skysight-inc/HackerNews huggingface dataset:
Watch this 90s commercial for 3dfx: https://www.youtube.com/watch?v=ooLO2xeyJZA

GPUs always had more compute / Gigaflops than traditional computers. GPUs in fact have more to do with 80s-era supercomputer architecture than normal CPUs.

https://www.youtube.com/watch?v=ODIqbTGNee4
Regardless of the publication intentions, I like to see contemporary folks who have made an impact on the world through technology being recognized and elevated.

In economics, where I come from, people are not afraid to give accolades to relevant people, whether treasury secretaries, banking economists, or professors.

I feel that in tech, due to the lack of publications that have technical capabilities to understand that impact plus the lack of goodwill from the media in general, there are a lot of folks doing relevant work out there that is ostracised due to this "cult of tech CEO/entrepreneur" or intentionally under the radar to not bring any negative light in their lives.
Ideally no runtime should alter strings passing through ("in transit") from one runtime to another - unless it does some processing on them.
I work with some teams in India and I am ~12 hours offset time wise. I find that they often will often just send “Hi” in Slack. By the time I see that, they are already offline. If I respond with something like “What can I do for you?”, it will be another 12 hours before they see that and then another 12 hours still before I can see whatever request they make.

I’ve tried to suggest to some of them that they lead with their request, but that has not helped much.
While I agree, there is a whole generation of people who know what a DHT is, it's not really that obscure.

I'm talking about of course very late 90s, 00's P2P file sharing, Kademlia, torrents but also later "eventually consistent" databases ( remember those? )

The crypto 20 somethings hype beasts came way later.
That's the claim Jensen has made, and while there isn't any particular evidence besides his word to go off for the founding goal, it's worth considering that between 1993 and 1998 they only put out 2 chips. The first one was quadratic primitive based (which, sounds more focused towards a future of compute applications, due to the ease of representing equations in such a form), and the second one was a last ditch effort triangle primitive chip to avoid bankruptcy after DirectX settled on triangle primitives. So I don't really think those years count for much in terms of determining what their goal was.

Their release cadence only really picked up in 1998, and just 2-3 years later they had the first 'programmable' GPUs with early shaders.

As such, saying that NVIDIA wasn't always aiming for GPU compute feels kinda like saying that SpaceX wasn't always aiming for feasibly reusable rocketry because it took them ~15 years to build up to their current version of it.
Restocking could have the same effect as replanting trees: numbers stay the same so it absolves the industry.

But the ecosystem is still getting worse as it gets devastated by the constant churn and artificially restored new areas are not as diverse as the original one.
Fickling now has modules for PyTorch, polyglots, and modular analysis
Can you try disabling (setting to 0) browser.display.use_document_fonts?
I think that just goes to show how misleading GDP can be!
I'm very curious if there are any databases running in production environments on Btrfs or ZFS.
While I new that the shell has emacs-style bindings I didn't know these were really readline based and supported things like undo. I should go read up on more readline keybindings.
All of us were always free, and are still free, to contribute to making his wiki page better!
> KK theories introduce an extra spatial dimension beyond our usual (3+1) which is postulated to be "compactified". This just means that it's curled up on itself

You've just explained "compactified" in terms of being "curled up", but that doesn't really help (for me, at least). What does it mean for a dimension to be "curled up"?
Localised confusion, indeed: You're still labouring under the misapprehension that you're on a tech website here.
My understanding was that they were offering a specially-patched version of Yuzu to their Patreon supporters, that included improvements for games that _weren't released yet_.

*Making money* by helping people run Zelda _before it came out_ was begging for trouble.

Nintendo's approach to fan projects and emulators is ridiculous, don't get me wrong — but Yuzu authors were definitely playing with fire and overstepping what's generally accepted in the community.
I refer you to my reply to your sibling comment.

