model. It improves accuracy a lot because there are a lot of similar-sounding words hard to tell apart you can eliminate because of context. Depending on the performance, you may have to lean heavily on the language model to get decent results. Even though it sometimes causes errors, it prevents more.
CRTs had a shadowmask / specific phosphor placement, right? sure, you could run whatever resolution, but is that not kinda using a mechanical upscaler?
Yes, I believe the course of the history of the Linux desktop would have been very different had GNUstep took off, especially around the crucial years of 1996-1998. In our timeline KDE started in 1996 and GNOME started in 1997, and neither desktop adopted GNUstep, instead preferring the Qt and GTK+ GUI frameworks, respectively. However, suppose instead of KDE and GNOME being developed, the community rallied behind GNUstep, speeding up its development. Had GNUstep been completed by 1998 or 1999, this would've been revolutionary, especially if some type of Wine-like compatibility layer was built to support NEXTSTEP/OPENSTEP binaries, thus immediately providing the Linux desktop high-quality commercial applications such as those from Lighthouse Design (https://en.wikipedia.org/wiki/Lighthouse_Design), as well as providing a path for companies with legacy NEXTSTEP/OPENSTEP codebases to bring their code over to GNUstep running on Linux or one of the open source BSDs (IIRC, NEXTSTEP was built on top of a 4.2BSD userland running on the Mach microkernel).

Why did we end up with KDE and GNOME instead? I wrote about it in more detail here (https://mmcthrow-musings.blogspot.com/2019/06/some-thoughts-...), but in short, my opinion is that (1) GNUstep wasn't ready when KDE and GNOME were under development; the developers involved preferred to use existing GUI toolkits, and (2) there might have been a reluctance to using Objective-C in the mid-to-late 1990's.

Another fascinating consequence of a world where GNUstep took off is two competing implementations of the OpenStep API: Apple's (Cocoa) versus GNUstep's. Would Cocoa and GNUstep have diverged from each other, or would GNUstep have followed Cocoa like in our actual timeline? Would a GNUstep desktop have (1) stuck to OPENSTEP's UI conventions, (2) moved to Mac OS X's UI conventions, or (3) chartered a new path? We'll never know, but it's fascinating to think about what could have been.
We anticipate it to be significantly less than $10 per month. The final cost would depend on various factors. Primary factors being the price of the service (which will be set by the developers of the service) and size of the deployment (larger deployments will have significantly lower cost per user).

How will the money be split amongst the contributors will need to be determined by the community itself. The community (we assume the community to be a not-for-profit registered company) could employ engineers full-time and/or build a framework which will assign a dollar value to every contribution based on factors like quality, complexity, quantum, etc. Semut does not play a role in this. We enable open source projects to be available as a service with minimal engineering effort and enable monetisation of the service (while the code remains open source).
Hyper confident opinions, stated in the form of facts....shocking.

Imagine if people wrote code with the same style of logic and epistemology they practice when discussing metaphysical affairs.

Assume whatever you would like, and enjoy assuming that all your assumptions just so happen to be factual...I doubt it will cause much harm to me, though I am less sure the same is true for those you proclaim/perceive to have concern for.
Category theory has very hard definitions and not many theorems. Would not recommend. It has Grand Unified Theory vibes so pseudo intellectuals have a hard on for it.

Don't waste your time trying to understand people who write to make themselves sound smart. You aren't missing out on anything.

Here is a recent article from TOPLAS, imo a top programming language journal. No category theory here...

https://dl.acm.org/doi/10.1145/3564619
This has become my main source of news for the past couple of years. I highly recommend it.

There's a GitHub repository floating around somewhere with code for an rss feed of it which works great for getting it on mobile.
> This sounds a lot better than

You can justify pretty much any horrible thing with "sounds better than a torment nexus"
>all of this is to say that arithmetic, math is not highly encoded in language at all.

How did you learn arithmetic then, if not by being shown numbers and equations, and having math rules and concepts explained to you through language?
As an SRE I'm not too worried on a 25 year horizon. Yes I pulled that number out of my ass.

Depending on the quarter only 10% to 25% of my time is writing code. The other is dealing with: finding high level reliability concerns, figuring out what solutions to implement, diving into complex acute production issues, evaluating trade-offs for fixes, finding ways to make things more efficient, negotiating what to prioritize with other teams/orgs/leadership, etc.

