skysight-inc/HackerNews huggingface dataset:
Everything you say is true, and Google has cards left to play, but this is absolutely an existential threat to Google. How could it be otherwise?

For the first time in a very long time, people are open to a new search/answers engine. The game they won must now be replayed, and because it was so dominant, Google has nowhere to go but downwards.
Lawstodon – A Directory for Legal Professionals in the Fediverse
What series of operations can lead you to end up with dy/dx though? Like Integral{x^2){dx} is how you're introducing dx into a formula, but it's not like integration just works over division, so I'm a bit stuck on the construction phase
Another commenter has mentioned nonstandard analysis but I find that most people (commonly physicists, engineers) who are manipulating dy and dx are not actually using the framework of nonstandard analysis.

What usually is going on is you mentally replace dx and dy with Delta x and Delta y = y(x + Delta x) - y(x), where Delta x is some small nonzero quantity. After doing your manipulations, you take the limit as Delta x -> 0. Then you have rigorous statements like Delta y / Delta x -> f'(x) (this is the definition of derivative), and Delta x/Delta x = 1, and (Delta x)^2/Delta x -> 0 (ability to neglect second order terms), etc.

You do this type of thing so many times and it becomes rote and annoying to explicitly mention the limits and the reader is trusted to formalize it themselves as an exercise.

The stuff that you are "allowed" to do is taught in a first course in real analysis. After taking such a course, you will be able to justify for yourself which manipulations are valid.
I work with Langchain on a daily basis now, and so often I find myself asking; do I really need a whole LLM framework for this? At this point, the assistant I am writing, will likely be more stable rewritten in pure Python. The deeper and more complex the application becomes, the more of a risk Langchain seems to become to keeping it maintainable. But even at less complex levels, if I want to do this:

1. Have a huge dataset of documents.

2. Want to ask questions and have an LLM chat conversation based on these documents.

3. Be able to implement tools like math, wiki or Google search on top of the retrieval.

4. Implement memory management for longer conversations.

Its still a lot more straightforward to maintain it in Python. The only thing where it becomes interesting is having agents execute async, which is not that easy replicate, but at the moment agents are not that helpful. Not trying to diss Langchain too much here, because its such an awesome framework, but I can't help seeing past it other than just being a helpful tool to understand LLM's and LLM programming for now.
Part of the problem w/ the price coming down is the size of the panel, it runs front to back?

I'm sure in design phase it makes it look SUPER nice, but.... is it worth it for removing one of the lines?
your article says what I said, not what you are saying. It points out:

The “rule of thumb ideal” is 15, he said: “It tends to correlate with a mortgage payment that is roughly affordable for most households, and a rental rate that is also roughly affordable for most renters.” That's basically saying that there is a linear relationship as I said. (yes, short term prices can move independently from long term because liquidity, menu prices, etc, it's why economists always say "in the long run")

and the article asks "How long can it last?", i.e. they are admitting that the prices will come back into alignment, which wouldn't happen if there was no alignment to be had.

The article does not mention "naive expectation" at all, you made that part up. Would it surprise you to meet somebody on HN who knows more about the math of finance than you and the SF Chron put together?
On the flip side, I found only one person (I'm sure there are more) that are attacking the software efficiency side of things. You would be quite surprised how inefficient the current LLM software stack is, as I learned on a CPP podcast [0]. Ashot Vardanian has a great github repo [1] that demonstrates many ways compute can come way down in complexity and thus cost.

[0] https://cppcast.com/ai_infrastructure/
[1] https://github.com/orgs/unum-cloud/repositories?type=all
I would love to see a mapping of languages to features. I recognize this might be a large table.
Banks don't need deposits to loan out, as loans create deposits.
Apple "services" revenue includes the App Store. So their biggest competitor is the Google Play Store.
You choose what to talk about and what to share. It's open ended to give you the ability to share as much as you're comfortable with. You can tell the story of your career, no need to get any more personal unless you want to.
It’s close enough to a pure scam to not make a difference.
I would like the source too. I would be very surprised if Bitcoin energy consumption passed even half of what is consumed for porn and video games. I expect the amount of energy being used to maintain Bitcoin to be a rounding error in comparison.
> Ramping up and down in response to renewables will be an important function of any nuclear reactor installed today.

