skysight-inc/HackerNews huggingface dataset:
Self-disclosure seems like easy low-hanging fruit. I respectfully ended a relationship with a poly individual long before she did anything that I would have considered cheating. It became a question I asked on every first date, and I am now engaged to a mono individual. You might be surprised how many individual would openly admit that they are mono, poly, casual or what-have-you, provided that they are not discriminated for admitting it. I'm incompatible with non-mono sexualities and being open about that spectrum allows me to avoid "cheaters" and them to avoid "clingy."

Apps can then strictly filter according to those preferences (some allow disclosure, all have fuzzy filtering at best).

I don't think the core idea in the post would work, though. Scarcity would only be present in the app, genders that enjoy a natural abundance of choice would probably open the other apps after swiping left on everyone in this one.
> Well, it's also a problem of device manufacturers dropping support for devices too quickly. There are still android 4.1 devices sold on amazon, and you really can't expect web developers to support that.

Are you kidding me? If you're looking for shiny stuff to add to your resume, yeah, you can't possibly support those! If you're an HTML5 game developer, yeah, gotta use the latest and greatest. But if you're in the business of selling shoes, why do you need anything newer than Android 4.1 in order to process the transactions?!
I stand corrected. But in all honesty, that smacks of privileged elitism. Do these pop quiz, brain teaser interviews really prove the person can be successful on the job at Google?
OKRs require empowered product teams
Back then, most all the Javascript you ever saw was client-side form validation. Single-page-apps were still a long way off, so all web apps were built in form submission style: the user fills out some form data, it gets sent to the server, the server tells them they filled it out wrong and re-presents the form to the user. You could make that a little more user-friendly by having Javascript validate the form _before_ the users submitted it: but you had to validate it again on the server side because the user might have Javascript turned off, or might be a hacker. That meant that, for most web developers, Javascript just meant extra work: you had to duplicate your form-validation logic in a very finicky, untestable, untyped programming language. Browser makers were working on adding some flashier stuff like drop-down menus and image rollovers, but they didn’t work across different browsers (all both of them), so even the few people who did know how to use the extensions were encouraged not to. It seemed like everybody who could avoid Javascript did - I can’t really for the life of me understand how the early Javascript developers actually got anything done in it. It was a really painful way to develop software until maybe ten years ago.
Yeah, who doesn't think this will devolve into voting rings and positive re-enforcement loops?

I don't see how this will turn out well.

I think they are better off with self-regulated groups ala Flickr and Reddit with some appeals system (like Flickr). Otherwise it will be abused because it's set up that way.
I'm not sure that I follow your point. What would you have people do instead? It seems to me that having a home in a place one wants to live is part of basic prosperity.
Thanks, that's very helpful, and explains why mel-cepstrum didn't work so well. So far, I found that I'm getting the best results with FFT + log scale, particularly against audio with fundamentals stripped.
(thanks mrkurt)

It is anycast that I'm going after. Requirement for unmetered bandwidth (or cheaper than AWS et al) is because of the kind of workloads (TURN relays, proxy, tunnels etc) we'd deal with gets expensive, otherwise. For another related workload, per-request pricing gets expensive, again, due to the nature of the workload (to the tune 100k requests per user per month).

So far, for the former (TURN relays etc), I've found using AWS Global Accelerator and/or GCP's GLB to be the easiest way to do anycast but the bandwidth is slightly on the expensive side. Fly.io matches the pricing in terms of network bandwidth (as promised on the website), so that's a positive but GCP/AWS have a wider footprint. Cloudflare's Magic Transit is another potential solution, but requires an enterprise plan and one needs to bring-your-own-anycast-IP and origin-servers.

For the latter (latency-sensitive workload with ~100k+ reqs / month), Cloudflare Workers (200+ locations minus China) are a great fit though would get expensive once we hit a certain scale. Plus, they're limited to L7 HTTP reqs, only. Whilst, I believe, fly.io can do L4.
> Some emulators have run-ahead now, which removes internal processing frames from games. Combined with an adaptive sync monitor, 1000hz USB polling, and other tricks, emulators can actually respond to inputs faster than the original gaming consoles did on CRTs. It's pretty much the closest thing we have to magic.

