skysight-inc/HackerNews huggingface dataset:
I challenged myself to avoid packaged food for a week. It went so well that I continued, in the process learning to cook from scratch.

I was surprised to learn that it took less time, cost less, tasted better, and led me to see packaged food as unnecessary.

I wrote a bunch of posts on it since I felt my ignorance and inexperience kept me from a better life and wanted to make the experience available to others http://joshuaspodek.com/avoiding-food-packaging-2
I am a heavy Emacs user, so I need to occasionally write emacs-lisp. The other lisp I use from time to time is Fennel. Clojure I use at work. I have to say: having to use other lisps makes you appreciate how incredibly nice Clojure is. I think every programmer at least should try Clojure.
I'm waiting to hear about when they start to rewrite their JS interpreter in Rust. It will make things kind of interesting, especially if it becomes a stand-alone capable JS inrepreter.
Well I guess they've killed the market for terminal ad-blockers.
I have three kids, A loaf of bread will last us a week. I suppose it depends on your menu.
This is a good summary, and I can follow up on a couple points. (I don’t have direct experience with Crispr data, but I’m currently a PhD student in a computational genomics program, and have 4 years of experience in a lab that does crispr experiments in addition to my projects.)

Related to both the idea of inserting DNA and off target effects - the issue is that scientists can engineer a cut, but then rely on the cell’s repair mechanisms to “stitch” the cut DNA back together. These mechanisms are inherently stochastic and error prone and are how many somatic mutations, such as those in cancer cells, arise. So for off target effects, even if you make the cut at the right place, you can still end up with new unintended SNPs and indels nearby. And for inserting new DNA, it’s not a guarantee. You can provide the template that you want to incorporate, but it might get missed, or get copied in more than once or in the wrong orientation.
> Anyone have any ideas of innovations since say 1980 other than in semiconductor manufacturing?

if you take a very reductive and somewhat pessimistic view, there have been very few true "innovations" in the history of mankind.

the wright brothers' plane was just a scaled up kite with a motor and no tether. the first computer was just a sophisticated abacus (or Babbage's machine if you prefer).

obviously the first plane was a huge stepwise advancement in tech and likewise for the first transistor computer. if you look at something like the internet today and consider how it's changed in twenty years, it's barely recognizable in capabilities. lithium ion batteries are vastly better than what was available for consumer devices a few decades ago, and you basically couldn't have mobile computing without them.

we certainly allocate a ton of capital towards technologies of dubious value (eg, social media), but we are still in an era of unprecedented technological advancement. I suspect it's just harder to find the stepwise jumps when most of the foundations for current technology are pinned down and many people are making incremental progress in parallel.
Although that may be standard thinking in some circles, in reality there are clearly areas where more money would lead to far more goods and services, making everyone in the area richer.

Building up a community like Angola is one example. Any area where people are unemployed and could use their time more productively is another example. Even John Maynard Keynes famously said this. The trick is to find out where to invest for the next high-growth thing, and the government can make a big difference. Past examples included:

Interstate Highway System

Microwave Research + Silicon Valley

GPS and Moonshots

ARPAnet and other DARPA projects

Now it's going to be solar, battery, seaweed for cows and other sustainable energy practices. Printing money and using it to build up infrastructure isn't necessarily bad. Another approach to looking at this is MMT, though I disagree with some of their conclusions.
I get that, but why couldn't you use something like GC for resource management. Maybe I sound stupid here, but it seems like the kind of task that machines would be better at than humans.
My opinion: Programs, like ships, sink in the C.

C++? In C++ that means take C, make it better but use the original.

Give me a strongly typed language and check for overflows and the like!
Statement still stands, public to public in many areas the US is going to cost much more (up to 3X). It just gets REALLY gross when you bring in the private schools.

https://www.insider.com/college-canada-us-differences-2018-1...
Show HN: A job board that shows many routes to find jobs (Desktop Only)
I disagree with Patreon and FAANG as possible socially acceptable routes, and have no problem with ads in the console. (Grant's are clearly OK). So I guess that might be subjective?

I do think that instead of everyone putting in an "ad dependency" is not the best way to go about it, but to at least directly negotiate with cloud companies to do it would be awesome.
On Stuttering
Aw, I was hoping we were going to dig deep into a "no u" situation.
How would they know they like it if they don't know how to do it? How does a singer making millions at 18 become a singer if she hasn't been singing since she was 3? How does an artist become world-class if he hasn't been drawing since he could hold a pencil? How does a veterinarian become the best in his field if he's never cared for an animal until he was 18?

