Blue Zones - Places In the World Where People Live to 100 and Stay Healthy - <AUTHOR> http://singularityhub.com/2009/07/20/blue-zones-places-in-the-world-where-people-live-to-100-and-stay-healthy/

<comment><USER2> _do they have special genes? ... the answer is no_

That's not true. In Sardinia and Okinawa studies have shown that genetics play a significant factor in longevity. For example, Sardinians have historically tended to reproduce later in life. This has favoured genes that contribute to longevity, or at least it has selected against those that contribute to early mortality.

A healthy lifestyle will contribute to a longer life, but it's misleading to imagine that everyone could achieve 100 if they just made the effort.

<comment><USER3> Wait, wait... so you're saying that all we have to do to make ourselves live longer as a species, is to not let anyone procreate until they hit whatever that generation considers "old age"? Interesting; I'm surprised this has never been a part of any sci-fi description of a utopia...

<comment><USER4> The Heinlein "Howards Families" comes pretty close: [http://sciencefictionbiology.blogspot.com/2007/07/heinlein-a...](http://sciencefictionbiology.blogspot.com/2007/07/heinlein- and-human-breeding.html)

That link doesn't reference your exact idea, but I thought that was part of that. However, since I can't grep my collection I can't prove if that's actually something Heinlein said, or a confabulation on my part.

</comment></comment></comment><comment><USER5> So basically... anyone who wants to do YC is doing it wrong.

Sure, if you have a stress free life you'll live longer. If you eat 30% fewer calories, you'll live longer as well.* But you'll be poor and hungry.

*Although that was a really crappy study. They excluded all the primates that died from the statistical analysis.

<comment><USER6> There're a lot of philosophies that say poor and hungrier is in some ways a happier way to live.

Perhaps there's no "wrong" way to live life, and the people who die young and the people who die old are both happy with the choices they made.

<comment><USER7> Yet perhaps many are frustrated by never having agency to make those choices in the first place.

</comment></comment></comment><comment><USER8> Virtually the same material was presented on "How to Live to 101" episode of a BBC show called "Horizon" - [http://www.bbc.co.uk/sn/tvradio/programmes/horizon/broadband...](http://www.bbc.co.uk/sn/tvradio/programmes/horizon/broadband/tx/101)

One notable difference was that the whole part about Sardinia revolved around a group of people roasting whole lamb and then washing it down with copious amounts of wine. "Low on meat" diet, right :-)

As far as I remember their conclusions were (a) eat less (b) stay active (c) keep an interest in life. With (c) being the most important part.

</comment><comment><USER9> Anybody know how many 'hot-spots' like this would be predicted due to clustering at levels predicted by chance?

"The only way to determine whether a cluster is a "real" cluster or just a "chance" cluster is to do a full scale epidemiological study, which is an expensive and time consuming process, and may still give disappointing results." [http://pmep.cce.cornell.edu/profiles/extoxnet/TIB/epidemiolo...](http://pmep.cce.cornell.edu/profiles/extoxnet/TIB/epidemiology.html)

</comment><comment><USER10> I wanted a map.

</comment><comment><USER11> How is their no map in this post?

<comment><USER12> because i think the point of this post is that location doesn't actually matter. the "blue zones" are places where culture and/or circumstances have forced all of the people in the area to live a healthier lifestyle. makes it impossible to live there and not be healthy, so the area's statistics improve.

<comment><USER13> Given how much one's behavior is impacted by external constraints, location _does_ matter quite a lot. I suspect that if you moved the newborn offpsring of two morbidly obese Americans into a family on Okinawa the child would most likely live a rather healthy lifestyle.

<comment><USER12> the point, though, is not that that there is anything special in the water or something. its just circumstances that promote general health as we currently understand it. want to live longer? exercise and eat right.

</comment></comment></comment></comment><comment><USER14> Thanks for this, very awesome!

</comment><comment><USER15> With nothing on how exactly he identified the groups this is just silly pop sci. You can't arbitrarily select your subjects.

The whole thing immediately looks very suspicious if you go to <http://www.bluezones.com/> Obviously somebody is out to build a cult and make a lot of money.

</comment><comment><USER16> The lesson I walked away with is: live a stress free happy life with plenty of continuous low stress excersize and a healthy diet not consisting of fried fatty sugary foods.

Sub points Excersize can lead to stress - incorporate a lifestyle of excersize Have good relations with family -- less stress but out of your controll often Organic food is good.</comment>


Yahoo Glue - <AUTHOR> http://glue.yahoo.com/ <comment><USER2> Anyone else think this looks like a computer generated version of what Mahalo.com is trying to do?</comment>


Unix and Flow-Based Programming - <AUTHOR> https://groups.google.com/d/msg/flow-based-programming/iaKhbABJ9fw/XlrMf-dnBgAJ <comment><USER2> > _I was going to mention Unix "cat" but forgot._

> _Wildly simple - it takes at most one argument._

That is asinine. Why would a program be called 'cat' if it can't con _cat_ enate multiple files?

Also, his "grash" program is seriously deficient in the handling of signals – it completely ignores the issue. There are _many_ subtle issues with signals which have to be handled correctly when writing a shell: [http://www.cons.org/cracauer/sigint.html](http://www.cons.org/cracauer/sigint.html)

<comment><USER3> > That is asinine. Why would a program be called 'cat' if it can't concatenate > multiple files?

Because he only thinks it's the "echo file to terminal" command.

The main use of cat was mentioned in the Programming in the UNIX environment article.

> The fact that cat will also print on the terminal is a special case. Perhaps > surprisingly, in practice it turns out that the special case is the main use > of the program. [...] But what about -v? That prints non-printing characters > in a visible representation. Making strange characters visible is a > genuinely new function, for which no existing program is suitable. [...] The > answer is ''No.'' Such a modification confuses what cat 's job is > concatenating files with what it happens to do in a common special case - > showing a file on the terminal.

[http://harmful.cat-v.org/cat-v/unix_prog_design.pdf](http://harmful.cat-v.org/cat-v/unix_prog_design.pdf)

<comment><USER4> Like a lot of people, he overuses cat when it's not needed. `cat FOO | more` is approximately equivalent to `more < FOO`, except the first one spawns an extra process for no reason.

<comment><USER3> > except the first one spawns an extra process for no reason.

I wonder how many processes I could spin up in the time it would take for me to figure out "hmm, no, invoking that command would use one more process than necessary..."

I don't give a hoot about that stuff when I'm doing stuff interactively. e.g. when using `more`.

</comment></comment></comment></comment><comment><USER5> > Then Tannenbaum came out with his book and it didn't really take off.

> Then Torvalds open-sourced linux and that is what started to gain > popularity.

 _cough_ BSDi _cough_

<comment><USER6> To support your point:

[https://web.archive.org/web/19990224090656/http://www.bsdi.c...](https://web.archive.org/web/19990224090656/http://www.bsdi.com/company/)

Seeing the list, now I'm sure which BSD that SCC likely used in their Sidewinder firewall. They modified it to have mandatory access controls to contain breaches of subsystems. This was before SELinux, etc. Never used BSDi, though, so can't say much about it except its users were getting pretty of mileage out of it given rep of products based on it. Least in appliances.

<comment><USER5> We used BSDi to launch an ISP in 1995, with 20 modems and 512kbps of bandwidth.

I still have the Cdrom and we do hosting nowadays.

<comment><USER6> How much did it cost out of curiosity?

<comment><USER5> I really can't remember. I didn't order it myself.

</comment></comment></comment></comment></comment><comment><USER7> Well yeah, but that's not really how complex systems are developed anymore. Modern software development uses the object as the modular unit of granularity, not the process -- and APIs, perhaps augmented with message queues, for communication rather than pipes, sockets, and file descriptors. This is because it's much easier to statically reason about objects with well- defined APIs and they can be composed more flexibly with appropriate fabric: interacting locally or across process, user, or system boundaries.

This model dates back at least as far as Smalltalk but what really caused it to take off was -- wait for it -- Windows COM. So modern development has moved on from the Unix philosophy and embraced the Windows philosophy.

<comment><USER8> Uh, this is crazy wrong. Maybe in the desktop era objects were more important, but processes have come back with a vengeance now that everything is a distributed system.

I'm not sure what you mean about objects being composed across system or process boundaries. Name a successful system where that's true. Who uses DCOM? Distributed objects _failed_. I occasionally see people trying to bring back this way of thinking (e.g. they want methods instead of RPCs and protobufs), but they have not succeeded, for fundamental reasons.

In reality it's not either-or. You need both ways of thinking. Objects are static (they exist as an agreement between the compiler and programmer, and are usually thrown away at runtime); processes are dynamic. Many programmers that think only in terms of objects learn the hard way that their programs are brittle and inefficient. System operators think in terms of processes, and this way of thinking is essential for resilient systems.

In addition, objects are losing importance in distributed systems because state in a single machine's memory is not very useful. In real distributed systems you need replicated/resilient state with varying consistency guarantees. An object doesn't help you with any of those things.</comment></comment>


Mark Cuban on Why You Need to Study Artificial Intelligence - <AUTHOR> https://bothsidesofthetable.com/mark-cuban-on-why-you-need-to-study-artificial-intelligence-or-youll-be-a-dinosaur-in-3-years-db3447bea1b4 <comment><USER2> The title is clickbait, but the problem with the religious fervor of machine learning/deep learning is that entrepreneurs/VC keep arguing that deep learning is magic and can solve any problem if you just stack enough layers. (see also: [https://www.reddit.com/r/ProgrammerHumor/comments/5si1f0/mac...](https://www.reddit.com/r/ProgrammerHumor/comments/5si1f0/machine_learning_approaches/))

Meanwhile, statistical methods for non-image/text data with identifiable features can often work better than neural networks, but they are not as sexy. (Good discussion on HN about this: [https://news.ycombinator.com/item?id=13563892](https://news.ycombinator.com/item?id=13563892))

<comment><USER3> I have no experience with the entrepreneur/VC side of this coin, but Data Scientists know the differences between traditional regression based ML and CNNs. We know that doing image recognition or NLP is best suited to nvidia/tensorflow/keras/deeplearning/buzzword/buzzword. We also know that SVMs & Random Forests & regression lines work just as well as they always have to make predictions based on your click-thru data.