Super Smash Bros Melee has a little bit of polling lag on console (the tournament standard) due to poor coding. By removing this lag (or rather, making it configurable), you can "hide" network latency behind this lag people are used to, and online play can feel like local play.

Like you said, magic!
It really depends how much you care about your parents/grandparents. If the projections out of Harvard today are correct and 40-70% of the world population ultimately contracts the virus, and if the mortality rates of those over 60 are correct - then there's a very real chance that many of the people on this thread will be attending the funerals of family members within the next 18-24 months.

The internet is full of people in the younger demographic, so it's not surprising they are not overly concerned.
Fun to see `sentry.io` as one of the dependencies, kind of an interesting level of recursion on an incident mgmt app
Or, to put that another way: if you knew what algorithm the AI would be using to discriminate the signal from the noise in your data, why would you need the AI? Just write that algorithm.
this may be a low emotional intelligence take, but I've often thought that dating and hiring are fairly similar problems. you're almost suggesting that people submit dating resumes and cover letters for consideration. on the one hand it seems strange that we don't use even the weakest signals used by hiring managers when we search for potential matches. on the other hand, this would obviously take a lot of the "humanity" (for lack of a better word) out of the process.

for what it's worth, I've never really encountered issues with people outright lying or seriously misrepresenting themselves on dating apps. the people I've met up with were more or less "as advertised". I think the problem is more that a couple pictures and a short bio just aren't a lot to go on for judging compatibility. also in my experience, people tend to have a list of things they definitely don't want in a partner, but don't actually know what they do want. all my successful long-term relationships have been with people I knew for a while before I ever considered dating them. I never considered them an obvious match upon meeting them.
Why would anybody expect blue ticks to behave "good" in the first place? Even being a high ranking professional with plenty to lose is no guarantee that they won't, nor is there any guarantee that lower levels will be better.

The only thing to hint is if there is some sort of enforcement mechanism but that is a foregone "who watches the watchers" situation.
Excellent point. If we are building these rigs by hand (which is a likely option considering the initial usage context), the cooling solution would probably be a Noctua NH-U14S or similar. I already have one of these in my office attached to a 2950X and it is dead silent. You can definitely hear it when every core is pegged, but it's hardly noticeable over any other arbitrary workstation. The sound is nowhere near as intrusive as something like a blower on a GPU (or god forbid a sun microsystems blade).
I'm not sure there is a rise. 'Science' is a huge domain. Machine learning if I had to guess maybe plays a role in < 1% of them, and that may be overstating it.

Also it's doubtful to even categorize machine-learning as science. The goal of science is to generate insight and knowledge, ML solves particular engineering problems or searches problem spaces, it doesn't build fundamental scientific models.
If you had one solid money fountain, isn't that what you'd also do, though? Throw a lot of other things at the wall which you expect would have a high chance of failure but high reward if they succeed. (Though Amazon seems to have managed something similar without randomly shutting down AWS services and such.)
For someone 'rational' and 'cool-headed' you seem awfully hysterical, peppering this entire discussion with your certainty. It's fascinating.
Yep, that's the other side of the "resume-driven development" coin.
Kepler’s Scientists Are Doing What Seems Impossible: Turning Pixels into Planets
Pretty sure this is just crappy microservice engineering where the microservices disagree with each other. I always see the match counter being wrong, matches I declined linger anywhere between an hour and a day...

I just disable all notifications from these apps.
Rules to Cook By
Definitely!