I once took a computer build/repair class in college. I learned a couple neat things but it was overall a waste of time. Not a week after that class was over did my friend who took the same class ask me to build his computer. If you don't live it, you probably won't be it. If you've never done anything, you probably won't be able to do anything.
That is impressive!
There was no Apple data breached. User endpoints were attacked, using various well crafted exploits against their software. This isn't a GDPR (privacy) issue, no company data was leaked, its end user data from their device. Apple tries to protect your data on their devices, but all software has bugs. Bad guys will try to exploit these bugs to reach their goals.

Google does research into making it hard for attackers to compromise user devices. That is the purpose of PZ team. There are no numbers because nobody has these numbers except for the attacker. I am guessing Google has some ball park numbers based on search traffic or web analytics.

If you want to know if you were affected, you need to ask yourself if powerful adversary wants access to your data, possibly because of civil unrest occurring in their territory; and if you visit strange websites related to this. Only the adversary knows for sure, not Apple, Not Google.
Google reveals major iPhone security flaws that let websites hack phones
Number one cause of burnout is organizations adopting Atlassian products and treating the process like some sort of finite state automaton
Is the relevant model here simply a sum of 2nd order terms?

It's widely known to practitioners vanilla Neural Nets don't do very well on small datasets because of overfitting issues -- which can probably be corrected with very careful regularization and parameter optimization, but where generally it's best to just use simpler methods.

Polynomial regression is one of those, but I'm not sure how it compares to other methods such as random forests and KNN variations.

Those methods don't scale very well, in particular PR (if I'm interpreting correctly) doesn't scale, because depth is essential to solving complex problems with computational efficiency.

The researchers conveniently refer to those more complex tasks as a 'work in progress'... when they are what NNs are mostly used for (i.e. it starts getting interesting with CIFAR-10). That said, I would be curious to see performance of deeper polynomial regression networks. They become almost identical to NNs then, but maybe some methods of PR could be extended to give an edge in some cases (e.g. perhaps better regularization techniques than dropout/etc).
Crispr and related biotech comes to mind
Humans are awful at rare events and vigilance tasks, too. That's part of why we're seeing machine vision and machine learning starting to outperform humans in e.g. grading radiology screening scans.

The total incidence of child abuse of all types from infancy to adulthood is on the order of 1 in 3. This is not terrifically rare-- it's of higher prevalence than pregnancy and of positive screening events.

A much bigger concern is non-causative correlations. It'd be pretty easy to train ML to be racist or look for e.g. indicators of class, which are correlates of abuse.

As to false positive rates-- you can pick your false positive rate to be whatever you want it to be, by twiddling the threshold for a positive result. I'm not sure false positives are of that great of a concern, if the output from a system is a notification to school administrators that they may want to keep an eye out for this student.
I switched from Python to Clojure. And I used handful of other PLs before that. I can say the same thing: "so far I used no other language [but Clojure] where I managed to get something working just as quickly and painlessly". I liked Python. But I love Clojure.
Protocols, Not Platforms: A Technological Approach to Free Speech
How do you know they were mistakes?

You believe they were mistakes now, with hindsight, for your life, but how do you know whether the same choices that you think were bad for you, might be wonderful for your kids?

I think of it like this: we all have many possible paths to take in life. But we only travel one.
How about 'follower'?
I agree, though they do make the pretty strong statement of

NNAEPR suggests that one may abandon using NNs altogether, and simply use PR instead.

in the blog post, which sounds to me like they're going for a finding.
Canada has an immense unguarded border with a country that has several million uneducated people living in extreme poverty.
That's fair and I now know more. I'm not convinced that this is the biggest issue with JS engines/browsers, but I certainly have more evidence against me :).

It's interesting how many of those are labeled OOB. Does that mean that we're talking JIT flaws that allow OOB access to memory? Is it's actually tricking the JIT itself into allowing OOB access, or is it actually OOB'ing the JIT?

I wonder what the performance impact of all JIT code being forced to do bounds-checking would be...
All of the terminal ads I’ve seen have been nothing like you suggest.

They’ve looked like echo “Hi please send me money”
> When a child writes "daddy touches me between the legs" in an essay, it doesn't matter if a human spots it or an AI that forwards it to a human, this needs to be investigated either way.

When a child writes a set of things that individually are not very concerning, they may have cues that could say "hey, this kid, you should maybe keep an eye out for evidence of abuse."

Particularly attuned, experienced individuals might spot these cumulative cues, but we all know that this is not all people dealing with children.

It's an interesting problem.
s/curiousity/curiosity
I don’t want to give up Splenda in my coffee or Coke Zero, so I take metformin in conjunction with intermittent fasting to game my blood sugar.
Do you know the applications timeline YC W20?
Does anyone know when interviews are held, and in general the timeline for applications to YC?

I can observe 3 dates on https://apply.ycombinator.com/

25 June: Applications Open

25 Sep: Deadline

16 Oct: Invites Sent

1) When is the interview?

2) How are the invites sent?

3) Do they conduct interviews in London?

If anyone has more details about the dates up to YC W20, I would be thankful.
People need more space in cities.

