skysight-inc/HackerNews huggingface dataset:
Why are you so condescending?

It's always very jarring to come across a post that is so drastically different in tone when you're just trying to follow a comment thread.

> I think you should take a step back and meditate over your post.

I wish you'd follow your own advice.
The mention is here:

"3.2.2. Efficient Implementation of Cross-Node All-to-All Communication

In order to ensure sufficient computational performance for DualPipe, we customize efficient
cross-node all-to-all communication kernels (including dispatching and combining) to conserve
the number of SMs dedicated to communication. The implementation of the kernels is codesigned with the MoE gating algorithm and the network topology of our cluster. To be specific,
in our cluster, cross-node GPUs are fully interconnected with IB, and intra-node communications
are handled via NVLink. NVLink offers a bandwidth of 160 GB/s, roughly 3.2 times that of IB
(50 GB/s). To effectively leverage the different bandwidths of IB and NVLink, we limit each
token to be dispatched to at most 4 nodes, thereby reducing IB traffic. For each token, when its
routing decision is made, it will first be transmitted via IB to the GPUs with the same in-node
index on its target nodes. Once it reaches the target nodes, we will endeavor to ensure that it is
instantaneously forwarded via NVLink to specific GPUs that host their target experts, without
being blocked by subsequently arriving tokens. In this way, communications via IB and NVLink
are fully overlapped, and each token can efficiently select an average of 3.2 experts per node
without incurring additional overhead from NVLink. This implies that, although DeepSeek-V3
13
selects only 8 routed experts in practice, it can scale up this number to a maximum of 13 experts
(4 nodes × 3.2 experts/node) while preserving the same communication cost. Overall, under
such a communication strategy, only 20 SMs are sufficient to fully utilize the bandwidths of IB
and NVLink.

In detail, we employ the warp specialization technique (Bauer et al., 2014) and partition
20 SMs into 10 communication channels. During the dispatching process, (1) IB sending, (2)
IB-to-NVLink forwarding, and (3) NVLink receiving are handled by respective warps. The
number of warps allocated to each communication task is dynamically adjusted according to the
actual workload across all SMs. Similarly, during the combining process, (1) NVLink sending,
(2) NVLink-to-IB forwarding and accumulation, and (3) IB receiving and accumulation are also
handled by dynamically adjusted warps. In addition, both dispatching and combining kernels
overlap with the computation stream, so we also consider their impact on other SM computation
kernels. Specifically, we employ customized PTX (Parallel Thread Execution) instructions and
auto-tune the communication chunk size, which significantly reduces the use of the L2 cache
and the interference to other SMs."

It's definitely not the full model written in PTX or anything, but still some significant engineering effort to replicate, from people commanding 7-figure salaries in this wave, since the training code isn't open.
I don’t quite understand what the difference between the Groq version and the actual r1 version are. Do you have a link or source that explains this?
This is going to have a catastrophic effect on closed source AI startup valuations. Because this means that anyone can copy any LLM. The person who trains the model, spends the most amount of money. Everyone else can create a replica at lower cost
It's fine to be in the minority; doesn't make you wrong. Steam reviews are far from a good indicator of actual quality.
Hookworms and the Myth of the "Lazy Southerner"

https://www.pbs.org/video/gross-science-myth-laziness/
nanoGPT contains some new ideas. https://github.com/karpathy/minGPT is more plain
I love it too, though I never use it for working with entire projects but rather for smaller text editing tasks because it's so snappy. It's my scratchpad for notes and stuff, I will investigate and edit single files, and I use it for find-and-replace within a directory.

Though for the single file operations, it really depends on how I'm currently interacting with the system. If I'm browsing the files in a GUI then I'll use ST. If I'm in a terminal I'll use neovim.

One enhancement I would love to see to ST is better large file support. If I open a 330MB CSV in Notepad++ it displays instantly and uses 350MB of RAM. If I open the same file in ST it takes a few seconds to show and uses 1.5GB of RAM. (This is with both editors using no plugins beyond whatever is default)
Creators who use Nightshade on their published works.
This does not ring true. You are associating too many traits with each personality type. It sounds to me like you are defining more of a "me vs. others" list than building up something universally true across people.

