nio VS simonwillisonblog

Sure. No problem.

Even Windows has popen these days. There are some tiny popenr/popenw wrappers in https://github.com/c-blake/cligen/blob/master/cligen/osUt.ni...

Depending upon how balanced work is on either side of the pipe, you usually can even get parallel speed-up on multicore with almost no work. For example, there is no need to use quote-escaped CSV parsing libraries when you just read from a popen()d translator program producing an easier format: https://github.com/c-blake/nio/blob/main/utils/c2tsv.nim

I think it's a pretty nice prog.lang. You may be very happy. Though nothing is perfect, there is much to recommend it. By now I've written over 150 command-line tools with https://github.com/c-blake/cligen . A few are at https://github.com/c-blake/bu or https://github.com/c-blake/nio (screw 1970s COBOL-esque SQL) or in their own repos.

If it helps, I like to use the "mob branch" [0] of TinyCC/tcc [1] for really fast builds in debugging mode, but this may only work if you toss `@if tcc: mm:markAndSweep @end` or similar in your nim.cfg. Then I have a little `@if r: ...` so I can say `nim c -d:r foo` for a release build with gcc/whatever.

[0] https://repo.or.cz/w/tinycc.git

[1] https://en.wikipedia.org/wiki/Tiny_C_Compiler

When you have "format wars", the best idea is usually to have a converter program change to the easiest to work with format - unless this incurs a massive expansion in space as per some image/video formats.

With CSV-like data, bulk conversion from quoted-escaped RFC4180 CSV to a simpler-to-parse format is the best plan for several reasons. First, it may "catch on", help Microsoft/R/whoever embrace the format and in doing so squash many bugs written by "data analyst/scientist coders". Second, in a shell a|b run programs a & b in parallel on multi-core and allow things like csv2x|head -n10000|b. Third, bulk conversion to a random access file where literal delimiters cannot occur as non-delimiters allows trivial file segmentation to be nCores times faster (under often satisfied assumptions). There are some D tools for this in https://github.com/eBay/tsv-utils and a much smaller stand-alone Nim tool https://github.com/c-blake/nio/blob/main/utils/c2tsv.nim . Optional quoting was always going to be a PITA due to its non-locality. What if there is no quote anywhere? Fourth, by using a program as the unit of modularity in this case, you make things programming language agnostic. Someone could go to town and write a pure SIMD/AVX512 converter in assembly even and solve the problem "once and for all" on a given CPU. The problem is actually just simple enough that this smells possible.

I am unaware of any "document" that "standardizes" this escaped/lossless TSV format. { Maybe call it "DSV" for delimiter separated values where "delimiters actually separate"? } Someone want to write an RFC or point to one? It can be just as "general/lossless" (see https://news.ycombinator.com/item?id=31352170).

Of course, if you are going to do a lot of data processing against some data, it is even better to parse all the way to down to binary so that you never have to parse again (Well, unless you call CPUs loading registers "parsing") which is what database systems have been doing since the 1960s.

With https://github.com/c-blake/nio/blob/main/utils/catz.nim you can get similar format agnostic decoding/decompression not just in tar but in any pipeline context (based on magic numbers, not filename extensions and even doing the copy loop needed for unseekable inputs to replace the early read).

Part of the value prop is that you can directly author/access any library code in your native prog.lang in your query as naturally as native imports and routine calls. Awk is pretty established and for trivial one-liners you may not need any libs, but there are a lot more Go/Python/etc. libs than awk libs, AFAICT.

Beyond lib existence there is lib API understanding. There is not only language learning to be saved, but also lib ecosystem learning. I'm sure 'perl -na' folks could rattle off dozens of examples with CPAN package PDQ. I know many people who would say learning the ecosystem is what takes the most time...

There is also little barrier to using the same approach to also "compile" your data as well as the code. This is basically how 'nio qry' works as a kind of open architecture ghetto DB. [1] I mean, yeah, Big Iron, corporate database XYZ probably also has some ugly, non-portable extension language with 1970s prog.lang aesthetics that also sacrifices much value of SQL standardization.

