skysight-inc/HackerNews huggingface dataset:
> However, everybody on this site has decided that they're useless because of a single, incorrectly read, out-of-context tweet from 4 months ago.

Actually, they lost any credibility to me when they wanted to appoint Robert Mugabe as an ambassador years ago.

In more recent times, their position on the use of masks was criticized as confusing[1].

And let's not forget their equally confusing tweet on immunity to SARS-CoV-2 from a week ago or so (which was ultimately retracted). So not just one from 4 months ago.

Of course it's a big organization, so caveats apply. Nevertheless, they didn't do the best job at communication.

[1] https://blogs.bmj.com/bmj/2020/03/11/whos-confusing-guidance...
> Fresh hell, they all seem to be build dependencies of each other. ‘sed’ is its own build dependency.

Well, they are the "core" utilities after all. This becomes less of an issue the further out in the ecosystem you get.

> at the exact versions and in the exact locations on the filesystem that the build tooling is willing to look.

This isn't strictly true.. you just need _compatible_ versions to be available, and most build tools and even the compiler itself will check several commonly used locations for code.

There are a few corner cases, but by and large, this isn't as big a problem as it might be for other languages that make writing incompatible interfaces orders of magnitude easier than with C.

> Specifically, hasten the day where my entire application dependency tree doesn’t bottom out in some Autotools, CMake, shell script, project.

Each those solve the same problem at different levels. Perhaps this is because there is no _one true_ way to replace them, and the advantage is that each project uses the tool most suited to their case.

Perhaps the built-in tools with these "modern" languages are a good general tool for the majority of developers, perhaps they aren't. If they aren't, then now you have the same problem all over again in a new ecosystem.
(and Why) to Log Your Entire Bash History
Working on an operating system that uses some of these modern / safer alternatives, the concerns around bootstrapping, lack of spec, lack of formal memory model, long compile times, and larger output binaries are valid. They are real and present challenges for us, that we choose to work against. It is currently extremely difficult to produce a binary of the size of bsd cat using these technologies, and very large amounts of work are needed to close that gap, if it even can be.

In a new system you may not need cat though, but if you're a unix system with a heavy shell and textual basis, you do need lightweight versions of these things - light to build, light to run, and well integrated into the environment.

What's the path out for unix systems? I have no idea, but at least as of today I have not seen a modern safe language that is ready to replace unix use cases. Maybe zig? It's hello world is at least under 10kb.
when? i have a 4k on 1080ti and its money
This is a weird interpretation of that sentence. There are lots of fields where human-level performance has been achieved. See Go, for example.
A GC only protects you from memory errors, not threading errors.

In general, Rust allows you to write software that doesn't break silently. That's a quite good value proposition for large scale software, where other languages often require programers to be super careful with refactorings, while in Rust you can really refactor all the things.

The reason people are afraid to do large refactorings in say C++ is often "security-related": fear of introducing segfaults, memory errors, undefined behavior, threading errors, etc. but one can also see these fears as "productivity-related" (hours and hours of debugging), or through many other lenses (shipping bugs to users, having a segfault in the middle of a demo that costs you a client, introducing a segfault one day before the release of your game, etc.).

In general, every programmer wants to have a certain degree of security that their software "works" for some definition of "works". For some this security might be actual network security, but for others it might mean that they don't want their data-science app that has been running for a week burning thousands of dollars to crash due to a segfault while writing the results.
Maybe someone who knows a bunch about this stuff can enlighten me. I was kind of under the impression that a large solar flare would damage _all sorts_ of electronic equipment, by inducing currents wires all over the place.

- If we had extra transformers on hand, how would you protect them from also being damaged?

- If a solar flare is powerful enough to damage these transformers, would it also have damaged a large proportion of devices that use power? I.e. even if you could get the electric grid working, would there be working systems of any complexity to use the power?
My main advice

1. Start easy.

It's tempting to grab a textbook or video series because it gets good reviews on Amazon or likes on YouTube. That's all good and fine, but it's more important to get a good introduction to the topic. The key here is to get a rhythm going and it's very easy to disrupt your study rhythm if you start too hard. So, much like working out, start out easy, with something you can easily grasp. Moreover, do less than you can. As they say in weightlifting, leave a couple of reps in the tank. Don't go all out as you're running a marathon, not a sprint.

2. Be consistent

The key to finishing something is to do be consistent. Intense 5-day seminars can work, but you're going to need a very good teacher and have a lot of motivation to get through it. For self-study, consistency is much more important. I would recommend somewhere between 4-10 hours a week. Anything more than that is going to burn you out and anything less and you'll forget previous lessons. 1 hour a day for me on a given subject and taking weekends off works for me. The key is to build up momentum and keep it going.