There may be some value to that on a personal level - self-knowledge is a good thing. But I don't think that can be extrapolated out to the general population. There is far more variety between humans that that.
These are the FP8 distilled versions of DeepSeek we've started testing at Jam & Tea.

We use LLMs for real-time gameplay. We released Retail Mage last year on Steam as a tech demo of what we can do. We've found FP8 to be the current sweet spot for accuracy and performance for our use case. It's one of the many techniques we applied last year to bring our real-time inference costs down by 3 orders of magnitude to make Retail Mage releasable.

Anyway, we're just sharing this with anyone who finds it useful.

You can read a few more note by our ML engineer, Yudi, on LinkedIn here:

https://www.linkedin.com/feed/update/urn:li:activity:7290455...
Additionally, I was under the impression that all those Chinese models were being trained using data from OpenAI and Anthropic. Were there not some reports that Qwen models referred to themselves as Claude?
I recently thought of a related question. Actually, I'm almost certain that foundation model trainers have thought of this. The question is to what extent are popular modern benchmarks (or any reference to them, or description of them, etc.) bring scrubbed from the training data? Or are popular benchmarks designed in such a way that they can be re-parametrized for each run? In any case, it seems like a surprisingly hard problem to deal with.
What you describe sounds more like an attempt to classify aspects of the "Big 5" personality traits in some kind of binary system. Your "fact-based" persona seems to be low in agreeableness while the "story-based' is rather high in it (put very simplified).
MoviePass Might Pivot to Crypto
Reasonable take, but to ignore the politics of this whole thing is to miss the forest for the trees—there is a big tech oligarchy brewing at the edges of the current US administration that Altman is already participating in with Stargate, and anti-China sentiment is everywhere. They'd probably like the US to ban Chinese AI.
It varies a lot by model, tokenizer, and language.

For DeekSeek 1 token ~= 3 English characters.

See: https://api-docs.deepseek.com/quick_start/token_usage/

It comes out to around 1-3 words/second. This is not so slow that it's maddening (ex 2 token/second is frustratingly slow, like walk away and make coffee while it's answering slow), but it's still slow enough to make it hard to functionally use and not break flow state. You get bored and distracted reading at that pace.
January Windows 10 preview update force installs new Outlook
This was my impression, too. I've been reading years of hype, so I bought the game a few months ago, and I was unimpressed. But the fact that it's kind of an objective-less sandbox wasn't what got me.

I've played plenty of open world games and enjoyed them. In fact, even in games like Morrowind or Starfield or Grand Theft Auto or the like, which have big worlds and specific objectives, I've always found myself ignoring the quests and preferring to explore on my own terms.

I remember hopping around in Morrowind as a kid, trying to become as powerful as possible, and seeking out baddies to best. Then in Grand Theft Auto I'd go on epic crime sprees to see how long I could elude the authorities. And in Starfield I built an incredible network of trading posts that spanned the galaxy to see how much I could enrich myself.

What made these games fun is that, despite not following any missions or objectives, I was able to do impressive and interesting things and have fun. Perhaps that's possible in No Man's Sky, but in my first couple hours of playing, it didn't seem like it. It seemed liked I'd be going around doing boring and uninteresting things, and that it wouldn't be fun.

So it's not that it was a sandbox that bothered me, but that it was a sandbox devoid of fun.
I would suspect the infinity fabric links are already saturated with the local RAM’s memory bandwidth such that you will not get more by accessing another socket’s RAM.

Chips and Cheese suggests things are even worse than this as the per CCD bandwidth is limited to around 120GB/sec, which probably ruins the idea of using the 9015, as that only has 2 CCDs:

https://old.chipsandcheese.com/2024/10/11/amds-turin-5th-gen...

https://www.techpowerup.com/cpu-specs/epyc-9015.c3903

Anyway, leveraging both sockets’ memory bandwidth would require splitting the layers into partitions for each NUMA node and doing that partition’s part of each GEMV calculation on the local CPU cores. PBLAS might be useful in implementing something like that.