Maybe we should explain the cost/benefit of the buzzwords vs. the science?

<comment><USER4> It's simple. More buzzwords equals more money. So whatever it is you're _really_ doing, just find some way to semi-plausibly attach the latest hot buzzwords to it.

Most of the "dinosaurs" around here should know by now that you don't get paid to do what works; you get paid to do what the boss/customer wants. (And that's not always going to be exactly what they _asked for_ , either.)

As long as you continue to throw money at me, I'll continue to chase your wild geese, hunt your snipes, fish for your red herrings, and joust with your wind turbines. Most of us here can learn fast enough to always stay one or two steps ahead of the boss on whatever topic they might latch on to. And that becomes genuine experience if it somehow manages to graduate past the business fad phase.

</comment></comment></comment><comment><USER5> Reading HN I worry that we're going to have _the opposite problem_ \- a glut of people will try and (badly?) learn ML and then realize there aren't enough ML jobs.

I've a PhD and held ML-engineer positions in a few different companies - I've good industry awareness.

Most applied ML, for most companies, right now, is actually relatively simple models (hand-coded rules! logistic regression! You'd be shocked how common these are.) The bulk of the work is data cleaning, gathering, integration, deployment, productisation, reliability, avoiding pathological cases, special- casing, Product, UX. You do need ML specialists who understand the stuff, to make it all work and come together - but the ratio of ML specialists to the wider team is low. Maybe 1 or 2 specialist on a team of 10 for an ML heavy product.

This is going to remain the case IMO. Yes, there will be small teams, in highly resourced organizations (GOOG, FB etc), academic research labs, or occasional hard-tech startups, who do new model development. Maybe if AI becomes huge, you'll see more traditional Fortune 500s spin up similar efforts.

But there'll be a much wider set of people&businesses applying and tuning well understood approaches, rather than doing new model development. And you just don't need as many ML specialists, for that approach.

Even with deep learning, the tooling will advance. I mean, even look at all the research papers describing applications at the moment - so many of them are using pre-trained models. Industry will be similar. Tooling will advance, and you'll be able to do increasingly more with off-the-shelf pieces.

I think ML is absolutely going to have a big impact - I buy at least some of the hype. But should all developers, or even a substantial minority of developers, start learning ML as a career imperative? I don't think so.

Finally, it takes serious time to learn this stuff. Its easy to dabble (and worthwhile doing - its fun; and sometimes you can do powerful things in a using tools in a very blackbox manner!). But actually thoroughly learning it takes time. It takes serious time to build statistical intuition, as just one example.

We could easily end up with a great many career developers who have a specialization in ML, frustrated they never get to use it.

<comment><USER6> This is not my field, but a serious question--I once read that part of the motivation of pharmaceutical companies in hiring researchers was not so that they would all produce ground breaking independent research, but rather because they would be capable of reading the literature (again, not my field). Is that true at all for machine learning? Would companies hire people who would be up to date with the literature so that they could implement algorithms that others have developed in an academic context and put them into production?

<comment><USER5> Yes, I think that's true.

Basically, the interfaces of the models/tools/abstractions people will use will be 'leaky'.

For example, you can take a machine learning method from scikit learn, which works really well on the scikit learn example, and apply it to your problem.

Any developer can do this pretty quickly. If it works, and gets good accuracy out-of-the-box, then great.

But if it doesn't work, what do you do? How do you know where to look, what could trip it up? Are your features OK, or is it a problem with your model? Or maybe you framed the problem wrong? When you get into this sort of area, that's when you need an ML expert, who knows whats actually going on under the hood - or can at least learn the particularly model quickly - and can make progress faster. A more general developer will slow down drastically once they start reading the documentation for how the model/system actually works.

And hopefully the expert will frame the project better from the very start, solving issues before they even arise, because they know the kind of issue that _can_ occur, or suggest easier paths to solutions.

So, agree with your point there.

But how many such experts do you need? In my experience, only a small number on a bigger team. ML folk are highly leveraged, but need a lot of support to get their product into production - to manage the data (if its worth applying ML to, there's probably a lot of data, so a big data engineering task, maybe connected to a live system), to think about the UX etc.

This will all evolve on several levels of course:

\- The tooling will get better; model/data deployment/management will get easier. But also and non-experts will be able to get more done as ML becomes more robust out-of-the-box.

\- We'll get better at building ML products (e.g. team structure, data infrastructure, UX (designers learning how these things work), company org (e.g. a lot of friction between Agile and ML))

\- Businesses will want to do bigger things

But if I had to guess, we'll be picking up low-hanging fruit for a while, and most of the work, for most companies, will be in the support infrastructure and application, with just a minority of specialist ML roles.

</comment></comment></comment><comment><USER7> I'm going to go against the grain here and (gasp) not hate on deep learning. People should realize that although many older statistical methods and "traditional" machine learning methods such as LDA, SVMs and decision trees may be good enough for business tasks, they are not the cutting edge of AI research. I think people are forgetting exactly how difficult image classification and object detection was before the advent of deep learning. People hating on "stack more layers" forget that "stack more layers" is EXACTLY what improved imagenet performance to such as massive extent. ResNets pushed the limits by figuring out how to stack more layers in a beneficial way.

And let's take a look at AlphaGo, how would you do that with SVMs or decision trees? Just get over the fact that deep learning provides a level of "intuition" (Go's search space is famously greater than the estimated number of stars in the universe).

I think that a part of the problem is that older ML PhDs are angry that deep learning is so easy (until the learning rate fails to provide convergence of course...) and would prefer that their preferred methods would still reign supreme.

I'll end this wall of text on the note that OpenAI's Ian Goodfellow notes that all projects at OpenAI use deep learning right now, but they are not dogmatic and will consider other approaches if they work well. I think this is the path that should be taken. On the other hand, I also see a bright future for uniting traditional techniques with deep learning such as attaching a SVM to a CNN and combining decision trees with CNNs both of which have resulted in good results.

<comment><USER8> >> I think that a part of the problem is that older ML PhDs are angry that deep learning is so easy (until the learning rate fails to provide convergence of course...) and would prefer that their preferred methods would still reign supreme.

I think that's definitely a part of it, and I feel that way sometimes myself (not that I'm a PhD). But there's another side of that reluctance that lies on the axis of model accountability and explicability. A lot of modern ML/Deep Learning doesn't -feel- like we're understanding anything any more than we did ten years ago. Yes our black-box results are better according to the tests we've laid out for them, but there's something more slippery about the 'why', beyond the handwave of 'complexity'. Maybe this is just the way it will be going forward (in the spirit of Quantum's "shut up and calculate"), but it is not easy to give up something that you can wrap your head around with something that kind of just takes care of itself, especially if you're in the business of seeking knowledge instead of results.

<comment><USER7> I'm not sure I fully buy the "explainability" argument against deep learning since our goal is human level intelligence and human intelligence isn't easily explained either.

On the other hand, we're nowhere near human level intelligence in most tasks (Go, Poker and image classificaiton non withholding) so I can understand the argument for explainability from a practical perspective. I think we're making some good progress in that direction though, and I'll list them below:

1) Attention maps in CNNs can tell us what the net is usually looking at.

2) "Attentive Explanations" use attention mechanisms to point to the object of interest to generate an explanation for VQA tasks, check the paper (warning PDF): [https://arxiv.org/pdf/1612.04757](https://arxiv.org/pdf/1612.04757)

3) A recent project used a similar explanation mechanism that forced the network to output "what it was thinking" while playing an Atari game.

4) NTMs (neural turing machines) allow weighted memory access, which alleviates the back box issue to some extent.

<comment><USER8> >> since our goal is human level intelligence and _human intelligence isn 't easily explained either_

I think this might be where the real divide lies. To present a false dichotomy, there are two schools. One that is interested in building systems that attain human-level intelligence, and another that is interested in understanding the nature of human intelligence by building models using our closes understood analog (computation).

We're definitely making progress on Deep Learning models that tell us more about how they think they work, but philosophically, I'm not sure we're making progress on understanding the nature of what they experience. I don't mean this in any polemical sense, just trying to explain the particular dissatisfaction (and it -is- dissatisfaction, not contempt or disdain. The stuff is amazing) I feel towards these advances.

</comment></comment></comment></comment><comment><USER9> I would be far more inclined to heed this advice if Cuban have any indication of understanding ML as anything more than a magic black box; fairy dust to be sprinkled into every pitch deck to solve any objection or solve difficult problems. The bandwagon is passing through folks, jump on board with Mark or you will have fewer buzzwords with which to craft your deck...

<comment><USER10> Was he talking to engineers or owners / executives though?

""" The Upfront Summit is LA's premier technology event, with more than 750 of the country's top investors, startups, and corporate executives """

If he was talking to executives, it may be sound advice. It's extremely likely the hot business opportunities in the short-term will be applying ML techniques to outstrip competitors trying to solve problems with traditional hand-coded solutions. In business-speak, "Learn ML" translates to "Familiarize yourself with the space and hire the people you need who know the topic," because that's how a company "learns" something.

</comment></comment><comment><USER11> Sort of a content-free article, but the headline is an interesting bold claim that conjures a lot of thoughts:

\- I know enough machine learning to be dangerous, but I'm hardly ever asked to use it. I designed a Bayesian classifier for my own startup around 6 years ago, analyzing political donor networks. I've completed the Stanford ML course. Back in college I did a math minor, so I'm comfortable with linear algebra, calculus, etc. I'm pretty comfortable with statistics of both kinds. But my bread-and-butter is freelance web development . . . and I'm not really even sure how to find work doing more MLy things.

\- I've read over and over that the most time-consuming part of ML work is data collection & cleanup, and that matches my own experience. It is the same thing that killed so many data warehouse projects in the 90s. You don't need a Ph.D. to do it, but it is a tough and costly prerequisite. So it seems like you'll need non-ML programmers even for specifically ML projects.

\- In a similar vein, Google has written about the challenges of "operationalizing" machine learning projects.[1] Having a little experience collaborating with a team doing an ML project, where they did the ML engine and I did the user-facing application, I can say that many ML experts are not experts in building reliable, production-ready software.