Michelangelo did a less efficient job painting the Sistine Chapel per square meter than a housepainter would have.
I'll double down on personality that parent comment pointed out. If you see someone submit a project they worked on instead of formal education then you need to see what their exact contribution is and how they interact with other devs. Look at past github comments, issues, etc. Lurk in their chat server or pull logs. Expect to see a more casual attitude than what will show up at work, but pay attention to how contributions are handled, how credit is handled, and how disagreements are handled. It's not a universal problem, but I've seen some of the worst developer drama around volunteer open source video game projects.
“I took a speed-reading course and read War and Peace in twenty minutes. It involves Russia.”
― Woody Allen
Btrfs seems to work perfectly well in synology NAS. It must be some other combination of options or functions in use from what is available in synology that garners the bad reputation
I'm absolutely not going to short Nvidia stock, but it's plausible that they're overvalued.

Nvidia GPUs are pretty flexible in terms of computation and extremely power hungry. It may be that a next generation of more specialized hardware, such as TPUs or something, outperforms Nvidia GPUs on machine learning tasks to such an extent that those GPUs are obsolete for those tasks. This next generation could come to market sooner than Nvidia anticipates.

Another possibility is that ML researchers figure out some ways to radically reduce the amount of compute required for good training and inference on _less_ specialized hardware. It's really impressive what you can do with llama.cpp. If open source models running on consumer grade hardware ever get to 90% as good as ChatGPT (which, to be clear, is absolutely not the case currently), then those top end GPUs are overkill for most use cases.

I don't think either of those scenarios is particularly likely, but they're at least plausible.
Thanks for the tip! I don't have experience with strace, and I'm wondering if I'm misunderstanding what you're saying.

I tried running your suggested command, and I got 2,800 lines of output like this:

execve("/nix/store/vqvj60h076bhqj6977caz0pfxs6543nb-bash-5.2-p15/bin/sh", ["sh", "-c", "echo \"60016000526001601ff3\" | xx"...], 0x7fffffffcf38 /* 106 vars */) = 0
brk(NULL) = 0x4ea000
arch_prctl(0x3001 /* ARCH_??? */, 0x7fffffffcdd0) = -1 EINVAL (Invalid argument)
access("/etc/ld-nix.so.preload", R_OK) = -1 ENOENT (No such file or directory)
openat(AT_FDCWD, "/nix/store/aw2fw9ag10wr9pf0qk4nk5sxi0q0bn56-glibc-2.37-8/lib/libdl.so.2", O_RDONLY|O_CLOEXEC) = 3
read(3, "\177ELF\2\1\1\0\0\0\0\0\0\0\0\0\3\0>\0\1\0\0\0\0\0\0\0\0\0\0\0"..., 832) = 832
newfstatat(3, "", {st_mode=S_IFREG|0555, st_size=15688, ...}, AT_EMPTY_PATH) = 0
mmap(NULL, 8192, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x7ffff7fc2000
mmap(NULL, 16400, PROT_READ, MAP_PRIVATE|MAP_DENYWRITE, 3, 0) = 0x7ffff7fbd000
mmap(0x7ffff7fbe000, 4096, PROT_READ|PROT_EXEC, MAP_PRIVATE|MAP_FIXED|MAP_DENYWRITE, 3, 0x1000) = 0x7ffff7fbe000

Am I doing it wrong? Or is there more training involved before one could usefully integrate this into debugging? Because to me, the output is pretty inscrutable.
And tell me what is Nvidia trying to fund with the AI business?
Why not? Common characters are easier to type and presumbly if you are using regex on a unicode string they might include these special characters anyway so what have you gained?
Some people connect their ego tightly to their accomplishments. Others are emotionally fragile to what they perceive as negative experiences. Some achieve great things by what they perceive as great sacrifices, and have a lot of difficulty maintaining what they have achieved. Some at or near the top of a field perceive their accomplishment primarily as being "best", and are consumed with angst when they are no longer best. The public explanation they give may not describe how they are different than someone trying to understand.