As for a speed up from using 3090/4090 cards, that is a bit involved to estimate. The model has 61 layers. The way llama.cpp works is that it will offload layers and the computation will move from device to device depending on where the layers are in memory. You would need to calculate roughly how long it takes for each device to do a layer. Then multiple by the number of layers processed by that device and sum across the devices. Finally, normalize to get the number of tokens per second and you will have your answer. DeepSeek R1 has 61 layers (although I think llama.cpp will say 62 due to the embedding layer if it counts for DeepSeek like it does for llama 3). It has 37GB of activated weights, so you can do 37GB / 61 / memory bandwidth to get the time per layer. You probably want to multiply by 1.25 as a fudge factor to account for the fact that these things never run at the full speed that these calculations predict. Then you can plug in these numbers into the earlier calculation I described to get your answer.
> Meanwhile, the US is in a more fragile stance, with lots of internal fighting and even pushing [intelligent] people out of the country.

Oh, good grief. Amazing how people find ways of squeezing Orange Man Bad into anything and everything.

PS - I am not going to stay awake at night worrying that ICE will be deporting hordes of illegal aliens working at US AI companies.
Worry not, we have lots of drugs we can prescribe for this in the US
From the R1 paper

In this study, we demonstrate that reasoning capabilities can be significantly
improved through large-scale reinforcement learning (RL), even without using supervised
fine-tuning (SFT) as a cold start. Furthermore, performance can be further enhanced with
the inclusion of a small amount of cold-start data

Is this cold start data what OpenAI is claiming their output ? If so what's the big deal ?
Interesting. That’s pretty high but I guess not surprising. It’s sort of like paying cost of a hotel room and meals and also prison staff. On the other hand, it’s not that much more than what cities like SF or Seattle spend on each homeless person that their programs cover.

Unrelated, and I am asking this seriously: isn’t outsourcing imprisonment how the present nation of Australia (excluding indigenous people) got populated?
Belief that the CCP is behaving poorly isn’t racial prejudice, it’s a factual statement backed by a mountain of evidence across many areas including an ongoing genocide.

Extending that to a new bad behavior we don’t have evidence for is pure speculation, but it need not be based on race.
$1,524.76/day/person. Makes you wonder where the money went. Obviously paying the guard salaries and whatnot adds up, but that's luxury midtown Manhattan hotel room prices for every single inmate. It would be cheaper to hire three people for every single inmate to personally stay with them in 8 hour shifts to make sure they don't get into trouble.
In what sense is the federal government "the boss" of private sector businesses? This isn't an oligarchy yet, right? They don't have to behave obsequiously, they are choosing to. They're doing it for themselves, not for their shareholders or their employees. It's an attempt to grab power and become oligarchs because they see in this government a gullible mark.
I don't disagree, however for the AP to refuse calling a spade a spade to me makes it clear than when it comes euphemizing genocide, we're not really any better than China.

But that said, while you're right, it is a loop and the media can't be fully deresponsibilized when they become a victim of the narrative they helped shape.
Depending on your perspective, pawns that get promoted?
I think you're mixing epistemic theories and social harmony. On the epistemic side, there are definitely ideologues who rely on really broad models of reality that overrule low level facts, like Lysenkoism, and others who fixate on low level facts and miss patterns. But most people don't really have a epistemic foundation at all, and just passively absorb "facts" socially without seriously considering their truthiness. All of this is kind of orthogonal to how you express yourself though; ideologues can be just as disagreeable in my experience.
I can answer the opposite of that question. Why Emacs?

For me, Emacs is valuable not for the things it can or cannot do, it's valuable because it gives me the perception of complete control over the things on my computer.

The other day, I was watching my teammate showing me some stuff over Zoom, and I didn't want to derail his thoughts by constantly stopping him: "hey, wait, don't scroll away, I'm still reading that," "wait a second, what was that URL again?" etc. So, the only thing I could do was take screenshots.