Actually, just a recent observation with Jehovah's witnesses. There were always ladies that looked like they passed 100 years, giving out free advertisements in European train stations. Recently they use girls with tremendous fuckability!
Webpage Screen Resolution Simulator
Yes, I think that will help. For me personally it is also helpful to be able to analyze the problem by myself, without having to talk through it. Being able to write some code in an editor is also helpful as it springs my brain into action. Not sure how to adapt all of that for a whiteboard interview. Maybe a mental trick? Or an entirely different way to approach the problem?
I think the accessibility of web browsers and npm allowed the JavaScript ecosystem to explode, hence it's staying power.
I loved building JavaScript apps when JavaScript wasn’t cool yet. (2006-2010)
partition p xs = foldr (select p) ([],[]) xs
select p x ~(ts,fs) | p x = (x:ts,fs)
| otherwise = (ts, x:fs)

That is the entirety of `partition` in the standard library.
Thank goodness you are completely incorrect on all of your points.

As a self-admitted solid 5/10 average-as-it-gets human, not only do I acknowledge my own existence, but I've also managed to, somehow, get dates.

Said more crassly: Perhaps not everyone is as shallow as you.
Because that high-compute job needs to be distributed on many, many machines, and if you're using cheap preemptible instances you have to handle machines dropping off and joining in while you're running that single job.

It's definitely not something that you can launch manually - perhaps Kubernetes is not the best solution, but you definitely need some automation.
> except that blockchain processing in a datacenter is permitted

Well, Nvidia, y'see, my new blockchain does AI training as its Proof-of-Work step...
Yep, I made it through the hiring committee and got denied at the SVP level. Was fun getting a literal congrats from the recruiter, then meeting my future team that gave me the thumbs up, then getting a call that it wasn’t going to happen... rough rollercoaster
These days, though, you can have it both ways with a Jupyter notebook or something similar. It's literate, in that you can keep thoughts and discussion in markdown cells, and you can neatly combine computations in computation cells.
Some kinds of inference are expensive, yes, not going to dispute that. But 99.95% of it is actually surprisingly inexpensive. Hell, a lot of useful workloads can be deployed on a cell phone nowadays, and that fraction will increase over time, further reducing inference costs or eliminating them outright (or rather moving them to the consumer).

For the vast majority of people the main expense is creating the combination of a dataset and model that works for their practical problem, with the dataset being the harder (and sometimes more expensive) problem of the two.

The dataset is also their "moat", even though most of them don't realize it, and don't put enough care into that part of the pipeline.
Thanks for the reply!

Yeah; I always added type annotations to my code and ran Dialyzer...I wish there was a stricter compilation mode for that. That said, I really liked the 'optimistic' part of it, so I didn't spend a large amount of time correcting my type specs when proper testing proved it work.

I can agree with bfrog's comment too; Rust's typing can definitely help eliminate a bunch of classes of bugs...but honestly I'm not sure I ever ran into them using Erlang in production anyway. Immutable data + message passing tends to make it easy to implement things correctly, whereas some of Rust's more standout features seem designed to solve problems caused by the language itself picking a different set of tradeoffs (i.e., borrow checking as part of what is necessary to manage memory without risking it going out of scope prematurely, or being unable to be reclaimed at a deterministic time by the compiler). I'm not familiar enough with Rust myself to really comment though; I just know that in two and a half years of production Erlang, the only bug we ever encountered was caused by a C driver (and our own bad design in not circuit breaking calls to it, leading to restarts that trickled up the supervisor chain under heavier load than we'd tested for. None of which would Rust have been able to help us with. In fact, even the driver, the issue was an unnecessary network call that sometimes hit an empty cache, causing a huge network hiccup that led to an unhandled timeout). It got 'correctness' as well as 'fault tolerance'. At least as much as a language can (i.e., we could still implement the wrong things, such as when we implemented an O(N^2), but correct, algorithm, that we had to fix to an O(N) when we noticed certain calls being too slow)
No mention of MASS by Microsoft? It was afaik one of the first pretraining schemes for a full transformer outside of XLM.