3. Power through by stepping back.

There will be sections where you're going to feel lost. You're going to feel frustrated or not know what the text or video is talking about. This is where you need to "deload" a bit. Take a week to review all the material you've learned so far and redo some of the exercises. Everyone has these and the key is to not lose momentum. Many a study has stopped due to one obstacle. The key is to step back for a bit and try again without losing the momentum you've built.

4. Remove distractions.

Not everyone has the discipline to follow these, and most of the time your brain will try very hard to distract you when you encounter a hard problem. The key is to minimize all your distractions during your study time. This means no email, social media, walks to the fridge or anything else. You start and don't stop until you've finished your hour (or 30 minutes or whatever you committed to). It's okay if you only got through 2 pages during that time as long as you didn't get distracted. Give yourself permission to stall a bit. And if this happens a few times in a row, step back and try again (see 3)

5. Get a buddy

The best way to study is with someone or some group that's studying the same thing. There are lots of forums for all of those topics that you can engage in to answer some of your questions and possibly find someone to study with. Getting some accountability is an excellent way to keep up your momentum.
The OT link mentions that:

The code is available, and will be licensed under a Free license when I'm ready.

So he may or may not relicense it to a free license...
See also https://www.semanticscholar.org/paper/A-Concurrent-Bidirecti.... I used the insert algorithm from this paper in my evaluation of linear probing algorithms, where it outperformed Robin Hood: https://github.com/senderista/hashtable-benchmarks.
> Are you forgetting the time they sent local filesystem searches to some spyware company?

That was not a remote hole.

> OSX is a toxic, vendor-supplied-malware infested cesspit that I've never used

Sure, but is any of the vendor-supplied malware in that cesspit a remote hole?

I'm happy to have broad, open-ended arguments about who sucks more in new and innovative ways, but let's finish the argument we're already having first. Is OpenBSD meaningfully more secure than other operating systems on the axis they are choosing to advertise, namely "remote holes in the default install," than other OSes?

In particular, whatever you believe about deliberate backdoors, toxic cesspits, being actively opposed to security, etc., none of that is something the choice of programming language is in any way relevant to. If Theo's argument were "We don't need Rust because we are the only operating system that isn't actively opposed to security, so everyone else has lost the game already," we'd be having a very different conversation. But it's not and we aren't.
The author is from the 1990s era of Linux / FOSS, before kindness was part of the culture, when the culture had a tough competitive streak where mistakes and humility were seen
as signs of weakness and disrespected. High expectations wee tightly bound with low levels of patience. And many people were scared off from contributing.
Solar storm of 1859

https://en.wikipedia.org/wiki/Solar_storm_of_1859
Very interesting project, thanks for sharing!

The "open positions" page might interest some people here. They have two 2+ years postdoc positions open with no teaching duties at Virginia Tech.

http://popcornlinux.org/index.php/positions
The reason you don't have crazy nonsense like this is that it would be a field-day for political persecution. Prefect for corruption.

A politician with clout doesn't like what some CEO said, or that he bankrolled your opponent?

Destroy their business by setting the prosecutors on them, jail their CEO, destroy their business by seizing the cashflow, and then 2 years down the line, charges dropped. Whoops.
I love this, but it suffers from an issue I've observed in my own attempts to make mouse-based drawing tools in the browser with JavaScript. If you move your mouse too quickly, the low polling rate of events becomes evident because rather than showing a smooth curve, you see straight lines that are drawn between the two points that were captured for each event.

This is my white whale.

I don't currently have the math chops to fix this in my own implementations, but there are others who have succeeded where I have failed. For example, the web client/controller thingy for the game Drawful 2 by Jackbox has addressed this. Since you can't increase the polling rate in the browser and you can't arbitrarily read the mouse position during things like requestAnimationFrame, you're forced to interpolate the movement of the mouse given the past few events. They're using curves in Drawful 2 instead of straight bitmap-style canvas drawing like in the first Drawful.

But beware, this has a downside. It's very easy to incorrectly interpolate the movement and exaggerate the curve, making it curvier than the actual movement of the mouse.

