mtrn

If people would focus more on usability, comprehensibility, clear algorithms and project structure and precise requirements we could probably skip debating over languages altogether, because programs would look beautiful in any language.

Can anyone recommend an a good paper or essay on this subject? This development looks like an amazing economical shift and I would love to read semi-sci-fi-ish scenarios by serious economists studying past and present systems.

> There is nothing about: part of speech categories, relative clauses, morphology

This is an interesting and deep question. I believe that there are multiple ways to tell the story of a phenomenon. Using POS categories or verb tenses helps us to organize and learn about the medium. It is important for humans to know what a verb tense - in theory and practice - is, to be able to form not just grammatical sentences, but also ones, that express things clearer.

However, there is no rule that says that these concepts must be learned first before you can do anything else. In a sense, I see the (neural) machines taking a step back.

Whereas earlier attempts at language modeling took into account a lot of linguistic concepts, maybe even tailored to a specific human language, the more end-to-end approaches ignore these things and get better results. What can this tell you about the concepts? They are certainly useful and have been established by a scientific community. The machine, as it reads not just tens or hundreds of sentences but billions, creates a mathematical model, that happens to have aspects, that have very useful real world sides to them. A machine that learns a language model - or that learns translation, can teach us new things about words, and ultimately also about the world. I believe this is a beautiful aspect of the current neural renaissance.

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Kanerva in a preface to Geometry and Meaning writes:

> We think of some sciences, by their very nature, as being more mathematical than others. We even refer to physics and other heavily mathematical sciences as "hard sciences," as if to imply that social sciences and humanities are somehow soft or easy. Another way to see this picture, however, is that mathematics itself is hard and that it would be applied first to sciences that themselves are relatively easy. [...] It matters greatly that the mathematics be appropriate. [...] Mathematics is a tool for coping with complexity. [...] This brings us to the substance of [this] book: the exploration of mathematics that would be appropriate for describing concepts and meaning. The branch of mathematics that has traditionally been associated with meaning is logic. Logic is also discussed here, yet the main emphasis is on identifying mathematical spaces that would lend to modeling of meaning. (http://www.puttypeg.net/book/chapters/foreword.html)

Impressive. I just wished some engineers could take at least a single day off to regenerate - https://www.youtube.com/watch?v=A1YxNYiyALg&feature=youtu.be... - especially when they are on a world changing mission.

Raymond Hettinger highlighted the community aspect for languages very well in this keynote: https://www.youtube.com/watch?v=b_pTxGu2L04&feature=youtu.be... - he of course talks about Python, but the principles apply to any language or ecosystem.

As a footnote: My first impression of Airpods was: Of course! These are not smaller earbuds, they are an iteration towards implants or patches or invisible computing devices in general. From that perspective they seem make more sense: Condition the user to a world with less wires, where machines get real dialog systems. The outrage over the earbuds comes from people comparing things to the past, not the future.

In your experience, what personal characteristics, educational background or personal trait did successful individuals have?

Machine learning is an interesting case, in that the gap between theory and praxis is quite wide.

You can basically create, run and evaluate a model within 10 minutes (e.g. with scikit-learn or Tensorflow). It would even be an acceptable model that might solve your company's problem.

But you have to plan in a few years of deliberate practice to work through statistical learning theory and its prerequisites to get an overview and to be able contribute to the scientific or open source efforts in that field.

> don't think this new framework has much chance of gaining wide adoption

I don't believe it needs to, I believe diversity in a relatively young field is an advantage as it helps to not get stuck in a local minimum, so to speak.

Distraction is the right word. Focus on harder to measure notions of systematic, analytic or creative thinking are happily exchanged for measurable educational innovations like iPads. If there are two schools: one where they use iPads and another where they build some weird touch device from technological scrap parts - which school would you rather send your child to?

Adalbert Stifter once said: The work of a poet is done before the first tram passes by.

I haven't used mapillary, so just a question: is the user-generated content made available to the public?

Knights tour was one of the earliest Java programs we wrote at the university. Fun times, even found an old jar with some cool Swing visuals: http://i.imgur.com/6Q5ODT2.mp4

Pandoc's Markdown to Word conversion saved me when I was writing a book. Thanks and happy birthday!

