skysight-inc/HackerNews huggingface dataset:
>"GPGPU compute is a solved problem if you buy Nvidia hardware"

Which is valid? If your problem can be solved by writing a check, then it's the easiest problem to have on the planet.

Netflix didn't have to put out 3 PhD dissertations on how to improve the SOTA of live streaming, they only needed to reliably broadcast a fight for a couple hours.

That is a solved problem.

Amazon and Cloudflare do that for you as a service(!). Twitch and YouTube do it literally every day. Even X started doing it recently so.

No excuses for Netflix, tbh.
There are never enough USB-C ports.
The big difference of all the examples you’ve mentioned is dedicated full-time crews on the ground where the events are produced.

I’m pretty confident that when the post mortem is done the issues are going to be way closer to the broadcast truck than the user.
I don't know the space well enough, but I think the missing piece is that YC 's investment horizon is typically 10+ years. Not only LLMs could get massively better, but the chip industry could be massively disrupted with the right incentives. My guess is that that is YC's thesis behind the ask.
> Notably this was a problem with all the Sars-Cov2 vaccines, none seem to have prevented transmision from an infected person to a vaccinated person. Why wasn't this seen in the clincal trials, one wonders?

It was seen, then ignored by the media so the average person didn't realize what was going on. Remember that 95% effective? It wasn't 100% because vaccinated people not only got infected, they actually got sick (they were only testing once symptoms showed, not everyone in the study). The study it came from also only lasted 3 months, if it had gone on the planned 6 months it would have almost certainly gone much lower. I think they did end up having a follow-up at the 6-month mark (don't remember the results), but they got the EUA on the 3-month results.
No, its not at all different. Like I said, bad faith.

Edit: Lol didn't recognize your username. If you didn't begin your engagements on such an adversarial footing, you might get more constructive replies.
And the Python version: http://www.composingprograms.com/
That was hilarious, thank you
They can also eat at the storage. Also some chipmunks have their food storage next to their bed.

So knowing how big the cheeks are, is a useful information, but in this context not clear.
I suppose allowing developers targeting x86_64 Linux to still use Macs and the power efficiency of ARM CPUs, since I don’t think (maybe wrong) that ARM Windows machines support emulation inside WSL.

But that’s more feature parity with x86 Windows machines, not an advantage.
VirusTotal just passes on the file to the actual virus scanners (a for-loop with an api as a front-end) - it's up to each individual virus scanner to scan as they see fit (including scanning any unreferenced holes and compressed zip entries in a zip archive).

I have no idea why those virus scanners don't check nested archives. Maybe time/cpu constraints?
Mentioning DEI was a little sarcastic. I've seen comments on HN where DEI was claimed as a subjective criteria that hinders economic success.
This is true, but also, keep in mind that the JWST was insanely hard and almost cancelled a few times :)

The SGL would be much, much harder than the JWST would be, and the JWST was already stretching our capabilities.

The SGL needs to be 650AU away from us.
Voyager 1 and 2 are currently 165AU and 120AU away.

The JWST is 0.01 AU from us.

And you can only look in one direction after the probe finally gets into position. Once you're 650AU away, it's not really feasible to move "sideways" far enough to look at something else.
> Where are the low and mid budget movies?

At Cannes and your local 'art' cinema ? To be fair, I don't watch movies much, but I do still go to these sometimes.

> Where are the games publishers on low budget games?

Who said anything about publishers ? (And Valve dumped theirs as soon as they could.)

> Sure single person self-funded passion projects exist. They always have and they always will. And sure what one person can do is more than they ever could in the past. It's still not the same as something that's forged by a team of visionaries each with unique backgrounds and skillsets.

Ok, I have no idea what you're talking about, are you "no-true-scotsmanning" here ?

We have a great recent example : "Factorio (: Space Age)", which started as a one-person idea, took form as a 3-person company, got after release a 20k€ Indiegogo funding, then blazed a trail of success over the next 12 years, now with something like 5 million sales for the base game and a 30 person company.

