skysight-inc/HackerNews huggingface dataset:
I joined Yahoo in 2013, and my impression was that it was a company that still made a ton of money, because at one time a lot of really clever people used to work there, and their stuff continued to make money, but the people working there were not clever enough to build on it, they were barely able to keep up on maintenance of it.

I encountered a ton of cool technical solutions to things that were Really Hard Problems in the 90's or 2000's, and that was appropriate for hardware from that era, but the outside world moved on, while everyone inside Yahoo still thought that their shit was hot shit.

There were for sure a lot of smart people still working at the company, but the company had 0 cool factor, so they had an incredibly tough time recruiting and retaining people that could move the state-of-the-art forward.

...and no buzzword management strategy like OKR's or whatever is going to change that fundamental problem.
Have you considered taking 45 minute walks at the times you used to commute? Audiobooks/podcasts are just as good while walking, and the light cardio might be more stimulating and enjoyable than the driving was. Or do something else with that time. Just because you’re no longer forced to drive for nearly 2 hours a day doesn’t mean you need to work an extra 2 hours.
Actually cmov-based searches often (usually?) result in a slowdown unless non-obvious measures are taken.

A cmov-based search has the problem that the probes for each level are data-depedent on the prior level. So you cannot get any memory-level parallelism, because the address to probe at level n+1 isn't known until the comparison at level n completes.

Branchy search is at least right half the time (in the worst case) on the next direction, 25% of the time for 2 levels down, etc. So it gets about 1 additional useful access in parallel, on average in the worst case, compared to cmov search.

Except for very small searches which fit in the L1 cache, where misprediction cost dominate overall time, branchy is competitive and often faster.

Now you can take countermeasures to this problem with the cmov search. One is to increase the arity of the search as in the OP, another is explicit software prefetching, etc, which might put cmov back on top.

This has all been assuming the worst case of totally unpredictable branches. Real world searches might be expected to be less-than-random as some elements are hotter than others, etc. Any predictability of the branches helps out for branchy search.
Yah my feelings about running a startup are completely different for bootstrapped/hacked up companies (I think that's the term?)
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How can one play Worms World Party (or even Armageddon) on Mac OS X these days?
Longreads.com is the site for you.
The downside of OKRs is that it incentivizes everyone to sandbag their efforts and then stick to that effort.
Also no one is going to stick their neck out on goals which are ambiguous or lack clarity. There is just no incentive - in fact there's a massive dis-incentive.

If you have a startup with less than 300 people and you have good communication and goal setting, don't use OKRs. Use KPIs and then nehlp your teams to keep iterating.

Input management is so much more effective than output management but it needs visionary leadership. Read: High Output Management - Andrew S Grove (ex Intel CEO).
To me, the only point on this list that hasn't improved much is "Ruby on Rails needs to more or less work in ANY environment".

Ruby's install/user story for Windows is still Not Great, and Ruby version wrangling on any operating system is a question that you still get 100 answers to ("use asdf/rvm/rbenv/chruby blah blah blah").

For the rest:

1) It's certainly Fast Enough now. More important webperf issues are happening on the frontend side nowadays. Who cares if your backend takes 500ms to respond when it takes 5 _seconds_ to compile the JS on the client.

3) Solved since Rails 4.0 IMO.

4) Discourse has more or less proven this can be done, with some hard work. Also, Heroku more or less standardized the 512MB VPS size, and nowadays 1GB is pretty cheap and becoming more common, so Rails doesn't struggle with memory limits anymore.
Or online. Cheaper and less frostbite for kids in places with extreme winter conditions.
The issue with a million mile battery is one of testing. If your car has 500 miles of range, a million miles means 2000 charges and discharges. At a standard C/5 rate, that's 2.3 years to finish testing. Even at a fairly brisk 1 C that's 83 days. It makes iterating on a design -which can mean changing component amounts by fractions of a percent- incredibly time consuming.

Dahn's research is so well respected because he was incredibly good and thorough in measuring tiny amounts of heat and voltage changes in batteries so that you could trace their degradation over a much smaller number of cycles, then try them out at longer scales. Tesla has been funding much of his lab. There are very few people who can do this kind of research outside his lab, and IMO he's a wizard who will end up with a Nobel if he makes a few more big contributions.

