skysight-inc/HackerNews huggingface dataset:
Well, no. rm -rf / is a completely different beast. It is documented and expected for starters.

They may have valid reasons to do that, even if not common.
Research code is generally an abomination, scraped together by MS/PhD students who may never have had any industry exposure to best practices, norms, testing, etc. There may also be the fear of releasing buggy code, which if/when discovered, will discredit the paper. Far safer to just not release the code, since it isn't mandated (which should absolutely 100% change)

Source: am former producer/publisher of abomination research code.
Spacemacs is great for creating a more complete, out-of-box experience. Only change I typically make is to use holy-mode for great righteousness.
I’m using 1Password 7 for Mac with 6 vaults. Seems to hover around 300Mb.

Spark is a native app right? If it’s not they definitely nailed the look and feel of a native app.
Sure, but regardless of people doing dumb things, it's still worth asking "why did docker delete non-orphaned named volumes?" -- though you could also question whether someone was actually mistaken about them not being "orphaned" - you could probably arrange an unfortunate timing collision between someone running prune and a container being respawned.
Bought the IKEA charger because it was so slick and compact. Very happy with both charger and batteries, can recommend. Crazy low price as well, but to me that wasn't a factor.

Charger review here: https://lygte-info.dk/review/Review%20Charger%20Ikea%20Ladda...
Excellent idea. We've though about Machine learning transformer including NLP . This NLG is something which would definitively nice to have. Please create an issue and we will prioritize it.
It doesn't let you write generic components that you can use across all fx's, it just lets you use the same limited state API to set state in different fx's. Most of the effort with porting code amongst different fx's is refitting your logic into their different component models. So instead of using the well-tested, documented, native reactive model in each FX, yo'd be limiting yourself into using a limited, non-standard state wrapper API. I don't see any value in this abstraction myself. Forcing myself to use it would generate more abstraction/boilerplate in refactoring out custom logic so it's not tied to any FX.

If you want to write code that targets multiple JS fx's you're better off with a well thought out proper solution that lets you develop components that you can use in all major components like https://stenciljs.com or alt solution that lets you target Web Components.
No, interpreting "continual" the way you did would mean I should believe that we can't conclude our friends to be intelligent either (I don't believe that). Maybe I should've said "prolonged" rather than "continual".

Let me elaborate on my previous point with an example. If you look at the recent works in machine translation, you can see that the commonly used evaluation metric of BLEU is being improved upon at least every few months. What I argue is that it's stupid to look at this trend and conclude that soon we will reach human performance in machine translation. Even when comparing against the translation quality of humans (judged again by BLEU on a fixed evaluation set) and showing that we can achieve higher BLEU than humans is not enough evidence. Because you also have Google Translate (let's say it represents the state-of-the-art), and you can easily get it to make mistakes that humans would never do. I consider our prolonged interaction with Google Translate to be a narrow Turing test that we continually apply to it. A major issue in research is that, at least in supervised learning, we're evaluating on datasets that are not different enough from the training sets.

Another subtle point is that we have strong priors about the intelligence of biological beings. I don't feel the need to Turing test every single human I meet to determine whether they are intelligent, it's a safe bet at this point to just assume that they are. The output of a machine learning algorithm, on the other hand, is wildly unstable with respect to its input, and we have no solid evidence to assume that it exhibits consistent intelligent behavior and often it is easy to show that it doesn't.

I don't believe that research in AI is worthless, but I think it's not wise to keep digging in the same direction that we've been moving in for the past few years. With deep learning, while accuracies and metrics are pushed further than before, I don't think we're significantly closer to general, human-like AI. In fact, I personally consider only AlphaZero to be an unambiguous win for this era of AI research, and it's not even clear whether it should be called AI or not.
The interesting thing about DropBox was that their "MVP" was a video, and then actually building the first viable product took 4 engineers 1.5 years.

I would say that there aren't hard & fast rules to any of this. It took Google 2 years to build their MVP, and they also had multiple grad students working on it. The only "rule" to startups is that you have to survive long enough to get to the point where lots of people want what you've built.

But there is a significant advantage to speed. Letting an MVP drag on for more than a couple weeks introduces a lot of different failure modes. You get demoralized and give up. You get too attached and fail to pivot when the initial version doesn't work. You build something too complex for initial users to understand. Technology changes and makes all your past decisions obsolete. The market changes and the problem you solved is no longer relevant. You run out of money.
Basically when you see a RNN in industry, chances are somebody has made a huge and expensive mistake. And quite likely the person behind it thinks that they've applied cutting edge research to a real world problem (when they have done neither).
I wonder if this is actually the other way, that is, so many words and names of Greek origin are associated with ancient philosophy and classical wonders (Archimedes, Pythagoras, Parthenon, etc.) that these words end up sounding "great".
When I was in high school we experimented with block scheduling, which was a fad at the time. We only had three classes a day, for two hours each, and then we changed even or odd each day.