How is that not "a team of visionaries each with unique backgrounds and skillset" ?!

Or the amateurs at Spring-Recoil / Zero-K / BAR, which show how you can do that even better than the professional, commercial RTS.

Or indeed one person projects like Shadow Empire (with some publisher support), which show how you can make a brilliant 4X/Wargame on what I assume is a tiny budget...

And there are probably many other examples here...
Author here -- I don't disagree! I actually noted this in the article:

> Well, it turns out that LLMs are also pretty valuable when it comes to chips for lucrative markets -- but they won’t be doing most of the design work. LLM copilots for Verilog are, at best, mediocre. But leveraging an LLM to write small snippets of simple code can still save engineers time, and ultimately save their employers money.

I think designers getting 2x faster is probably optimistic, but I also could be wrong about that! Most of my chip design experience has been at smaller companies, with good documentation, where I've been focused on datapath architecture & design, so maybe I'm underestimating how much boilerplate the average engineer deals with.

Regardless, I don't think LLMs will be designing high-performance datapath or networking Verilog anytime soon.
I see good stuff yet the scope creep including AI and opening every imaginable file seems to be a slowdown
If your LLM is producing a proof that can be checked by another program, then there’s nothing wrong with their reliability. It’s just like playing a game whose rules are a logical system.
Microwaves are great a two things (and little else...): warm up liquids and make popcorn. Neither are properly done by an air fryer.

I have both tools and they have completely different uses.

edit: both sport 7-segment digits though
> Writing is complex, LLMs once had subhuman performance,

And now they can easily replace mediocre human performance, and since they are tuned to provide answers that appeal to humans that is especially true for these subjective value use cases. Chip design doesn't seem very similar. Seems like a case where specifically trained tools would be of assistance. For some things, as much as generalist LLMs have surprised at skill in specific tasks, it is very hard to see how training on a broad corpus of text could outperform specific tools — for first paragraph do you really think it is not dubious to think a model trained on text would outperform Stockfish at chess?
Many years I asked a very wise person: "what would happen if adobe port photoshop to Linux?"

The answer was "nothing". I asked why; the answers was: "no Photoshop user will migrate for Linux because of it, no gimp user will migrate to Photoshop".

Also, I've read in HN once: that are more people using Linux on the desktop than there are Photoshop users. People overestimate photoshop as a killer app.
Maintaining Security CTF Skills with Spaced Repetition
I think this comment and the parent comment are talking about two different things. One of you is talking about using nondeterministic ML to implement the actual core logic (an automated script or asking Dave to do it manually), and one of you is talking about using it to design the logic (the equivalent of which is writing that automated script).

LLM’s are not good at actually doing the processing, they are not good at math or even text processing at a character level. They often get logic wrong. But they are pretty good at looking at patterns and finding creative solutions to new inputs (or at least what can appear creative, even if philosophically it’s more pattern matching than creativity). So an LLM would potentially be good at writing a first draft of that script, which Dave could then proofread/edit, and which a standard deterministic computer could just run verbatim to actually do the processing. Eventually maybe even Dave’s proofreading would be superfluous.

Tying this back to the original article, I don’t think anyone is proposing having an LLM inside a chip that processes incoming data in a non-deterministic way. The article is about using AI to design the chips in the first place. But the chips would still be deterministic, the equivalent of the script in this analogy. There are plenty of arguments to make about LLM‘s not being good enough for that, not being able to follow the logic or optimize it, or come up with novel architectures. But the shape of chip design/Verilog feels like something that with enough effort, an AI could likely be built that would be pretty good at it. All of the knowledge that those smart knowledgeable engineers which are good at writing Verilog have built up can almost certainly be represented in some AI form, and I wouldn’t bet against AI getting to a point where it can be helpful similarly to how Copilot currently is with code completion. Maybe not perfect anytime soon, but good enough that we could eventually see a path to 100%. It doesn’t feel like there’s a fundamental reason this is impossible on a long enough time scale.
Not gp but when we built our house we put magnetic switches in the jamb that close when it senses the metal bolt.
I think I would rather characterise it as hardball action by Qualcomm that got an expected response from Arm. The fact that Qualcomm told everyone except Arm in advance of the Nuvia deal is a tell.