\- Will there ever be a Wordpress of machine learning? If there is, the author will be rich, but you won't need a Ph.D. to operate it. But because ML requires hooks into your existing systems, I don't know if this will ever happen. What _will_ happen I think is plugins to existing e-commerce systems for product recommendation or other off-the-shelf ML-powered features. These already exist, but I assume they will become more prevalent and powerful over time. In any case, the mainstreaming of ML for business will be inversely correlated with the expense to implement it, which suggests it will be easier and easier for non-expert developers to use (and misuse).

EDIT: Added the (now-)third bullet point I forgot before.

[1] [https://research.google.com/pubs/pub43146.html](https://research.google.com/pubs/pub43146.html)

<comment><USER12> > and I'm not really even sure how to find work doing more MLy things.

I think this is key - prospective clients won't ask for it because they don't understand where it could be used, and they won't understand the heavy ML methods. An approach there would be to pitch things like improving search results using a bayesian classifier applied to analytics data as a cheap upgrade when quoting other work. Until people are used to even the basic statistical approaches they won't be ready to invest in something more drastic.

</comment></comment><comment><USER12> One of the things I've realised is that the more I'm looking around, the more I find opportunities where people "should" have seen the opportunities of basic bayesian models, simple clustering algorithms etc. and other simple mathematical/statistical methods 20 years, but didn't, and still don't. That has massively changed my perspective on how quickly the onslaught of machine learning will come.

E.g. when I was reading up on genetic algorithms etc. 20 years ago we also expected the "revolution" to be right around the corner, and that things like genetic programming would change the world in a few years time. And while various of those methods found use some places, most places that could have used at least some of the simpler ones, still don't.

In other words, I think talking about a 3 year timeline is crazy. It's getting more attention, sure, but there is so much low-hanging fruit that most developers could be busy for the next 20 years putting in place the most trivial algoriths all over the place and we still wouldn't have picked off even the low hanging fruit where the computational resources and algorithms and data to make a big impact were well within reach 20 years ago.

This certainly means there is plenty of room for a lot developers to do very cool stuff and build careers on machine learning today, but it also mean most developers will not have to learn the state of the art - or anything near it - for a very long time.

As a concrete example I give to people, consider all of the search boxes out there on various sites - product searches, location searches, site searches - that are straight keyword based searches that don't take into account _any_ clickstream data to improve ranking. The proportion of search boxes I see that take advantage of the available data is vanishingly small, even though very basic analysis can improve the perceived relevance of the results massively.

We certainly will see more companies invest in proper machine learning as the payoff gets higher and difficulty in taking advantage of it drops. But we will also see a huge proportion of sites that could use it continue to ignore it for years to come.

There are big business opportunities in finding ways of making a dent in that portion of the market, though, and so learning this stuff can certainly be well worth it on a personal level, but I don't believe in his timeline in terms of the overall market.

<comment><USER13> If competition with basic keyword search survives, the benefit of implementing something more sophisticated might just not be worth it. With search you usually know what you are looking for and can pin it down quite well with classic keyword search, discovery happens elsewhere.

<comment><USER12> > With search you usually know what you are looking for and can pin it down > quite well with classic keyword search, discovery happens elsewhere.

Having looked at search terms users enters on a lot of client sites, I don't believe that for a second. Users are exceptionally bad at composing search terms.

<comment><USER13> You are probably right. Who searches? Is it really just the long-tail that can't be served by good navigation and the most important content in prominent places? Or could one optimize the rest first? (of course, a bit of statistics on what is accessed frequently helps here too)

</comment></comment></comment></comment><comment><USER14> Statements like these suggest that another AI Winter is coming (sooner than 3 years I guess)

"""He thinks even programming is vulnerable to being automated and reducing the number of available programming jobs."""

I believed something similar could happen within 1-2 years of learning/writing AI programs (more than 12 years back). I believed it so much that it consumed most of my weekends as I took on the Genetic Programming approach. Yes! computers can write programs - BUT trying reading those. Eventually after spending hours or days, you will be able to read those programs and you might find a simple "hello-world" program represented by a complex mathematical equation. Good luck trying to get such program fixed by humans. Imagine an experience decoding deep-learning-neural-nets. However, that is black-box from a programmer perspective.

From a business/management personnel perspective - the code is a black box anyways. When they get NNs that can generate required software, they will replace the people-manager with a NN-manager (who is a programmer btw!)

<comment><USER15> Are you referring to something like this?

Using Artificial Intelligence to Write Self-Modifying/Improving Programs [http://www.primaryobjects.com/2013/01/27/using-artificial- in...](http://www.primaryobjects.com/2013/01/27/using-artificial-intelligence- to-write-self-modifying-improving-programs/)

<comment><USER14> No, that looks like GAs with string/array representations. Similar thing worked for me when I tried randomly referencing nodes within a chromosome (say from index A to index B) - generating a graph like structure

The outputs are like this for some not-so-easy targets:

Op nodes ['ADD', 'ADD', 'MUL'] EXPR: ['ADD[ni_99](ADD[ni_49](I__7[ni_43](), ADD[ni_19](I__8[ni_66](), ADD[ni_79](GET_CONST_3[ni_25](), I__9[ni_71]()))), I__1[ni_61]())', 'ADD[ni_13](I__6[ni_17](), ADD[ni_49](I__7[ni_43](), ADD[ni_19](I__8[ni_66](), ADD[ni_79](GET_CONST_3[ni_25](), I__9[ni_71]()))))', 'MUL[ni_68](GET_CONST_8[ni_73](), FLOAT[ni_42](I__1[ni_91]()))']

With genetic programming (using an AST), it can solve complex equations:

However, this simple equation i.e. correct answer "(a + b + c - d) / e" could be evolved and will result into either of these (depends on my luck maybe)

Case1: ((int)((b+((c-d)+a))/e)&(int)((b+((c-d)+a))/e))

Case2:

((((int)a&(int)(((((((mod(e,a) _c) /e)_(((((int)(d-a)&(int)b)+e)/a)/e))/((((int)e&(int)c)+e)+(c+(e/a)))) _c) /e)_e))/((((int)e&(int)c)+e)+((b/e)+(e/e))))+(((((((((mod(e,a) _c) /e)_(((((int)(d-e)&(int)b)+e)/a)/e))/((((int)e&(int)c)+e)+((b/e)+(e/e)))) _c) /e)_ <..........10383 characters here.........> ))))))/e))/((((int)e&(int)c)+e)+(((d-e)/e)+((d/b)/e))))+(((mod(e,a)/e)+(b/e))+(((c/b)+((d+b)/e))/e)))))))))

The GP output (case 1 and 2) above was generated with a tweaked version of [https://github.com/rogeralsing/go-genetic- math](https://github.com/rogeralsing/go-genetic-math)

</comment></comment></comment><comment><USER16> That's as strong as a statement as Trump: Learn Machine Learning or you'll be a Dinosaur in 3 years...

Maybe if it was coming from Bill Gates, Mark Zuckerberg, or another tech titan with some actual coding experience and a deeper level of learning about what ML even is. Cuban's a business man, and most CEO's I know don't have a clue about the stacks that run their own company, let alone what's popular.

That said, I do think ML will be important, but I develop ecommerce apps and things of the such in Laravel, unless I move into AI and Neural nets I don't see needing to know a lot about ML (though I wouldn't mind moving in that direction as that space picks up) -- but there's still plenty of opportunities without it.

<comment><USER17> Making machines learn, applying machine learning to successfully solve problems, and positioning business assets to benefit from machine learning are three very different pieces of the "learn machine learning" puzzle. I don't know how any human would be able to go from 0 to having a good grasp of even one of these pieces in three years let alone all of them.

I suppose there will be (and to some degree already are) machine learning magic wands, but they are going to be the kinds of things that suck capital out of the companies that utilize them (through loss of proprietary data and competition blocking moats.)

</comment></comment><comment><USER18> Assuming we're all going to be deep learning programmers is quite a bit foolhardy. I think what's really relevant to consider is AI winters can and do happen[1]. I would not disagree deep learning has done some amazing things, what I would say is it does have limitations.

What causes AI winters is when an advance such as deep learning can be applied to new problems and leads to increased interest. And while this new thing is really good as a subset of problems and impresses the public, of course it can't displace humans at everything and naturally has it's limitations.

So funding pours in, everyone gets hyped, and then those natural limits are (re)discovered and everyone gets all anti-AI research. Of course many people knew the limitations all along, but the dream is gone and so is a lot of funding until the next thing comes along.

This is probably natural to a lot of fields but AI just seems more prone to these boom and bust cycles because it's really exciting stuff.

[1] [https://en.wikipedia.org/wiki/AI_winter](https://en.wikipedia.org/wiki/AI_winter)

<comment><USER19> Exactly. 25 years later, I'm still waiting to be replaced by an Expert System. A lot of the tech that fueled the hype train (logic programming! genetic algorithms!) is still really neat, but it didn't work out the way we expected. Same thing will happen with ML. It's the Prolog of tomorrow.

</comment></comment><comment><USER20> Good luck with that. Any place doing serious ML will require the person to have a PhD or have publications and presentations at conferences like NIPS/ICML. Even most CS grads with a bachelors do not have the math background required unless they double majored in math or stats.

This is more VC/founders who are hyping up AI and need more ML folks so they can drive down costs.

<comment><USER21> Utter nonsense. A PhD signals two things: that a person has the same degree of mastery of core material as a person with a master's degree and that he or she has the determination to do additional original research sufficient to produce a 100 page paper.

It isn't required for any serious research effort, except by the accident of inertia. And it certainly isn't a necessary indicator of determination.

<comment><USER22> You seem to make extremely light of "doing original research" here. A PhD _or equivalent_ is absolutely required to do serious research in the field. Sure, you can always get the depth of knowledge required without a formal program, but the reality is that few do. Most people just take Machine Learning 101 then think they are a domain expert.

That said, there is definitely a place for non-PhD level ML practitioners. I don't think the industry has stabilized in this regard, but I can definitely see a "machine learning developer" type position becoming quite common. This is not the same as someone doing original research, but would definitely meet the needs of a great many business use cases.

