skysight-inc/HackerNews huggingface dataset:
Oregon should never be the gold standard for how to do anything, ever. Can they even pump their own gas yet?
All absorbed? That's a pilaf, or a terrible risotto.
> What did it record? Who knows?

How is it any different than traditional voting, where you drop your ballot into a black box and trust the poll workers would count it correctly?

You can do random spot checks select boxes to make sure the machine is tabulating correctly. If they're all correct, you can be reasonably sure the others are correct as well, unless your adversary has incredible luck.
I don't really want a robot wandering around doing laundry. I think what most people want is a box you dump clothes in and they come out folded, an extra machine next to the dryer. That would be a genuine time saver. I hate scaling Mount Foldmore.
You are quite incorrect. I have decades of experience hiring in China, including foreign-educated Chinese, Hong Kong Chinese, domestic educated Chinese, and foreigners. Mostly this was for R&D work, but also operations and other roles.

You know what I found? The value of Chinese domestic university education was a net negative. For instance, in R&D work, I found it to be a solid predictor of futility in the face of unstructured problems. Local employees who had never been to university outperformed those who had - every time.

While I wasn't hiring Tsinghua elites, I did hire from a range of universities across a range of provinces. Many of these graduates would last only days before being fired. I found no more efficient way to screen than to allocate tools, space and a task. Domestic employment law is supportive in this regard.

If I had to generalize, when performing R&D work, the university educated Chinese people were the worst performers, mostly due to no capacity to handle unstructured problems but also due to assumptions of being in a "team" and active seeking bureaucratic excuses for lack of progress. They would freeze up and have no confidence reasoning forward when questioned. The "made it without university" Chinese people were the best performers, and excellent communicators. And the foreigners were generally somewhere in the middle. Overseas educated Chinese were essentially equivalent in this regard.

Other foreign bosses in China have reported to me that they prefer to hire women who have already had children as they are stable employees willing to do what needs to get done, graduates and in particular young men are considered near to useless, with zero loyalty, commitment or motivation.
No it doesn't. Xfce components can be tried with an external Wayland compositor (I've seen mentions of labwc or wayfire) but the work on xfce/xfwm4 compositor hasn't started yet.
During EA (early access), we don't recommend using PPG (Prisma Postgres) for production loads. For now (during EA), there's no ability to scale up the base system config.

However, when we roll out the service in GA, you'll be able to "upgrade" the base system and one of the plan tiers will support autoscaling along the lines of what you've described.

The EA launch is for us to get PPG into the hands of our users and to vehemently listen to requests/requirements/bugs... your request has been noted and thanks for raising it!
I would really appreciate someone documenting exactly which variant of CRC32 is being used here.
Neptune, from AWS is one, right?
Meanwhile, bigendian numbers sort correctly with a byte-wise sort, great for on-disk data structures.
As someone who has been on a journey from a 6 man startup to a larger company going through a merger I’m really feeling the pull of creating/joining a new startup. If nothing else for the joy of being a small team on a mission and work with people who are really invested.
> (controversial) stance on the scientific method.

That stance is well-covered here.[1]

Some of the problems in science come from experiments too close to the noise threshold. This is most of social science and psychology. The hard-line position is Rutherford's "If your experiment needs statistics, you ought to have done a better experiment."
Related to this is Hoyle's "Science is prediction, not explanation."
For phenomena that led to useful engineering, repeatability and predictability are very good.
Otherwise the products won't work.

People tend to forget this, because controversial research topics are often close to the noise threshold. It something turns out to be real, and you can get it to happen further from the threshold, it becomes routine engineering. It's then no longer controversial. Your result gets a few lines in the Handbook of Chemistry and Physics. This sort of science makes the world go.

Philip K. Dick's “Reality is that which, when you stop believing in it, doesn’t go away” remains useful.

Taking this hard-line position is useful, because humans are evolved and wired to see patterns near the noise threshold. This is a useful survival strategy for detecting predators in the brush, even with a high false-alarm rate.
Once past survival level, it's less useful.