During the lunch break, I decided to solve this thing for myself. I wrote a command that checks ~/Desktop - it's where I drop my screenshots, then finds any .png file that was created no longer than 2 minutes ago, sends it to tesseract for OCR, and opens the text in a buffer. Took me less than 20 minutes.

Sure, there are many ways to get something like that done, but after trying so many different options, I was never able to extract the same feeling of control from any other alternative.

I have a command that inserts the url of my active tab in the browser, with description, in the correct format (e.g., markdown). I wrote that myself, because at some point it bothered me that I had to do that manually. There are many examples such that, where if I weren't using Emacs, I probably wouldn't even bother to acknowledge the existence of such small annoyances.

What makes Emacs truly exceptional isn't its vast feature set, but rather its ability to foster a problem-solving mentality - the "Emacs brain" - where no obstacle, regardless of size, goes unaddressed or unresolved.
This is why we need a push for radical transparency when it comes to public spending.

What did they spend $556,539 per inmate on, exactly?

Taxpayers deserve an itemized receipt.

Otherwise, by accepting overspending as the norm, it obfuscates corruption & large-scale grift as taxpayers get fleeced.

There's also substantial opportunity cost - that's $500K+ that could be going toward education or useful public services, that ended up in someone's pockets instead.

Transparency invites accountability.
"Costs the city" and "costs the prison" are not the same thing.
Some info that may be missing:

- v2/v3 (not r1) seem to be cloned from o1/4o output, and perform worse (this cost the oft-repeated 5ish mm USD)

- r1 is specifically a reasoning step (using RL) _on top of_ v2/v3 and performs similarly to o1 (the cost of this is _not reported anywhere_)

- In the o1 blog post, they specifically say they use RL to add reasoning to LLMs: https://openai.com/index/learning-to-reason-with-llms/
You forgot "are a child".
Are you a Chinese military troll? The fact that China engages in industrial espionage is well known. So I’m surprised at your resistance to that possibility.
I don’t disagree, but I was responding to a claim that the JVM has _all_ the advantages of fully native languages. Fully native allows you to choose to have no runtime, or a garbage collector, and in some environments (realtime, OS kernel, AAA games) that is overwhelmingly the preferred option.
SQL relies on RDBMS's type system, just like C++ devs rely on C++ OOP.

the problem lies with lax/weak table design that allows too lax data (all string nullable fields for example), instead of strict types like int, float, varchar, foreign key constraints etc.

you dont need unit test if you table design is clean, because SQL operators are deterministic and are tested by the RDBMS vendor

just need integration test, dry run test, periodic data integrity checks at the system boundaries when data is ingested/egress

SQL represents operations on the Sets of data and their relations, so you need not unit test on a single row, but a test suite on your entire DataSet (backup copy or synthetic copy)
It's not open source, we have no idea about the data used to train the model, and the paper doesn't explain it all.
Fair enough. But that doesn’t change the idea that going to college should ultimately be about increasing your chances to be employed not an education for education’s sake
The game certainly has had changes and additions. Whether those constitute improvements is a matter of opinion.
If true, the question is: did they use ChatGPT outputs to create Deepseek V3 only, or is the R1-zero training process a complete lie (given that the whole premise is that they used pure reinforcement learning)? If they only used ChatGPT output when training V3, then they succeeded in basically replicating the jump from ChatGPT-4o to o1 without any human-labeled CoT (and published the results) - which is a big achievement on its own.
Too much iodine can lead to thyroid problems, and this has been a problem in some subgroups in Japan: https://academic.oup.com/jcem/article/107/6/e2634/6516999
Sure, that's still not really a clear ideological underpinning to me though.

Is the core that goal to progress away from capitalism towards more governmental control?

If so I guess that is at least defining a directional goal, but using the blanket term "progressive" there is effectively blocking out anyone who wants to progress towards a different goal.