I think settlement is unlikely - we are two years into the lawsuit. Arm really doesn’t want Oryon cores dominating - I think independent of price - and Qualcomm probably feels it has little to lose.

(I’m the author of this post)
Did anyone manage to read the whole essay? I often notice with text like these, that they try to imitate scientific writing, but never quite manage (they always end in some kind of uncanny valley). The author states his premise quite nicely in the abstract, but the article does not really provide a consise supporting argument and instead just makes semi related points. This is another pattern I noticed, layman authors often seem to think that dumping lots of loosely related "evidence" somehow strengthens the argument.

I wonder if there are good resources which would help lay scientists to write good articles (maybe an opportunity for an LLM proofreader?)
The bottleneck for LLM is fast and large memory, not compute power.

Whoever is recommending investing in better chip(ALU) design hasn't done even a basic analysis of the problem.

Tokens per second = memory bandwidth divided by model size.
one thing to note is that the second chapter's "picture language" is not supported in MIT Scheme in 2024. There used to be a package but it's like 2 decades out of maintenance. In Dr. Racket however, there is a package specifically for working through those problems.
hi, this is my article! thanks so much for the views, upvotes, and comments! :)
Because, as said before, zip managing splits ends with two sources of truth in the file format that can differ while the whole file still being valid
I find the PyMC situation confusing. But PyMC should be able to use JAX in the backend: https://www.pymc.io/projects/examples/en/latest/samplers/fas...
> The computer revolution is a revolution in the way we think and in the way we express what we think. The essence of this change is the emergence of what might best be called procedural epistemology — the study of the structure of knowledge from an imperative point of view, as opposed to the more declarative point of view taken by classical mathematical subjects

Ironic, given the increasing use of functional programming in domains where old-fashioned imperative/OO programming used to reign alone.
I notice a lot of articles end abruptly when they just start to get going. Maybe people get tired of writing and publish whatever they have?
this is not the Python version of SICP. It's a different book inspired by SICP. There's no "picture language" in chapter 2, and there's no "metacircular evaluator" and "register machine" in chapter 5.
My rule for writing documentation is as follows: first use of a commonly abbreviated term is written in its complete form, with the acronym or short form in parentheses. Then, the rest of the text in that same page can freely use the shorter form as needed.

So "the File Transfer Protocol (FTP) is bla bla... When using FTP, remember to bla bla..."

I think that's the most structured and correct way to introduce an acronym. Another style is to use "short form (long)" but "long form (short)" feels better to me (although I'm not a native speaker so maybe I got it the other way around!).
> replace most medical professionals with genAI language models as soon as the regulations allow

Understandable, I guess. But not feasible now, nor in the foreseeable future. The problem is not even "AI" performance. The real problem is that the useful data isn't available to machines, because it's mostly acquired through meeting patients in person. It's gonna take lots of money to make machines that can compensate for that.
You cannot shrink the federal government by firing "unelected bureaucrats"
Majority of superbowl viewers watch it on cable. Streaming gets fewer than 10M concurrents
Solutions are already being made for spent nuclear fuel, no reason why that wouldn't apply in this scenario. In fact its massive overkill for this particular situation but still an option if its needed:

https://www.youtube.com/watch?v=aoy_WJ3mE50
We're about 30 years too late to complain about the art style.

I don't disagree with the comparison of the visuals to flash games, but that's more or less all you can get to without a lot of backlash over completely changing the game's appearance, since the originals were very low-resolution highly cartoony things.