The science classes loved it, because we could do longer more involved experiments that would take more than the usual 50 minutes, and the students liked it because it meant for example only doing math homework every other night.

It was extra awesome for me in senior year. I had a normal second period class, but my 4th period was teaching at the local elementary school and my 6th period was Academic decathlon, which became "at home study hall" in the Spring after we were eliminated from the competition. So in spring of my senior year, I'd go to school for two hours, hang out at the elementary school for two hours teaching kids, which was super fun and didn't have any homework or stress, and then go home at lunch time and be done. On "even" weeks, it meant that I did that three times in a week, and was off by noon on Fridays. It was a pretty sweet deal.

I also like the block schedule because I liked only dealing with half as many classes for twice as long. I felt the same in college -- I loved doing summer school because we'd go twice as long each day for only 8 weeks instead of 16.
The thing about the moon landing is that there was a rival superpower at rough technological parity, and the technology in question could be used to lob nuclear weapons at one another with great accuracy.

No nukes, no ICBMs, no Apollo.
Wow. This article you linked seems worthy of its own HN submission. Thanks for sharing it!
I've never been willing to consider docker volumes persistent. In the big picture, a requirement of "posix filesystem semantics" and "persistent" is a pretty inconvenient and/or expensive requirement.
Goats used to reduce fire risk by eating fuel for wildfires
I'm confident that everyone's IRA would be better kept in a low-cost mutual fund that tracks a popular index.
I’ve been doing research in DL field for the last 6 years (just presented my last paper at IJCNN last week), and I can say with confidence we have no clue how to get to AGI. We don’t even know how DL works on the fundamental level. More importantly, we don’t know how the brain works. So I agree with pron that your “relatively soon” is just as likely to be 10 as 100 years from now.
I've done several huge rewrites over my sordid career, and a strategy that works well is to abstract your bad data design behind a good one. This involves some kind of transformer layer between your bad data design spec and your abstracted better one. There's of course performance hits of some kind no matter what, but the hope is that they're worth the benefits of the cleaner code/architecture that the better data design spec affords. It's difficult I'll grant, much harder than abstracting simply bad code, but it's possible, and also makes it that much easier to replace the actual data design at some point in the future, and remove the transformer layer. Hope that makes sense!
> I've been using Slack on the desktop daily since the alpha version. I've never found it to have UI lag.

Try telegram on desktop and compare the UI performance. Slack definitely has UI lag. Not nearly as bad as Teams though.
There are multiple launch systems that will have the payload capacity to go straight to the moon within the next few years. Why not just use those?

No one will care about a Lunar space station, it's not enough of a step forward to capture the public's attention. It's sad that NASA's 'futuristic' new proposal is to do half of what we were able to do 50 years ago. People will quickly vote to cut funding for it, and maybe they should.
Each part of a script can be replaced with actual code over time without committing to trying to automate the entire thing. I think it’s a pretty nifty idea that helps avoid putting the whole thing off for later.
Whilst I'm not a fan of the name, I'm more discouraged that it needs to specify a fx at all which suggests that the library hasn't come up with a generic solution for all fx's but rather a library of quirks to abstract over a limited set of fx's.

Since it only has hard-coded support for 3 frameworks, there's no benefit to using magic strings, it would be preferable to use a typed API like:

XSM.useReact({ ... })

Where you can provide fx-specific options for each fx it supports. It also hides all the config options available behind a generic API which you have to dive into the impl [1] to see what options are available and what args each config option supports. Everyone would be far better off bringing all config options to the API Surface area, you could easily type-check all options in TypeScript which ensures correct usage of the API and let you know of any additions/removal or breaking changes.

[1] https://github.com/peterluhub/xsm/blob/master/xsm.js
Well, the super rich getting richer is the status quo, so I kind of feel like nothing much changes if this never happens. Now, riding that happy PR wave and failing to deliver would be lame, but perhaps they really believe this. I think it will depend entirely on how much really gets open sourced in the end. I want to believe they’ll really do it.
Ask HN: Have you ever created a physical product for sale?
If so, what was it? It doesn't have to be technology-related e.g. Printed items (book, poster, notebook). It could be a mug, t-shirt, tote bag. Or maybe it was some mechanical or electronic device.

Most of us work with digital products, so what was the experience of creating a physical product like in contrast?
I didn’t compare OpenAI to the Manhattan Project. I was pointing out that if a small number of people discover a plausible conceptual pathway to AGI, a similar project will happen.
The next sentence of your last paragraph says:

> Sellers are able to choose whether to share identical inventory or not.