<comment><USER21> I'm not taking it lightly at all, considering I've done it. I know exactly what it requires and what it signals.

</comment></comment></comment></comment><comment><USER23> Honest question : once the technics will settle a bit, and libraries are created, what will be needed, apart from knowing that machine learning algorithm are based on some kind of stasticial inference, with a few settings here and there ?

I mean, we don't need a phd in image compression to create a service that streams videos. We just use libraries. Same for everything in computer science, it always end up packaged in some kind of reusable code or service, and only some specialists remain working in the field to work on marginal improvements.

Why would ML be any different ?

<comment><USER24> Once you've plugged your data into an ML system and gives you a classifier, are you done? What if the results are not good enough, do you just move on to another problem?

If you don't just move on to another problem you will need people who know how to push these systems further.

<comment><USER25> But at some point, there is a difference between turning dials of the systems vs implementing new novel ways of these systems. Obviously we always need new novel approaches, but how much of that should stay in phd/academic/research world and how much spreads out into engineering day to day activities?

I am rather newbish in the whole space, but most everything I've seen is quite often just knowing enough to turn the right dials the right way. And I do wonder how long will it be before some of these dials can start turning themselves with more iterations with a simple, "yes that's what I want, or no that's what I don't want"

Sure, it might take some more cycles for it to find optimal in this example.

<comment><USER24> It all comes down to ROI of going further; if the ROI is small, people won't go much further than twiddling some knobs. I think there's a reason you see people throwing a lot of analysis at finance.

Understanding what models are doing and adding new features/data transformations is standard work for ML practitioners now. If you believe the deep learning hype, architecture engineering is the new feature engineering, and to the extent that that is true, industry will essentially resemble academia to some extent. Maybe not making anything groundbreaking, but mixing ideas together.

</comment></comment></comment></comment><comment><USER26> Either he's right about machine learning, or this is exactly the kind of thing bubbles are made of.

<comment><USER27> Of course he is right. I saw some dinosaur characteristics already showing up when I looked myself in mirror this morning.

<comment><USER28> You are so lucky! I can't even look into a mirror since I learn 3 years ago that a NoSQL ninja will soon stab me in the back and steal my job because I work with that declining SQL old stuff!

<comment><USER29> Those made me laugh embarrassingly loudly.

</comment></comment></comment></comment><comment><USER30> I'll place this in the same folder as the articles claiming Wix will eventually replace web developers.

</comment><comment><USER31> Normally I'd laugh off any Mark Cuban antics but he isn't wrong. AI is going to greatly reduce white collar jobs with economies of scale.

Luddites of 18th century thought they would never be replaced and continued on their trajectory.

<comment><USER32> In three years? No way.

A lot of white-collar jobs may be automated (or otherwise changed beyond recognition due to technology) after about thirty years maybe, but not three.

<comment><USER31> I agree 3 years is way too short. I'd say 15 years is even early. 30 year seems maybe, 100% in 60 years.

</comment></comment></comment><comment><USER33> (Pre-apology. I am not trolling, please don't get my comment below more than what I intended: another perspective to look at the strong reaction Cuban's comments incited.)

Reading through the comments, I see that Cuban's statement upset and even angered several HN commenters. That is a strong emotional reaction.

I am not saying it is the 5 stages of grief, but the first 3 fits: denial, anger, bargaining, depression and acceptance.

Also from Howard Aiken: Don't worry about people stealing your ideas. If your ideas are any good, you'll have to ram them down people's throats.

<comment><USER34> I 'm not even sure why it provokes such reaction. Neural networks have existed for 4 decades ; without the deep- part, but we know their potential power and we still have not been replaced. Granted, this time it's different. I think what worries most of us is that neural nets need lots of data and we don't have access to it. Still, they are easy to learn and we should be learning about them (note to self).

</comment></comment><comment><USER35> No thanks. Fundamentals and not hype is what makes one not a dinosaur.

</comment><comment><USER13> I think prosthetic knowledge will become deeper and more accurate in the long run. And if it scales we don't need many people building the general purpose AI.

With this prosthetic knowledge we will have to learn much more what to ask and know how much the machine knows.

One has to quickly grasp the abstract that is one level too high or detailed for the machine to find and than find the seperate answers of the level below to recombine them. You can't yet ask where to open a restaurant, but you can google for demographics and write a program to map ratios between income, foot-traffic density and restaurant density.

Once we can ask what and where is the most profitable business in to start in town, we probably still don't get a step by step guide how to do it, interior design included. Where the rubber meets the road there is still a lot of oppertunities to decide on and complex data we can grasp more easy than the machine.

</comment><comment><USER36> Just like there isn't such a thing as polymaths anymore because the world has so many specialized skills, I think there won't be the possibilities of things like "full stack developer" in the near future because of the complexities for development. Some things that contribute to the complexities will be: ubiquitous controls, advanced AI, internet of things, augmented reality, machine learning, and new technologies we don't even have yet. We are in the golden age now where a single person can sometimes create a better website or app compared to a whole development team at a fortune 500 company. I think our Internet world will become so complex in the very near future that a single person simply won't be able be capable and they'll have to become specialized in only a portion of it.

</comment><comment><USER37> Sorry, I refuse to visit such a clickbait headline.

</comment><comment><USER38> I think what he meant to say was that companies should learn it in 3 years or the competition will drive them out of business. I don't think he meant individuals will be dinosaurs, but startups that fail to take advantage of ML/AI.

</comment><comment><USER39> Three years ago, Machine Learning on a resume meant: "Good candidate."

Currently, it means: "Jumps on bandwagons, caution."

In three years, it'll mean: "Brainless buzzwords, avoid."

</comment><comment><USER40> I want a nickel every time someone says programming jobs will be automated in 5 years. This goes back to the beginning of programming and it hasn't happened.

</comment><comment><USER41> Machine learning would imply the machine needs to learn it not me. Knowing something about it and actually using it are quite different. While it might appear "everywhere" most of programming is still not ML and probably won't me. When I started in 1981 I didn't know C yet, that did not make me a dinosaur then either.

</comment><comment><USER42> "Mark also said that what happens in the next 5–10 years is just going to blow everybody away, especially in the field of automation. He thinks even programming is vulnerable to being automated and reducing the number of available programming jobs."

He's talking out of his ass here. This won't be happening anytime soon (if ever)

</comment><comment><USER43> I kind of read it "learn it and you'll be a dinasaur for 3 years". It made me quite excited at the prospect. I started to practice growling and running at a curious forward angle , but on second reading I find myself disappointed.

</comment><comment><USER44> I wonder to what degree he means. Because if he means "really" learning it, this is akind to the "learn to program in a week" books. It takes much more than three years to learn well.

<comment><USER12> Here's my suggestion to people worried about this: Learn about how to use bayesian models and clustering methods, and how to recognise where they may be applicable, and you will already be able to produce things that will astound executives out there, and deliver very real value for your employer / customers, and those methods are simple - you don't even need to understand the maths to be able to make use of them, though it helps.

By all means, start learning actual machine learning methods too, rather than just statistical methods, but as I pointed out elsewhere on this thread: there is low hanging fruit _everywhere_.

Not nearly all of those will need "proper" machine learning, and even fewer will be willing to pay what it will cost to hire people with in-depth machine learning experience or pay the development costs or computational costs anytime soon. But a lot of them will buy into the buzzwords and look for a cheaper halfway-house or be open to pitches.

</comment></comment><comment><USER45> This is so dumb. You arent going to understand or get a job in machine learning unless you have at least a masters in the subject. Its extremely difficult and complex. I see tons of college students taking machine learning classes in anticipation of becoming a dinosaur amd none of them could get a machine learning job afterwards. Programming has always been pretty easy. The ai revolution wont be like the home computer revolution. Its going to be led by a relatively small group of academics, scientists and engineers working in prestigious research positions.

<comment><USER46> Currently there just aren't that many ML jobs out there to apply for - but who knows what the landscape will be like in 5 years or so?

Your assertion, though:

> This is so dumb. You arent going to understand or get a job in machine > learning unless you have at least a masters in the subject. Its extremely > difficult and complex.

...couldn't be further from the truth. You can understand this stuff without a masters in the subject. It really isn't too difficult or complex. Sure, I will admit that understanding how to take a derivative might be useful, but despite not having that knowledge (but I'm working on obtaining it), I have still been able to implement successfully working ML solutions - at least in a classroom- type environment.

My last success was getting a virtual car to drive around a virtual track, staying on the track and negotiating the curves, using an implementation of the NVIDIA End-to-End CNN architecture and some data I generated (plus augmentation and some other fun stuff). I used Keras and Python 3, running on my workstation at home, with a 750 ti SC as my "GPU" (I really need to upgrade this). My model converged very well after 10 epochs, but after 20 the loss was pushed pretty low to sub 1%. As far as I could tell, there wasn't evidence of overfitting (I need to do more investigation on this, though).

This was all done as part of Udacity's Self-Driving Car Engineer Nanodegree, which I am taking part in. Prior to this, I also completed Udacity's CS373 course in 2012, and Andrew Ng's ML Class in 2011. My motivation for all of this has mainly been my interest in autonomous unmanned ground vehicle robotics technology. I have an ongoing side-project in developing such a platform (seemingly back-burner'd a lot, though - life getting in the way, I guess). Even so, if a job offer comes about because of it, I'm not going to complain.

As it is, I believe the knowledge has helped me land positions, since it shows my dedication to improving my skills in problem domains outside of the everyday software development tasks. When potential employers have asked about it, I can show them some code I've worked on, while mentioning how some of the more simpler ML methods could help in a business problem domain. It sets me apart somewhat from other candidates, I believe.

Especially those who think the topic isn't worth their time to learn, because it may be "difficult and complex".

</comment></comment><comment><USER47> It doesn't matter how far technology gets, there are some -isms and they are the real Dinosaurs that we have to get over and we are too small.

</comment><comment><USER48> Oh yeah? Does Mark Cuban know artificial intelligence himself or is he just asking people to study it and work for him? :)

</comment><comment><USER49> I am sysadmin/devops what machine learning tools and topics would you recommend to learn for that field?

