skysight-inc/HackerNews huggingface dataset:
I doubt there a cli or "hacker" ways of creating a roadmap. For a dead simple roadmap you just need a bullet point list with the items sorted in the order you want to crack them.

I do some personal goals and plans for the year in Evernote, which is to say, not a hacker way at all. But it works and I just need to sync between 2 devices.

Trello, Spreadsheet, and Presentation are another good way to build a roadmap. Again, far from being a hacker way but it works with small teams. In fact, it also works for huge companies. I've seen powerpoint used for building roadmap in a 2K+ person company.

Finally, the least hacker way but probably the most comfortable (when you know exactly what you need) is to use existing tools made for this specifically:

- https://www.getshipit.com

- https://www.productboard.com

- https://www.productplan.com

- https://craft.io

- https://www.prodpad.com
New insights into genes that drive cancer: A study of 2,700 samples
An Android infection persisted after a factory reset
>The nice thing about the Go/Lua journal is that it’s far more flexible than the C# version, due to being able to write pages in Lua. Which means I’ll be able to

To what?!?! D:
Only if someone wrote that epub in the first place, though.
Honestly if Facebook had not been so savvy and bought Instagram and WhatsApp it is likely it would of been considered a failure already
Of all the “irresponsible” uses of energy, this is the one I endorse the most.
The key is that the input needs to be comprehensible.

If you bootstrapped those people with a month or two of 1:1 lessons with a native speaker and then started them watching anime aimed at young kids with no subtitles, slowly moving them up to more complex examples, still without subtitles, they would end up learning to understand Japanese passably well after enough hours of it.

If you just dump them “countless hours” of complicated Japanese which they can ignore while reading English subtitles, then they’re going to end up learning a few words and phrases but not really becoming fluent.

If they started with poor English reading skill it’s not a completely useless way to practice that though. (Reading books would be better, but reading anime subtitles is better than nothing.)
> Also, export doesn't help as note links are internal references.

During export Trilium fixes the internal references to standard HTML links so they reference pages in the structure like "./sub-folder/my-topic.html" (but yeah, it was not always like that).
But

> Did you win the Putnam? [0]

[0]: https://news.ycombinator.com/item?id=35076
Wow this looks amazing.

I don't exactly understand, how the texturing works:

"Buildings were textured using a procedural system which utilized a shader that could overlay 2 UV regions from a single atlas. Each UV tile could be spread apart with an offset to get the proper spacing between windows and other detail elements"

This sounds like magic to me.
Hangul Word Processor
Destiny – Prettier for File Structures (JavaScript Only)
Easy, have a look at the quality of Tizen.

https://what.thedailywtf.com/topic/15001/enlightened
Byuu 0.8 (first beta of Higan developer's new multi-system emulator)
Just like Google Android team does, oh wait...
Is UOS a Deepin OS with a new theme? Its developer responds
I use a collection of tools from this repo to automate mundane developer activities such as posting release notes slack messages containing linked pivotal or Jira story titles: https://github.com/sufyanadam/pivotoolz

There's a bunch of stuff in there that saves you seconds each time you have to work with a user story or cut a branch or merge etc... Saved me a bunch of time over the years!
Show HN: IRedis: CLI for Redis with AutoCompletion and Syntax Highlighting
A previous Met Office supercomputer purchase was discussed here:
https://news.ycombinator.com/item?id=8519820
Annapurna Circuit Trek
Such as a security bot?
Some of the best books I’ve read in my life, I picked up almost randomly in a store - maybe they were highlighted by employees, maybe they had a particularly nice cover or backcover... that feeling of having discovered a gem on my own, or the fun of spending an hour browsing dozens of books to find The One, maybe talking about it with friends or employees, is so satisfying that it keeps me going back.

The online experience is severely lacking, imho. Maybe it will be different for generations that grew up with Amazon, but to me the bookstore experience is superior. I think they are missing a trick by not allowing me to couple their experience of serendipitous discovery with the convenience of ebooks.
How education Technology is shaping the lives of students
> That only seems to work in children [...] it takes work for us adults!

It takes a lot of hard work for children too. They just have no other choice, and usually some adults going way out of their way to help as much as they can.

> beginner book/audio recommendations if you want

Please! Anything with an easy level but appropriate subject matter for young kids?

I studied French in high school and would like to start reading some French kids books to my 3.5 year old, but I haven’t made the effort to find any yet.
I appreciate the author sharing his experience but I must admit that it was less exciting that I expected it to be. He basically used off-the-shelf hardware, ran an off-the-shelf program and then waited for a while. There's no obvious innovation, anybody who cares enough to break that record and has ~$20k lying around can do it.