[1] https://www.nytimes.com/2018/10/25/magazine/bruno-latour-pos...
A mobile camera that can open doors is quite useful, but that's not on the same level as robot auto worker that could stamp out parts on a press.
They do actually make several claims as to the efficiency of the architecture compared to the Transformer, as you can see by the many graphs throughout the document. Their claim that their architecture is the only one that allows for gradually increasing the number of weights is a prominent one too, though, so I'll explain why I don't find that claim credible.

The idea of gradually increasing the size of a Transformer to save on training costs is not a novel one, and researchers have explored ideas to this effect almost since the Transformer's inception. There are many ways to do it. We can start with a small number of layers, and then add in more initialized to the identity. We can keep the number of layers constant and start with a small, then increase the width throughout training, initializing the extra weights to zero. We can reformulate all weight matrices as LoRAs and start with a tiny rank, then slowly increase the rank until we reach a full-rank equivalent. Or we can use two or three of these strategies and mix them any way we want.

The performance of the resultant model is entirely dependent on what strategies you use, and how you mix them: whether you choose to increase width, depth, or rank all at once, one at a time, or somewhere in-between, and whether you increase those values linearly, exponentially, or by some new function you just thought of. Because there are so many ways to gradually increase the size of a Transformer, when you think of a new way, you've got to pick a strong baseline to compare against.

The authors choose the baseline Net2Net (2015). The paper, written two years before the invention of the Transformer, regrettably does not include pre-trained Transformer results for the authors to compare against. So, the authors train their own Net2Net model, and provide a couple nice graphs where the TokenFormer loss curve is under the Net2Net Transformer's for the entirety of training in Figure 6 and Figure 7. They provide no details of the training setup that produced these graphs: the model size, layer count, and width are all missing, as well as basic hyperparameters like the learning rate and batch size. They train on enwik8 (100MB) and seem to repeat data: near the end the TokenFormer reaches sub-0.5 perplexity levels, an impossible result for English text with reasonable entropy that a language model has never seen before.

Why choose this strange, home-grown baseline, reliant on a method developed in 2015, to compare against? Why not at least use a method tuned specifically for the Transformer (such as [1](https://arxiv.org/abs/2203.06211), [2](https://arxiv.org/abs/2401.02415), [3](https://arxiv.org/abs/2309.03852), to name a few!) If their progressive scaling method is truly better, it would only benefit from comparison against a strong baseline.

The authors' progressive scaling method is an idea that has been explored many times by other ML researchers. Their method in particular is compared against a weak baseline with no concrete details other than the loss graphs. In my humble opinion, it's merely an effort to shoehorn a claim of novelty into a paper that isn't.
Tell me you're under 24 years old without telling me you're under 24 years old.

The US 2000 election was a fiasco of the failures of paper ballots. Officials spent weeks scrutinizing ballots and to this day nobody thinks they got it correct to within the margin of error.

That's when electronic machines came in. They are not necessarily better, but nobody who lived through that nightmare thinks fondly of the clarity of paper ballots.
/lib/js/dq.js is part of their codebase.
"modern websites" means IE11+ for cash, it's a fairly old library.
> I get borderline religious vitriol pushback

I can see that. Because you're posting incoherent scenarios with no evidence.

Meanwhile we have Spot being deployed in Australian mines for surveillance where the environment is constantly changing. Not sure how they would accomplish this if everything they do is CGI.
Isn't Intel still the primary supplier of server CPUs? (as well as windows?)

They're taking a beating, but I feel like every few years we hear an "intel has fallen behind", and then they dust themselves off and are at the top again.

Though Nvidia can charge a huge premium for GPUs, those machines still need a CPU (if I'm wrong, please correct me).

Is anyone building ARM based servers? It looks like Intel has fought back against the Arm on Windows battle, and possibly won with their newest power saving Ultra 2s.

