tastyminerals

You should also try D to see that seamless C interop has always been there for many years.

It may outclass it in performance. However, all my life I've been waiting for something that runs over 10h on a single charge. I am naturally surprised that this is not something that ppl truly appreciate in a laptop. Hell, I even bought a cheap Atom laptop once just to have more battery time. So as of now, there's literally no decent competitor to M1 laptops. One must be living under a rock to buy anything but Apple and this is coming from someone who doesn't have Apple products and always hated their walled off ecosystem. I am reconsidering my life choices :)

What?! There are static languages that compile faster: Nim, D... Honestly, I used ggplotD library and it takes roughly two seconds to compile and miliseconds to show the plot.

Julia is fast but not faster and very memory hungry. If you care about squeezing every bit of performance you generally go to C++. If you too lazy for C++ you go D. Hence to me, Julia is an odd tool. Interesting but more as a language with some cool scientific libs that Python might not yet have.

Noice! Reading through the release notes leaves a feeling of D being a mature language long enough.

If you're looking for magnitutes faster scripting alternative to Python like once me, take a peek!

Rust is not a very good example here considering the amount of time the op might have spent waiting for the compiler and steep learning curve of the language...

Why don't you try D if type-and-compile is what you enjoy?

not on mobile but as a service -- Abbyy is the market leader in OCR from documents.

Julia looks more like Python than a fp language tbo and that was why I staed away. The most elegant fp code I've seen was written in Scala.

I read through Arraymancer readme and the rationale and got very mixed feelings about the project and its purpose. It's everything and nothing at the same time. NumPy like syntax and functionality, sklearn algorithms and look, deep learning too, here is and example and some screens which we borrowed from Scipy. Seriously? Sorry if that might be too judgemental but it sounds and looks amateurish. And I thought of benchmarking it against D mir... Also, the name... And this is what I feel about Nim in general, rushed and undercooked.

Thanks. So here are the points for D according to the table. Very few breaking changes because language is pretty mature. Not sure if Nim is as stable but just this one fact is enough for me personally.

D has slices, ranges and lazy evaluation which is a joy when you do data number crunching. Nim does not have them.

Also no mention of dpp in a table is surprising tbo.

D PRs take time mostly because they go through a rigorous community review. And by that I mean your PR does need to hit the quality bar. Which is only good and does not make a language a sandbox of community features like C++. See the PR for macros in D and why it didn't happen. Another reason is the lack of people of course.

Also, all good points. Appreciate that.

Thank you for the detailed answer. It clears things up.

Ok. But going back to the issue. I live in Munich and know at least two big companies who use D in production and organize meetups. I have yet to see a single company that uses Nim.

It was a developed by too few ppl from the start and by the time it became usable it was way too late

Are you the same person who attacked ppl on D forum. The nickname is familiar and the style ;)

Chill. All languages have dusty corners and given the amount of ppl D has it's obvious that not all things are fixed in time but they were and they will, history already proved it. Besides, complaining is easier right?

Depends on where do you read ;) But tbo D community concentrates around D forum and in majority consists of former C/C++ veterans. Being a younger language Nim lures younger and active members who probably never heard of D anyway.

Historically D never advertised itself enough imho and that is a shame. I blame the lack of proper leadership and management at the start. Its early development progress has been a rocky ride many languages would not survive at all but it did and for me personally it's a testament to its maturity and resilience newer languages still have to prove.

With all due respect, Nim is a great language performance wise however I fail to see how is it different from D. Many advertised features have been present in D for a long time.

Syntax wise Nim it is a step back. It's hard to read and understand while any C/C++ dev will have next to no effort reading through D code. And of course while D is C ABI compliant it interoperates with C++ well too.

I seriously doubt that Nim or any other language in this regard has better metaprogramming than D.

Nim might have a speed overhead in certain tasks but that depends on a benchmark. Besides, does Nim have anything similar to NumPy which is actually faster? D does.

Can you be a little bit more concrete about the tech you are building right now that is not possible to build using classic ML approaches? You see, I am actually going to work thinking about how should we reduce the model size and still keep it within reasonable accuracy bounds so it would not be worse than a rule-based mixed with classic ML system that we use. And here I learn about immesuarable potential, insults and billions of dollars.

I thought so too, now I believe that it was sheer naivety. If anything, the realization that education matters is the last thing they come to because this is not their task. Pumping resources out while maintaining the belief of being competitive is what all this government was doing all the time. Take a look at the yearly budget, you don't need to go too far. And it was like this since I remember. Nothing changed in the colony except the managers.

You can't even imagine. The whole east Russian speaking conglomerate of contries is basically a test to your human nature and survivalism.

And don't forget that "modern alternative" should boast as good as Lua C ffi which is a tough thing to beat. Should I mention luajit?

Once you get to know Lua tables and then metatables, you will question the existence of different data structures :)

D, Rust -- just what first springs to mind.

I feel like MS laptops are getting bashed left and right by various online experts these days without a decent reason. Apple products are not less cheaper and follow the same "100EUR for a charger" scheme. If you calculate the totals, MS laptop is no more experiensive than the Apple one. Except with MS products you also get a true mobile experience if that is what you are after.

The only drawback is Windows and its tooling. Which you can still circumvent with WLS. I wish Surface lineup was 100% Linux compatible, alas.

I have surface book 2 and have been using it both for development via WLS + VS code and as a tablet for drawing, taking meeting notes etc. I would never come back to Mac or any Linux compatible laptop because I got used to its versatility.

I simply cannot comprehend how a laptop with detachable screen, which is powered by GTX1060 and has by far the longest battery life on the market can be awkward. Couple this with better than mac keyboard, good 4k display and corpus that never overheats like Mac. It is also more silent. Please tell me which laptop currently has all these features?

For accuracy and speed. The market SOTA Abbyy is far from being accurate.

NLP algorithms are just fine. It is the combination of regexes, NLP and deep learning that allows you to achieve good extraction results. So, basically OCR / pdf parser -> jpeg/xml/json -> regexes + NLP / DL extractor.

Gini GmbH performs document processing for almost all German banks and for many accounting companies. For banks it does realtime invoice photo processing -- OCR and extraction of amount, bank information, receiver etc. For accounting it extracts all kind of data from a PDF. Unfortunately, only for German language market. But here you go, ABBYY by far is not the only one. In fact ABBYY does only OCR and has some mediocre table detection. That's it.

Yes, most invoices are in PDF but only about 40% of them are native PDF meaning they are actual documents not scanned images converted to PDFs. There are are also compound PDF invoices which contain images. So, in order to extract data from them, one needs not only good PDF parser but an OCR engine too.