skysight-inc/HackerNews huggingface dataset:
For sure, it's not a business model by any means, really just a quirk of the times.

In this specific case, she had all the coins that accumulated over a year or so, and just took the big jar in on her errands. Probably added 10 minutes or so.

$9 isn't a big deal for her, but for someone who is unemployed with low earning potential, $9 (or milking the incentive structure) would mean a lot more.
I’ve wondered if it’s ok for black people to use HN, I’ve also wondered if it’s even ok for black people to be in tech. The term “woke” was coined by black people for the purpose of empowerment and self-liberation, co-opted by white liberals to feel like they’re doing something, and then I see this site, which is supposed to be the antithesis of “woke” corporate culture.

Black people have no choice to interpret this as “we want to keep ignoring a soft genocide”.

No black person would want to be “unwoke” because to us that means enslavement, that’s how I know OP is nonblack.
> OKRs done well are effectively a method of improving KPIs by recursively breaking work up into subtasks
I strongly agree. (thumb up)

Well, of course Ops can have OKRs as an HR evaluation method. KPI's shortcoming is obvious, most of the results need to have a quantified indicator which is not very appropriate for engineers' situations.

But it still can be used as a complementary of OKR to provide clear numbers or date time as a target.

I just guess that iterating the OKR every week and month is quite challenging. And most of the OKR stays unchanged even after months of iterations. HR and managers need to figure out the way to keep everyone update their OKR effectively.
`leader/follower` is one option you can consider.
The dataset can be obtained around the web. It's mostly CommonCrawl, Reddit, Toronto Book Corpus, and Wikipedia.

You can find a very comparable corpus open sourced and easy to use on the [T5 repo](https://github.com/google-research/text-to-text-transfer-tra...)
This recent discussion lists a bunch of options: https://news.ycombinator.com/item?id=23811866 - which is best depends on the context
Ah, that sounds much better
I’ve found when I’m hung over or exhausted (e.g. kids were up all night), are the times when I can really plow through all the mundane todos that have been sitting around forever. It’s almost like my mind is happy to have a bunch of stuff lined up that takes minimal effort. When I’m “fresh” and energized, in the absence of another forcing function (e.g. deadline), the easy stuff is too boring, and the hard stuff results in analysis paralysis.
Technically, it's only illegal against older workers

Specifically, discriminating against someone over 40 due to age. (29 USC § 621: https://www.law.cornell.edu/uscode/text/29/621 )
My statement is that I do not believe that Google is well run today, or in the recent future, and that OKRs are part of that. I believe that their position is not earned through strong organizational structure in recent years, but that they simply have a strong foothold in an extremely powerful market.

What allowed them to 'win' in that space decades ago? I don't know, nor do I feel the need to know in order to just much more recent history. It could have been organizational structures that either in a different time, or with a different group of people, or at a different scale, or whatever, were the key. Or something else. I have no comment on it.
Thanks for the pointer. Missed that thread
W.r.t. the Markov model, I just mean that something even that trivial can sound lifelike. It's not surprising that throwing billions of times more data at the problem with more structure can make the parroting better.

> So no, human language is not predictable and regular, at least not in any way that we know how to describe formally.

I don't know what to say about this other than perhaps the NLP community has been a little too "academic" here and I disagree.

Grade schoolers routinely are forced to make those boring diagrams for their particular language, and that has tremendous structure. When you add that structure (function) with the data of billions of real-world people talking, it's not surprising that the curve fit looks like the real thing. Given how powerful things like word2vec have been that do very, very simple things like distance diffs between words, it's not surprising to me that the state of the art is doing this.
Did the article imply it wouldn't?
Harpers magazine and the New York review of Books are my go to publications.
We have a credit card with Capital One because they allow for credit cards to minors with a monthly limit that you can adjust. My 3 kids started out at $250/limit (way more than I expect them to need but also what we could live with if one of them got carried away). My oldest hit her limit once for textbooks and then again for college application fees. So we increased just her limit.

It's really nice that they can use this to get familiar with credit cards and show to us that they're trustworthy. Instead of me buying a textbook or buying tickets for movies (back in the pre-Covid days) or making sure I have cash, they take care of it themselves and I get the statement.

I don't know if there is any benefit to them for credit scores because my oldest isn't quite 18 and none of the credit agencies will report until they are 18. But they're all on 1GB/data plans (Tello for $11/month) on their own credit cards.
I wish there were a freely available copy online, I could link, but the passage is at the end of chapter 2 of Syntactic Structures. It's not a footnote, but rather the crux of his argument, I believe:

> "... a structural analysis cannot be understood as a schematic summary developed by sharpening the blurred edges in the full statistical picture. If we rank the sequences of a given length in order of statistical approximation to English, we will find both grammatical and ungrammatical sequences scattered throughout the list; there appears to be no particular relation between order of approximation and grammaticalness. Despite the undeniable interest and importance of semantic and statistical studies of language, they appear to have no direct relevance to the problem of determining or characterizing the set of grammatical utterances. I think that we are forced to conclude that grammar is autonomous and independent of meaning, and that probabilistic models give no particular insight into some of the basic problems of syntactic structure."