If anything it got me a lot more curious about this y-cruncher program and all the fun optimizations it must implement.
If you're talking about Jax, there's a couple different reasons to bother for research

1. Full numpy compatibility.

2. More efficient higher order gradients (because of forward mode auto diff). Naively it's asymptotic improvement, but I believe Pytorch uses some autodiff tricks to perform higher order gradients with backwards mode, at the cost of a decently high constant factor.

3. Some cool transformations like vmap.

4. Full code gen, which is neat especially for scientific computing purposes.

5. A neat API for higher order gradients.

2. and 5. are the most appealing for DL research, 1., 3. and 4. are appealing for those in the stats/scientific computing communities.

PyTorch is working on all of these, to various degrees of effort, but Jax currently has an advantage in these points (and may have a fundamental advantage in design in some).
Yeah, you probably right. I am always puzzled about how much math to include and how deep to go on an introductory article. Thanks for your feedback
A very good point that experience has taught me:

It is not a platform language. Thus just like any guest language brings its own tooling, idiomatic library wrappers around platform libraries, an additional code generation layer to debug, having to write FFI (or type declarations to platform libs).

Having said this, I do use TypeScript in the context of Angular or BabylonJS, but that is because those frameworks are the "platform".
Does the Sound of Noisy Eating Drive You Mad? Here's Why
15min of looking through the code and my best guess right now is that it's a reimplementation of higher-level primitives, such as optimizers and layers, found in Tensorflow/Pytorch/etc, but based on a variable backend (you can pick jax or TF), together with a collection of models and training loops. I think the idea is that most of the code is simpler and more modular than what you would find in TF, which makes the models easier to read.

However, I don't yet understand what the use case is, or how it helps you to "learn" anything.
I would hope if you're doing serious opsec you're using ephemeral keys or isolated virtual environments for various endeavors.
That isn't very basic and never has been. If it's just a read-only site then all you need is a CDN, not load balancing with multiple regions running Kubernetes clusters.

What other cloud vendor or PaaS offers this? The only one that has seamless global deployment is Cloudflare's Workers but that's limited to Javascript code in a lightweight functions environment.
Enterprise Web and Mobile App Development Company in USA
Is your problem that you know its bot-generated, or that you think there's some flaw in the pictures?

What if you didn't know that the painting was the work of a bot?

What if it was just some abstract painting that someone took enough fancy to to pay to have put on a canvas?

Personally, I couldn't really tell them from the human-generated wikiart pictures that seeded the algorithm. Those human-generated pieces didn't speak to me either.

I'd love to see the algorithm work on some other art style seeds.
But what is it? It says it is an API or module? Is it a DL framework? Is it an extension of TF/Jax with new models? Is it a set of tutorials? Are we to work through the code? Is a part of the doc for Jax? Is it a set of implementations of Jax code into concrete models?

All these things come to mind when going through this Github.

By now I think to have figured out that it is a module that implements some DL models using Jax. So it is like an extension to Jax. It "helps" you to understand how to build the models in Jax if you go through the code. You could also load these abstractions as a Python module and use them in code, but I would doubt that this would "help you understand deep learning". So the real intention is to go through the code and see how Jax implements, for example, a transformer.

Alternatively, this could be an early stage of some PyTorch-type framework over Jax and TF. So essentially, another Keras.
1 ulp precision means that there are at most two possible results from given operations. Without an explicit guarantee (probably impossible, as this would essentially pin the algorithm down) they are still not reproducible.
Hey gojomo,

It's pronounced it 'kweh-muse'.
Obviously there are reasonable requests and making sure you get your work done, but the last two companies have been my own startups and we have no hard limit.

If you have one where you work then it looks like it's a culture issue, as I've been saying.
Now, some of you may not ever write computer programs, but perhaps you cook. And if you cook, unless you're really great, you probably use recipes. And, if you use recipes, you've probably had the experience of getting a copy of a recipe from a friend who's sharing it. And you've probably also had the experience — unless you're a total neophyte — of changing a recipe. You know, it says certain things, but you don't have to do exactly that. You can leave out some ingredients. Add some mushrooms, 'cause you like mushrooms. Put in less salt because your doctor said you should cut down on salt — whatever. You can even make bigger changes according to your skill. And if you've made changes in a recipe, and you cook it for your friends, and they like it, one of your friends might say, “Hey, could I have the recipe?” And then, what do you do? You could write down your modified version of the recipe and make a copy for your friend. These are the natural things to do with functionally useful recipes of any kind.