It seems like federalist or anticapitalist would be much more clear. At least then the goals they want to move towards are the distinguishing factor rather than the act of changing from where we are currently.
It's a reasonable definition, especially when classifying biochemicals, but there are always edge cases.

For example : https://en.wikipedia.org/wiki/Carborane that definitely do have C-H bonds but are mostly B-B, B-C, B-H.
Thank you for the clarity.

> But that thing you wrote is a static effect system.

The thing I wrote is expressible in Java's type system as it is today. So you're saying that Java has a static effect system?
VC funded companies (almost[0]) never repay it.

They only try to create enough value that the VC can one day sell their stake for more than they paid for it. The key is convincing the VC not that that is particularly likely, but that if it happens there's a chance it'll be a lot more than they paid for it.

[0] occasionally a company gives money back to investors when it fails
You pointed out a historical inaccuracy I wished to correct. You were the one that brought up the past and then incorrectly depicted it. You're reading a little too much on this.
couldn't imagine clicking on something to rebuild the program!

Do you really think that's how people use IDEs?

I've never used an IDE that didn't have comprehensive keyboard shortcuts, and I don't remember one that didn't allow customization of shortcuts.
I think for my viewpoint to be internally consistent it needs to happen internationally as well as domestically.
ofc this is all a pipedream anyway, there's barely an appetite for lifting the people in the tenderloin out of poverty and I'm trying to convince people that we'd all win by tending toward a "humanity vs the universe" viewpoint that's based on the idea that all the folks on the planet deserve to have it good.

"when you're used to privilege, the loss of it feels like oppression"

It will hurt to fix this, but I don't think it needs to hurt that much I think it would hurt a lot less if we were actually trying to make it happen rather than occasionally being dragged kicking and screaming in that direction.

(i do not have any meaningful ideas how to bring about this kind of change, (maybe a fake giant squid alien in manhattan? :P))
The goal with most of these AI features is not to solve a real problem users are having, it's to add a feature that uses AI. This will not change because it's not wrong of the individuals making the decision. The project manager gets to say he shipped a cutting-edge AI project. The developers all get to put experience working with very hireable technologies at a serious company on their resume. There will be no adverse impact to the bottom line, because the cost to develop the shitty AI feature is a drop in the bucket, and the cost to create a competing product that accomplishes the core thing users are using that product for but without feature bloat would be very high, and probably unsuccessful since "less feature bloat" has never been sufficient to break the static friction threshold for users to switch.

So it won't change, because there is no lesson to learn. No individual involved acted irrationally.
I think being fact based doesn't make you put your foot in your mouth, that's perhaps correlated though. You can have empathetic-delivery/patience while being staunchly objective. With some patience/skill you can win people over to accepting or at least considering what might be a truth.

It's rarely cut and dry as to what is true though, and you have to speculate at much in order to make sense of any real world complex situation.
We’re not getting this for free. PEPFAR data systems are still down and 20 million people are not getting access to life saving medication.
> What matters is stuff for which there are no workable alternatives elsewhere.

But we have to limit ourselves to somewhat common use cases. If a company is making a piece of software especially for one or two big clients in their industry, then that has nothing to say about any personal computing platform.

Your example Docker is software which has been especially created to deal with the shortcomings of Linux. Of course we cannot expect it to be great on any other platform. Likewise, we cannot blame MacOS for lacking specific software that has been made by people who explicitly hate Apple, such as a lot of self hosted and open source stuff.

Most Mac users do not mess about with virtual machines or WSL/WSLG, as in your examples. But there are myriad personal and professional use cases that are supported by good native software. In comparison Linux is lacking in native apps. No good photo editor, no good office suite, no good e-mail client. So I wouldn't call it a strong platform if we compare.

And it isn't copium to me. It's quality of life question to be able to use native software, and as a non-programmer I can be more productive with GUI software that isn't some laggy cloud service.
There's no zero sum games in a growing industry like this.
Nintendo is _very_ protective of its brand. They acted like this long before AI.
They're testing in Upper Minnesota and upstate New York. Upstate New York contains the snowiest city in the US, Syracuse.