kaleidic

Yes - that's right : people mostly shouldn't need to hold such high Bitcoin balances to buy things. What's in the way is the state interfering so you can't change dollars for Bitcoin with your bank and there aren't services that do that which are convenient enough. In time this will change so you can just make Bitcoin payments from your checking account.

Money has three functions : unit of account, store if value, medium of exchange. Cryptocurrency isn't great at the first two, but if we presume the scaling problems will be solved then it is pretty good at the latter because it doesn't require you to trust the banking system. So there is an unbundling of the functions of money described by Eugene Fama originally and then tidied up and better articulated by Tyler Cowen and Randall Kroszner in their book on the New Monetary Economics in about 1992.

Its completely irrelevant what the price of Bitcoin is for its usefulness as a medium of exchange.

This medium of exchange aspect is very important because it makes banks no longer special since its possible in time to make payments without a banking system. Thus the role of the state in regulating banks can disappear eventually - no deposit insurance, no bailouts and no too big to fail.

Credit can be provided by funds because the information asymmetry of banks no longer applies when you can port your banking records via API.

It's a big world out there. Would you ever imagine that D would be taking market share from... Extended Pascal? But there's a naval architect who designs great big ships with a 500k sloc codebase he is exploring porting to D. Web guys get the attention but enterprise users are a much bigger world than just that.

If something is growing very quickly then saying it hasn't yet dethroned C, so it won't ever be significant seems to me to be a bit brittle thinking. Compound growth and the passage of time - thats what has been underway for some time now.

http://erdani.com/d/downloads.daily.png

Plus betterC and gpu target.

Garbage in, garbage out. Github's language detection isn't perfect, and people in the D community simply aren't particularly focused on marketing and popularity contests. See here for example :

http://www.mail-archive.com/digitalmars-d-learn@puremagic.co...

Not only is it not quite dead yet, it's growing rapidly : http://erdani.com/d/downloads.daily.png

DMD downloads direct from home page only.

Or indeed https://github.com/kaleidicassociates/excel-d which schweiguy may find more appealing :)

Auburn sounds makes audio plugins in D and share how they avoid using GC in blog posts. Not that bad even for audio. Sociomantic and Weka both do soft real time.

Thanks for sharing.

Friend of mine started a company called Resolver Systems to do that for Python (end result). Nice experiment but bad timing for launch just before the crisis. Have got some algorithmic and infrastructure things in D, though plenty is done in other languages too. I ported Bloomberg API to D - it's open sourced bit currently not yet directly used in production. May start to be in coming months. It's not so hard to turn spreadsheets into code (its rarely the spreadsheet itself that does something complicated) so would rather rewrite that than try to do it automatically because code is easier to read, though I had dinner with a Dutch girl who is a professor who works on spreadsheets as functional languages.

See bachmeier work on D to R integration.

On Windows it's fine, but same library packaging problems as for C++...

Ios kind of works but is lacking bitcode on mobile devices.

Lacking a bit wrapping of system and gui calls but for android see dlangui and Jni is not so bad.

It's very practical to write libraries in D. Possible to write whole apps, but I wouldn't start there for now.

See Sociomantic 's Ocean library. But you don't need to go that far in practice in most uses. If you keep GC heap small, disable the GC in critical code paths, have threads that the GC doesn't get involved in, and use allocators most people will be fine.

It's much easier to generate code adapted to that cpu and machine in D because of compile time features. Plus it was an excellent team of a few people working for a few years that built mir. Actually I am joking - mostly one guy working for a few months (with a little help) made mir Blas. A pretty nice example of productivity of D. Also an illustration of the high calibre of person found in the D community.

Weka use D for making systems that store Petabytes of data in production. They don't really like the GC kicking in on that situation. So they write the first draft of code using the GC, and then for production make it not use GC - pre allocating largely. If you really care about latency I guess you can't really afford to use malloc necessarily.

But for the rest of us, D is not really comparable with Java but people tend to think if it the same way. I don't use classes myself (I had one but a guy didn't like it and removed it, though one or two in library code may have crept back recently) but allocate structs on the stack. The latter is more idiomatic generally in D. Depends how you count it, but at 120k sloc, maybe 200k if you include the periphery.

It's easy to allocate without GC using the std.experimental.allocator and emsi containers. Regional heaps, free lists, whatever hybrid model you want.

See excel-d for one example.

If you keep the rest of your heap small, say below 200Meg most people will be fine.

If you don't want to use D, blame the docs and lack of examples - still not as good there, but way better than before and all the unit tests are editable and runnable now. But I think the GC thing is more FUD than a real objection for most people.

What kind of support problems did you have? I found the opposite. It was possible to get such a good level of programmer from the community I was better off having found them letting them go work for the D Foundation on rebuilding compile time function execution. Libraries - meaning a bit more work to have idiomatic style use, but if you write D as C, that's usually okay - and wrapping is a one time cost.

I would say that I have found it to be more of a problem on Windows. That'd because the general C/C++ package management solution on Windows is quite... Old fashioned, and that's not always a D specific problem.