I do think it's an important point for people to recognize. Scientific theories don't arise on their own out of large-scale statistical analyses. There is a lot of faith being put in deep learning methods these days, which are great for prediction, but not inference.
I have spoken to people who have admitted their racist ideologies and motivations for voting. And I’ve interacted with people who knowingly vote for their own economic interests at the expense of society’s interests because they fundamentally believe they should take whatever they can get.

The latter example especially takes place in local elections regarding things like zoning and local ordinances and work contracts.
I got a buddy who works for DSCO, a company which, among other things, sells software that makes it easy for brick-and-mortar stores to sell products online and have the products ship from the retailer's warehouses. Around the time of the pandemic, they change their software so that the stores themselves would look like warehouses to the software. That way, they could ship from any of these so-called warehouses and then support ship-from-store on the websites of their customers. This functionality was sort of in in demand before the pandemic, but many potential customer said "no thanks, we'll build it ourselves". After the pandemic hit, everyone went scrambling to DSCO for help to support ship-from-store.

This article seems to talk about the next logical step away from ship-from-store: turn the store into a shipping yard.
Or, for more recent and perhaps relevant examples: Transnistria, Abkhazia, South Ossetia, and the Donetsk Republic.
Yes. Definitely, sustained poor management can lead to a company's downfall. You have to continually sabotage your company to kill it. Just mediocre management or incoherent management won't do it. (But it might set the stage for worse decisions)

Google does seem to sabotage a lot of its products, but so far hasn't really sabotaged its core products or its company. As long as they don't destroy the dollar printing press (Adwords/search), they can keep pissing away money on dumb things and it won't kill them.
Binary search can be implemented using conditional move instructions instead of branching. Given the branches are unpredictable, this yields a huge speedup. It can be implemented like this in pure C, if written in a way the compiler can recognize. In my experience this is the fastest binary search.

[1] https://pvk.ca/Blog/2012/07/03/binary-search-star-eliminates...
You don't believe the average 33-year old candidate is far easier to influence and manipulate than the average 60-year old candidate?
Man Dressed as Delivery Driver Executes Hit on Federal Judges House
> ...a lower quantity of real goods and services can be purchased for the same amount of currency. There isn’t any evidence that this has happened following the Fed’s QE programmes, despite most mainstream economists freaking out about the same point at the time.

AAPL in feb ~$320
AAPL today ~$385

TSLA in feb ~$900
TSLA today ~$1500

Inflation is not equal across all sectors of the economy, is a transfer of wealth that disproportionally benefits some.
Bless you kind stranger
Reacting mostly to the ending/conclusion here.

I don't know about other founders, but for me, startups are basically the only vehicle for solving big problems that nobody else will/can solve.

Often the reasons that (nearly) nobody else is trying to solve your exact problem are 1) it is risky/unlikely to monetize well, 2) it is hard, grueling, or boring work that may not even function right in the end, 3) might believe it to be impossible or not worth it.

But if you have a big problem in front of you and you strongly believe it can be solved and should be solved, then what other choice do you have but to start a startup?

There are lots of people (maybe myself? I dunno.) who feel strongly about solving a problem but also feel that they don't have "what it takes" to be a successful startup founder. I have a failed startup in my past. The failure process wrecked me for years, emotionally, socially, financially, the whole thing. I'm okay now, don't worry.

But are there any other reasonable options for "trying to solve a big problem that is otherwise being ignored" other than starting a startup?

I want to solve big problems I care about. I have that ego discussed in the article; often I find I do believe I have the right combination of things to solve a particular problem better than other people. So I feel like it is my responsibility to do it.

But being a startup founder is hard and if your personality or circumstances aren't a good fit, then, what do you do? Just stay frustrated that the problem isn't being solved?
I don't agree. I suspect you may have been put off by the beginning (before the 0:57 mark), where he may sound annoyed by the question. Personally, I don't think he was; he does agree that it's an excellent question, and continues happily from there.

His roundabout analogy about the seemingly infinite rabbit holes of "why"s makes an important point that some phenomena are not explainable in a satisfactory way without a considerable theoretical framework, and any layman-friendly analogy is ultimately going to be inaccurate.
It is nice to see benchmarks of elementary algorithms, but none of these is new. Benchmarking would be more convincing if more distributions were used. For example, we know that interpolated search is O(lglgn) for uniform distributions that are used here, but can be linear in pathological cases.
the building owner gets a cut, even with the more fully managed option.
>you could call him a democratic asshole

Is this an idiom wherewith I'm unfamiliar?
Sure, but sometimes the history involves a superpower teetering on the brink of fascist dictatorship, or a once-in-a-century pandemic wreaking havoc around the world. Events that will define the space of possibilities for decades to come.