You could certainly have redone 1 and 2 in 3's engine, but that's a different market, in a lot of ways.
Do these fatwa-issuing bodies just represent the bureaucratization of Islamic law for the benefit of the state?
Why Do Empires Fall?
It's helpful for the users
I use the "right over left and left over right makes a knot both tidy and tight" every time unless I'm in a hurry, which I usually am if I'm tying a bow, in which case it's completely a coin flip as to what gets tied.
Adobe hasn’t been disrupted somehow. The format lock-in is too strong. I’m avoiding it wherever possible.
Is there a comparison image? I’d like to see screenshots of the original and the corresponding screenshots of the remastered version.

Update: the trailer shows the old and the new version at ~26s, direct link: https://m.youtube.com/watch?v=_iWMpW_C7Z0&t=26
So.. like trafshow.
I thought Avalonia was not WinUI based, giving Avalonia more freedom an consist platform behaviour.

Thanks for sharing, appreciated.
Not this again. This is all the fault of one unscrupulous doctor who has been discredited over and over, and even removed from participating in a previous investigation because his methods were so shoddy. Must be election season.
The problem seems to be that each individual split part is valid in itself. This means that the entire file, with the central directory at the end, can diverge from each entry. This is the original issue.
No, its not at all different.

And that's your mistake. The statements are clearly quite different. In exactly the same way that the statement:

The tumor is benign

Is obviously quite different from:

The tumor is irrelevant

If you didn't begin your engagements on such an adversarial footing,

Nothing of the sort is happening here.

You were provided with a necessary correction, in the hope that it would be helpful to you.
Related:

Yggdrasil Network - https://news.ycombinator.com/item?id=41669625 - Sept 2024 (3 comments)

Yggdrasil P2P mesh E2EE IPv6 network - https://news.ycombinator.com/item?id=30156551 - Jan 2022 (77 comments)

Yggdrasil – Early-stage implementation of an end-to-end encrypted IPv6 network - https://news.ycombinator.com/item?id=27577201 - June 2021 (102 comments)

Show HN: Yggdrasil Network – compact mesh routing experiment for mesh networks - https://news.ycombinator.com/item?id=18863554 - Jan 2019 (15 comments)

Announcing Yggdrasil Network v0.3 - https://news.ycombinator.com/item?id=18751991 - Dec 2018 (3 comments)

Yggdrasil: End-To-end Encrypted IPv6 Networking - https://news.ycombinator.com/item?id=18666245 - Dec 2018 (1 comment)
It's still $55k, that could be used somewhere else! Assuming the $5k/kg cost of getting something into LEO. Actual cost is even higher because more delta V is required to get off LEO.
> In fact, I’d go further and say that it’s the only computer science book of that age that I’d happily and usefully read again without it being just for historical interest: the content has barely aged at all. That’s not all that unusual for mathematics books, but it’s almost unheard of in computer science, where the ideas move so quickly and where much of what’s written about is ephemeral rather than foundational.

I recall that when MIT stopped teaching with SICP, one of the main claims was that programming now is often not about thinking abstractions through from first principles, and creating some isolated gem of composing definitions. Instead, we interact with and rely on a rich ecosystem of libraries and tools which often have individual quirks and discordant assumptions, and engineering then takes on a flavor of discovering and exploring the properties and limitations of those technologies.

I think now, (some) people also are at the point of not even directly learning about the limitations and capability of each tool in their toolbox, but leaning heavily on generative tools to suggest low-level tactics. I think this will lead to an even messier future, where library code which works on (possibly generated) unit tests will bear some fragile assumption which was never even realized in the head of the engineer that prompted for it, and will not only fail but will be incorporated in training data and generated in the future.
Not an expert, just trying to add some more context.

With time-delay cosmography[1] one exploits that unless the source is perfectly in the center of the line of sight, then the photons that make up one lensed copy have traveled a different distance from the source than photons that make up a different lensed copy. This effect can be used to measure absolute distance and give an accurate measure of the Hubble constant.

With dual source-plane lensing[2] one exploits that if two different sources lensed by the same lens, one can take the ratio of the measurements between the two sources and get results that are significantly less affected by the lens itself and is completely independent of the Hubble constant.