Realistically, it's not going to happen. PWRs are inherently stable, that's one of their big selling points. If anything goes wrong and the reactor becomes too hot, the water expands, moderates less the neutrons and they don't slow down enough to trigger fission events, so the rate of fission decreases. If for some reason the reactor stops producing enough heat, the water cools down and more fission starts happening. And there are other negative feedback processes in place too, for example Doppler broadening [1].

This is great for safety, but not so great for load following. If you want to load follow, it's probably going to be many times cheaper to just invest in a bunch of batteries.

[1] https://en.wikipedia.org/wiki/Doppler_broadening#Application...
> Specifically, a runtime (IMO) is the set of variables and their associated functionality that exist in the global scope, or are expected to be importable in a predictable and standardized way.

All of which is provided by V8 in this example. The global object, math object, "Object" in general, Arrays, etc are all the runtime. All this tutorial series on embedding V8 is doing is instantiating an existing runtime environment and adding using the APIs to insert a few new APIs.

All together you might say you've got a custom runtime as you have the baseline "JS runtime" + some new APIs and that's clearly a new runtime environment that is distinct from the JS environment on a web page, vs. the one in a worker, vs. in node, etc. But that is at best "extending a runtime", not "rolling your own".

Using the embedding APIs provided by a JS runtime as documented and intended, is not "rolling your own". By that definition I could make an app, embed a WebView, and claim I rolled my own browser runtime, which I would hope is more clearly absurd. Or I could "roll my own Command-line" by reading a string from a user, prepending some commands, and then passing it to system().
1) App Store

2) Everything else
Aren’t they basically the same rate?
Is `dy/dx` ever distinct from `d/dx y`? Generally I've treated `df(x)/dx` as just another way to write the operator `d/dx` applied to `f(x)`, which I don't think of as a fraction.
Please don't do this. It's always obvious when you're receiving an automated email, and if someone is too naive to recognize an automated email, you probably don't want to work for them anyway.
"algorithmic discrimination" uh what does that mean?
That would actually be an educated guess or a guesstimate. A guess is as good as any.
Some criminals had really great moms that raised them right
This sounds like a growing company. They need to balance risk with reward. Im hopeful they will find right balance before it kills their business
I disagree that this is a fundamental thing.

C++ doesn't exactly do "automatic typedef'ing of structures".

The difference is that in C++, if you define a type "struct foo", you can refer to it either as "struct foo" or as "foo" (likewise for class, union, and enum).

In C, if you define a type "struct foo", its name is "struct foo". If you want to call it "foo", you have to define an alias using "typedef".

Personally, I see "struct foo" as a perfectly valid name. I seldom feel the need to define another name for it. (typedef is the only way that a C type's name can be a single user-defined identifier; "int", "char" et al are keywords.)

I'll define a typedef for a struct type only if the code that uses it shouldn't know that it's a struct type.

Yes, it's a little extra typing. I save up the keystrokes I save by typing "{" rather than "BEGIN" and use them to type "struct". 8-)}

This is a matter of personal taste, and if you want to call it "foo", there are common idioms for doing that.
That would only hold water if they ever actually had to face consequences.

Do well? Get a massive bonus!

Do poorly? Get a massive bonus!

Do incredibly poorly? Leave with a golden parachute (aka massive bonus).
DAMMIT WHERE WERE U 3-4 years ago?!
Is it really serious or is it media trying to make it look serious? Out of a million randomly selected first graders, how many are going to witness a gunman before they graduate?
Not true at all.

https://www.zdnet.com/article/stop-the-lies-the-day-that-mic...
Let me introduce you to a new concept.

