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Which web search do you prefer over perplexity?

Let me share a personal story. Back in 2014 when I was working at Cloudflare on DDoS mitigation I collaborated a lot with a collage - James (Jog). I asked him loads of questions, from "how to login to a server", via "what is anycast" to "tell me how you mitigated this one, give me precise instructions you've run".

I quickly realised that these conversations had value outside the two of us - pretty much everyone else onboarded had similar questions. Some subjects were about pure onboarding friction, some were about workflows most folks didn't know existed, some were about theoretical concepts.

So I moved the questions to a public (within company) channel, and called it "Marek's Bitching" - because this is what it was. Pretty much me complaining and moaning and asking annoying questions. I invited more London folks (Zygis), and before I knew half of the company joined it.

It had tremendous value. It captured all the things that didn't have real place in the other places in the company, from technical novelties, through discussions that were escaping structure - we suspected intel firmware bugs, but that was outside of any specific team at the time.

Then the channel was renamed to something more palatable - "Marek's technical corner" and it had a clear place in the technical company culture for more than a decade.

So yes, it's important to have a place to ramble, and it's important to have "your own channel" where folks have less friction and stigma to ask stupid questions and complain. Personal channels might be overkill, but a per-team or per-location "rambling/bitching" channel is a good idea.

It depends where you're coming from, I suppose. The web is pretty popular. Web developers are more familiar with HTML, CSS, and JavaScript, and with various visualization libraries in the JavaScript ecosystem. I quite like Observable Plot [1].

I'm not familiar enough with Python or Jupyter to know how you would build similar visualizations with them. What would you use?

[1] https://observablehq.com/@observablehq/plot-gallery

Yeah, last time I had to do this was about a year ago and I used parquet and arrow on S3-compatible object stores and put a bunch of metadata in postgres and the whole thing. At that time we used Prefect for orchestration which was fine but IMHO not worth what it cost, I've also used flyte seriously and dabbled with other things, nothing that I can get really excited about recommending, it's all sort of fine but kinda meh. I used to work for a megacorp with extremely serious tooling around this and everything I've tried in open source makes me miss that.

On the front end I've always had reasonable outcomes with `wandb` for tracking runs once you kind get it all set up nicely, but it's a long tail of configuration and writing a bunch of glue code.

In this situation I'm dealing with a pretty medium amount of data and very modest model training needs (closer to `sklearn` than some mega-CUDA thing) and it feels like I should be able to give someone the company card and just get one of those things with 7 programming languages at the top of the monospace text box for "here's how to log a row", we do Smart Things and now you have this awesome web dashboard and you can give your quants this `curl foo | sh` snippet and their VSCode Jupyter will be awesome.

It's a shame that they don't have you writing marketing copy! The docs are indeed a lot more reasonable looking (to me at least). I work for a small proprietary fund and not some Godzilla company these days so maybe I'm just not the audience, but whew, for purchasing decision makers with subject matter background, that home page would have been a back button real fast if it wasn't linked from your thoughtful comment.

I'm interested in your opinion as a user on a bit of a new conundrum for me: for as many jobs / contracts as I can remember, the data science was central enough that we were building it ourselves from like, the object store up.

But in my current role, I'm managing a whole different kind of infrastructure that pulls in very different directions and the people who need to interact with data range from full-time quants to people with very little programming experience and so I'm kinda peeking around for an all-in-one solution. Log the rows here, connect the notebook here, right this way to your comprehensive dashboards and graphs with great defaults.

Is this what I should be looking at? The code that needs to run on the data is your standard statistical and numerics Python type stuff (and if R was available it would probably get used but I don't need it): I need a dataframe of all the foo from date to date and I want to run a regression and maybe set up a little Monte Carlo thing. Hey that one is really useful, let's make it compute that every night and put it on the wall.

I think we'd pay a lot for an answer here and I really don't want to like, break out pyarrow and start setting up tables.