[1] https://github.com/c-blake/nio

I get ~50% the speed of the article's variant with no SIMD at all in https://github.com/c-blake/nio/blob/main/utils/c2tsv.nim

While in Nim, the main logic is really just bout 1 screenful for me and should not be so hard to follow.

As commented elsewhere, but bearing repeating, a better approach is to bulk convert text to binary and then operate off of that. One feature you get is fixed sized rows and thus random access to rows without an index. You can even mmap the file and cast it to a struct pointer if you like (though you need the struct pointer to be the right type). When DBs or DB-ish file formats are faster, being in binary is the 0th order reason why.

The main reason not to do this is if you have no disk space for it.

Simon Willison has pointed out several examples of prompt injection attacks and why it may never be a solved problem:

I want more people to have link blogs.

I have one in the sidebar of https://simonwillison.net/ which I've been running since November 2003. You can search through all 6,836 links here: https://simonwillison.net/search/?type=blogmark

I can post things to it with a bookmarklet. It has an Atom feed.

It's such a low-friction way of publishing. A lot of https://daringfireball.net works like this too. I also like https://waxy.org/ and https://kottke.org/ for this.

I'd love to see more of these.

My approach is to publish to my own blog at https://simonwillison.net and then copy and paste content from that into a Substack newsletter at https://simonw.substack.com a few times a month.

It's been working really well.

Substack don't have an API, but they do support copy and paste - so I built myself a tool that assembles my blog content into rich text I can copy and paste straight into the Substack editor.

I wrote about how that works here: https://simonwillison.net/2023/Apr/4/substack-observable/

Hah, yeah securing something like WordPress can be a challenge, especially if you're running a bunch of plugins.

My blog is a pretty straight-forward Django setup without many other dependencies, so it's a lot less of an attack surface: https://github.com/simonw/simonwillisonblog

That specific prompt is just an example and it's pretty bad, it was the shortest and simplest prompt I could come up with that would be easily understood.

You can set response content-types (text, html, json, etc...). If you use json it will get pretty good results because I have some is some logic to attempt to pick out json or json5 objects from the text output. I dont yet have logic to support json arrays, but I'm hoping to add that soon.

But still client side validation is needed for applications with untrusted input. I dont attempt to solve prompt injection. I saw a lot of interesting posts on this topic from this blog https://simonwillison.net/. I need to find sometime to read more about it.

Try this one instead, it should be better

I've started to consider "commit to writing about it" as the price I have to pay for giving into the lure of another project. It's one of the main reasons I publish so much content on https://simonwillison.net/ and https://til.simonwillison.net

A project with a published write-up unlocks so much more value than one which you complete without giving others a chance of understanding what you built.

I've maintained internal blogs (sometimes just a Slack channel or Confluence area) at previous employers for this purpose too.

I think you are asking specifically about practical LLM engineering and not the underlying science.

Honestly this is all moving so fast you can do well by reading the news, following a few reddits/substacks, and skimming the prompt engineering papers as they come out every week (!).

https://www.latent.space/p/ai-engineer provides an early manifesto for this nascent layer of the stack.

Zvi writes a good roundup (though he is concerned mostly with alignment so skip if you don’t like that angle): https://thezvi.substack.com/p/ai-18-the-great-debate-debates

Simon W has some good writeups too: https://simonwillison.net/

I strongly recommend playing with the OpenAI APIs and working with langchain in a Colab notebook to get a feel for how these all fit together. Also, the tools here are incredibly simple and easy to understand (very new) so looking at, say, https://github.com/minimaxir/simpleaichat/tree/main/simpleai... or https://github.com/smol-ai/developer and digging in to the prompts, what goes in system vs assistant roles, how you gourde the LLM, etc.

Simon Willison's Weblog