Open up how you frame personality types and life experiences, and you can think of possibilities beyond "I don't see how".
I don't see them as opposed to each other but instead choices of different options from a menu of management technique.

In the case of Kanban you are writing well-defined tickets and limiting how many can be in progress at once. It's a common practice in many kinds of systems such as short order restaurants and cafes (e.g. at the cafe for our engineering school the people who take orders also make the food and they don't take your order until the depth of the queue drops)

For Scrum you are adding a bunch of extra options such as:

* regular meetings

* estimation of tickets

* sprints

Really the game is to develop a process that works for your product and your team. About 10 years ago I was working on a product that had an A.I. model in it that took 2 days (mostly unattended) to train if everything went right. We rebuilt the model for each 2 week sprint. I found Scrum's practice of accounting for punchclock time as opposed to calendar time did not work for this project because people would wind up starting the model training too late to have it done for the sprint, which was particularly problematic because early on model training might fail and it might take 2 or 3 attempts to build a model. I pushed for applying PERT charts so we could always start that kind of task early so the sprint could succeed even if we had some trouble with the model. We had a culture of not working on the weekends but actually running a model build over the weekend was a good answer and usually took about 30 min of somebody's time to monitor.

In the dark ages before agile I frequently worked on teams that didn't really know how to build their product. You can easily have a few people working for a year with their IDEs, not thinking it was a problem that it took a new dev 5 days to get their build sorta working, then when it comes time to deploy they could spend anywhere from 2 weeks-6 months to actually make a build you can put in front of customers. Agile teams who don't have a totally broken process have that problems solved because they regularly make a complete build. The typical 2 week cadence of Scrum is faster than many organizations but it can become a source of delays. For instance if you really understand build and deploy a manager could ask for some (truly) tiny change like adding some space above a button and that change could be put in front of customers in 2 hours as opposed to 2 weeks.
There is also the benefit to any exec whose compensation is related to a rising stock price, right?
At my work, I'm finding so many incredible things that GPT4 API can do to make my company run much more efficiently.

For example, being able to feed a potential customer's invoice into GPT and ask it to see what kind of services we can offer to beat its price. Our sales people had to spend hours doing this before. Now it's done in 2 minutes through an engineered prompt. And it's incredibly accurate.

The problem with GPT4 API is context size and price. That's it. Both are bottlenecked by faster and cheaper compute.

That's my bull case for more compute, not bear case like OP asked.
> Why not just use the most powerful language to orchestrate everything?

I usually do everything in a single language, but sometimes that's not the best solution. It's not a matter of how powerful the language is in a general sense, but how good it is at a particular kind of task.

But even ignoring my projects that involve multiple languages simultaneously, I still regularly use several languages in total, even if only one per project. So having a build system that's independent of the language is still highly desirable.

> That begs the question of whether compiler upgrades should force build system upgrades.

My answer to that is "no, never", of course. That leads to increased complexity for me, in exchange for no gain. The build system should have no special knowledge or expectation of what language or language tools are being used.
In some ways Nintendo suing the original project was a good thing. It brought the project to the attention of a lot more people. Now there is a new version with a bunch of bugs fixed. Who knows how many new developers will be working on it now.

I have to think Nintendo knew this. They had to defend what they could and did so because the original project actually seemed to be doing some sketchy stuff. They know they can't stop everything though.
Wink wink nudge nudge.
I mean, Higan/BSnes, SNES9X, Project64, Mupen64, FCEUX, mGBA, and probably dozens of others that I'm missing have been around for a very long time, and as far as I'm aware haven't had any legal issues from Nintendo, though that might be because all of them don't require any kind of BIOS.
My nervous system just short circuits from the idea of blood draw/donation. I start shaking, get super tense, and white out in a minute or so. Also, my veins are not super visible which makes the experience super tense.

It's something that I can't control, and is miserable for everyone involved.
I would hold a code review hostage if any file does not end
with an empty new line.