Hi... You have a superb blog. Somebody right now on forum is trying to port your hash map code BTW. Yes past is a shame, though it's momentum relative to itself that matters for a language more than versus others. If Go takes off for network services it doesn't particularly hurt D, because total market is so big. Language has really taken off past years, and I use it within a hedge fund environment. Work with some refugees from C/c++ - we couldn't imagine returning to those languages for what we use D for.

One sample project we built for internal use is here: https://github.com/kaleidicassociates/excel-d/blob/add64bit/...

There are many languages that fit certain general descriptions, but that doesn't mean that the experience of using them will lead me to think they are at all comparable in terms of how well they help me solve the kind of problems I face. Go and Scala - I somehow dont think they are close substitutes for each other. The kind of person that likes D's generics will not be the kind that is ultra happy with Go. The kind that likes the short learning curve and plethora of network libraries in Go might not be thrilled by D early experience. It all depends.

You can write D without using the garbage collector, or more pragmatically disable it or have threads doing work that are not registered with the GC. Some standard library functions require the GC, but a diminishing number, and you are no worse off than writing pure C. Just stick @nogc on the relevant code and it won't compile if you use the GC by mistake. Also, D generates less garbage than some other languages when written idiomatically, as you pass structs on the stack.

Quite right, though the high water mark approach predates 2008.

I learnt from Popper that the facts are theory - laden and from Feynman that science is the belief in the ignorance of experts.

This whole attempt to control the discourse is doomed. There's no such thing as objectivity - ones understanding of the world is shaped by one's experiences and who one is, and that's true for institutions too.

Character matters for an editorial institution, as does form. Snopes built its reputation one way, and became something quite different. And yet they have been granted a role of high influence by Facebook and thus it's in the spirit of good journalism to look into the extent to which they deserve this influence, and the character of the people involved does matter.

One could say that the Mail also isn't a globalist paper and so that naturally sets their perspective against Snopes.

There's a link between the process that elsewhere he mentions people need to go through to adapt there - developing a tougher skin is part of it, and that relates to learning to regulate amygdala activation - and current political questions relating to political correctness, triggering, safe spaces and the like. The research suggests that the answer to fear is incremental exposure - see treatment for arachnophobia for example - but that is not how we tend to think about it in our society today.

Eg How Trigger Warnings Are Hurting Mental Health on Campus - The Atlantic https://www.google.co.uk/url?sa=t&source=web&rct=j&url=http:...

My background is from the hedge fund investment side (though I have been programming since 1983 and have been increasingly involved in tech the past few years) and I have found these principles to be invaluable. I try to reread them a couple of times a year and in the past handed out copies to CEO and owner of the corporate partner of my startup fund.

There's a resonance here with Andy Grove's constructive confrontation and the kind of zero based idea they had about lines of business after realising mistake with memory vs cpu.

I think the main difficulties with it come from Dalio's insistence that everything is a machine - hunan beings, the family, the firm and the economy. I don't believe that is true - even code has an organic aspect to it, and firms are certainly organic.

And I think that shows in the difficulties he has with sustaining the principles as he steps away. If you read the comments on glass door, few complain about the principles but they do complain the principles aren't properly applied. So I think that's because he neglects the human aspect and if it's a cult if is insufficiently a cultus. (see TS Eliot).

Any approach can end up becoming a substrate for opportunistic and political behaviour. And most people aren't cut out for quite that level of directness.

But I learnt much more from Dalio than the stuff where I think he gets it wrong, and it's pretty powerful stuff because he has set out a coherent philosophy.

Charles G Koch has similar ideas about getting to the heart of things and bring critical. He says if a supervisor isn't being challenged by employees after a couple of years then he shouldn't be a supervisor - but the obligation is on both sides. See his books or YouTube interviews.

Yes, well the little guy always wants to unseat the dominant player, and when there is some personal history involved, things get more mixed up (technical, emotional, manner of expression). In your shoes I would be irritated by that too. But a project if it develops eventually transcends the personalities involved, and that seems to be happening now.

Note that I replied to a different version of the parent comment. Thanks for updating.

Personally I started using zeromq, but was a bit disturbed by the experience of the saltstack guys with timeout problems and memory leaks. Probably fixed now, I should think. But more than that, the LGPL and MPL 2.0 licences aren't great for a commercial project that might in future need to be distributed to a different entity. So the license alone is a reason one might welcome greater diversity in available choices.

Reasonable doubt is a legal term, not a scientific one.

Pattern prediction is one thing. But what happens when your model is both unrealistic in ways that some people think matters and doesn't predict the shape of things in the future well at all ? (Anyone can fit the past)...

It's not a question of whether humans have any influence (I think you would be hard pressed to find any serious scientist who would hold that position) but of the balance between human and natural factors. The set of people who hold dissident beliefs is not tiny, and many of them are very serious people indeed. One can't dismiss them for saying many are not specialists in the official field of climatology because insights can come from many places (and there is the matter of playing games with the journals and people deliberately using political power to shut out dissident views).