Could an AI do some of these things? Sure. Are they going to be able to figure out the right stakeholder to talk to, negotiate with them, get buy-in and decide on overall designs/solutions? No.

I'd be a bit concerned if I was a frontend developer (though any decent one could pivot to something else.) however.
It isn't a matter of Ethics. Ethics implies that I have control of the situation (Do I kill the person who wants to die or not) or (Do I stop AI or not)

I am not in a position to decide to stop technological progress. So I am choosing control what I can, which is my attitude.
> Shockingly, it's drug overdoses.

Yeah, no. Drug overdoses account for ~100k of the annual 3.4 million deaths. That's less than 3%.
Not an arch user but a zfs user. I skip zfs on root , except on FreeBSD because that is the most solid. For Linux info a basic raid 1 for root and boot and create a zfs mirror on the other drives. Normally I have 6 drives (mirror plus the 2 os drives). I then take some space on the os drives to create a slog mirror for zfs. The heavy usage comes on the zfs mirror anyway the os is really just there to power vms.
Steve would have been extremely familiar with the music industry and their legal reach, starting all the way back in the 80s when Apple Corps sued Apple Computers.

https://en.wikipedia.org/wiki/Sosumi
I did not know the source of this meme (insanely racist), but I still find it funny.

Kill JavaScript. Behead JavaScript. Roundhouse kick JavaScript into the concrete. Slam dunk a JavaScript baby (Node.js) into the trashcan. etc.
What about it is far-fetched?

Contemporaneously to this story, Apple disabled screen capture of DVD movies and introduced PT_DENY_ATTACH (preventing debugging of the DVD player) at the behest of the MPAA.
> Every single one of my coworkers is using Copilot

And all of you still got a job. Copilot has been out for a time now, if it was transformative we would see companies releasing a ton of products and fix all the bugs and then fire most of their developers etc the past half year, but that didn't happen.

Making developers a bit more productive wont have an impact on developer jobs. It changes your day to day job a bit, but that is like switching to another IDE, it wont transform the industry. Even if it reduces the need for developers by an entire 10% it is not that big of a deal, it would be worth many billions but for an average developer they wont notice much of an impact. It is like the productivity improvement of giving developers another screen, a better computer, a better IDE etc, those are nice but they didn't transform the industry.
As someone from Ohio, I can confirm.
While I agree, I don't think this is what Dijkstra was speaking about. A lot of the "AI interfaces" are just underpinning the real technical representation. For example, if you say "Which customers recently bought product #721?" this might generate a SQL query like "select * from customers where ...".

The interface is not the ChatGPT text box; it's SQL. The ChatGPT text box is just an assistant to help you do the correct thing (or at least, that's the way it should be used).
The thing that is important to keep in mind with advancements like this is that comparative advantage (https://en.wikipedia.org/wiki/Comparative_advantage) continues to exist. The most unintuitive thing about it is that everyone has a comparative advantage; this isn't because of absolute advantage or capacity, but because of scarcity and opportunity costs.

An AI can become better than us at everything they do - gaining an absolute productivity advantage - and human labor will still be necessary, and even valuable. It's unintuitive, for sure, but so long as scarcity exists, it remains.

The reason for this is simple: given an AI which can produce two goods, X and Y, faster and better than humans, one might think that all the world's X and Y needs could be satisfied. But this isn't the case, because resources (including time) are finite, and the AI must choose to produce X or Y with any given set of resources (electricity, GPUs, time, whatever). By producing X (which, let's say, it's better at, or is more valuable per unit of resources input), it can achieve optimal absolute output, but this comes at the cost of not producing Y. So long as the demand for Y remains unchanged, there is a need for some other agent to produce Y. This is the human's comparative advantage in Y production.

In short: the total sum of X+Y produced is greater when the AI produces X and the human produces Y, even though the AI is better at producing both, because the AI's opportunity cost of producing Y over X is greater than the cost to import Y from the human. The human can import X from the AI and produce Y and end up with a greater quantity of both than if they tried to create or import both X and Y.