That seems to indicate physical commingling. IIRC, avoiding commingling has an additional cost to the seller.
It's short for set configuration.

Maybe that just escaped you from some reason, but I would think it's perfectly understandable for just about anyone.

Curious if anyone else here had a hard time parsing it...
> "points on the screen" is the only reason we have to believe in particles

There are also the cloud chamber paths. But more generally, I would say most people's experiences correspond closer to stuff having well-defined localization which is more in the ballpark of particles than waves. Waves spread.

Also, this is not a matter of what is true, but rather what is plausible. A natural conclusion which works would be a good candidate to continue to pursue. My opposition to the paper cited was simply that it wants to argue that everything is a wave, something which seems to be an assumption not supported by evidence. That reality can be described that way is one thing, and a fine thing if it leads to interesting notions, but to say it must be a certain way is a completely different kind of claim.

> That doesn't seem reasonable to me. Particles exert forces on each other via gravity and electromagentism. I don't see how you're going to get a stable static vacuum configuration out of that without special pleading.

Particles in BM do not exert forces on each other. The wave function moves the particles about directly by specifying the velocity, not the acceleration. The forces are all in the wave function evolution (gravity is a bit of a mystery, but what else is new). Keep in mind there is a single wave function that represents the universe. It has a complicated dynamics which is where the forces are at work.

Maybe the short paper Are All Particles Identical [0] might help. It describes a version of BM in which all particles are identical and electron, quark, etc., are different states of a single particle type with the mass being incorporated into the wave function itself. Particles in that theory really are just points with nothing else intrinsic about them.

So the typical vacuum state might be just a small part of the story with a non-interacting sector. I don't know, but it certainly does not seem to rule out particles to me as being impossible.

> Just as if you want a completely accurate answer about what happens when you drop an apple you have to solve Einstein's field equations.

Yes, but if you present me with the solved system, I understand immediately what it is describing: a path through space-time of the apple. In a solved version is easy to see the correspondence.

This is not true of quantum wave stuff. It is true of BM. Relativity might mess with our intuition and be difficult to compute, but it is easy to understand how the elements correspond to our experience. That's the crucial difference.

Now, there is no reason to believe that the fundamental theory has to have that property. It might not. But it is extremely important than to be very clear about how the elements of the theory, the stuff it cares about saying what it state is, does correspond to our experience.

[0]: https://arxiv.org/pdf/quant-ph/0405039.pdf
i felt that way about the massachusetts-based lighthouse bank[0] founded in 2000 and unaffiliated with the current santa cruz-based lighthouse bank. high-interest checking, no-fee, internet-only bank. it was amazing until it got merged into brookline bank and essentially dissolved.

[0] https://www.bloomberg.com/research/stocks/private/snapshot.a...
there's a new trick/scam on amazon I am not sure if anyone else has noticed yet

seems designed to trick not only buyers but also sites like fakespot

a vendor lists an item for awhile, something cheap and reliable enough to gather plenty of legit 5-star reviews

then they leave the listing and ASIN but delete and change out the photos and the title/text with another item, not even similar item in some cases

so the ratings/reviews remain but the new product is given all their weight instead

cannot believe amazon does not detect and stop this
My guess is that tutorials and whatnot don't include, upfront or at all, a section on when to actually use redux.

It's really easy to get the feeling EVERYTHING needs to go into global state management, from variables used once in one component on one page, down to loop counters.

The simplistic contrived examples exacerbate this. A list of todos doesn't really need to be in global state. An auth system would though. However, all the examples only show things like list views or a detail view, that don't need to be globally available.
On BitMEX you can make leveraged short/long bitcoin trades without the downside of owing more than you put in. Max you can lose is 100%. It’s powered by a purpose-built stoploss liquidation engine
Restaurants do this. They are required to pay minimum wage if the $2.15/hr + tips doesn't average out to be at least minimum wage. As a restaurant owner, you can add lots of hours at $2.15/hr before you have to pay anything extra out of pocket.

That's how they are able to force waitstaff / bartenders to do setup / cleanup for $2.15/hr.
Americans tend to relocate very often, relatively speaking to the rest of the world, IIRC.

I think there may be some inherent sample biasing going on. I’m here because some European dude a few generations ago decided to move halfway around the world for a chance at a different opportunity, and I’d bet that influenced the risk tolerance of his kids as well.
> that's a pretty interesting datasheet! If you assume a constant-power load like a low-dropout boost regulator, it looks like it depends a lot on the current draw.