Wiki isn't the best source on this topic, but here is one list, for example: https://en.m.wikipedia.org/wiki/List_of_scientists_opposing_...

The work that has been done relies heavily on models and simulations. These are both not realistic (because there are many factors that are too complex to model, or that we don't yet understand fully) and have not predicted temperature well since the outturn of past years has been significantly lower than predicted by the envelope of such models.

The political climate clearly is not one where people feel free to speak (see other stories on attempts or proposals to criminalise the expression of dissident views under certain circumstances or to create legal liabilities) and in that situation many people will keep quiet and hide what they really believe. See Timur Kuran's work on preference falsification.

http://www.lhup.edu/~DSIMANEK/cargocul.htm But there is one feature I notice that is generally missing in cargo cult science. That is the idea that we all hope you have learned in studying science in school--we never explicitly say what this is, but just hope that you catch on by all the examples of scientific investigation. It is interesting, therefore, to bring it out now and speak of it explicitly. It's a kind of scientific integrity, a principle of scientific thought that corresponds to a kind of utter honesty--a kind of leaning over backwards. For example, if you're doing an experiment, you should report everything that you think might make it invalid--not only what you think is right about it: other causes that could possibly explain your results; and things you thought of that you've eliminated by some other experiment, and how they worked--to make sure the other fellow can tell they have been eliminated. Details that could throw doubt on your interpretation must be given, if you know them. You must do the best you can--if you know anything at all wrong, or possibly wrong--to explain it. If you make a theory, for example, and advertise it, or put it out, then you must also put down all the facts that disagree with it, as well as those that agree with it. There is also a more subtle problem. When you have put a lot of ideas together to make an elaborate theory, you want to make sure, when explaining what it fits, that those things it fits are not just the things that gave you the idea for the theory; but that the finished theory makes something else come out right, in addition. In summary, the idea is to try to give all of the information to help others to judge the value of your contribution; not just the information that leads to judgment in one particular direction or another. ... I would like to add something that's not essential to the science, but something I kind of believe, which is that you should not fool the layman when you're talking as a scientist. I am not trying to tell you what to do about cheating on your wife, or fooling your girlfriend, or something like that, when you're not trying to be a scientist, but just trying to be an ordinary human being. We'll leave those problems up to you and your rabbi. I'm talking about a specific, extra type of integrity that is not lying, but bending over backwards to show how you are maybe wrong, that you ought to have when acting as a scientist. And this is our responsibility as scientists, certainly to other scientists, and I think to laymen. For example, I was a little surprised when I was talking to a friend who was going to go on the radio. He does work on cosmology and astronomy, and he wondered how he would explain what the applications of this work were. "Well," I said, "there aren't any." He said, "Yes, but then we won't get support for more research of this kind." I think that's kind of dishonest. If you're representing yourself as a scientist, then you should explain to the layman what you're doing--and if they don't want to support you under those circumstances, then that's their decision. One example of the principle is this: If you've made up your mind to test a theory, or you want to explain some idea, you should always decide to publish it whichever way it comes out. If we only publish results of a certain kind, we can make the argument look good. We must publish both kinds of results. ... http://www.feynman.com/science/what-is-science/ The result of this pseudoscientific imitation is to produce experts, which many of you are. [But] you teachers, who are really teaching children at the bottom of the heap, can maybe doubt the experts. As a matter of fact, I can also define science another way: Science is the belief in the ignorance of experts.

When someone says, “Science teaches such and such,” he is using the word incorrectly. Science doesn’t teach anything; experience teaches it. If they say to you, “Science has shown such and such,” you might ask, “How does science show it? How did the scientists find out? How? What? Where?”

It should not be “science has shown” but “this experiment, this effect, has shown.” And you have as much right as anyone else, upon hearing about the experiments–but be patient and listen to all the evidence–to judge whether a sensible conclusion has been arrived at.

In a field which is so complicated [as education] that true science is not yet able to get anywhere, we have to rely on a kind of old-fashioned wisdom, a kind of definite straightforwardness. I am trying to inspire the teacher at the bottom to have some hope and some self-confidence in common sense and natural intelligence. The experts who are leading you may be wrong.

I have probably ruined the system, and the students that are coming into Caltech no longer will be any good. I think we live in an unscientific age in which almost all the buffeting of communications and television–words, books, and so on–are unscientific. As a result, there is a considerable amount of intellectual tyranny in the name.

So disingenuous. Clarium was a bit ... volatile, but as I understand it generated 8 percent and change compounded returns over the life of the fund, and it likely wasn't that correlated with other funds in your portfolio, which means the idiosyncratic volatility was less of a concern than it might have been investing in a guy that ran with the herd.

A fund that does well can shape its returns, but you cannot control investor behaviour. So talking about a 90 percent loss of assets without mentioning the compounded return of the fund is really a sign that you aren't trying to be fair, but just stick the knife in. Or, throw enough mud and some of it will stick.