I guess the web browser just wasn't designed with precision input capture in mind. But that doesn't mean we can't still aim for improvement. For a game like Drawful, more options are probably overkill. (They don't allow you to erase by design.) But for an art tool like this, it might be worth adding an option for input smoothing along with knobs to tweak to adjust the smoothing amount. Or not. I certainly can't fault you for not implementing such a feature given that I can't seem to get it to work.
Python homemade geoip tool for IP information
Much of theoretical computer science uses categorical methods, for example, as semantics for type theory. In that field, such techniques are often more natural than set-theoretic ones due to issues of computability, decidability, etc. So at the very least, much of that research as originally written would be inaccessible to a non category theorist. Whether that field counts as mathematics and if it does whether it is worth missing out on depends on taste of course, but an example would be 'homotopy type theory' https://homotopytypetheory.org
Let's not take the conversation down this direction please.
On my computer, there's the standard libraries and frameworks that provide things like GUI widgets, cryptography routines, and access to various user databases.
The cloud is the opposite of recession proof. Why do you use the cloud in the first place? Flexibility, scale, ease of operations. What are you gonna do with your servers during a recession, put them on Craigslist? Are you gonna put your entire datacenter on there too?

The same mechanic that makes the cloud attractive in the first place is what will bring the hammer down in a serious recession. Companies will turn every stone to use less capacity and save money, and they will easily be able to do it.
You can certainly do this using machine vision cameras. Either USB3, Gig Ethernet, or CSI interface (16cm max run length I believe). I forget how best to attach two displays to the Xavier but that’s seems doable.

I got my cameras from e-consystems and they’ve got some USB3 cameras that could do it. At least I’m pretty sure. My USB3 cameras just showed up and I haven’t tried them yet.
Do you really enjoy watching YouTube, or is it just easy to fire up their home page and click on recommended videos with promising titles that ultimately leave you unfulfilled, lonely and disillusioned?

Are you wondering how to break this cycle of content consumption? Do you need a break from the hedonistic treadmill of social media?
The biggest problem with the apps is most food isn't really that good delivered.

There's a reason pizza is #1 in delivery.

Once the cheese has cooled down it tastes better.
> Building Docker containers for ARM devices is a pain in the ass.

It's not so bad, you just need a beefy ARM machine to build the containers in CI. It would be silly to build a Docker container on the Jetson itself. You would never use an embedded device for compiles and builds, why would you build Docker containers on one?
Why is it a pain to build Docker container for the ARM architecture? Just curious, haven't had to do it myself.
A Prophet of Scientific Rigor–and a Covid Contrarian
These documents all look very smart, but how does anyone have any idea whether the numbers in them are even close to realistic? I can make up some cute hockey stick numbers for any of my businesses, but why should anyone trust them? Particularly for businesses that haven't even launched yet and therefore have literally zero hard data on whether customers will actually pay them money or how much or for how long. How many startups in that position, with no financial data and no evidence of product-market fit, can credibly predict even a year ahead that they won't pivot to some completely different plan, never mind 3 or 5 years out?

When I started my first B2C, a long time ago now, it was actually the bank where we opened our business account who asked these kinds of questions. We sat down, put our best guesses at plausible numbers into a spreadsheet for things like acquisitions and churn, worked out the money that would result.

Barely any of the key assumptions we made were within an order of magnitude of reality, and they were all in the wrong direction. For example, we have far higher churn than any example startup business plan I have ever seen just from card charges that fail with no obvious explanation each month where we don't subsequently recover and continue that subscription. That problem remains one of our biggest pain points to this day, and that effect alone has turned many an otherwise profitable month negative and reduced that business to a fraction of the size it would otherwise have been by now if everything else was held constant. No-one here saw that coming. No example plans or startup guides or financial advisors we consulted even mentioned the possibility, never mind giving any concrete figures for what we might expect.
This is a review paper. It's long. Past the first sentence I find it readable and well organized. It mentions some of the work on interpretability I'd expect to see, Finale-Velez, Rudin, Wallach, and LIME, but does not appear to mention Shapley. The bottom line conclusion is "In the end, the important thing is to explain the right thing to the right person in the right way at the right time." That's both an obvious truth and a differentiating mindset in research-first space. It's worth a skim.
It'd be a headache at first for logins and losing things in my Drive, but I would honestly feel a whole lot more freed up without it as I'm not v good at maintaining all my accounts, history, files, etc.
Even if you are self-studying, you can and should occasionally go talk to someone who knows the subject well to help you with the question. If you don't know anyone, post the question online.
I've been using Backblaze and find it intolerably slow.
There are a whole love of reservations on instances and lock-in to databases, serverless, networking infrastructure, etc. Its hard to leave.
I wouldn't know as I never lost it, but this is one way I heard of - a proven history of paying for the service.
I'm surprised there is no mention of capsules and capsule-routing algorithms.