Imho a bit unfortunate, as is calling the decoder or the encoder of a transformer "a transformer", as it has happened with GPT and BERT, which now forces people to use "full transformer" or using phrases like the title of the blog post.
Sorry, Building a Chatbot Doesn’t Make You an A.I. Company
I don't doubt that -- but as Gizmo385 noted, conservative journalists get blue checkmarks, too. (Just as a sort of anecdotal check, I looked up the eight people on the masthead of The Bulwark, a pretty new conservative online publication, and everyone but the art director has a blue checkmark, as do three of the five non-masthead contributors.) So the question still stands.

(If you're implicitly suggesting that journalists tend as an overall class to skew left-of-center, there's a good case to be made for that -- but that's not a Twitter bias!)
I don't think the intention is to persuade them. But simply by asking questions you start wheels turning that weren't turning before. Then they have to persuade themselves.
You don’t owe your employer undying loyalty
There have been a few pandemics in the last 100 years... A very recent one being the 2009 flu pandemic (swine flu).

HIV is an ongoing pandemic.
Fast forward 25 years and we have three different semantics for "not a thing"
You can get the best of both worlds by self-hosting and putting a CDN in front of that. This way you get robustness and your app will still function in isolation
Sssh! Valuations are a function of projected market size and opacity of the problem. Clarity like this collapses the uncertainty and destroys value. If you pour enough capital into rooms full of PhD's something's gotta hit.

My way of saying, you're very, very right.
I just spent $50K on coloc hardware. I'm taking a $10K/mo Azure spend down to a $1K/mo hosting cost.

But the real kicker is that I get x5 the cores, x20 RAM, x10 storage, and a couple of GPUs. I'm running last-generation Infiniband (56gb/sec) and modern U.2 SSDs (say 500MB/sec per device).

I figure it is going to take me about $10K in labor to move and then $1K/mo to maintain and pay for services that are bundled in the cloud. And because I have all this dedicated hardware, I don't have to mess around with docker/k8s/etc.

It's not really a big data problem but it shows the ROI on owning your own hardware. If you need 100 servers for one day per month, the cloud is amazing. But I do a bunch of resampling, simple models, and interactive BI type stuff, so co-loc wins easily.
catholic girls, you know how they go after the show...
I have two friends who told me they were trying to get competing offers so that they could use it in their promo packet. One was in the ads team, extremely sharp guy, trying to make Staff level in his 3rd year there.

Joe Beda, one of the creators of Kubernetes, had a giant competing offering from Facebook. Turned it down to stay at Google, got some more freedom, and now we have Kubernetes (!).

If you look on Blind, there is plenty of discussion of using counter offers to force the promo process to work.
> In the shell case, the terse program is like a Chinese classic. Written in its own jargon requiring basically a prior understanding of the program to read it.

However, if Knuth wanted to be terse, he could have been and write a Pascal program which uses his library routines without showing them ! -- in effect using Unix solution by Doug is equivalent to "not only you must use already pre-written libraries in order to be terse, they are even not the plain routines but they are instead packed as the whole executables, and to use these executables you have to use them on exactly this operating system, exactly using this specific shell, all that property of AT&T (at that time Linux didn't exist, and who had rights to use what wasn't clear, unless you've bought something expensive) just to be able to call these library routines.

So it can't be considered a serious "critique." At that time, under these circumstances, it was just an unfair ad.
Hahaha, I used to work for the parent company of AM and it is largely bullshit. I’d love to do an AMA about it sometime.

But, I mean, who would’ve guessed a company based on the idea of having affairs would have shady as fuck business practices? eye roll
When I worked as a consultant, mostly remote, working from Argentina was awesome. Buenos Aires is a great city, and the time difference is perfect for the lifestyle, as you are generally slightly ahead of the US, so you can play late and sleep in a bit while still getting a normal business hours day in.
Rest in peace, and thanks for the inspiration of what a dedicated, hard working person can achieve. I'm glad she got to receive the recognition she deserved in her life.
I was training ML models on AWS / Google Colab. After racking up a few hundred dollars on AWS I bought a Titan RTX (I also play video games so it does that very well also.
The tricky thing is that any text content has to have translation. You might be able to get away with not translating maps, since place names tend to be more stable (or at least generally pretty easy to work out) across different languages. For example, "Pologne-Lituanie" is going to be within the capability of most English speakers to work out, even if they've never heard of "Poland-Lithuania".