My reasoning would be if the file is transmitted and gets truncated
nobody would know for sure if it does not end a new line.
Brownie points if this is code end has a comment that the files ends there.

The article calls computer languages platforms but the are computer languages. Bash is not included. Weird. I believe the most common use of regular expressions is the use of grep or egrep with bash or some other shell but, who knows. Maybe I am hanging with the wrong crowd.
I agree with all of that. And in fact, that is what this city has. The car-free center thing works very well. You get a few large parking garages around the center, and inside you do everything on foot.

The rest of the city is spacious and has good car accessibility, so you can also get out quickly.
Even if the anonymous developer submitted the resume, they are giving the employer the power to dox them. There is a lot of trust there.
I am all in for allowing tax free bloated RnD departments just with the hope that once in a decade idea will propell the overall economy.

The marvel of modern computing is a result of RnD bloat that was done without immediate impact to the bottomlines of their own companies.
In Vietnam, marine wildlife sanctuaries help enormously. Fisherman are banned from fishing in certain areas, but can fish with great success around those areas. The protected areas allow stock to be replenished. It’s the goose that laid the golden egg phenomenon.
Buybacks and dividends are the same thing. Money leaves the company to go to shareholders. Neither is better/worse for R&D.
Subsidies always have a cost on public finances.

In Paris' case, the financial situation is bad and getting worse with a debt on track to reach EUR10 billion.

So it seems to me that Paris is borrowing like there is no tomorrow. This usually does not end well.
For me my internal monologue is replaced by almost entirely images. For example, if I'm learning about something in a programming language I'm mentally diagramming components and imagining how data structures are laid out as a network of items. To the extent that I do verbal thinking while programming it's usually just a internal vocalization for an interjection I would otherwise be tempted to say out loud like "why the fuck is this not working, this SDK is trash". And I only say it to myself internally so as not to interrupt other people around me.

For other things that are less abstract, with a concrete real world appearance, I'm constantly visualizing the outcome like I'm looking at a picture or watching a movie. This also applies to the "things that come to my mind without talking", which you mention. They drift into appearance in my mind as images as well.
Not only in web browsers unfortunately, also in Sublime Text...

My favorite (that I wish more editors supported) is ctrl+D for duplicating the current selection (or the current line if nothing is selected).
I guess Blackwell is too late in the design cycle to use N3. It would be interesting to see, at these sort of margin and volume. Would it make sense to have GPU on latest node? Next Gen 3nm GPU in 2025 and if they could move aggressively 2nm GPU in 2026.
They always take two months at the very minimum as well because buyers as to go to many banks or a loan broker. You have notaries involved and right to step away from a sale, no question asked for 10 days iirc.
Are you sure that book exists? I can't find it with a search or on his publications page [0].

And unless I have the wrong Mankiw, that doesn't look like a 19th century book.

[0] https://scholar.harvard.edu/mankiw/publications?page=3
> I've been thinking lately that one could probably leverage the same technology to evaluate the quality of research, possibly as a post-hoc verification.

I doubt it. They'll be just as effective as ChatGPT-detectors are. Completely useless.

> If not for anything, LaTeX formatting is tedious.

LaTeX formatting is a very, very, very small part of publishing research. At least it was for me.

> However, you can always seed an LLM with the bits of information you want explained and use the result as a basis for improvement.

That's what I tried to do with the argument in my PhD thesis. It didn't work. Also, at the point where you have meticulously thought through how to structure your argument (and that's what I needed to do to get ChatGPT to produce anything of value at all) you did 95% of the work already. Actually producing the text isn't the hard part of writing.

My point still stands: LLMs help way more if you want to produce low-quality papers than when you want to produce high-quality papers and as a consequence, the percentage of low-quality work will increase.
>Have a metal container nearby to drop them into for transport outdoors.