Capsules are groups of neurons that represent discrete entities in different contexts. For example, a 4x4 pose matrix is a capsule representing a particular object in different orientations seen from different viewpoints. Similarly, a subword embedding can be seen as a capsule with vector shape representing a particular subword in different natural language contexts. More generally, a capsule can have any shape, but it always represents only one entity in some context.

In certain new capsule-routing algorithms -- e.g., EM routing[a], Heinsen routing[b], dynamic routing[c], to name a few off the top of my head[d] -- each capsule can activate or not depending on whether the entity it represents is detected or not in the context of input data.

Models using these algorithms therefore make it possible for human beings to interpret model behavior in terms of capsule activations -- e.g., "the final layer predicts label 2 because capsules 7, 23, and 41 activated the most in the last hidden routing layer."

While these new routing algorithms are not yet widely used, in my humble opinion they present a promising avenue of research for building models that are explainable and/or enable assignment of causality at high levels of function composition.

--

[a] https://research.google/pubs/pub46653/

[b] https://arxiv.org/abs/1911.00792

[c] https://arxiv.org/abs/1710.09829

[d] If you're aware of other routing algorithms that can similarly activate/deactivate capsules, please post a link to the paper or code here.
It's not about the access, it's about that you can transmit over the phone network. If you can't transmit it it doesn't matter what client device you have.
It's hot right now. They're in the "ramping up" phase of popularity. Mainstream vendors are starting to take it seriously.
Haha, Rust go brrr
A Black Swan is probably more about the POV of an actor as opposed to somebody who knows this, then it's not a black swan.
Apple spends more than $30M/mo. on AWS. [1]

Comcast, I was told, spends over $1B/year on AWS but I cannot find any public references to back it up.

[1] https://www.cnbc.com/2019/04/22/apple-spends-more-than-30-mi...
Porn, Zen, and .vimrc
In the US, clinical medicine and law firms use it because it has an unusual legal status: it’s considered secure and positively delivered if some device at the other end acknowledges it.

In Japan many businesses are still wedded to a fax. It’s much easier to scribble a take out order on a piece of paper.
In terms of using it as an ARMv8 desktop workstation (with decent CPU performance, real SATA / Ethernet / PCI-e connectors) - some other contenders include the MACCHIATObin (quad A72) and Honeycomb LX2K (16-core A72, 750USD) from Solid-Run.
Thanks for putting so much work into comparing all these models! I'm the author of #3, and a founder of a financial modeling software company (the latter not reviewed here)

One thing I'd add for anyone comparing these models for their own use: Make sure the model you're going to use covers the authors #1-5 criteria for the parts you need. More features isn't always better. For example, if you run a marketing driven SaaS company, it doesn't matter if the model in question can't handle complex enterprise sales.

I have a big update coming to the model this coming week. All of those changes have been made in the actual model template already if were planning to take a look - it's just the update to the documentation that's still missing.
Yeah, not mentioned in my comment, but I routinely use Linux on the command line, and it's great. It's just when I try to use a desktop environment that it breaks down for me.
Heads Up: Entropy Overhaul
The supply chain goes like this... plants -> animal -> human consumption. Yes you can rewrite overnight to plants -> humans.

But on this topic I'm better off talking to the wall of bricks next to me than the HN audience
The Ubers and Lyft's save by committing to a certain level of spend. They have paid -- might as well use the resources, anyways -- unless they've since negotiated with Amazon.
This is why some countries do income-based fines. Get a speeding ticket in some Scandinavian countries and you may be on the hook for six figures if you’re rich.
Thanks for sharing jasunflower! I agree that some environment decisions, in particular in regards to sleep, are so important that one can even consider them "dependencies" for productive work.

This guide was initially meant to be referred to in those moments in which we are actively trying to get something done. I'll include soon a page about environment decisions -- let me know if you have any additional recommendations.
A common parts library supported by multiple EDAs would be nice indeed. But its pretty hard to pull of, since the library organization and styles are quite different between these.

I mean: Importing / exporting the geometry data of footprints and symbols shouldn't be too hard. But one also needs to find a common set of categories, tags, relations between the parts, etc. Otherwise one will end up with a huge library which is impossible to navigate.

Also I would be afraid to just create yet another format which will lead to even more fragmentation.
For those interested in this area for PyTorch models, take a look at Captum (https://captum.ai/). Still a lot of work to do, but we’ve provided a number of algorithms described in this field guide in the library. Always looking for collaborators and contribution of others.

Disclosure: I support the team that developed Captum.