</comment><comment><USER50> That page has so much JS bloat it made my top-of-the-line MBP lag just scrolling.

</comment><comment><USER51> anyone knows if there is a business need for human to train/label data? I have been thinking of going to a place w/ cheap labor cost (perhaps Vietnam) and set up an operation like this.

<comment><USER46> In the short term, perhaps.

In the long term, possibly not - there are already efforts and approaches being done in ML/deep learning to get models to label unlabeled data (google "deep learning unlabeled data" for tons of research info).

</comment></comment><comment><USER52> Ok, so where do I start?

</comment><comment><USER53> Why don't we just learn it in 3 years, then?

</comment><comment><USER54> No, you're not going to be a "dinosaur". 99% of extremely well compensated software engineering jobs do not involve ML. Using top large companies as a proxy of what things are going to be like in the world at large 3 years from now, maybe one in 200-300 engineers does anything in any way related to ML there. And that's a generous estimate. You do need to know what it is, roughly, but there's no need to drop everything you're doing and switch careers.

</comment><comment><USER55> Yeah. I'm going to be a clickbaitsaurus.</comment>


How Slavery Really Ended in America - <AUTHOR> http://www.nytimes.com/2011/04/03/magazine/mag-03CivilWar-t.html?_r=1&pagewanted=all

<comment><USER2> Rosa parks did not sit at the back of the bus because she was tired as most histories have it. She sat there as a courageous act of civil disobedience after being carefully selected due to her impeccable character (so that the incident could not be dismissed as an act by a person without good standing).

</comment><comment><USER3> OK yea so I'm flagging this one. Am I wrong?

<comment><USER4> I don't know, the 'contraband' term is like the ultimate pivot.</comment></comment>


Tech Superstars Build 'Startup Factories' - <AUTHOR> http://www.wired.com/2014/11/startup-factories/?mbid=social_fb <comment><USER2> This is not "the next big thing." It's actually symptomatic of a bug in silicon valley culture - high profile entrepreneurs aren't allowed to fail in the same way as normal folks.

When these studios work, it's not because the studio approach is inherently a better way to do things, but rather because the people running them are really awesome.

The only reason to start a studio, as far as I can tell, is to set the expectation you'll release a few crappy products at first.

This is normally what a startup does anyway. I guess the difference is that high-profile entrepreneurs aren't given the same leeway to fail, which kind of sucks.

<comment><USER3> Trust me, they can fail. I have both been one of these and invested in these.

They often get a first pass free but they still have to succeed in the normal way.

My next thing is unlikely to be venture backed until it already has some success or momentum.

<comment><USER4> I read the grandparent post as "People in Silicon Valley often have the unrealistic expectation that everything a previously-successful entrepreneur does will succeed. When their first try inevitably doesn't work, this poisons the well for subsequent refinement and iteration. As a result, previously- successful entrepreneurs are creating startup labs to set the expectation that everything coming out of it is an experiment and insulate themselves from the PR backlash of trying some dumb ideas to get to a good one."

Which is not at-odds with your comment, although as a previously-successful entrepreneur, perhaps you can speak to whether or not there really is that backlash and premature judgment that he posits.

(Personally, as someone without much of a brand name, I relish the freedom that gives me to try stupid stuff. There's no way I'd be brave enough to try my current startup attempt - which is really quite humble - if everyone expected me to invent the next big thing.)

<comment><USER3> I think that it is hard to build great products if you raise money first. Success is corrosive.

</comment></comment></comment></comment><comment><USER5> I'm a bit skeptical.

I'm not sure that a creative enterprise like entrepreneurship is amenable to any sort of factory model. While theoretically it could be a bit like drug discovery -- make lots of permutations, test them, iterate, goal seek -- the problem is with the human factors. Companies aren't organic molecules that can be reliably produced and then re-produced. They're made out of people.

I suspect that these entities would become echo chambers dominated by cronyism. The term "stars" already gives me that feel. The incentive structure gets all wacked out... it ends up being more about status within the startup ecosystem than shipping stuff that works and that the market likes. The SV ecosystem in particular already has this problem, and concentrating it more into a more institutional model might make it worse.

I think the same problem haunts modern-day academic "factory science," where people who specialize in getting grants are very good at getting grants and churning out very mundane, plodding science.

The best accelerators escape some of this problem by accepting open applications from anyone, anywhere.

<comment><USER6> This is the most coherent and observant comment I've seen on HN in a very long time.

</comment></comment><comment><USER7> >> "A lot of entrepreneurs are motivated to understand how to make their success repeatable," says Prof. Williams. "But what they have to recognize is there's a lot of luck involved in entrepreneurship, and most entrepreneurs in the tech sector might only get lucky once."

This actually seems like a good reason to start a studio or accelerator. Even YC understands that half of their companies will fail. In many cases this not because the founders are lazy or untalented but because there's a good deal of luck involved in creating a product that sticks. Consumer products in particular are extremely hit-based so it kind of makes sense to make a "record company" rather than put all your eggs into a single band.

<comment><USER8> I bet if you asked any of the founders mentioned in the post, this would be their explicit answer.

Launching 4 divergent products a year means you're 4x as likely to find a hit in that time frame.

</comment></comment><comment><USER9> Idealab has been doing this for 18 years now: [http://www.idealab.com/our_companies/](http://www.idealab.com/our_companies/)

</comment><comment><USER10> "Lately, however, a new formula has begun to take hold, one that challenges the very idea of how a business should be built. It plays out quite differently: you start a business, your business experiments with lots of ideas, many ideas fail but some succeed, you turn these ideas into new businesses, and the formula repeats on its own. Or at least, you hope it will."

Where I am confused/interested is how the investment/ownership works in this case. So if I start a company, discover a great business/product and then create another company around it, I would assume that the investors in the original company would get the same percentage in the new company?

</comment><comment><USER11> these sorts of efforts seem to simply stem from a thinking paradigm, that.. hyperbole ahead.. may be most easily accessible through programming, of organising your process in order to reuse as much functionality as possible for highest efficiency

musk talks about how interesting process manufacturing is: ~" very often people think of manufacturing as some rote process of making copies, which it isn't, which it actually isn't, it's building a machine that makes the machine, and if you think the machine is important, well then building the machine that makes the machine is also extremely important, and more often than not, what i've found is, um, it is the manufacturing that is harder than the actual product ".. Elon Musk, One on One with Elon Musk MIT AeroAstro Centennial Symposium .. ,45:13~47:39 .. [https://www.youtube.com/watch?v=SOpmaLY9XdI#t=45m13s](https://www.youtube.com/watch?v=SOpmaLY9XdI#t=45m13s)

</comment><comment><USER12> I can't help but see parallels to Skunk Works.</comment>


Ask HN: Canadian founders/consultants, what are options for ext. health benefits - <AUTHOR> Going out on my own starting May 1st, curious to see what others have done for extended/supplemental health benefits. Partner is on mat leave so we get some benefits through her plan, but I'm wondering if there are better options than Blue Cross or Manulife. Thanks <comment><USER2> Hey, I have experience with Blue cross and Sunlife and they were both fine. If you need any more details (or contact info for an agent to set everything up for you and pick you the best and most cost effective plan) I can refer you to one. Good luck on starting on your own BTW, hope it works out;)

<comment><AUTHOR> Thanks!! Yeah I was hoping there was a more "modern" service in the Canadian market, but seems like Blue Cross is the way to go.

Appreciate the help.</comment></comment>


Ask HN: Lesser known blogging apps? - <AUTHOR>

I've gotten a bit sick of having to constantly reinstall Wordpress, with all of its seemingly endless vulnerabilities and security upgrades.  It's also a pain to constantly have to look for new plugins and themes that work with the newer versions.
So I'm looking for a replacement that's secure, elegant, and less of a hassle to maintain.
Any recommendations? <comment><USER2> I recently found myself in a similar position, and found Jekyll ("a blog aware, static site generator") to meet my needs perfectly. Jekyll rejects the implicit assumption of most blogging software: that the solution requires a dynamic platform.

When you approach the problem with that in mind, what you end up with is exactly the three things you are looking for, something that is inherently secure and low-maintenance, with a blogging workflow that is simplicity itself.

      vim _posts/YYYY-MM-DD-title-of-post.markdown
      git commit -a -m 'new post'
      git push

Project Page: <http://github.com/mojombo/jekyll>

Introductory Post by the Author: [http://www.mojombo.com/2008/11/17/blogging- like-a-hacker.htm...](http://www.mojombo.com/2008/11/17/blogging-like-a- hacker.html)

</comment><comment><USER3> I like Textpattern. It's pretty bare bones, though. You have to put some work in, but once everything is running, it's pretty hassle free.

Link: <http://textpattern.com/>

By the way, the Textpattern Support Forum is one of Textpattern's hidden treasures and always extremely helpful.

</comment><comment><USER4> You want every feature of Wordpress, but you don't want Wordpress. Not once in the last 3 years have I had a plugin that didn't work with a newer version. I haven't had to "reinstall" it even once either. Maybe you just need to choose your plugins more wisely, or if you really care about the quality and security of your blog; write your own plugin.

You're not adverse to switching platform entirely and if the comments here are to be followed, you don't mind rolling your own platform. But you can't write your own theme that's compatible with future versions?

I'd say if you pay attention to the capabilities of Wordpress and actually use it as you're supposed to (I've not seen one major security vulnerability that affected the current version, someone can correct me if I'm wrong) you won't find a better fit for your requirements.

<comment><AUTHOR> Where did I say I wanted every feature of Wordpress?

Where did I say I didn't mind writing my own platform?

In your rush to defend Wordpress you're assuming a bit too much.

 _"I've not seen one major security vulnerability that affected the current version"_

But I'm not running the current version. In fact, I'm probably at least a few versions back, if not more.

 _"you won't find a better fit for your requirements"_

My requirements are: something more secure than wordpress, something elegant, and less of a hassle to maintain.

You're telling me there's nothing like that out there? Pardon me if I'm a bit incredulous.

<comment><USER4> "Where did I say I didn't mind writing my own platform?"