The bottom line is that the only way to really tell if a battery will last a year or a decade is to watch it for a year or a decade. No amount of technology lets you forecast the future with perfect accuracy, and battery longevity testing takes time. That's the only reason we don't have a million mile battery.
My take on this is: the only people who should become a founder are the people who can't bear the thought of not doing it. Anyone with less than "Give me libertly or give me death" levels of commitment should not even bother.
Or, for slightly less recent but perhaps just as relevant examples: Moldova, Georgia, and, most of all, Ukraine.
I will have to take a look at that paper. I didn't catch your edit before replying. It would certainly be worthwhile to verify that claim (or not) using the paper's model if I find some time. In any case, I think the underlying point is that these language models serve a purpose, but will not uncover an underlying structure for you or derive something like the phrase structure grammar proposed in Syntactic Structures. I may be extrapolating a bit based on other times I've seen Chomsky discuss this, though.
OK, well, I am taking cognomen as surname, as is common when referring to him today, by nomen + cognomen. Never met the man or had the joy of calling him Gaius.

There are modern people today with a surname of Caesar. Somehow, the name of the late celebrity Sid Caesar pops up for me. Wikipedia has more: https://en.m.wikipedia.org/wiki/Caesar_(surname) -- and I know of other languages where their cognate for Caesar is also a surname.

But yes, it is common to address people by their last name as a nickname. I seem to recall it was especially common back in school, something guys did kind of informally. Plenty of reasons explained here: https://www.google.com/search?q=call+someone+by+last+name

I also recall nickname variations of various surnames. Somebody called Fitzgerald might be called Fitz. Somebody called Smith might be called Smitty. Those are two I recall from school days.

And yes clearly, McDonald's and Hardee's are named for surnames.
Build a Native UI Android App with Python and BeeWare
Or foolhardy. Whatever is your preference.
Security Vulnerabilities fixed in Thunderbird 78
What is math?
If you want a non turn based version look up Liero (OpenLieroX). Gigantic amounts of fun to be had.
When Does a Pandemic Start to Erode Civil Liberties?
It is not the same thing. If you want more from DO or Linode they are happy to sell 2x the resources for 2x the price.
I have a rambunctious 4yo entering kindergarten this year. He needs direct attention of a present human, not a screen to watch.
> The need to be “in the know” was powerful, but I realized that I was consuming vast amounts of shallow information that resulted in shallow, uninformed opinions.

I'd like to applaud you for admitting this to yourself. I feel like a vital part of successfully navigating the internet age is to realize this very fact.
Sassafras
In so far as they have missed the transition from ICE to EV, they are all wrong. Tesla has such a huge lead on them, they probably will never catch up.
Wow, you just described me. Except I'm about 4 years into my career. Glad to hear that I have a type. It is oddly reassuring in a manner that I can't currently articulate.

Most places I apply I just don't hear back from. Places I have worked had no idea how to use me effectively. I've applied for very few jobs because of this (on the spectrum, have trouble with rejection). I do a lot of free or underpaid work or just do something that fascinates me. The poverty sucks but I love that I get to pursue so many interesting things.

I have faith that I will find somewhere that is a good fit one day. In the meantime, I get to explore my interests and grow. Thanks for this post, it gave my hope a much needed boost.
Its a good point. The counter point is the process of reviewing your notes to formalize these connections helps cement those connections into your brain. Basically when you have a thought these two things are connected the system lets you document that thought with minimal friction.

The connections between notes ideally provide an element of surprise. The process is geared towards the long term while minimizing immediate friction.
The answer is rbenv :)

The ruby language has also sped up a lot since 2008, which has helped Rails. I catch your point about the slowness being in the client these days, but 500ms would be an exceptionally unusually slow response from the rails application in any of the production rails apps I’ve run.
Carry on (The) Arithmometer
Lots of applications like that are done in Qt, e.g. 3D editing tools, game engine tooling, ... For mobile you might prefer doing independent apps (reusing some of the 3D code etc of course), but afaik other desktop frameworks are not better than Qt for that.
This is either something written by GPT-3, or the human equivalent. Zero substantive content, pure regurgitation.
Doom II Programming Quirk Can Take 12 Years to Spawn a Demon
I think you may be overestimating how many bellhops and valets the average person interacts with in a year...
"master" even on its own os potentially problematic because of the relationship with the word "slave" even if you cage that to "replica".

I'd suggest changing both, so you won't possibly be asked to change again later. I went with "Primary/Replica" here, because it's genuinely more logically descriptive of the roles, as well as moving completely away from older "traditional" use of language that might cause offence or hurt.
Because for the companies that don't, it is a threat to their existence. Teslas has opened their patents for anyone who wants them, and not one other company is keeping pace with their level of innovation. The entire ICE industry is now already obsolete. You don't think this should compell existing players to innovate?
This isn’t something I haven’t thought of. I’m hoping teams have prepared for this.
Sounds right. I think the fastest solution (of this approach) would do something like: get the Lx-cache-row sized batch; check upper/lower end; depending on result: choose next batch by binary division, or do linear walk to find the match. Not sure if doing it precisely would be an improvement over the magic numbers in the example though.

