mtrn

The final step is to break down these monopolies. The government can do that and has done it before.

Yes and no. I feel that not doing certain things is a very simple thing to "do" things - and I appreciate simplicity.

For example, I would probably prefer getting rid of half of the cars and trying to find ways so that people do not need to move that much, if they do not want to (for example making all possibly remote remote work actually remote) - as opposed to making all cars electric.

I do not own a car, I do not fly, I buy clothes used or new just once a year. My newest smartphone I bought five years ago (and I just bought a new battery for $10, so I can use it for five more years). My utility company stats says my energy consumption is overall very low. I eat meat once a month. I try to own as few things as possible. I try to write and deploy code in energy efficient languages (Go, Rust, C, ...) [1]. I self host some services on my arm board that consumes 0.79W when idle.

I do not feel, that it makes a large dent, but I feel that I'm way ahead what the average person does in order to reduce their environmental footprint.

Also, I do not feel I'm cutting myself short and I still depend on many of the niceties of modern civilization - but, I'd also be happier, if my footprint would be even lower.

[1] https://greenlab.di.uminho.pt/wp-content/uploads/2017/10/sle...

Was it always this bad and we just didn't see it before?

After about two hours of using FB in 2007 I had this crazy feeling that someone having access to all those people's photos and activities won't necessary end well; left and never looked back.

Question: How hard would it be to write create open source components to run a DSP collaboratively, e.g. with the power asymmetry created by aggregation

aggregated by DSPs

removed?

I support sourcehut, because I would like to see it evolve, and hopefully keep the no-nonsense UI approach. Having a nontrivial site with a usable interface running without JS in 2019 is beautiful on its own.

We used Jena for a project with 500M triples, the uncompressed file was about 80G. It mostly works fine.

I managed complex datasets of a few TB with standard Unix tools just fine. If you are lucky, you have a sustained read and processing speed of 200M/s (or more with, if you are put in some work), which allows you to sift through a TB in a good hour.

Sometimes I am wondering, how people will rationalize the layer bloat in 5-10 years, when hardware went through a few more upgrades.

I once taught[1] the building blocks of git (basically bullet time view of a commit) and people found it a bit too theoretical - even though it contained all the elements, that helped me to understand and appreciate the simplicity.

There is a point, where you go from memorization (add, push, commit) to deduction (graph, objects and refs) but when this point is reached, depends on many individual factors.

[1] https://git.io/fhWxg

I have been using something similar to ~/site/user/project for years and it worked well so far.

Maybe I am just naive, but this all seems terrible.

I do have most respect for TBH and I would consider everything he thinks and writes about, but this does not sound too good to me either.

The idea of linked data and semantic web has been around for almost two decades now and I have yet to see an application, technique or site that amazes me. On the contrary, most of the things in this space I have seen are bloated, unusable or simply unnecessary - whereas every paper sounds like revolution is around the corner. In that combination, it is the worst of both worlds: academic output, that claims practicality and fails to deliver.

Peter Norvig put it best, when he said: "The semantic web is the future of the web and always will be."

A recent discussion touches upon a few problems: https://news.ycombinator.com/item?id=18023408.

What really freaks me out is the day Facebook die, what will happen to all of this data?

Interestingly, Facebook owns your data. I believe if they wanted to, they could close the company tomorrow and put a facebook.tar.xz of everything they collected on archive.org or somewhere else.

Luigi is a great Python library for building multi-stage pipelines with parameterized tasks. It easily extend to new storage types and targets.

We currently use it to build a moderately complex product from dozens of data streams (files, APIs and things in-between) and millions of records. At its core is a DAG and topological sort, which capture the essence of pipelines and execution.

A DAG is easy to visualize, even its development over time[1].

[1] https://imgur.com/a/RuC0B5Y (generated from the projects' code, in this case https://github.com/miku/siskin)

If it's not overdone, an animated walk-through can give you an impression of how simple something is - here a short animation can be worth a thousand words.

For more complex topics I find animations less helpful.

Modernism. Cause and effect are separated. Or, as Flann O'Brien wrote: If one throws a stone up in the air, no one can tell where it will land.

I am glad, I do not need to worry that much about these things, thanks to my /etc/hosts file[1].

[1] One of many versions: https://gist.github.com/thomasbilk/1506210/2d20f47bbcca75b2f...

Yes, I used `load_data` and friends and it is certainly convenient. I was just curious about a kind of open source market place for models, where you could find niche models that people train in their spare time.

From the abstract:

Sharing the trained DL models has become a trend that is ubiquitous in various fields.

Apart from the Model Zoo[1], are there any other sites for sharing serialized models?

[1] https://github.com/BVLC/caffe/wiki/Model-Zoo

As a random data point: As I write this, irssi with perl and xmpp plugins consumes about 6M and never gets slow.

Did anyone read this book?

Just skimmed through a few pages, found a small name error:

Java millennium (Java ME) which is made to create Embedded Systems

I liked reading: Program design in the UNIX environment by Rob Pike. Sometimes, when I think about which features to add to a program I step back to see, whether a combination of program would actually yield better results. A practical view into what orthogonality could mean in the tooling world.

[1] https://nymity.ch/sybilhunting/pdf/Pike1983a.pdf

Thanks for the featuretools project, it sounds really useful. Is it Python 2 only?

Playing devils advocate here:

What annoys me the most is that, as a small company, I can't evade from my country tax system. I pay the taxes. All of them, at full rate.

How about a startup providing "tax-optimization" for the masses? Keep a cut of the money saved: win-win. Or win-win-lose, if you include the state.

The jq tool is great. Start using it today as a JSON pretty printer and learn it's more powerful features (selection, object creation) as you need them. The only thing I would like to add to jq would be the ability to use multiple cores.

It's XML without the tools.

XML can be really powerful, but a lot of real users actually don't know how to use XML. Many just use it as an enterprise version of JSON in which case I am happy to just work with JSON, plain and simply.

Also JSON processing can be easily parallelized, because it is easy to express in a newline delimited format (http://ndjson.org/).

This book helped me understand the basics of bitcoin as well. Great read.

> Everything is in a flat structure, except when it comes to salary and responsibilities. This part got a laugh out of me.

I had to smile when one interviewer described his company to me as very process oriented, but without the overhead.

I've been looking for a fast, simple, pure Go key-value store.

Shameless plug: If you have write-once (or seldom) and read-often kind of access pattern for JSON documents, I wrote a simple (619 LOC), pure Go key-value store, that supports this use case: microblob[1]. It logs in common format, uses a single file backend and scales up and down with RAM..

[1] https://github.com/miku/microblob

For people who believe code isn't literature descriptive names are wasted characters.

Data point: I do read code like books and I can't stand longAndMeaningful variable names. Rather, cut to the chase.

Me too. It's just hard to achieve. Are there any projects or books that inspire you regarding simplicity in design and implementation?