My point was exactly this. Rather than writing your own platform, which will most likely be less secure (but not vulnerable to blanket attacks), you could just write the plugins you want and a theme and then Wordpress is absolutely no hassle at all to maintain. Everything is done via auto-update and after you've made a theme you never have to touch code again and you wont have to suffer feature-wise.

I have never once had auto-update fail and I run 10-15 off-the-shelf plugins.

There are things more secure, they are elegant, but they are definitely not less of a hassle to maintain. I have yet to see any platform (though I haven't studied those outside of the Rails community that thoroughly) that have an auto-update feature so complete and problem-free that Wordpress has.

If you are to say just one good thing about Wordpress, it is that it is hassle-free to maintain. This is the reason it has become popular, the only way any sort of software can become popular is when people without coding experience or knowledge of how to admin a server can maintain and update it.

Since you haven't updated it for a couple of versions, I'd strongly recommend you do so and try using it again. A lot of development happens and I'd suggest you build a new opinion on what Wordpress actually is today.

If you still don't think auto-updating everything and installing both themes and plugins from the admin-page without having to touch the filesystem manually – you can try to find something easier, but I sincerely doubt you will.

</comment></comment></comment><comment><USER5> Write your own.

Use a framework (Pylons, Django, RoR, whatever) along with Disqus for commenting. It'll take only a very short amount of time, and you'll have total control.

Doing this won't make your site more or less secure, but it will prevent from being hit by blanket attacks that target popular platforms like wordpress.

(eg. 300 lines of Python on Pylons + 500 lines of css/templating (loc includes white-space and docs) = <http://janitha.com> with admin interface)

<comment><USER6> Just for a rough scope, mine is:

• 3000 lines of PHP (SQLite for storage)

• 500 lines of JavaScript (wysiwyg editor)

• 300 lines of CSS

• 0 code not written by me (well, ok PHP and SQLite)

That implements:

• Articles (including private drafts)

• WYSIWYG editing with XSS protection

• Comments

• Attachments.

• Account management, superuser separation.

• Search, time based navigation.

• RSS, sitemap.

</comment></comment><comment><USER7> Learn Django and roll your own in one weekend.

</comment><comment><USER8> Cushycms.com is easy...</comment>


Very Cool Search Engine: Parallax - Watch the Video - <AUTHOR> http://www.freebase.com/labs/parallax/

<comment><USER2> seriously cool.

<comment><AUTHOR> I know, it gets cooler the longer I've been thinking about it. The freebase database is the only real limitation on it though.</comment></comment>


'South Park' creators issue a mocking 'apology' to China - <AUTHOR> https://www.businessinsider.com/south-park-creators-issue-mock-apology-to-china-after-ban-2019-10 <comment><USER2> I love South Park and it's defense of freedom. We should boycott the NBA and blizzard for their cowardice and putting money ahead of democracy.</comment>


Equiphunt: Construction equipment rental in india - <AUTHOR> https://www.equiphunt.com/ <comment><AUTHOR> We provide a platform that makes lending and renting construction equipment easy. Our platform provides renters with cost-effective peer-to-peer rental equipment which are close to their project sites. Those who own equipment can benefit by earning revenue by renting out the idle equipment.</comment>


Internal status email: Twitter at 3 months old. 160 Users & 100 Tweets per day  - <AUTHOR> http://anarchogeek.com/2011/03/23/old-twitter-email-160-users-after-three-months/

<comment><USER2> This is remarkable, even to me. The main point: if you're doing a startup, things take a _long_ time. Longer than you'd expect. And overnight success is anything but.

<comment><USER3> Personally 160 users sounds like a lot to me. None of the unfunded services I've bootstrapped had reached that.

<comment><AUTHOR> Mind you, these aren't paying clients or anything, just a 160 twitter accounts. At the time you had to have it created FROM a mobile phone, so the onboarding process was clunky. We were showing it to our friends, tell them how cool it was. A team of 10, with 3 months to pressure their friends and family in to using the service, got 160 users.

</comment></comment></comment><comment><USER4> Does anybody have any information about the types of things that twitter did at first to market themselves?

This is a problem for me doing thingist (<http://thingist.com>)... the people who have found and signed up for it seem to have really liked it, but I'm having trouble figuring out how to get _more_ of those people.

(And I am an admittedly horrible marketing person)

<comment><USER5> If I were you I'd add a facebook like button to each thing and allow people to create lists of things they love just by clicking the facebook like button (no registration required, just save their list to a cookie).

Then if they signup they can save their list. This makes it easy for users to jump right it in, and may bring in a lot of traffic from facebook. Of course, some users may not want to share each thing they like on facebook, so you'd probably want a normal "love this" button as well for logged in users.

<comment><USER4> There are like buttons on the item pages... (like here: <http://thingist.com/t/item/4720/>) I tried putting them in the feed, but they looked really out of place (it made things look really really cluttered)

I really like the idea of [optionally] importing facebook likes... Hmm

(As a sidenote: can I just point out that facebook's API is freaking _awesome_?)

<comment><USER6> > (As a sidenote: can I just point out that facebook's API is freaking > awesome?)

No you may not. Facebooks API is horrible. I was just implementing the like buttons on my site and realized that they have to be iframes (even the FBXML or whatever its called creates iframes). This turns out a bit ridiculous on pages such as yours (if you put them on the feed page) and mine where you Twitter on the other hand allows you to just gives you a URL which points users to a link to share the page.

<comment><USER4> Well, you could write your own, but you'd have to have users authenticate the application. In my opinion, this isn't _much_ different than twitter, since both actions would require two clicks:

facebook: click your custom widget -> facebook prompt -> perform action

twitter: click your custom widget -> twitter prompt -> perform action

(Or just do like I do, and change the size of the iframe to 450x20)

<comment><USER6> as far as i'm aware, you can't really write your own. I was watching the network traffic for a submit and it was pretty ridiculous how many transactions it did when you clicked "like" (about 4 if i remember correctly). Having the users authenticate the action would actually be good for sites like mine but facebook doesn't seem to provide that option.

</comment></comment></comment></comment></comment></comment><comment><USER7> "We receive about 100 status updates per day". 5 years later, the average number of tweets per day is 140 MILLION.

(According to <http://blog.twitter.com/2011/03/numbers.html>)

<comment><USER8> Loved that! It's great to see that even great big things start small.

</comment></comment><comment><USER9> Google Cache Link : [http://webcache.googleusercontent.com/search?sclient=psy&...](http://webcache.googleusercontent.com/search?sclient=psy&hl=en&q=cache%3Ahttp%3A%2F%2Fanarchogeek.com%2F2011%2F03%2F23%2Fold- twitter-email-160-users-after-three-months%2F&aq=f&aqi=&aql=&oq=&pbx=1)

<comment><USER10> How did you find that? I found the original article in Google but there was no link to a cached version.

<comment><USER9> Take the URL you're trying to pull up and search for

cache:<target URL here>

<comment><USER11> In Firefox, you can also bookmark the URL

<http://www.google.com/search?q=cache:%s>

Then give it the keyword 'cache'.

From now on, from the URL bar, you can just type cache <whatever> and it will go straight to a search for the cache of that.

<comment><USER10> Very cool! Thanks for the replies, good to know.

</comment></comment></comment></comment></comment><comment><USER12> I'll be the first to say... Thank you for putting the vowels back in your name. "Twttr" looks horrible.

<comment><USER13> The name has always been "Twitter," but they were wanting to get the SMS short code "twttr." Unfortunately for them (fortunately for us?) someone already had it. :)

<comment><AUTHOR> It was always PRONOUNCED twitter, but we did write it twttr, everywhere, back in the day.

<comment><USER13> Right, that's what I meant. :)

<comment><AUTHOR> Yes, the twatter thing, wasn't something we thought of, but many other people had it pop right in to their heads. It was, unfortunate.

</comment></comment></comment></comment></comment><comment><USER10> Link is dead or down, I can't wait to read this!

<comment><AUTHOR> Not sure what happened, sshing in to the server and poking around.

<comment><USER14> Probably your Web server OOMing the box? Check dmesg.

Apache-specific advice: if you're on a small VPS or other box with not much RAM, and didn't tweak the distribution defaults for MaxClients and friends in its configuration, a HN-size load will OOM you rapidly, _especially_ with mod_php. The defaults for prefork MPM are nuts in the major distros (as in, assuming 4 GB of RAM or more for mod_php).

Since you're going up and down, I assume this is the case. I suggest dropping MaxClients to 5 for now and letting us wait a bit.

<comment><AUTHOR> Yeah, i thought i had it back up, went in to a meeting, came back and it's down. When i went in and looked at it there were a ton of apache2 processes. It's my blog server, so i don't pay a lot of attention to it, i probably should.

I dropped down the number of preforked apache processes, we'll see if that helps. It's also where i run some rails experiments, so we'll see. Load's back up to 7...

I had no idea hacker news got a lot of traffic.

</comment></comment></comment></comment><comment><USER15> Having just launched Momentomail and watching our userbase _slowly_ grow despite quite a bit of effort to get coverage, it's been a struggle to keep positive.

This is a great story that put a bunch of hot air in our balloon tonight as we realized we're actually not too far off this track.

We have no expectation of being another Twitter by any possible stretch of the imagination, but finding out that at this early stage we're tracking with a reasonable expectation is a great point of validation.

</comment><comment><USER16> "Older" hackers take note: Biz Stone, Evan Williams: 30+ founders club. They were both over thirty when twitter started.

<comment><AUTHOR> Ev started his first company when he was a teen, and kept starting them over and over again. Biz had founded Xanga, many years before. Sure, they were over 30, i think Jack and Noah were too, when twitter got started. All of them had started earlier companies in their teen's and 20's.

<comment><USER16> Jobs also started NeXT when he was 30 after founding another well known company years before. My point is age shouldn't be a barrier to starting a company you believe in, especially not the imaginary "30" line.

</comment></comment></comment><comment><USER17> Interesting how he signs of with "keep twttring". I that email was written today it would have been "keep tweeting".

<comment><AUTHOR> Nobody liked the word tweet. It was a term created by the user community, and only slowly accepted by the team.

</comment></comment><comment><USER18> For nostalgia's sake (if it's suitable to reveal), what was the original number that Twitter used?