Might this mean a reduction in language-oriented jobs for humans? Certainly, even probably. Retraining and exploration of new careers will be necessary. We can expect jobs to go away, and new jobs to be created; the personal computer and word processor flat out killed the entire typist industry, but created a dizzying array of new opportunities. If you stay still, you'll certainly be left behind, but I don't think we're at the point that we need to worry about human obsolescence any time soon.

(Of course, if we reach the point where all demanded resources can be produced without any effective opportunity cost, then we've achieved post-scarcity, and all bets are off, but that's not anywhere nearly as simple as just cranking a productivity multiplier up.)
Unrelated to the article: on mobile, the article scrolls while the side bar is fixed, even if you tap+drag on the side bar. What CSS is being used here? `fixed` or `pointer-events` or something?
Literally nobody is saying that about ChatGPT.

Not sure what the climate has to do with this, other than maybe signalling whose team you're on.
Fortunately in every company I worked, the main limiting factor to hire engineers seem to be money and not lack of tings to build. For a time, it might just translate in companies building more features and being even more wasteful than today.
This analogy does not make sense to me. We do not have equivalence between all of the infinite inputs and outputs here, we have equivalence in a finite number of cases and known cases where the two functions (human output and llm output) diverge drastically. Any mathematician worth their salt would tell you these functions are definitely not equal.

Now you could make the argument that these functions are close enough most of the time so it won't matter but unless you want to get really rigorous that's more of a stats / engineering perceptive not mathematics. Any more importantly that's very up for debate, especially in a high pressure situation like medicine.

Of course these models are wild and I'm quite impressed with them. I still can be worried about the damage someone who doesn't think things through could cause by assuming GPT-4 has human or super human level intelligence in a niche, high impact field.
> why is chess separated by gender?

Like most other sports, the "male" league is actually open to everyone, women just aren't competitive.
In related news, these methods multiply.
This is something that a year ago, if you saw it in a movie, your eyes would roll.
Good point. I didn’t mean the stack ranking thing, which is also degrading, stress inducing, and bad for morale! Much less the scandalous hire-to-fire.

I was specifically addressing the phenomenon described in the article, where the threat of the large number in future is demoralizing and destructive.

Reasonable people can consider them facets of the same phenomenon.
Shockingly, glorification of drug use (of all kinds; sugars and attention and plants alike) in all forms of media (which is itself prevalent and pervasive for most) along with similar glorification of rebellion against "normal" creates a maelstrom of influence on people of all ages, beliefs, and origins.
I was trying to do a thing with AppleScript, and the barriers I ran into were not with the language, but with discovery of the APIs that Apple surfaces to the end user. In that regard, you’re better off with AppleScript. I can’t believe just how bad the AppleScript documentation is, but the js documentation is even worse; using js is just using AppleScript but with an additional layer of indirection that doesn’t provide any productivity gain.
Men and women are generally different in physiology, psychology, and many other measurable ways. I don't see why it should be puzzling that there are specific spaces or areas in society that accommodate more of one than the other. This has been demonstrated numerous[0] times[1] by[2] studies[3] (and there are plenty that go both ways, I'll readily admit, but the measurements favor sex-segregated education for certain ages of school children, for example).

It is only people pushing something about "equality" that rejects that men and women are different that take issue with this idea.

[0] https://en.wikipedia.org/wiki/Single-sex_education#cite_note...
[1] https://en.wikipedia.org/wiki/Single-sex_education#cite_note...
[2] https://en.wikipedia.org/wiki/Single-sex_education#cite_note...
[3] https://en.wikipedia.org/wiki/Single-sex_education#cite_note...
How I've built this has an interview with Sam Altman that's 1+h long
The bright streak above and to the left of the center of the image looks like a phoenix or maybe a dragon!
I have some on the way - if you're right you might have changed my life
At the speed things go, give it a few months.
Its less than 3% of total deaths, but when they happen is important. They do, in fact, account for the falling life expectancy.
Under the current system, millions will lose their jobs and a handful of extremely rich people will get richer: capitalists. All of this will be completely lawful: is the law of the free market.

The only answer is to destroy capitalism and unite as workers. Only if we unite as proletarians, we can redistribute the inmense profits of automation and make sure to live a worthy life.
In some sense they already have sensory grounding if they are coupled to a visual model. It might sound vacuous but if you ask a robot for the "red ball" and it hands you the red ball, isn't it grounded?
Definitely hoping to get more materials up soon! Sorry it's barebones for the moment, we have a lot to do!
Amazon was in a somewhat unique position where they could ignore their investors, because they were raking in plenty of money.