Then again, I'd like to experiment with prefetch here as well. It may be possible to squeeze out even more performance.
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I hear this repeated often. But why? Whoever think it's not a good idea? There's a reason why contrast is usually maximized on readable paper. Text contrast is very important part of readability. I often see pretty much unusable sites, because someone thinks that it's so smart and cool to create sites, which content is clearly not worth of reading.
I'm not sure I understand the post, what's wrong about getting rich?
Ship-from-retail-store doesn't work very well. You get some random subset of what you ordered. The online ordering system needs to know the inventory to make this work right. Right now, I can get quick delivery of a random subset of what I order from Safeway, Doordash, or Costco.
They send some random gig worker into the store and mark up the prices. I'd rather have two-day delivery of exactly what I ordered.

So how good are these new outfits at that?
Propublica
As long as that charity isn't the owner of the grocery store's yacht club I like this idea. In practice, though, the types of charities usually offered are a) the business themselves like Goodwill, or b) controversial at best (say, a Komen-eqsue figure). If there was a way to make this choice with less friction I'd be much more willing to give up change entirely.
The core concepts behind OKRs (and others like it) are pretty good. The problem is that almost all of these methods require managers to cede power and control over to the developers. And that rarely seems to happen. So as a developer it just becomes another layer of bullshit to deal with.

It pretty much boils down to: Set well defined, well reasoned, and slightly ambitious goals...communicate them to your developers...and then leave them the hell alone to try and accomplish them.
> The fact that it can produce working code from a prompt in some cases shows rudimentary non-trivial reasoning.

No, “in some cases” doesn't show reasoning. It is, arguably, weak evidence for reasoning that supports other explanations. With the right input corpus, a Markov chain generator will produce working code from a prompt “in some cases”, and I don't think any one has a weak enough definition of reasoning to admit Markov chains.
I think what most of us want is to be free of the tyranny of employment. And I don’t think founding a company is best way to mitigate that if you aren’t completely into it, you could just go become a freelancer or start a small services Center in your locality.
Wouldn't earlier plagues been in times of ubiquitous stay at home mothers as well? Surely a good chunk of kids just got home schooled.
I don't think the trick of checking each end of the cache line helps much, except perhaps at the very end of the search (where there are say low 100s of bytes left in the region).

When the region is large it just doesn't cut the search space down almost at all: it's a rounding error.

Now you might think it's basically free, but clogging up the OOOE structures with instructions can hurt MLP because fewer memory accesses fit in the window, even if the instructions always completely execute in the shadow of existing misses.

There is a similar trick with pages: you might try to favor not touching more pages than necessary, so it might be worth moving probe points slightly to avoid touching a new page. For example, if you just probed at bytes 0 and 8200, the middle is 4100, but that's a new 4k page (bytes 4096 thru 8191), so maybe you adjust it slightly to probe at 4090 since you already hit that page with your 0 probe.

Making all of these calculations dynamically is a bit annoying and maybe slow, so it's best if the whole search is unrolled so the probe points according to whatever rules can be calculated at compile time and embedded into the code.

Much more important than either of these things is avoiding overloading the cache sets. Some implementations have this habit of choosing their probe points such that only a very small number of sets in the L1, L2 are used so the caching behavior is terrible. Paul Khuong talks about this in detail on pvk.ca.

Doing a linear walk at the end definitely helps a bit though: SIMD is fastest for this part.
This resonates very strongly with me. Everywhere I work, I find really cool things to invent and business process improvements. Sometimes the biggest impacts these have are at the megacorps due to economies of scale. Often though there's so much friction, overhead, and red tape that it's impossible to get buy-in from team members and managers in the megacorps. This happens even in the best cases where everyone is open-minded and supportive. Sometimes large groups just don't have the excess capacity needed to re-tool. In large companies that don't have the best case cultures, it's nearly impossible to implement improvements or use any cross-team resources (human, physical or digital) to bring an invention to life.

It seems you're absolutely right that a startup is your only option if your idea is a proposed solution to a problem that is outside the mission/domain of (your/any) current organization, and/or if any organizations which would be interested simply can't devote resources and time to developing, evangelizing, and implementing your solution.

However, the risk involved in the process is so damned high. I love working in teams, whether at large megacorps, small contracting groups, or on my own or my friend's startup ideas. I don't love the "burnt relationships, heartache, debt, lawsuits, depression" (as 'irjustin phrased it elsewhere in this thread), that can be associated with startups.