I call it "Not Everyone Is Motivated Solely By Money."
TikTok tracked UK journalist via her cat's account
Back then you had magazines to get info from. All of this is on the internet now. Often on social media like Reddit.
It's definitely ML-relevant, but I'd argue that it's in its own league, and is maybe a suitable ur-language for that league.
In AI? None (according to article). For their search engine? The distribution deals they have with Apple & android carriers for defaulting to them, and Chrome defaulting to them. If another search engine wanted to even release a product, theyd have to cross the distribution moat (possible on the web, just hard). For ads, the moat is their network of publishers. Competing ad marketplaces need to build a compelling publisher network to attract advertisers and compete for pixel space on publisher domains.
Urban Density and Home Prices
> Nobody is trying to change short selling rules.

Obviously, it was all just a ploy to trick Redditors into buying GME. If people actually cared about short selling, they'd describe new rules or regulations on the issue.

That's all it ever was. There's not much else to the story. I guess I could go over the bull$$$$ arguments over AMC, BBBY or FRC or any of the other meme stocks. But it's all just meming the stocks up in price.
Clearly didn't perform as well as you thought if they passed on you
Where's the line on 'unintentional'? When does it become careless?

Given how little it costs, it's kind of strange people skimp on it. My $100,000 property damage coverage costs $120 a year. I should consider upping it really.
A lot of the time those guys are just making magical promises to customers with no idea how what they want could actually work.

Then they throw it to engineering and either take the credit or shift the blame.
The runtime includes the engine (interpreter for example) and an environment, which could also include a standard library, bindings to the outside world and more.

For example, in the case of node, it's a runtime built around the v8 engine, using libuv for bindings.
> The IRCAM merged it with their Cube-based synthesis and processing system. Eventually that became Max/MSP, a commercial product with both MIDI and audio generation and processing.

Miller Puckette, the original author of Max, left IRCAM and went on to develop Pure Data (Pd) as an open source alternative. Pd introduced realtime audio processing. Max integrated Pd's DSP code and became Max/MSP. MSP stands for 'multi signal processing' or 'Miller S. Puckette'. (Miller himself named Max after computer music pioneer Max Mathews.)
Show HN: Low-level portfolio showcase projects beyond traditional CVs
You are more than just your CV!

I always feel that CVs are abbreviated and ATS-friendly but not human-friendly.

I want to write about what inspired me beyond all my work. about my unique story and experiences that set me apart from the competition.

it's important to make your resume ATS-friendly, don't forget to showcase the real you.

Portfolio:
https://gist.github.com/smalinux/2e9c5537fdac65501a655280352...

I appreciate any feedback or suggestions.
So you agree, this all requires esoteric knowledge and looking up specs for what each cable and device can support?

I mean, who in the world is going to do voltage comparisons, aside from us nerds?
> The other insurance company cut a laughably low-ball check, hoping the Rivian owner would cash it and go away.

yeah, it happens all the time. in california you don't need to talk to the other drivers' insurance company. they will hound you for days, just ignore them. absolutely do not submit to a recorded interview with them. ignore their threats, of which there will be many - all bullshit, made-up nonsense. forget your nice upbringing and be a total ignorant dick about it, because they're trying to get you to slip up verbally. this is especially prevalent with "lesser" insurance companies because they know they're about to be hit with an enormous bill.

i guarantee you the other driver will 100% lie their pants off with zero shame or remorse. their insurance company knows this, because all of their customers are shitty drivers who lie through their fucking teeth as easy as breathing. not only will they lie to the insurance company, they'll lie to their own god damn family. (one time the guy's daughter called me directly to try to ask me about my version of the accident because his english was non-existent - i hung up on her). they may be so good at lying that they convince themselves. stop and think about how incredible that is. these people are out there, driving around.

it happens every single time (again, because their customers are morons), which is why they resort to dirty tactics to get you (the good driver who is not-at-fault) to say something incredibly stupid due to naivete and because your parents taught you manners.