People are willing to live with far too little space compared to what a person actually needs to live well. I think it is a zoning issue where local governments need to force more working green space and workspace in general.

Living in small apartments without space to garden or build or maintain things makes people somewhat miserable consumer drones.
In that case, calling it a language seems like a stretch...
In the world of avionics, the concept of a “single point failure” is widely known and greatly focused on eliminating.

The failures that take down aircraft will likely involve multiple things going wrong, because the engineers (mechanical, aeronautical, system, software, etc) work hard to ensure a single thing going awry won’t down a plane.
Some older android devices running newer lineage/AICP/etc builds include a few libraries I wrote (in their entirety) for compatibility of old vendor prebuilts with new android versions - libdgv1 & libdmitry. Maybe I should C&D FB for laughs?
> if you look at something like the internet today and consider how it's changed in twenty years, it's barely recognizable in capabilities.

I'm not a internet/web person, so forgive me, but:

The internet today seems an awfully lot the same as the internet in 2000. In terms of 'unrecognizable capabilities,' are you thinking of streaming video or what?

Batteries is a good one, thanks.
Thats if you ignore economic, social, and historical conditions influencing nations. Theres many factors besides country size at play here.
>If the ad makes a remote call during execution (for an dynamic ad serve), it's an attack vector. There is always custom ad code for analytics that adserves use to fill (the ad placement space) and report back, called an admanager. As an advertiser, you can upload your own admanager (that that has your own custom code

Can you point out a real example of terminal advertising like this?
At the beginning the authors claim they're not just making a restatement of the Stone-Weierstrass theorem (any continuous function on a compact set can be approximated arbitrarily well by a polynomial), but reading through, I'm not sure what they're proving besides that. In fact, on pages 6-7 they simply appeal to that theorem before stating "NNs can loosely be viewed as a form of polynomial regression". Most of the rest of the paper is comparing polyreg and NNs on various datasets. Sec. 9 doesn't have anything doesn't have anything especially novel in it. For instance, in 9.3 they say they'll explore the causes of overfitting in the context of their "NN <-> PR" principle, but never actually do so...

Polynomial regression is nice because it's a little easier to interpret, and it's also a convex problem with a single, global minimum. OTOH you have to design features yourself, otherwise for high-dimensional problems polyreg quickly requires way too much memory and compute to solve in a reasonable amount of time.

This paper might have been more interesting if it had somehow connected neural nets to those facts, or if it had shown how insight on the way in which neural nets work can be used to improve polyreg. But (admittedly, from a brief reading) I don't anything like that here.
> The creators of those various libraries should have a valid legal case against Facebook here, if they want to exercise it.

Perhaps, but sadly, I don't actually foresee vendors wanting to exercise that right. From a business perspective, why bother?
At the very least, the privacy-respecting solution would be to upload hashes and only upload libraries once some critical mass of users had reported the hash along with a bug. Even then, you would only upload the files themselves from some capped number of users.
Terminology note: data like images and voice which have strong spatial or temporal patterns are actually referred to as "unstructured" data; while data you get from running "SELECT * FROM some_table" or the carefully designed variable of a clinical trial are referred to as "structured" data.

If this seems backwards to you (as it did to me at first) note that unstructured data can be captured raw from instruments like cameras and microphones, while structured data usually involved a programmer coding exactly what ends up in each variable.

As you say, deep neural networks based on CNNs are SOTA on unstructured image data, RNNs are SOTA on unstructured voice and text data, while tree models like random forest and boosted trees usually SOTA on problems involving structured data. The reason seems to be the that the inductive biases inherent to CNNs and RNNs, such as translation invariance, are a good fit for the natural structure of such data, while the the strong ability of trees to find rules is well suited to data where every variable is cleanly and unambiguously coded.
I figured it out by accident, after a whole lot of frustration: click on the image itself and the carousel will pause.
I and various other family members discovered the hard way that frozen > defrosted bread led to serious stomach discomfort — apparently because of the changes that happen to the starches when they're frozen. They change from their normal state into a 'resistant' starch, which can cause you problems if you have a tendency towards something like IBS.

Here's one BBC article that mentions it: https://www.bbc.co.uk/programmes/articles/4DfZMpv7BYJ3kGXdHx...

"Freezing turns starch into resistant starch... this means that your body gets far fewer calories from the bread. In effect, the resistant starch feeds your gut bacteria, rather than feeding you."
Release of “13 Reasons Why” Associated with Increase in Youth Suicide Rates
My yt experience is both play @ same frames but firefox waits for a couple of seconds before I'm able to click play / when I skip to a part in the video - whereas chrome is instant in both cases which can becoming annoying
They themselves are not, but lets look at another consideration. How will you catch a backdoor added to one of your dependencies?