Now a recipe is a lot like a computer program. A computer program's a lot like a recipe: a series of steps to be carried out to get some result that you want. So it's just as natural to do those same things with computer programs — hand a copy to your friend. Make changes in it because the job it was written to do isn't exactly what you want. It did a great job for somebody else, but your job is a different job. And after you've changed it, that's likely to be useful for other people. Maybe they have a job to do that's like the job you do. So they ask, “Hey, can I have a copy?” Of course, if you're a nice person, you're going to give a copy. That's the way to be a decent person.

— Richard Stallman, 2001 (https://www.gnu.org/philosophy/rms-nyu-2001-transcript.html)
Why cubist?

Is it that that's the style of art you like?

Or that you found to work best?

It would be really interesting to see the kind of images generated when its trained with other styles.
If that's important, you'll need to generate two sets of keys, explicitly assign one to each place and set IdentitiesOnly in your SSH configuration.

Most people don't care about this and so I'm comfortable with the default not being IdentitiesOnly

It's probably more surprising for any early adopters of FIDO for SSH, since WebAuthn (to do FIDO on the web) and its predecessor U2F both do ensure your identity can't be correlated between sites, but the new SSH support does not provide that.
The OS recovered right?

It was your program that did not
I have reviewed for a handful of organisations. My learning is that different orgs and funding programs need different emphasis. H2020 is all process and consortium, Epsrc is project and ambition.
The pricing changes to Maps were 2 years ago, that's hardly a pattern.

Microsoft also ends support for products every year, often with replacements, but there's still migration costs:
https://support.microsoft.com/en-us/help/4470235/products-en...

Apple also deprecates core APIs, not always with a replacement:
https://stackoverflow.com/a/53285999

Google does turn down lots of (smaller) free consumer services, but the meme that their behavior around consumer products should translate into not trusting them for B2B is not backed up in their behavior or historical data around support. They behave similarly to all the other major companies.

For example the App Engine Datastore has existed for 12 years and still works, despite the availability of Firebase RTDB, FireStore, Cloud Spanner, Cloud BigTable, etc.
Maybe? I'm guessing googlers are more in the 97-98 percentiles.
Trax is meant as a successor to Tensor2Tensor.

From my understanding of what Tensor2Tensor was (and thus what Trax is):

Basically, at it's core, it's a library of models, datasets, and utilities that are meant to be clear and work together nicely.

This is meant to be good for education, as you have an easy and unified way to run SOTA trained models on a wide variety of datasets.

This is also meant to be good for research, as much of research involves building on top of other people's models, and having a library of models with shared API (as opposed to the fragmented wilderness that is public research code) is meant to facilitate that.

I believe that it also ended up being used in industry as well, simply as a reliable source of pre-trained models.

PS: As Jax did not have an "official" neural network library until very recently, this also served as a neural network library for Jax.
You can define ‘better’ as quantifiable metrics like execution time. Check out the use of program synthesis in compilers for a actual use case of something similar :)
> I believe you have to be ideologically motivated to do this now, because it seems like a lot of average web users have come to expect SPA-style apps with fancy animations and client-side interactivity, and that's where a lot of interest in web design appears to lie at present.

A key point the author made in the article was that simplicity is appreciated. Here's an analogy: if Snapchat is the equivalent of an SPA-style site with fancy animations etc, then his app is a static webpage.

Just consider for a moment: the reason these analogies to old technology are even necessary is because what this one amateur did today would have definitely taken a team of engineers to accomplish 12 years ago.

You are absolutely correct, the standards for professional pop tech are always being raised to new levels, just like with every field, e.g. cooking. Nobody is saying opening a successful restaurant is getting any easier. However, amateur gourmet cooking for the family is demonstrably much easier today than ever before in history.
As someone, whose side project[1] graduated into a full-time company, I agree with a lot of stuff in this post -

> Lesson 0: Programming in a void is worthless

100% true. If you are trying to learn a language without a goal, you'll probably never graduate from tutorials. Imposing your own requirements/boundaries, just makes the learning part more engrossing and you'll make connections which you won't otherwise. Iterating as fast as possible is worthwile itself.

If you want to grow as a programmer even more, try to convert that side project into a paid one. It definitely changes your view of the world. As programmers, we want to see elegance in code but real life is messy. We want to separate the world of programming from the human life and sometimes for good reason. You might find satisfaction in writing pure code (and that's great) but there's an opposite world too which will humble the strong opinions within you. Haggling about microservices vs monoliths seems trivial in the grand scheme of things (the customer doesn't care!). I still debate about this with fellow devs but at the end of the day, I really don't get stressed about it. For me, programming is pretty much only about building solutions to existing problems which improves my or others lives. Everything else is just an opinion which will not be considered until its time is due.