An acquaintance wrote his thesis about Setun and later (2007) published a book about it: http://www.irmielin.org/setun-an-inquiry-into-the-soviet-ter...

I would like to see more such models in the future, because two world seem to intersect here: open source projects and the public domain.

Open source projects can have such a huge leverage, that the cost reductions in comparison to commercial offerings could be enormous. On the other hand, open source projects will gather people, who at least care about the specific domain (this does not mean, there is no politics). Treating software as public infrastructure could be a huge step forward.

So many things can go wrong. But how do you assess, where to draw a line? What could be used as a guiding light?

Currently I try to use the following scenario as orientation: If a completely new developer would walk in and wanted to install or build or contribute to a current system/project, how much I would have to explain to this person? How many, "yes, true, but only if" style statements would I need to make?

The optimum here is, that a developer will contribute, without me needing to explain or motivate anything.

Do you use a certain approach? How would you describe it?

Kanerva has discussed alternative computing styles as well. Especially, he asks, why it is hard to encode intelligence in such a rigid setup.

> The disparity in architecture between brains and computers is matched by disparity in performance. Notably, computers excel in routine tasks that we - our brains - accomplish with effort, such as calculation, whereas they are yet to be programmed for universal human traits such as flexible learning, language use, and understanding.

He focuses on the representation problem and develops a more flexible representation of concepts with what he called hyperdimensional computing[1].

[1] http://redwood.berkeley.edu/pkanerva/papers/kanerva09-hyperd...

I really hope for that. Working with Unix tools a lot, I appreciate these programs, that were already useful over thirty years ago.

The developer mindset needs to change as well. I seldom here people wondering about the sheer computing power of the systems they use.

Many developers also seem to get a kick out of building complex systems (with (most of the time too) many abstraction layers burning cpu cycles) - because they seem to believe building complex things somehow means having control over complexity - but I'm not sure about that.

> is there anything stopping you from re-implementing the Erlang memory/GC-model on the JVM

Apparently not, never used it, but impressive: https://github.com/trifork/erjang

Well, at least the TV shows invite mathematicians, that's not a bad start.

Whichever subject Prof. Konstantinov is an expert in, it's not cryptography: https://en.wikipedia.org/wiki/Kerckhoffs%27s_principle.

I would probably start with elasticsearch and establish a business case first. Only once that's proven and some need for lower level customizations arises, I would descend the stack.

For one, Lucene[1] is quite amazing. With a slight stretch of imagination, you can think of it as a document oriented database, with all fields indexed by default. Imagine loading 100M rows with 100 columns into an RDBMS and then index each column[2]. You don't necessary do that. With Lucene - and SOLR and elasticsearch for that matter - it's not even a thought. Additionally, you get to tweak your indexing with dozens of field-tested analyzers.

[1] http://lucene.apache.org/core/

[2] we do this (over 300G of complex data) with a tool called solrbulk and on a single server in less than four hours, https://github.com/miku/solrbulk

This reminds me of some open source angle on business: try to provide more value than you capture. I believe this to be a healthy attitude, hopefully more companies and entities can live up to this challenge.

A company once flew me to Madrid for an interview. Unfortunately, I cannot understand Spanish, but the receptionist at the hotel seemed to mumble to a friend: look they are flying people here, but our people are unemployed. It seemed a bit crazy for me as well, since I was unsure, if my person and skills justified that kind of effort.

The interview went fine and I think I was offered something around 30k, which was below my current wage in another (non-capital) European city, so I had to decline, although I loved Madrid and the team seemed really nice.

> I used sed today to complete a "large story" in a single command.

Great, I sometimes do that, too. Downside is that your patience level for "enterprise architecture" goes way down.

Just a thought: Is it mostly select statements that your colleagues write? Because if they do, they might not fear accidentally altering the data. I found that new programmers can get confused by the difference between things that are immutable and those that aren't.

There was a spreadsheet floating around on r/libraries from 2007 about the subscription costs in Tennessee: https://www.reddit.com/r/Libraries/comments/4jodic/found_an_...

> You may hate it but... you clicked on it. We're giving you what you want.

You tell me once, I need X, I won't care. You tell me ten times a day I need X, I might get tired. Color me pessimistic, but people in general just need to be told with clear words over and over what to do and without a strong independent or stubborn mind they will follow.