It is possible to link images and other things via Wikimedia, and my understanding is that Wikipedia does push for people to do this.
Being downvoted by people that don't know their Slashdot+iPod history:

https://slashdot.org/story/01/10/23/1816257/apple-releases-i...
I predict a great future for startups that sell pickaxes, err, tools for AI.

AI is like the new gold rush. And just like back then, it's not the gold diggers that will get rich.

"Most people in AI forget that the hardest part of building a new AI solution or product is not the AI or algorithms — it’s the data collection and labeling."

https://medium.com/startup-grind/fueling-the-ai-gold-rush-7a...

(from 2017)
Ugh but it’s so hard to let this go, I lie awake at night thinking to myself “stop spending so much time doing work” and every morning I wake up and crush work again because it feels good. Work is like a drug :p
Start at a big company. The brand recognition will get you more interviews in the future, and Big companies hire a lot of people... which if you're spry will allow you to build a decent network (effectively alumni). Of course the work is significantly less stimulating and if you have an entrepreneurial spirit you'll be progressively more bothered by the bureaucracy (as a gross generalization), but generally the tradeoffs are worth it for ~2-3 years
Purely speculative and something I haven't thought that much about, but my immediate answer is that men are more desperate and trying everything they can.

Women have an easier time getting attention/dates in general so fewer of them bother with online dating at all.
electric wont kill diesel as towing still kills the battery fast. once electrics can tow long distances then I will worry for the tech. (in consumer of course disel is dead and in some states yes, electric is better . ie southern cali and if your rich enough to have solar panels )
To be fair, Google in the early-mid 2000s was actually a really good career option. If you played your cards right you could easily be comfortably retired today if you started at Google in, say, 2004. In fact I know someone who started at Google fresh out of college in 2005 and was in "FIRE" (Financial Independence, Retire Early) zone by 2017. They quit Google, didn't work for a couple of years, and then took a senior position at a San Francisco startup, where they work 35-hour weeks playing with shiny new hardware tech and couldn't care less whether they're laid off.

Google is still a great place to land as a new college grad, but these days I would consider many other options as an experienced professional. There are indicators that Google is starting to run into issues detailed in The Innovator's Dilemma, particularly with respect to its Cloud business.
Show HN: Chrome Extension to Test Multiple Endpoints
A problem I have at work is that when there is a bug in an environment we usually have to check a handful of endpoints to rule out any particular problems. This process is tedious and way to manual for 2020!

We can use postman, but our testing are usually endpoints that are easier to test with the browser. So in that vein I created this Chrome Extension that allows you to upload a JSON or Yaml file with all of the endpoints you want to test and produces a report with the response body and other particulars of the calls.

I built this with Stenciljs and Semantic Ui.

github: https://github.com/grantlouisherman/rest-diagnostic-stencil

Chrome Webstore: https://chrome.google.com/webstore/detail/rest-diagnostic-tool/bhjmilcdbpbhpnokhkhmphfgbikhiojd

I would love feedback of other ideas on how to improve. If you hate it, please be kind :)
> support every single stupid thing (among thousands) and even mimic some of the bugs so that models work "the same".

Do you need to do the stupid things performantly, though? Because that sounds like a case for skipping microcode shims, and going straight to instructions that trap into a software implementation. Or just running the whole compute-kernel in a driver-side software emulator that then compiles real sub-kernels for each stretch of non-stupid GPGPU instructions, uploads those, and then calls into them from the software emulation at the right moments. Like a profile-guided JIT, but one that can't actually JIT everything, only some things.
The algorithms that run on cell phones tend to be specially optimized and quality-reduced neural networks. For example, https://arxiv.org/abs/1704.04861