Some startups are well-positioned for co-operative mutual interest VC money (repl.it would be a strange thing to bootstrap). Some startups are fantastic for bootstrapping (Sparkfun/Adafruit), and many could probably succeed just fine doing either (mailchimp, bootcamp come to mind). Still others probably best operate via philantrophic arrangements (OpenStax).
> working strings of source code from prompts it (presumably) hasn't seen before

I'm saying that "presumably" is wrong, especially on what it was: a simple React program. It would not surprise me if the amount of shared structure and text in the corpus is all over the place.

This can be tested by making more and more sophisticated programs in different languages, and seeing how often it returns the correct result. I don't really care, because it can't reliably do basic arithmetic if the numbers are in different ranges. This is dead giveaway it hasn't learned a fundamental structure. If it hasn't learned that, it hasn't learned programming.

The examples are not really that impressive either. They are boolean logic. That a model like this can do copy-pasta + encode simple boolean logic and if-else is... well.. underwhelming. Stuff like that has been happening for a long time with these models, and no one has made claims that the models were "reasoning".
I had the opposite experience. Big Bank would not take my loose coins but happily gave me paper tubes and accepted the rolls a couple days later.
If a watcher doesn't understand the lesson, was it a good session? As an acolyte, why not enlighten us? Or should I just keep watching a condescending asshole avoid a question until I understand something that makes you happy?
From what I understand, the human brain runs off somewhere around 20 watts. Maybe our silicon is really really bad, but I'm more inclined to think we're missing part of the puzzle still.
The limited data I've seen is that online learning wasn't effective compared to in person classes. Now admittedly that was an natural experiment conducted in the worst way possible, but it certainly matches my experience that young kids thrive most with at least some in person learning.

Utilizing outdoor space is a good idea until late fall in the northern US, and possible due most of the school year in places with moderate climate.
Can you expand on what you mean by some random subset of what you ordered?
It's like the Federal Reserve has massive, if indirect, control over the whole economy. That's funny.
I probably should have phrased it differently. I think the attitude in China is that, if somehow forced to choose between individual liberties and economic prosperity, many will choose the latter -- because they see it as enabling the former more capably than any sort of constitutional rights.

Btw I'm intentionally trying to stay take a neutral stance on this topic when discussing my understanding of attitudes in China. In fact my personal viewpoint is that economic prosperity without a strong and healthy respect for human rights will have bounded lifetime, but that's a different discussion. Regardless I think it's important to understand all the viewpoints.
https://github.com/zombodb/pgx/releases/tag/v0.0.7

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This is interesting and so is Foam[1]. I've a dumb question. Can I use VSCodium[2] instead of VSCode? (I tried it super-quick with foam on VSCodium and I gave up.)

1. https://github.com/foambubble/foam

2. https://vscodium.com
It think that's just a regular old Or gate.
I take notes with Apple pencil on iPad. I feel more creative when writing. Plus, I tried to enforce structure using various apps including org mode, but it turned out either I am bad at using structured note taking or my use case of ideating and planning is not very structured. And it feels less effortful than typing to me.
If you want help setting limits, I made an extension called Intention that many people find helpful: https://www.getintention.com/

HN thread of its launch: https://news.ycombinator.com/item?id=22936742
This is the reason why I added a sentiment filter to the rss reader I built. Now I can put together a few rss feeds in a folder and filter out bad news, needs some more work but it gives good results already. (Https://aktu.io)
And what about people who have lower blood iron levels? Is lower better or worse than higher?
Why do people keep posting paid articles here? Most people don't have subscriptions
Hoping for a Covid-19 antiviral that limits virus spread
The react programming example isn't the only example of GPT-3 writing code. There was an example of it writing python programs going around before they opened up the API. It was impressive. There was no reason to think it had seen the exact examples before.

Also it isn't the case that one needs to be perfect at algorithmic thinking to be capable of some amount of reasoning. I don't claim that GPT-3 is perfect, but that its not just copy and pasting pieces of text it has seen before. It is coming up with new sequences of text based on the structure of the surrounding text and the prompt, in a manner that indicates it has a representation (albeit imperfect) of the semantic properties of the text and can compose them in meaningful ways. Handwavy responses do nothing to undermine the apparent novelty it creates.

>encode simple boolean logic and if-else is... well.. underwhelming. Stuff like that has been happening for a long time with these models, and no one has made claims that the models were "reasoning".

Seems like you're just moving the goalposts as always happens when it comes to AI advances. What do you take to be "reasoning" if that isn't an example of it?
Waterfall Glen, a forest preserve outside Chicago, IL, has a waterfall but is named after Seymour Waterfall.

https://www.dupageforest.org/places-to-go/forest-preserves/w...
Is it happening faster or are you consuming it quicker?
I think they meant "random subset of what you can order"