talk to your company's adjuster EXCLUSIVELY. they will abrogate the entire thing through the appropriate channels. if you have a dash cam the entire process takes like a week. if you don't have a dash cam, do the smart thing and buy one. don't tell anyone other than your adjuster about the footage. once they catch the other party in a lie based on the cam footage it's an open-and-shut case. upload an unlisted video to youtube so that you control access to the video (to the extent that nobody runs youtube-dl on it). you need to think two steps ahead of whatever moron is on the other end of this claim.

when i got hit, along with my video submission, i annotated a google maps screenshot with a full diagram of the accident with both street and satellite imagery. yeah - my claim had satellite photos - you think this is a motherfucking game? i pre-wrote my recorded statement and read it back into the phone like i was back in grade school. i probably did 80% of the adjuster's job for them.

as soon as you are involved in an accident it's a legal battle with no holds barred. you never know what absolute cockamamey horseshit (medical bills, injuries, etc.) they will just fabricate out of thin air. the crowd on HN is either broke as a joke, or upper middle class++ - if the latter, protect your ass in every way possible. put your business thinking cap on as soon as you get in the car.
chaos.social is run on four dedicated servers

https://leah.is/posts/scaling-the-mastodon/
Stand strong. You're far from being alone. Cryptocurrency will succeed eventually. It's the only consistent monetary system we have left.
#embed will be in the C23 standard. It's not yet implemented in GCC 13.
This links to the 2018 edition of this book. Each edition points to a newer one until the book splits into two books. This section doesn’t seem to have changed much throughout the editions, but I figured people might like to see the most recent version of the content overall.

https://papl.cs.brown.edu/2018/index.html

https://papl.cs.brown.edu/2019/

https://papl.cs.brown.edu/2020/

https://papl.cs.brown.edu/

https://dcic-world.org/2023-02-21/func-as-data.html#%28part....
> The article claims meta won but it seems like nvidia is the winner: everyone uses their chipsets for training, fine tuning and inference. And the more entrants and niche applications show up the more demand there is for their product.

Like the saying goes: during a gold rush, sell shovels.
Of course not, they have to get first the approval from the Nuclear Regulatory Commission. They estimate this would take 3 years. I don't find that unrealistic, since it's based on an existing (i.e. approved) reactor design, AP1000. NuScale got their approval last year, and they applied in December 2016 [1]. So about 6 years for a design submitted by a new company with no prior experience whatsoever.

[1] https://www.nrc.gov/reactors/new-reactors/smr/licensing-acti...
if OpenAI was interested in not being viewed as an evil corporation they'd be actually "Open", actually non-profit, and they wouldn't have cozied up to Microsoft.
"They don't seem that bad, they've murdered more men than women"
> Also interesting:

The issues here are:

- if it's defined, then people will rely on it, which means UBSan can't report it as an error if it sees it.

- IIRC x86 defines the overflow behavior differently for scalar and vector ints, so x86 compilers that want to do autovectorization would probably leave it undefined.

C's original sin here is that the numeric promotion rules are wrong ('unsigned short' should not promote to 'int'!) but as long as you can't fix that, you can't get rid of UB and still be performant.
Strong arguments, ideally legislation would ensure plastics break down and if not, some sort of breakdown cost incorporated into the goods. But that stifles industry and innovation. Maybe we can have incentives for packaging that breaks down, I believe the technology exists at this point in time.
The only Atari machine featuring a DSP (the same Motorola 56001 as in NeXT machines) was the Falcon, which was introduced in 1992 - four years after the introduction of the NeXT system (and one year before NeXT black hardware was discontinued). Less than 20,000 Falcons were produced [1], whereas around 50,000 NeXT machines were built.

AFAIK the only Amiga that would have come with a DSP in a default configuration is the never released A3000+ which used an AT&T DSP3210. Prototypes of the A3000+ existed in 1991.

The major contribution of the original Atari STs to music were the built-in MIDI ports, which made it easy and simple to connect digital synthesizers, keyboards, etc. The music capabilities of a regular ST were rather constrained due to its outdated AY-3-8910/YM2149 sound chip (the SID in a C64 was more capable). Only the STE introduced PCM audio.