[1]: https://arxiv.org/abs/2210.10833

[2]: https://arxiv.org/abs/2204.03020
The trailer they embed for the release announcement shows them swapping, since like the Diablo remaster, I believe you can realtime toggle the changes on and off.
> by and large, the processes people are scrambling to place LLMs in are ones that typical machines struggle or fail

I'm pretty sure they are scrambling to put them absolutely anywhere it might save or make a buck (or convince an investor that it could)
The examples given here are not on the same scale. The numbers known so far:

- 120m viewers [1]

- Entire Netflix CDN Traffic grew 4x when the live stream started [2]

[1] https://www.rollingstone.com/culture/culture-news/jake-paul-...

[2] https://x.com/DougMadory/status/1857634875257294866
“Oh shit I better remember all that matrix algebra I forgot already!”

…Then takes a class on anything with 3d graphics… “oh shit matrix algebra again!”

…then takes a class on machine learning “urg more matrix math!”
Here’s an interesting study we could do.

Is there a placebo effect for car repair. And how does it compare to human “repair”?

You could pretend to fix peoples car issues and see if they report it improving.

Assuming the mind can’t fix cars mentally it would let you isolate what part of the placebo effect is perception.

Discuss..
I think the comparison would ruin the author’s argument.
That’s because we are still waiting for the 2008 bubble to pop, which was inflated by the 2020 bubble. It’s going to be bad. People will blame trump, Harris would be eating the same shit sandwich.

It’s gonna be bad.
I don't care about boxing or UFC or the grade-A douchebags that are the Paul brothers, but I tuned in just because I had the time and a Netflix subscription.

It was actually great that the fight itself was so boring because it justifies never having to spend time / money on that kind of bullshit. It was a farce. A very bright, loud, sparkly, and expensive (for some people) farce.

The value I got from it was the knowledge that missing out on that kind of thing isn't really missing out on anything at all.
You can build kind of blocks that you use, but for anything more complex you're pretty much forced to use a kind of free HTML field, which of course is just a text field where you either suffer by editing html and their templating system in a browser text field (the templating is something Django compatible) or you copy and paste from your text editor which is also a form of torture. I've edited the wrong template on occasion, and saved it. Even if you just stick to their wysiwyg you still have to sometimes add conditional blocks and this also is for me anyway difficult. They have developer mode too, which is your email as a giant yaml.

So they support a bunch of things, but personally I would not use it for anything except simple marketing campaigns. We do use it for that, but someone had the idea of having all customer emails go through it, and I don't really like it.
I didn't learn till I was a teen(I was taught several times, but have never been a fan of non-sandals so always forgot within a day or two).

Then I found what it actually is, it's a doubly slipped square knot, a square knot is right over left and left over right, and slipped versions are usually just finishing with a loop that goes back the way it came, so I can figure it out from the much easier to memorize verbal description.
Well, considering it was multiple small streams I would expect them to keep them up. No have their entire streaming service have issues.
I don't disagree that Netflix could have / should have done better. But everybody screws these things up. Even broadcast TV screws these things up.

Live events are difficult.

I'll also add on, that the other things you've listed are generally multiple simultaneous events; when 100M people are watching the same thing at the same time, they all need a lot more bitrate at the same time when there's a smoke effect as Tyson is walking into the ring; so it gets mushy for everyone. IMHO, someone on the event production staff should have an eye for what effects won't compress well and try to steer away from those, but that might not be realistic.

I did get an audio dropout at that point that didn't self correct, which is definitely a should have done better.

I also had a couple of frames of block color content here and there in the penultimate bout. I've seen this kind of stuff on lots of hockey broadcasts (streams or ota), and I wish it wouldn't happen... I didn't notice anything like that in the main event though.

Experience would likely be worse if there were significant bandwidth constraints between Netflix and your player, of course. I'd love to see a report from Netflix about what they noticed / what they did to try to avoid those, but there's a lot outside Netflix's control there.