<comment><AUTHOR> The first email i've got from jack, saying he's got a prototype running on his laptop is from March 14th 2006. He called the app "twttr stalker" in that email. I remember it being "friend stalker" as a joke name thrown around as well.</comment></comment>


Standardized grasping and refuelling on-orbit servicing for geo spacecraft [pdf] - <AUTHOR> https://nereus.mech.ntua.gr/Documents/pdf_ps/AA17.pdf <comment><USER2> My group's mission at NASA is highly related: [https://sspd.gsfc.nasa.gov/restore-l.html](https://sspd.gsfc.nasa.gov/restore-l.html)

We're going for LEO reservicing. It's quite a challenging mission, especially since our client was never meant to be reserviced let alone rendezvoused with in the first place.

<comment><USER3> Interesting project. A lot of the NASA publications keep the identity of the client very vague ("A satellite in LEO owned by the U.S. government" as one brochure puts it), which makes me suspect that it must be something "hush- hush" like NRO. Then I find a press release saying the client is Landsat 7 – [https://www.nasa.gov/feature/nasa-s-restore-l-mission-to- ref...](https://www.nasa.gov/feature/nasa-s-restore-l-mission-to-refuel- landsat-7-demonstrate-crosscutting-technologies) – which doesn't sound that "hush-hush" at all.

<comment><USER2> There was a time when we weren't exactly sure which client we were going to refuel, but as far as we know, it will be Landsat-7. I believe NRL and possibly others are working on reservicing more "hush-hush" clients, but I can't say for certain for that very reason haha.

</comment></comment></comment><comment><USER4> This could have been done long ago, but it didn't pay. The first orbital docking was over 50 years ago. The booster cost to get to geosync orbit was so high that refueling missions weren't worth it.

This would be a good use of used Space-X boosters. If it succeeds, great, and if it fails, you've only lost a used booster and the refueling rig. It costs a second stage every time, though; you don't get that back.

</comment><comment><AUTHOR> More at [http://forum.nasaspaceflight.com/index.php?topic=42501.msg29...](http://forum.nasaspaceflight.com/index.php?topic=42501.msg291469#new)

<comment><USER5> Just for context:

Is this research group an official European Space Agency (ESA) group? How probable is that they will launch a test mission with this system? How probable is that the European missions will adopt this (or a minor variant)? ISS? NASA? Russia? China? Other?</comment></comment>


Unsafe cookies leave WordPress accounts open to hijacking, 2-factor bypass - <AUTHOR> http://arstechnica.com/security/2014/05/unsafe-cookies-leave-wordpress-accounts-open-to-hijacking-2-factor-bypass/

<comment><USER2> I think the real problem is that Wordpress appeals to a lot of casual users who are understandably not security experts and the default settings are not secure. Getting a Wordpress server started and working isn't too hard but actually setting one up correctly is almost a full-time job.</comment>


Ask HN: Jobs with Relocation in the US? - <AUTHOR> I'm a US expat who has been living abroad for way too long.
I plan to begin looking for a job probably July-August (expecting the ongoing situation to get better) and I'm wondering what are my chances of finding a job with relocation support.
Not sure how would companies react to the fact I'm currently outside the country with all the intentions to go back. I also never held a job in the US, all my experience is overseas.
I'm a SWE with 5 years of experience in a handful of markets (finance, health, fast food). I've worked with React, NodeJE, Serverless stack (AWS) and have dealt with a lot of proprietary technologies that I rather not talk about.
Worst case scenario for me is just couch surf at my cousin's house in FL, which I rather not do.
Am I being too hopeful to find a job with relocation, living overseas? <comment><USER2> Same chance as getting a signing bonus or company car or them paying extra for a recruitment agency I'd say. For a company it's an expense just taxed differently. I once got such a package consisting of immigration lawyer + flight cost + rental car one month + furnished appartment one month + shipping my stuff, about 12.000 USD total. The HR department called it package and all was organized by a separate company specialized in that. At least the big companies deal with this multiple times per year if not per month.</comment>


The Golden Age of Cord-Cutting Is Over. Now What? - <AUTHOR> https://www.theringer.com/tv/2019/7/12/20691261/hbo-max-cord-cutting-golden-age-over-new-streaming-services <comment><USER2> Piracy is going to be on the up and up.

We can't all justify 3-4 $8.99 and up subscriptions.

<comment><USER3> Just what I was thinking. While I imagine this might trigger a price war and bring subscription costs down for consumers, there's going to be a lot of people that aren't going to pay subscriptions for 3 or 4 separate services.

<comment><USER2> I hope it sparks a price war, but even then it's still hard to stomach. Especially given the amount of active users allowed on an account, it's hard to even share logins anymore.

Netflix keeps increasing their price, and if it goes up any further, my one and only video subscription may get cancelled.

</comment></comment></comment><comment><USER4> Years ago, I honestly didn't see the streaming wars going down like this - Netflix was there and it just kind of ruled over the roost.

Then, slowly, HBO Go came along. I couldn't live without West World. Now, The Office is moving to NBC's service.

So years later, are we really any better off than what cable provided us, say, a decade ago? A _mostly_ all in one solution. That's what I long for at this point.</comment>


Apple says no Java for you, removes plugin from browsers on OS X 10.7 and up - <AUTHOR> http://www.engadget.com/2012/10/18/apple-removes-java-from-osx/ <comment><USER2> If you care about good journalism, follow the source. This is Engadget aggregating an Ars Technica story. That's fine -- there are good reasons for aggregation -- but if you are going to share on social networks, take the time to click to the original and reward the _real_ reporting -- in this case from Dan Goodin.

[http://arstechnica.com/apple/2012/10/apple-removes-java- from...](http://arstechnica.com/apple/2012/10/apple-removes-java-from-all-os- x-web-browsers/)

<comment><AUTHOR> Sorry bout that :)

</comment></comment><comment><USER3> They are uninstalling the Apple-provided Java browsing plugin and letting Oracle handle the browser plugin from now on. Sounds good: why keep Java around by default as a potential security hole now that very few sites use it?

They still provide Java for applications like CrashPlan, Minecraft, or JungleDisk which need it.

<comment><USER4> Don't forget Runescape, one of the biggest MMORPG's in the world, which uses Java for it's 3D front end client, but even they will be gone soon; they're moving to HTML5.

<comment><USER5> Wow, I never thought I'd see the day when Runescape wasn't Java.

<comment><USER6> I didn't know runescape still existed, I played that game 11 years ago.

<comment><USER4> It was really big for a while, had in excess of 200,000 players on at a time, then poor decisions on part of the company who runs them and being bought out by another company caused the game to be less popular than it was.

Currently it stands at about 110,000-140,000 people on at once per night, which while being no mean number itself, consists of a large number of bots, or computerized players, programmed to perform tasks which generate in game money to be sold to legitimate players on external websites.

The % of bots was said at the last RuneFest to be around the 30% mark, but since most players have used some form of botting program in the past, it is more likely to be around 50%.

Over the years, there has been a lot of turmoil in game, from free trade and the wilderness being removed, to it being reinstated, to the release of pay- for-perks via the squeal of fortune, a relatively new money making venture by JaGex, instigated by the new owners (Possibly named MMG, I can't remember off the top of my head) whereby players can buy spins on a virtual wheel of fortune, with prizes ranging from experience lamps, to 50 coins, to rare items and weapons (in a form which may not be sold) all the way up to 200,000,000 coins (which admittedly is extremely rare.)

The culmination of these changes has resulted in a player backlash, whereby the forums (and not just the 'rant' forum) are constantly filled with topics and players complaining, wishing the game was how it used to be.

Adding to this, several staff who felt strongly about the future of the game, also being players themselves, quit their positions at the company, including the CEO. (There is a much longer story and this is very watered down.)

But to give a proper response: The game is still very much existential, though internally, it is filled with anger and cheating.

~

I am in no way affiliated with JaGex, I know some of the staff use HN and I don't want to get any of them in trouble, the new owners tend to act first and think later.

</comment></comment></comment></comment></comment><comment><USER7> I switched from FreeBSD as my desktop to OSX about four years ago because:

a) I needed a unix based desktop

b) I needed end user components (browser, printing, etc.) that just worked

Circa 2008, everything in Safari "just worked" - every site, every player, every piece of embedded bullshit on every little web 2.0 site blah blah blah.

But now I need to manually futz around with flash every two weeks to keep it working ... and now java as well ?

I think OSX still has an edge for me, in terms of getting things done, due to printing and ... ? It's getting awfully close to even, though.

<comment><USER8> Since I was the lone developer using windows at my workplace, I decided to give Apple/OSX a fair shake. The fact OSX was unix based seemed awesome to me (some of my projects are in C).

Then began the hell of trying to do anything "unixy" on OSX. Custom libraries just for the mac (custom libev??), needing to install XCode Dev Tools to get gcc compiler(???). Sigh.

In the end I just ended up running a CentOS VM in virtualbox, and I do my development there. The ONLY benefit I currently gain from a Mac is creating iOS apps.

<comment><USER9> A thousand times this. I used OSX at one job where everyone else was too and was appalled at how bad it is for getting work done. It's pretty and shiny but broken by design in terms of usability. Switching windows is a pain in the ass (different shortcuts to 'alt-tab' between windows of the same application), maximizing a window doesn't work properly, no way to change the window manager. Those are just my gripes with the GUI. As parent pointed out, the best way to do *nix-based work on OSX is to run linux on a VM. This throws the 'is unix-like' argument out the window.

So a crap GUI, crippled CLI, very questionable company policies and politics and to top it off it costs twice as much as everything else. You have to be out of your mind to buy into this.

<comment><USER10> > _no way to change the window manager_

Is this actually the case? I use Linux as my primary OS, but I recall seeing xmonad running in osx on a macbook.

<comment><USER11> That xmonad was almost certainly managing the X11 apps while the native apps were being managed by the standard Apple window manager.

Most Mac users (including myself) make no regular use of any X11 app.

(In fact, shortcomings in X11 and software that relies on X11 are the main reasons I left Linux in the first place).