- Scan them and hope someone else noticed and reported before you used it?
- Assume your team mates reviewed them when they were updated?
- Add SIEM like capabilities and monitor network connections?

It should really be all 3. There are counter points of course, but if you vendor them, they'll in a PR and reviewed just the same as the rest of your code.

Of course, where do you stop? You trust your distro to do the right thing and you don't review that code, etc. So the more generic question is why do you trust the golang modules you use?
Nobody is questioning that they give some software back but giving software back simply does not fund open source. Most people cannot convert their contributions into money as deftly as FAANG has converted 10,000s of people's contributions into a quarter trillion dollars.

It does not fund the tools that power their current open source projects.

It does not fund the tools their next open source projects will use.

It does not fund the brilliance their next open source projects will iterate on.

It does not fund the mistakes their next open source projects will know to avoid.

They need all of that stuff before they have even a clue what to make next, and they need the open source community to try everything a hundred different ways to see which is good.

We will still be arguing about this in twenty years as open source transitions into a mostly Indo-Chino-Russo-African dominated landscape because western developers can't afford to work on open source unless it's through their employing-FAANG company.

Long before that all the current FAANG open source we're supposed to be grateful to receive instead of funding will be obsoleted and tossed aside because only a handful of ideas in it actually mattered after all.
Spiky things hurt and round things don’t — would be interesting to simulate pleasure / pain of shapes against a virtual hand using a simulation then train a deep net to learn the pain response. Bet you would have similar findings.
https://github.com/goproxy/goproxy as well
"fact remain that the number of crash so far is 0" makes zero sense.

And you even got an answer to your question. The number of deliveries is different. What's your point?
On the Path to Go 2 (2019) [video]
I've been obsessed with Clojure for a while, but seriously struggle finding a job where I can use it professionally. How'd you manage that? Any tips?
> I'm mentioning health care, gun violence, shoddy leadership, and homelessness as practical reasons I can see the USA just not even being comparable in terms of quality-of-life - these are facts that can easily be backed up by data I'd be happy to provide.

1. Health Care - Anecdotally, I've known people who moved down to the US from Canada because they could no longer receive care (or timely care). Of course, these specific individuals were elderly, but take from that what you will. Also, I've read that the U.S. pours more money than any other country into medical research (though I could be wrong about that).

2. Gun Violence - As always, the picture painted of the U.S. as being some sort of warzone where you are constantly afraid of being shot is just...false. The vast majority of the U.S. has the homocide rate of Switzerland (a country with many guns and low crime). There are generally just a few pockets of insane levels of violence related to the drug trade. As for suicide, it is an issue, but there are other first world countries that have few guns but comparable levels (e.g. South Korea) that your source fails to mention.

3. Homelessness is an issue, and I honestly don't know what the reason for the difference is between Toronto and Chicago. For California, climate may be a factor, but it definitely seems to have become worse in recent years.
There's a limited instruction set, no loops, built in verifier exists so that no anomalous code can be executed on the in kernel virtual machine. More so, this feature is in 4.X kernel and I think there's been no exploit discovered in the wild.
More importantly, they're backed by the CMHC so they don't have to concern themselves with risk.

https://www.cmhc-schl.gc.ca

And if there's a crisis large enough that solvency of CMHC might be questionable, they don't have to worry either because the bank of Canada will gladly buy their mortgages, passing the risk onto taxpayers.

https://www.macleans.ca/economy/business/the-real-canadian-b...
It's great that you're voluntarily becoming self-sustainable, but many actions which are great when done voluntarily make for poor public policy. In many areas, it's simply impossible to write a policy that is fair to everyone. Or it could work fairly but it doesn't scale.

Ending agricultural subsidies sounds nice in theory, but what other consequences will it have? I sure wouldn't want to have to tell the low-income part of town "Your food is now twice as expensive, but if you just plan better and don't throw as much away it'll work out the same." Poor people can't afford tupperware! Lack of planning isn't their problem. Being poor is expensive.
If this was being done for fingerprinting, wouldn't it make more sense to use a hash of the libraries?
Management by "make metric go up" is almost always terrible in every situation, since human misery is generally not considered an important metric (too hard to measure!) and metrics themselves cannot expose long-term consequences of optimizing for a metric at the expense of anything that isn't being measured.

Death by metrics isn't the fault of Jira--Jira provides tools to do many things more effectively, and gathering metrics is just one of those. Providing effective tools to ineffective people, unfortunately, does allow those people to shoot themselves (and in management's case, everyone around them also) in the foot more easily.

Exacerbating this, as you mentioned, is that metrics do provide a simple, cheap representation of productivity, even if that representation is not aligned with reality. Middle management can present this to upper management to show that they're doing a "good" job, and upper management will be none the wiser about what's not exposed by the metric until a while down the road when problems created by optimizing for those metrics become more apparent.