Before doing that, try watching some experiments with fireproof containers specifically designed for these fires, to have an idea how quick and violent this can be, and how bad most of these containers are at preventing it from going from 0 to inferno or to a toxic cloud suffocating you in seconds. This might or might not help you plan for the worst case, or better yet forget about doing DIY battery pack repairs at all.
How We Made Real-Time Data Aggregation in Postgres Faster by 50k%
Learn how we accelerated real-time data aggregation in PostgreSQL by 50,000 % by tweaking the query planner.
If we were willing to ignore the ability to actually type it, you don't need Unicode for that; ASCII has a whole block of control characters at the beginning; I think ASCII 25 ("End of medium") works here.
This was a widely spread myth, now generally considered incorrect.

Yuzu did not offer improvements before launch day. There were badly patched unofficial versions that were trying. Nintendo does allege though that Yuzu was doing research to develop the patches before launch day.
New goal: A "Sanjay popup". Hahaha.
tl;dr

OpenAi is on track to put out GPT-5 sometime mid-year, likely during summer, according to two people familiar with the company. Some enterprise customers have recently received demos of the latest model and its related enhancements to the ChatGPT tool, another person familiar with the process said. These people, whose identities Business Insider has confirmed, asked to remain anonymous so they could speak freely.

"It's really good, like materially better," said one CEO who recently saw a version of GPT-5. OpenAI demonstrated the new model with use cases and data unique to his company, the CEO said. He said the company also alluded to other as-yet-unreleased capabilities of the model, including the ability to call AI agents being developed by OpenAI to perform tasks autonomously.

OpenAI is still training GPT-5, one of the people familiar said. After training is complete, it will be safety tested internally and further "red teamed," a process where employees and typically a selection of outsiders challenge the tool in various ways to find issues before it's made available to the public. There is no specific timeframe when safety testing needs to be completed, one of the people familiar noted, so that process could delay any release date.
I would say gravity is a force, how the heck is this 100lb weight a 100lb weight?
When I started at my current company 2 years ago we were doing a rigid form of scrum. Over time, I’ve been able to bend that with my teams towards something that works for them and the product they are working on, instead of the other way around. What we ended up with is closer to Kanban; we stopped sprints and sprint planning and replaced it with WIP rules, and pulling work on the board when needed. We refine stories as needed, which means we don’t spend more time in meetings than we absolutely have to to gain alignment.
We've retained things from scrum we deemed useful, like the retrospectives, and some sort of regular alignment with stakeholders.
Altough not part of scrum or kanban, we’ve exposed engineers more to customers, instead of internal stakeholders, which means the solutions we’re making are much closer to what customers actually need vs what a stakeholder thinks they need.
Overal, the feedback from both engineers as well as stakeholders has been very positive, citing less meetings and more time to make an impact, as well as faster time to impact.
Eh, I wasn't even referring to forgetting how to write bubble sort or hashmaps from scratch. But just being able to reason about different algorithmic solutions to a problem, and intuit something about their complexity and requirements.

Thinking back to a recent-ish discussion here about the (very elegant and efficient) algorithm behind Shazam, and some of the comments here being along the lines of "haha, that's so quaint, nowadays you could just use a neural net". Nevermind how that would even work as well.

Or programmers excited about neural networks forgoing the much simpler, and in many cases completely sufficient, computer vision algorithms built into OpenCV, in favor of trying to train their own model from scratch.
I think the fear is that this is only the beginning. Nintendo successfully killed one emulator, why would they stop there?

Nintendo certainly knows about Ryujinx and is patiently waiting for them to screw up anything legally so they can bring them down next.
Five Themes Discussed at Princeton's Workshop on Decentralized Social Media
The problem with this so called 'market system' is it allows people to chose their neighbors through bidding only on properties they know the poors can't afford.

If the French wanted citizens to have the freedom of (dis)association they would have written it into their constitution.
I was able to solve it by disabling notifications... Really annoying though.
Selected Twitter Threads and Odyssey Text Comparisons – Emily Wilson