One of my unrealized project ideas was to create a battery life estimation calculator, something you could feed in battery configuration, some power supply details (efficiency, cutoff), and consumption figures and get an estimate of battery life. The log-log charts are not all that easy to read and have only limited number of curves available.
>US SEC has accredited investor requirements specifically to keep people from being fooled into making "dumb" investments

What stops me from liquidating my 401k and investing all of my money into a company that misses their earning goals this week? Where does the US SEC come into play here?
The Conceit of Certainty
solipsistic - adjective. of or characterized by solipsism, or the theory that only the self exists, or can be proved to exist

-- https://www.dictionary.com/browse/solipsistic

... in case anyone else had to Google that
ML has been used to automatically translate long-lost languages
It's Not OpenStack or Kubernetes, It's OpenStack and Kubernetes
I've set up Windows 10 computers multiple times spanning the past two years or so and making a local account was never hard or complicated. With the ethernet plugged in each time. Strange that what the article shows never happened to me.
Why Is Hacker News Called *Hacker* News?
You see, I'm not an old timer, but still old enough... like I was born in the late 1980s.

Why is this called Hackernews? Where's the "hacker" or "hack" here? Honest question!

Because I only read "X invested in Y" or "Y funder Z". Lot's of startup culture, sprinkled with some IT.

Where is the hack? Where are the hackers? (I know, but I won't tell you ^^)
That phrasing is part of the problem, not the solution. You're conflating the idea of a manufacturer (Proctor & Gamble in this case) with a reseller. Amazon tells you both, but since the retail products are (should be) identical, neither they nor you really care whether or not this particular box came from "Joe's Nutrition" or "Sally's Supplements", and worrying about that distinction is like arguing against the fungibility of money (did that dollar bill in your pocket, which you got from an ATM, "come from" your job or your side gig?).

It's not the comingling that is the root cause here, it's the fraud. It doesn't matter whether or not Amazon buys their pills from Joe or Sally, what we care about is that they're not selling fake pills. Focusing on comingling seems to be missing the point. We have even less ability than Amazon to detect the fact that Joe is selling fake pills, so they'd still make it into people's mailboxes.
I've bought supplements from Amazon on a regular interval without issue. Maybe I just jynx'd myself. If I ever received fake supplements, I would treat that as being poisoned and report it to the CDC, FDA, FBI and local news.

My only bad experiences with Amazon to date was with NVidia video cards. Twice. Shame on me for falling for it twice. Each time they swapped out the cards with slower clock speed video cards. They also censored my feedback. Apparently nobody else checks their cards clock speed once installed?
Oh, I'm well aware of the hype around AGI. My personal view is that AGI is kind of an asymptotic goal, something we'll get kind of close to but never actually reach. Nevertheless, I would like to work on more pragmatic goals, like improving the current state-of-the-art language models and text generation networks. I'm actually starting by reimplementing Seq2Seq as described by Quoc Le et al.[1] for text summarization[2] (this code is extremely messy but it'll get better soon). It's been interesting to learn about word embeddings, RNNs and LSTMs, and data processing within the field of Natural Language Processing. Any tips on how to get up to speed within this field would be helpful, as I'm trying to get into research labs doing similar work at my university.

[1]: https://papers.nips.cc/paper/5346-sequence-to-sequence-learn...
[2]: https://github.com/applecrazy/reportik/
There are plenty of valid reasons to be critical / skeptical of the data science / machine learning bubble, but the last few articles I've read about the research actually makes it sound not-too-bad. 7/18 releasing enough code to reproduce sure beats the rate at which other fields release code, even when the code is still critical to confirming the results. In fact it's almost more understandable since the code is a larger portion of the intellectual property that might be valuable to whoever is funding the research, if it's a private entity, or university staff who might still want to monetize the research. I saw another one recently about reproducibility, something like 85%. Which sounds terrible - until you remember that something like 90% [1] of science papers weren't successfully reproduced in an attempt to do so. I'm gonna go dig up citations if I can find them quickly...

[1] 1 quick citation before I get back to work: https://www.bewellbuzz.com/technology/many-published-studies...

It's terrible, but no more terrible than many other comparable fields.
Most likely there isn't a business there. If prospective customers say "We can only use it after we have these other 4 features", then chances are, when you build those 4 features, they'll say "we need these other 5 features and then maybe it'll be useful".

There are some exceptions, and some really prominent startups (eg. Reddit, AirBnB, and Twitch) that took off after adding certain features, but usually they had an initial version that was halfway-promising, and they decided on the additional features by observing what people were trying to accomplish with the product rather than by asking people. There are other companies (eg. Instagram, Whatsapp, AirBnB again) that became popular by taking away features.

Typically what's going on with the "We need X, Y, and Z first" crowd is that people start comparing your product to existing products in the space, and then suggesting all the other features they have. If you start going down that path, you'll never catch up, because by the time you implement them, the product your chasing will have implemented new stuff. You need to enter new markets where there isn't a standard competitor that you'll be measured against - but that means that a good number of ideas you'll think up won't actually be useful.