> Lesson 2: Organizing my thoughts is important, but tricky to figure out

Agree. Especially difficult if the software doesn't structure the knowledge in the same way as we think. As a dev, I have never been satisfied with any specific solution. But don't fret honestly. It's unlikely that any given piece of software will work for all your cases. Always take the context into consideration. Plenty of times I work on paper if what I'm thinking doesn't go into a specific tool. Don't try to fit yourself into a box when your mind itself can't. That said, a mindmap (big picture) + a task manager (big picture broken down into specific tasks) + a note taking app (learnings + thoughts derived from completing specific tasks) covers most of my bases. For publicly available information, I store it in a tool of my own making[1]

[1] https://getliste.com
You wouldn't have an HR department as they currently exist, imo. Too many companies lump too many roles into that space because they don't fit need buckets besides "people stuff." Like just split of disputes into a department like you would compliance or an outside auditor.

But honestly it's an organizational systems and behavioral science problem. Look at the trends of HR problems that cause risk to the business (either directly through settlement or brand harm, or indirectly by losing good talent, also personal risk like being able to sleep at night), then isolate the feedback loops that allow the discord to amplify and eliminate them. So go trawl some unis that have systems researchers and spend money on IO psychologists, also listen to them because they're better educated on the subject than most business folks.
Pixels are not so easy to buy for some reason (outside of the US), only through the web site and some stores.

I'm also voting with my wallet against Apple taking out the headphone jack.
Unfucking the many many ways that banks screw up exporting financial transactions into well-formed OFX files that MoneyDance can consume
I don’t know about you, but if I were a big company evaluating vendors for my scientific computing / HPC cluster, whether or not a vendor has open source drivers would be pretty low on my priority list. If AMD comes out today with a CUDA competitor that people use with high adoption, companies will switch, and it won’t be because AMD’s drivers are open source.
KubeEdge v1.2 is out now – KubeEdge
> > Cigarette smoke feels like it sucks the air out of a nonsmoker's lungs from quite a wide radius [...] makes people involuntarily gag

> Unless you have an allergy or something, this is entirely in your head.

The fraction of the population with asthma is easily high enough that there's plenty of people for whom it's not in the head.

Personally I just hold my breath and speed up until I've passed those people, but its most definitely unpleasant.
Neither of these are Graph NNs though (although it was a weird question because Graph NNs solve a different problem)
I’m not sure, but to me at least halving 17 to get 8.5 is an almost completely intuitive process, whereas multiplying 17 by 5 seems to require an extra cognitive step to reduce it to shifting the decimal point and then halving (or vice versa). Never mind the extra step when presented by the problem of taking 17% of 50.
I discovered Skin as a teen and it rocked my sensibilities. I still find it to have the best adult dark humor short stories. What did you not like in Skin?
Note that this will vary greatly by funding agency and the specific call.

For example, the NSF can do a degree of steering, etc. The CDC, depending on program, has either full control, or absolutely none at all.
From a practitioner:

1. Meh. PyTorch is close enough to not worry about it, and is better in some places.

2. Meh. All the methods people use in practice for deep learning in particular do not use higher order gradients. Most higher order methods are prohibitively memory expensive, and memory is at a premium in acceleration hardware (and so is the bus bandwidth - so you can't "swap to RAM"). I do agree that higher order gradients are the next frontier in optimization though - current optimizer research seems to have stalled, so people focus on training with huge batches and stuff like that. Most SOTA models in my field are trained with SGD+momentum - super primitive stuff. I don't see how Jax would solve the memory problem though. You still have to store those Hessians somewhere, at least partially.

3. Do agree, that's cool if it actually parallelizes nontrivial stuff which e.g. tf.vectorized_map barfs on. Although in a lot of cases you can "vectorize" by concatenating input tensors into a higher dimensional tensor.

4. Meh. Not sure why I'd want that if I already have tracing and JIT.

5. This is #2

With PyTorch though, you get close enough to Numpy to feel at home in both, and there's so much code written for it already that you can usually find a good starting point for your research pretty easily on github and then build on top of that.

If you need to deploy, there's also tracing and jit, which lets you load and serve models with libtorch.

I see what you're saying regarding "advantages", I'm just pointing out that PyTorch might be "good enough" for most people. If I were on that team, I'd focus on providing comfortable transition from TF 2.x which is a dumpster fire (with the exception of TensorFlow Lite which is excellent). That, IMO, would be the only way for this project to achieve mainstream success unless PyTorch disintegrates over time.
Like others here, I am building something myself [1].

[1] https://dashboard.darekkay.com/docs/
I’ve Made More Than $300K from Writing