</comment></comment></comment></comment></comment><comment><USER12> ...if only Java in the browser wouldn't have failed so bad (and it did long time ago, Apple's decision is just a sad reminder of this), we would actually have the "nirvana" of using Python (Jython), Ruby (JRuby), Clojure and more IN THE BROWSER! Same language on the server and in the browser, even on mobile, and the ability for every developer/team to CHOOSE that language from a few option that run on the JVM... (I know we'll have this one day, with languages that compile to Javascript, but... it could have so much more beautiful, another lost "alternate reality", like the ones in which Lisp went mainstream and even OSs were build in it... sigh...)

How dump could Sun and Oracle (I know, the browser Java fight was maybe already lost when Oracle came in...) be not to realize the potential ecosystem that could grow around this? Sigh...

<comment><USER13> Native Client is the next hope for Python, Ruby, etc. in the browser. Much better than trying to compile an existing language to JavaScript.

<https://developers.google.com/native-client/>

<comment><USER12> Hmm... I just can't imagine either Ms or Apple being friendly towards NaCl as it would basically be a way of drilling more wholes into their boats (like competing with Silverlght or the broader "issue" that webifying desktop and mobile apps would risk making iOS or Windows irrelevant and welcome in even more low-cost Android and Linux solutions... every Desktop/iOS app to browser app transition basically makes these guys loose money one way or another...)

</comment></comment></comment><comment><USER14> I don't expect to see much difference in my day-to-day browsing, I can barely remember the last time I encountered a Java applet - most of the time I see them they are some sort of unimportant and old technology demo.

However, I'm of the understanding that in Europe, a lot of bank websites use Java applets as their primary way to do online banking, in which case I can see this decision affecting a lot of people.

<comment><USER15> Maybe after enough thousands of WebExes get delayed another 15 minutes each, Cisco will take this as a sign.

(WebEx has a totally pointless Java applet that only serves to launch the native client app.)

<comment><USER16> On the IE side they do this with ActiveX. I always wondered why they did not come up with a simple webex:// uri.

</comment></comment></comment><comment><USER17> I wasn't too worried about this when i read it, but it appears the latest oracle java plugin is not supported on chrome. I get this message from the download page:

"Chrome does not support Java 7. Java 7 runs only on 64-bit browsers and Chrome is a 32-bit browser.

If you download Java 7, you will not be able to run Java content in Chrome and will need to use a 64-bit browser (such as Safari or Firefox) to run Java content within a browser. Additionally, installing Java 7 will disable the ability to use Apple Java 6 on your system."

So now it looks like I'll have to flip over to firefox if I want to use a site that requires the java plugin - kind of a nuisance.

<comment><USER18> Chrome is only 32-bit? Apparently, yes, at least on the Mac. The issue has been open for 3 years:

<http://code.google.com/p/chromium/issues/detail?id=18323>

"Snow Leopard will be released in less than 2 months. I believe we should start testing a 64bit version of Chrome so it can be ready when SL ships."

<comment><USER16> Chrome and Dropbox are the last non-64bit process on my machine.

Their argument is YAGNI.

<comment><USER19> Not the worst argument, given that each Chrome tab is its own process.

<comment><USER16> > Not the worst argument

It is when it's the only process requiring and loading up a slew of 32-bit dylibs.

</comment></comment></comment></comment></comment><comment><USER20> Sensational; Apple planned on passing off Java to Oracle for a while. Oracle now distributes a Java 7 JRE for OS X directly.

</comment><comment><USER21> The built-in Java was optimized for Retina display and all texts were crisp and sharp. After the update and a manual installation of Oracle's Java Runtime, everything is blurry again.

</comment><comment><USER22> Completely stupid headline; removing words 2 through 6 (and the comma) would fix it.

<comment><USER23> I rather appreciated its snarky nature.

</comment></comment><comment><USER24> I love Apple and their little "surprise, all your users will have to do something to get your app to work today, hope you help desk is staffed!"

And Oracle is no better, making changes as "security updates" that have no pre-release, which is fine in theory but in practice has tended to break our app.

</comment><comment><USER25> Some online photo printing service sites use funky Java Applets to let you upload image files by picking from thumbnails generated on the client side.

Other than that I can only see this move as a plus for internet security.

</comment><comment><USER26> I can't remember the last time I used Java on the client side but I'm sure it was hellish.

</comment><comment><USER27> At the risk of sounding a bit ridiculous, good for them. The less Java, the better.

<comment><USER28> > The less Java, the better.

That's a pretty broad generalization. As Java+Scala programmer I personally seldom use, see or write Java applets. Advocating against the use of Java in general is just silly however. Java (+other JVM languages) is very well suited to backend systems, and with the addition of modern web frameworks like Play it's pretty good choice for frontend work too. Java (+other JVM languages) is used heavily by companies like Google, Amazon, Twitter etc.

> At the risk of sounding a bit ridiculous

You do indeed sound ridiculous, especially since it's just Apple no longer maintaining their own Java plugin, but letting customers install the official plugin from Oracle, just like customers do for every other major operating system.

<comment><USER29> Java is a perfectly accpetable language, as long as i can't tell when an app is using it. Server-side java is great, android is great, but as long as shitty programmers keep writing java apps that make use of some awful GUI toolkit and require the user to install a JRE, people are going to keep hating java. In many cases, the fact that an app is java based can be directly blamed for a poor user experience. sure, it's not the language's fault, but it is what it is.

</comment></comment></comment><comment><USER30> Unlike the previously built-in Java, Oracle's Java plugin doesn't seem to work with Chrome on the Mac due to Chrome being 32 bit. Anyone know a workaround?

<comment><USER31> There doesn't appear to be one other than "Use Safari"

</comment></comment><comment><USER32> Doesn't change much, since the earlier change to the OS meant you don't even _have_ Java by default.

</comment><comment><USER33> I keep Java disabled in Chrome anyway, so no complaints here.

</comment><comment><USER34> Pretty soon, this URL won't be a 404 - <http://www.apple.com/hotnews/thoughts- on-java/>

<comment><USER35> I believe you're looking for [http://www.apple.com/pr/library/2010/11/12Oracle-and- Apple-A...](http://www.apple.com/pr/library/2010/11/12Oracle-and-Apple- Announce-OpenJDK-Project-for-Mac-OS-X.html).

</comment></comment><comment><USER36> How to enable Java browser plugin again: <http://news.ycombinator.com/item?id=4672511>.

</comment><comment><USER37> Consider the sun sanked in the west, they should remove java long time ago.

</comment><comment><USER38> Java is dead in the browser dear Google/Mozilla please remove it from chrome and firefox also forbid it</comment>


Ask HN: Are personal websites not allowed here? - <AUTHOR> Hi everyone, long term HN user here. Recently I updated my website[0] and put a lot of work and detail into it, so I shared it to HN to see opinions about it. I followed HN rules the best I could, with the title reading:
> Show HN: Francisco.io – my new developer website
Few hours later I saw it had 37 votes. This was around double of the, at that moment, top Show HN link (which was submitted at the same time) but my link was nowhere in the Show HN nor in the main page. Comments were picking up steam until they stopped at a moment. I can see some of my submissions as [flagged] but this one was never flagged. These strongly lead me to believe my website was taken down by an admin.
So the question is, are developers portfolios/personal websites disallowed here? I have reviewed several times the guidelines (before and after) but found nothing, besides the obvious "Show HN". I feel like developer websites might fit within what other devs/hackers find interesting.
[0] https://francisco.io/ <comment><USER2> The dividing line for a project like this is whether there's something unusually interesting about it, either in the site content or how the site is made. If people feel like it's just a standard personal website like they themselves might make, they tend to have a "why is this on HN" response and flag or post complaining comments. But if they run into something unexpected and have a "why didn't I think of that?" reaction, such a submission can get a lot of upvotes and become popular.

Home pages consisting of links to articles or projects don't do well on HN, because HN itself is a list of links to articles and projects. It is better to pick the most curious or substantive of the things and submit that instead.

</comment><comment><USER3> From the guidelines[0]:

> _What to Submit: On-Topic: Anything that good hackers would find > interesting._

> _In Submissions: ... Please don 't post on HN to ask or tell us something._

To the best of my knowledge you can submit personal sites, but some people may flag it. That's up to them. To the best of my knowledge the mods won't interfere unless the submission flagrantly contravenes the guidelines, which yours doesn't (as far as I can tell).

But the best thing to do is ask them. In the main, we can't tell if something got flagged, or modded down, or whatever. Only they can tell you what happened.

[0] [https://news.ycombinator.com/newsguidelines.html](https://news.ycombinator.com/newsguidelines.html)

<comment><AUTHOR> Updated; I can see my submissions that were flagged and this one never was. I am asking now _the community_ whether they think personal websites are okay:

> Hi _everyone_

I will also contact the admins separately, thanks for the tip.

<comment><USER4> there's thresholds, on a post that already has enough upvotes/comments [flagged] is only shown after a few users flagging, but the ranking is affected before that.

<comment><USER2> Correct, and this is what happened.

</comment></comment></comment></comment><comment><USER5> I think the issue with your site, is that is seen as outrageous "self- promotion" (which reading from your comments wasn't your intention) here.

Shown HN, is oriented to showing stuff you did, you should highlight some aspect of you new site, which is to the interest of the HN community. For example: "I built my site, crafting my site generator based in GO, which compiles in only 0.5s"

</comment><comment><USER6> Mail the mods and ask. They are friendly.

But I feel that "Show HN" isn't a suitable format for just showing your personal web site. It's more for products or projects.

I'd submit your articles as regular submissions, if I were you.

</comment><comment><USER7> Personal websites are generally acceptable assuming there is actually something of interest to the reader, but it isn't really what Show HN is for. That is more for some kind of project. Also, as with any post, individuals will react as they see fit and details like timing will impact how well it does.

You really can't infer all that much based on how well or how poorly an individual item does. There are just too many variables for the performance of one item to be very informative.

Also 37 points is not bad. Plenty of stuff gets completely ignored.</comment>


List of Lists of Lists - <AUTHOR> https://en.wikipedia.org/wiki/List_of_lists_of_lists <comment><USER2> Disappointingly, not "List of lists that do not contain themselves"</comment>