I guess someone more knowledgable about Amigas than me can add some facts about its sound capabilities.

[1] https://stcarchiv.de/stc1993/10/interview-atari-bob-gleadow
This was both funny and ironic at the same time.

Upon clicking reply fastidiously, i got the hn 429

"Sorry, we're not able to serve your requests this quickly."

Wow.
Yeah, today.
It’s like a database, I imagine - so the answer is probably “unlikely,” that you need memory per-request but instead that you run out of cores to handle requests?

You need to load the data so the graphics cards - where the compute is - can use it to answer queries. But you don’t need a separate copy of the data for each GPU core, and though slower, cards can share RAM. And yet even with parallel cores, your server can only answer or process so many queries at a time before it runs out of compute resources. Each query isn’t instant either given how the GPT4 answers stream in real-time yet still take a minute or so. Plus the way the cores work, it likely takes more than one core to answer a given question, likely hundreds of cores computing probabilities in parallel or something.

I don’t actually know any of the details myself, but I did do some CUDA programming back in the day. The expensive part is often because the GPU doesn’t share memory with the CPU, and to get any value at all from the GPU to process data at speed you have to transfer all the data to GPU RAM before doing anything with the GPU cores…

Things probably change quite a bit with a system on a chip design, where memory and CPU/GPU cores are closer, of course. The slow part for basic replacement of CPU with GPU always seemed to be transferring data to the GPU, hence why some have suggested the GPU be embedded directly on the motherboard, replacing it, and just put the CPU and USB on the graphics card directly.

Come to think of it, an easier answer is how much work can you do in parallel on your laptop before you need another computer to scale the workload? It’s probably like that. It’s likely that requests take different amounts of computation - some words might be easier to compute than others, maybe data is local and faster to access or the probability is 100% or something. I bet it’s been easier to use the cloud to toss more machines at the problem than to work on how it might scale more efficiently too.
As someone who is very interested in decentralized services (as in my day job involves decentralized databases and I'm actively working on WebGPU support for training) I'd say that the browser-based vision is a fair way off.

The software ecosystem is pretty immature, and there are numerous things that need to change before the core technologies are good enough to fine tune competitive LLMs.

I do think fine tuning moderate sized LLMs on your own (pretty expensive) hardware using consumer GPUs maybe possible this year.

Unfortunately all the evidence is that training (as opposed to inference) requires high-precision, and hence high memory. This is something that consumer GPUs for the most part lack. New techniques are likely to be required (eg better sharing of training on low memory GPUs) but it's hard to predict how they will develop.
> That's not a settled debate; not remotely.

In my opinion it is neurotoxic, based on studies I have seen (such as this one that we are commenting on) plus my own direct personal experience. Even without the psychoactive components, the smoke is carcinogenic (like tobacco) and toxic to all cells, including neurons. Go take a massive bong hit, then tell me your mind and lungs feel healthy. Cannabis is blatantly toxic filth.

> because you can't make the assumption that people would "never have become psychotic without the drug"

Somehow you are ignoring the entire point of the article/study that we are commenting on.
> This so-called "competition" from open source is going to be free labor. Any winning idea ported into Google's products on short notice. Thanks open source!

How else, exactly, is open source supposed to work? Nobody wants to make their code GPL but everybody complains when companies use their code. I get that open source projects will like companies to contribute back, but shouldn't that go for everyone using this code? Like, I don't get what the proposed way of working is here.
>They had all of the leverage and could charge as much as [they] wanted.

That's how it works! You got cheated.

On an unrelated note, I upped my liability insurance from the $25k minimum to $100k just because of those crazy repair prices. It only cost like $17 or so more.
I picked up on this too. Everyone involved has a perverse incentive to portray the narrative as the work of genius, innovative hackers. That's the issue with an article like this, where all the quoted sources are people directly involved. I would have appreciated some 3rd party analysis of just how sophisticated this attack really was, and how much of the blame should really rest on the lax standards of the victims. Mandiant in particular doesn't have much excuse.