At those times it’s a bit more important to stay at least partially informed than when the biggest crisis is a new highway project going over budget or a political leader’s extramarital affairs.
Shanghai's STAR market brings in new dawn for Chinese tech
Worms 2 was my favorite PC game. I remember the mods with rope games opened a whole new world, and provided endless hours of fun and challenges. Armageddon I remember slowed down the ropes so that wasn't possible anymore. Did they ever fix/change that?
IMHO “Slave” is the problematic word here. I think it’s better to avoid the slavery analogy and instead use “worker” or “replica”.
Thanks for pasting the whole thing. It's an interesting argument. The core empirical claim is

> If we rank the sequences of a given length in order of statistical approximation to English, we will find both grammatical and ungrammatical sequences scattered throughout the list; there appears to be no particular relation between order of approximation and grammaticalness.

It's totally not clear that this would be true with modern language models, after you control for (1) the length of the sentence and (2) the words in the sentence (as mentioned in the thing I linked above).
Wearing a mask in completely about politics in the USA. Most if not all social media posts about people wearing masks have people wearing completely useless fashion items on their faces. I'm sure it is mostly because they don't know better and partly to virtue signal.

In any case there hasn't been any studies related to efficacy of wearing a mask in public to reduce the risk of infection, so not wearing a mask is not as crazy as some people make it out to be.

This all said if I would use public transport I would be wearing a mask (just not a cloth mask or a surgical mask) or if I visited other places which were packed with people, but best solution is to just not go to places which have a lot of people in them.
Seven 'no log' VPN providers accused of leaking 2TB of user data
Added bonus of the alarm going off in the morning across the room helps that 2-3 seconds of initial wake up to be more "productive" in waking up - gotta stand and walk for a second before the alarm goes off. Less likely to fall back asleep after just that little interruption.
The problem tends to be that "is-a" is conveniently short but it confounds several different types of inheritance.

Inheritance in most OO languages really means "api is a superset of, and implementation is a specialization (and possibly superset) of" while in natural language "is-a" implies a relationship where some facets might be expanded, while others may be more restricted.

This is really partially a weakness in expressiveness of our languages, partially a problem of our frequent insistence on mutability. Often the problem goes away with immutability: If your "square" is immutable and inheriting from a "rectangle" class that allows setting width and height to different values isn't a problem, because the result would be a new object and that result can be a rectangle.

But sometimes we also genuinely would be best served by inheriting implementation and public API separately without having to create cumbersome facades etc. - it's just that making an API of a subclass a subset of the API of the superclass violates a lot expectations people tend to have about OO systems, and so few systems outside of prototype based ones seem to allow it without resorting to ugliness like overriding methods to make them throw exceptions etc.
Wow, this exact same thing happened to me. I called AirBnB support and they said they most likely can't restore my deleted account, how did you get them to reinstate your account?

I was so upset I lost all my data, trips, and reviews!
> lithium ion battery will surpass both energy and power density of gasoline, which seems impossible even from physics point of view.

Sure, I can do the math on that.

Gasoline has about 45 MJ/kg[1]. 1 kg of lithium contains 868x10^23 atoms, or 13.9 megacoulombs if each atom donates a single electron. Since a joule is one volt-coulomb, every electron must average out (nominal) to 3.24 volts. Todays li-ion batteries have a nominal voltage of ~3.65 V, and the nominal voltage of li-air batteries are 2.91 V.

The actual voltage of li-air is ~90% lower than the required voltage to reach raw parity with gasoline, which makes sense
given that the theoretical limit of li-air batteries is 40.1 MJ/kg (.9 * 45 = 40.5).

Reaching the same power density as gasoline in vehicle engines (=<9 MJ/kg) isn't too bad (very close to 10x best current consumer batteries, closer to weirder chemistries), but parity with the real power of gasoline is a very hard ask. Donating more than one electron per lithium would require some serious re-evaluation of what we know about chemistry. If you only have one electron per atom, you have almost no weight left over for other materials to use to develop a voltage difference with. A battery that exceeds gasoline's full heat energy would need some very exotic materials- either lighter atoms[2], different ways of storing electrons[3], or ways to store energy besides electrons[4].

[1] divide by 5 for a realistic engine efficiency. At that rate, a gallon of gas provides 9.4 kWh- enough to get a Tesla model S over 35 miles.

[2] there are none, besides hydrogen, which itself isn't really helpful. It's not very good for electrochemistry.

[3] preferably, in a different state than me. Electrons hate each other. A 3 Ah battery has 11,000 hateful coulombs in it, each electron within a less than a nanometer of the others around it. That's a 10^9 on top and a 10^-9 on the bottom. Not positive on the math on that but I'm reasonably sure it's in the thousands of megatons. It is rapidly trying to change chemical and then geographical state.