Do they really need to beat Nvidia?
The MDN page you linked to includes a nice selection logger example. It just doesn't work on my Safari (iOS).
Can this work statistically? For a giving number of attempts, you can ger a required number of successes to make sure it's a statistically meaningful result.

In theory, this approach could help address the non-determinism of LLMs.
your mockachino link is broken my friend
Another example of "Everything looks suspicious when you don’t know how anything works."[0]

Mailed ballots are verified against voter registrations and signatures are checked against the signature on file. This woman with a bunch of ballots for former residents of her apartment would gain essentially nothing and open herself to serious criminal penalties if she tried to vote as anyone except herself.

[0] https://www.msnbc.com/opinion/msnbc-opinion/elon-musk-electi...
There's a pretty wide range of possibilities between "videos were all faked because this is the most secure election in history" and "let's not take the video at face value and await further verification because it's election season and there's plenty of bad actors trying to sow distrust in the election system by posting misleading/manipulated videos".
Decay and losses are just two of the many constraints that could be mixed like paints to create new systems.

Limitations, artificial or not, are not always bad. Walls, for example, can be seen as limitation or protection depending on how it's used.
> Aren’t they leaving more size/speed improvements on the table by supporting it?

Only tiny ones, I don't remember the details now, IE11 ended up providing almost all the same APIs.
That is a good idea, but ChatGPT still seems to figure it out.

Prompt

See if you can solve this arithmetic problem:

George picks 33 cows on Tuesday. Then he picks 69 cows on Wednesday. On Thursday, he picks triple the number of cows he did on Wednesday, but eight of them were a bit large than average. How many cows does George have?

---

Answer

Let’s break it down step-by-step:

1. On Tuesday, George picks 33 cows.

2. On Wednesday, he picks 69 cows.

3. On Thursday, he picks triple the number of cows he did on Wednesday. So, 69 * 3 = 207 cows on Thursday.

4. Among the cows he picked on Thursday, 8 were larger than average—but this doesn’t change the total count.

Now, adding it all up:

33 + 69 + 207 = 309

So, George has 309 cows in total.
I do not think you'll get anything close to that with these robots.
> I'd bet good money Tesla has Optimus doing real work in their factories, at scale, long before anyone else.

On what do you base that?

Tesla is so far behind BD, who are behind the Chinese

My money is on the Chinese
For this reason, my browser's Downloads folder is /tmp.
Couldn’t agree more. Professionals use battle proven tools. Amateurs reach for whatever is the most shiny tech currently being pushed by cloud providers or open source advocates.
Bowery, once a leading indoor farming company valued at $2.3B, shuts down
You can modify every item in a query pretty nicely with a one-liner in modern browsers now:

document.querySelectorAll('input[type=checkbox]').forEach((i) => i.checked = false);

This takes advantage of iterable NodeList and iterator helpers.

Many parent queries can be done with element.closest()
I've been in the sleep industry for almost 5 years, and I never knew this. Wow!! Thanks for opening my eyes. I assumed it was some publicly funded body.
If he were designing a bridge, however ...
This statement makes no sense.

We have had robots stamping parts for years. There is no need for a humanoid style configuration. Meanwhile what is needed and far more complex are robots that can interact with unpredictable people in unpredictable environments.

Boston Dynamics has already demonstrated they can do this.
Nvidia makes cpus. A ton of their server grade and network gear has arm cpus. my company almost exclusively buys amd cpus. With apple doing their own arm cpus, its doesn't leave a large market for intel.
That's a very feel-good "why" that doesn't answer on "how", which is 99% of the work. How exactly do you select what to forget?
> The US voting machines are just waiting to be hacked, just a matter of when, not if.

The US election system is very distributed and fragmented - there is virtually no standardization.

Even in the tightest margins for something like President you'd need to have seriously good data to figure out which random municipality voting system(s) you'd need to target to actually affect the outcome.
Yes, but I'm surprised that they attribute "cutting-edge" to Lambda. It's about as old as Docker.
EMA, the European Music Awards?