Choosing to reinvest that money in the business caused some consternation, but the consistent revenue and growth let them ride out periodic misadventures and hits to the stock price. It turned out to be a good move in the long run, because they weren't bluffing about their business fundamentals.
> Amazon is free to ignore them, they’ll just have to deal with the consequences of that.

The consequences aren’t necessarily that significant: mainly the cost of raising further cash from the markets, which doesn’t look like Amazon will have to do for many years, if not decades.
I have been around political discourse long enough to realize that people saying "whataboutism" is a shibboleth that is used to excuse extreme double standards and hypocrisy.

If you are running a sports competition, and you are told "please ban these Russian athletes, because Russia's invasion of Ukraine is unprovoked and unjustified", I do not think it is a logical fallacy to ask "can I also ban US athletes for the same reason"? Or to ask "why doesn't the same principle apply across the board?"

I have heard ideoogically based people on all sides of an issue use "whataboutism" to escape having to discuss basic logic. If someone is trying to convince you that it's imperative you do X, it's not fallacious to inquire about what the principle behind the imperative is. And why the principle is being applied in this one particular case and not across the board. Otherwise it is "rules for thee, not for me". "But why not for thee too?" "Hey, stop the whataboutism!"

But it's even worse than that. Because if US goes halfway around the world and bombs countries to smithereens which present no threat to it, then that's objectively worse than trying to prevent a former ally from joining an enemy alliance and putting nukes on your border. The correct analogy would be the Cuban Missile Crisis, when USA sponsored the Bay of Pigs invasion, Cuba asked USSR for help, USSR placed nuclear missiles on it, and USA blockaded it and threatened war. One could totally understand USA in that scenario. That's the analogy. Going halfway around the world to bomb countries that don't present a threat to you, is SO MUCH MORE NEEDLESS than what Russia did in Ukraine, that it is all the more deserving of, oh I dunno, 1 athlete being banned somewhere?

Where am I wrong?
GPT4 has nowhere near the number of neural connections that a human brain has. It’s hardly surprising that its mental abilities are like those of a well trained pet.

Once neural nets approach the complexity of the human brain, along with the right training I don’t see any reason that the ability to solve problems by deduction and logic won’t emerge.

And an AI won’t have to devote neural capacity to things like eating and wiping it’s arse, so it will probably get there sooner. Like an idiot savant we’ll probably have AI that are developing new mathematic and physical theories that aren’t even what we’d consider self-aware.
Is there any evidence to think that? Are there games similar to chess that are dominated by women at the top levels? Is there some reason to think that chess-ability genes are evenly distributed by gender?

My own intuition is that, just like there are more men above 130 IQ and below 70, there are probably more great male chess players than female. This is just the idea of greater male variability which is found across a number of different measures - everything from variation in height to things like polydactyly being more common in men.
ORMs generally give you a lot of nice things, and you usually (always??) can just write pure SQL and use the models you've defined (and all those nice things).

So, use an ORM, but write SQL if you want? Sounds like a good idea, actually.
Those that are in control of that progress and whether or not they release certain capabilities to the general public are the ones that will have to deal with the ethical bits, and society as a whole can do so as well. Politicians can make laws based on ethics.
I used JSON-LD spec because it is preferred by Google, but it requires a lot of duplicate effort of the actual page content. Its almost as if it is designed for sites that use heavy JavaScript frameworks and not for HTML/CSS sites.
Make Kexts a chore to use and discourage everyone from making them as they have recently done?
> It's another if you lose the most qualified and respected 6%.

I doubt that’s the case. The people deciding to lay off are just getting rid of 6% of their ‘resources’, they don’t consider that those 6% might be doing 50% of the work.

So 3 years on they’re just wondering why their engineering team is so useless, and thinking back to the good old times.
Very nice! Congrats. Is that screenshotted website available publicly anywhere?
That's not bias, it's use of relevant context. If you're going to have an LLM doing diagnoses, you're definitely going to feed it that sort of context.
It’s distracting and messy.

I’m not reading a book for half-baked insights scribbled in the margins by past readers unknown.