[4] preferably on another planet from me. If you're storing energy with a different force than the electromagnetic force, you're pretty much guaranteed to be doing some real fuckery to subatomic particles, and they are not going to be happy.
Title should be: I don't want to take VC money and I don't think you do either
It seems you think a differing point of view in a debate must be delivered via condescension, which is unfortunate.
The more recent results (by the same author) is this paper: https://arxiv.org/pdf/1509.05053.pdf

The conclusion is still that CMOV is best, but once the data stops fitting in the cache there's alternatives worth considering.
>It doesn't at all.

Assertions aren't particularly useful in this discussion. Nothing you said supports your claim that GPT-3 doesn't show any capacity for reasoning. The fact that GPT-3 can create working strings of source code from prompts it (presumably) hasn't seen before means it can compose individual programming elements into a coherent whole. If it looks like a duck and quacks like a duck, then it just might be a duck.

Here's an example of rudimentary reasoning I saw from GPT-2 in the context of some company that fine-tuned GPT-2 for code completion (made up example but captures the gist of the response):

[if (variable == true) {
print("this sentence is true")
}
else] {
print("this sentence is false")
}

Here's an example I tested using talktotransformer.com:
[If cars go "vroom" and my Ford is a car then my Ford] will also go "vroom"...

The bracketed parts where the prompt. If this isn't an example of rudimentary reasoning then I don't know what is. If your response is that this is just statistics then you'll have to explain how the workings of human brains aren't ultimately "just statistics" at some level of description.
Wider branching factors (3-ary, 4-ary, etc) are less efficient in the total number of comparisons, but give you more memory level parallelism, and large searches are dominated by memory access behavior and critical paths, not total comparisons or instruction throughput. So better MLP can make up for the inefficiency of higher arity searches... to a point.

E.g., with 4-ary search, your search tree is half the depth of binary search (effectively, you are doing two levels of binary search in one level), but you do 3x the number of comparisons, so 1.5x more in total.

However, the comparison (1 cycle) is very fast compared to the time to fetch the element from memory (5, ~12, ~40, ~200+ cycles for L1, L2, L3 and DRAM hit respectively). The 4-ary search can issue the 3 probes in parallel, and so if the total time is dominated by the memory access, you might expect it to be ~2x faster. In practice, things like branch mispredictions (if the search is branchy) complicate the picture.
I totally understand how this feels. I've always been a night owl, staying up in my teenage years until 3 or 4 in the morning working on a project. I can just think more linearly when my brain is tired.

Pre-covid I was regularly doing an intense morning spin class before going to the office, so I was "tired" when I started my day, and my productivity was great. Not perfect, but much better. Since WFH/SIP I don't have the opportunity to do the same kind of intense cardio, so I've relegated myself to blocking my afternoons so all my meetings get scheduled in the morning. Even then, I still am not that productive in the afternoon, and sometimes resort to getting work done in the evenings when I feel I can take on a larger task.
There's a guy who'd approve politically-motivated domestic wiretaps in the name of national security!
Dave McClure had a pretty aggressive talk about why not to do a startup[0] back in 2012 and it resonates with what's written here.

Startups are hard and we love to parade those who made it, struck it rich, but the reality is the vast majority don't. It also requires a skillset/discipline/constitution that is very different than what most people want to do.

In the very large group who don't make it, lies burnt relationships, heartache, debt, lawsuits, depression, even suicide/death. Which on closer inspection, the success group has a lot of the same traits. Only they made it out with IPO, sale, merger, self sustaining business to show for it.

It is scary. It is hard.

But to me, you won't know until you know. And if you want to know, the only way is to try.

That is reason enough.

[0] https://vimeo.com/15799330
Assasination attempt on judge of the Epstein/Deutsche Bank case
What is "IT" ? Do you mean sys admin ? Is that why you don't want to learn algorithms ?

Here is the problem, many people have patents, many people have words. You should be able to solve a simple BFS, DFS or DP problem. These algorithms ARE used in good jobs. Seems like most people here write CRUD apps.

Also, lots of FAANG engineers have lots of patents as well. That doesn't mean anything.
master/replica sounds perfect to me. That should be fine I guess?
I am this close to changing it, this is very good
I do find it interesting that in spite of the fact that so few companies will ever accept VC money or go public, this model is viewed by many as the dominant or only way to start a tech business. This is in spite of the fact that Technology businesses may very well have the lowest capital requirements of any type of company in history.

It was the same way in the 80s with finance. Even though most finance workers were (and are) accountants working boring 9-to-5 corporate jobs, everyone assumed that anyone in finance worked on Wall Street and snorted coke off of strippers in NYC nightclubs every weekend.