My local gym has a tier of cable so low that they don't even get CNN. For music, there's K-pop.
What’s the solution to wrangling these data projects?

The author’s experience is not far off from my own.

1. Any solution in place can only be understood by the person who created it

2. ”No, we can’t change that because then we’d have to validate everything from scratch again”

And therefore, as the author says:

> ”we'll continue with the work instead of fixing the critical production error”

I’m honestly not sure how to address it either. With traditional software dev we’d write tests, incorporate those into CI/CD, and start to course correct. We can use sample data to validate the code does what we think it does and that we didn’t break it.

But in these data projects, it’s not only the code that’s changing, but the data is also a moving target. You can write a test with sample data, but tomorrow your data might change because someone in sales added a custom field to the CRM, or IT upgraded the accounting software and all of the unique IDs changed, or someone upgraded their Excel version, or whatever.

And your code that works on the sample data needs to handle all of this, which obviously it can’t. You can try to validate the data somehow, check the schema, check if the number of rows hasn’t doubled or halved, and so forth, and then stop it from importing until you look into it, but also you can’t stop inbound data because an exec has a meeting in a few hours and expects their report to be updated.

I heard something about “data contracts” that’s supposed to address this, but it sounds like the next in a long line of buzz words intended to get management to buy another data product.

Has anyone worked in this kind of project that went well?
> You would think AI/ML could help with fraud detection.

I think that's a very big leap to make, that the ballots are going to where they're going because of fraud. Hanlon's razor applies.

> ballot box stuffing

Ballot-box stuffing happens when more ballots are cast than there are people who voted. This is difficult to do when voting by mail. Indeed, from the article:

> LeVan Hodson told KING 5, "Even if someone gets a second ballot (or more), whether under their name or someone else’s, we’ll only ever count one ballot per registered voter with their matching signature."

When you receive the envelope, you check the signature against what's on file. You also check records to see if the voter had voted elsewhere (such as at an early-voting location). You can check to see if the voter reported not receiving their mail-in ballot. You can do all these checks before opening the envelope. And once you do open the envelope, it's easy to see if multiple ballots had been included in the envelope.
Regardless of your opinion of goodness, not having networking seems to have been the upstream default:

https://news.ycombinator.com/item?id=40326057
There is rqbit written in Rust and does not rely on libtorrent: https://github.com/ikatson/rqbit
It's called a senior moment, and you'll have them too if you've never had one before. In a middle of a conversation, you'll just forget what you were saying because you got distracted.
Middle East & Asia, I'd guess.
They literally just released it in two more countries this week. So no.
> That’s why i prefer to have nice hardware e-stops on prototype vehicles.

Yeah, I kind of wonder if lawsuits/regulation might be the way to get those.

Because there will always be some sort of cost with that kind of thing.

I'm pretty sure a major reason garage doors have limit and occlusion sensors is because of regulation. (and even those suck - it is common for garage doors to incorrectly sense occlusion in bright sunlight)
The implication of the videos was that this was malice (and that generates clicks) yet if you read between the lines, it's simply incompetency - uncalibrated touchscreens.

My point is local jurisdictions do not have the knowledge or resources to properly maintain or deal with electronic voting machines (of which there appears to be no national standard) and maintain integrity. If they can't remember to perform basic maintenance like calibrate the screens, what other steps are missed or ignored?
AWS Neptune is really two different graph DBs, one a property graph model with Cypher queries and one a triple store with SPARQL queries.
I don't think you'll find a wheel speed sensor without a few "outputs incorrect speed" failure modes.
$ or Ctrl-E.
ChatGPT search relies on Bing to generate search results
Now do software in general.
Nice to see some research on human expression, unrelated to technology.

> Their insights are especially valuable for fields like AI, where understanding these nuances could help build technology that better respects cultural differences in expression.

Never mind.
Agree. For some reason many developers thinks that “new” is automatically better than “old”. Which is certifiably crazy.

Old typically means fully bug fixed, with known limits and work arounds, and lots of examples to learn from. And a long track record of solutions using it.

New typically means full of bugs, unknown limits and work arounds, and very few examples to learn from. Plus a high chance of being abandoned and not supported 6 months or a year from now.

Given that, why on earth would you ever choose New over Old? Unless it is for fun personal projects.
Yea I genuinely don't get the criticism, what's supposed to be so off the marks about dg's site? Self advertisement? Isn't that what this is for?
I grew out of it.

I started to really loath the spreadsheet data model. "it's a big bag of cells" was not really doing anything for me. I started wanting better data structures and programing environments to work on that data.

For the data storage and basic calculations on that stored data role, I mainly use a relational database, most of what I wanted in a spreadsheet was row level security, that is, for my rows to stick together(one to many bad sorts I guess), and relational databases provided this in spades.
Kinda related, hopefully someone here in comments can help: what’s your favorite precise nn search that works on arm Macs for in memory dataset; 100k times / 300 float32 dims per item ? Ideally supporting cosine similarity

Faiss seems big to get going, tried n2 but doesn’t seem to want to install via pip.. if anyone has a go-to I’d be grateful. Thanks.
Which do you suppose is more likely...

A) There was a voting machine that had a miscalibrated touchscreen that will be corrected before election day.

B) An evil democrat conspiracy is going to steal the election in Kentucky
Yeah not my domain so wouldn't really know. For FEniCS I know Gmsh[1] was used. There's some work[2][3] been done to integrate FEniCS with FreeCAD. It seems FreeCAD also supports[4] other FEM solvers.

But, I guess you get what you pay for in this space still.

[1]: https://gmsh.info/

[2]: https://github.com/qingfengxia/Cfd

[3]: https://github.com/qingfengxia/FenicsSolver

[3]: https://wiki.freecad.org/FEM_Solver
What media do you consume to believe nonsense like this?
Or Indonesia
They built a large codebase on a language that doesn't let you control memory, because that makes you "more productive". So just having Rails allocate a per-request arena that is asynchronously freed which would force the programmer not to have any objects that outlive the request, or just pre-allocating memory for a fixed amount of request handling per server instance, or whatever allocation behavior you want to do that is generally possible in C/C++/Zig/Rust/Odin/etc, requires hacking on the language itself. Which means your changes have to go through the Ruby team first. Any additional changes would also need to go through them, which increases the cost of change. Then there is a permanent layer of indirection between your GC callbacks and the semantics of what those callbacks do. Instead of just writing out the custom allocators you want, because that's impossible. How depressing.
Ask HN: Are There Any Fully-Documented Computers
I am writing an operating system as a side project. I am still in the design phase of the project, and I’ve been brushing up on my low-level programming skills. Recently there was a discussion here about the Asahi Linux team’s efforts reverse-engineering ARM Macs, and it had me thinking: are there any fully-documented modern computers? I know that RISC-V and POWER are open source. However, there are still other parts of a computer system to consider, such as boot firmware, buses, disk controllers, GPUs, networking devices, USB, etc. It would be cool to target fully-documented hardware for my OS project, but I don’t know if there are any complete stacks of fully-documented hardware.
Times New Roman you mean, surely

Can't improperly reference that legendary script.
I remember my attempts to use numbers on a mac to pull up some spreadsheets.

It was SO. IMPOSSIBLY. SLOW.

Maybe it's different now with M4 macs, but I still remember a friend telling me that response times above 1/10th of a second were not interactive anymore. Made total sense after that.
I find it hard to take anyone seriously who makes life harder for themselves for no good reason . Different strokes.
I worked in a place where excel was used for ad-hoc calculations. We became a Google shop.

Sheets was a piece of junk compared to excel. Anyone who did any real work rather than just looking at a spreadsheet or using a template got Excel back in about a week.
Ironically America's fragmentary and incoherent electoral system makes it extremely hard to steal an election there.
Large screen phone + landscape mode if needed usually works for me.