Why Are Data Science Leaders Running for the Exit? - <AUTHOR> https://www.linkedin.com/pulse/why-data-science-leaders-running-exit-edward-chenard <comment><USER2> This is an article making baseless generalizations that all data science is failing in Silicon Valley, and that the true need of a company is to hire a "data strategist." Unsurprisingly, the article is written by a self-proclaimed data strategist.

This blog post would be more compelling if there were citations or even general context backing up the authors pretty wild claims ("the vast majority (we are talking 80-90%) want to leave their current job", "failure rate of data science teams is over 90% right now", "the top 5 data scientists I have ever worked with, only 1 had a PhD").

As a data scientist working for a relatively well known startup in the Bay Area, I don't dispute that there are problems in this industry. There are many under-/un-qualified managers running around (I don't know if that's a data science specific problem, or if it also applies to much of engineering as well). There are ICs and teams that have trouble producing industry-applicable work because they're too academically focused. There are also business-driven teams that have trouble producing quality/reproducible work because they're too business focused.

That said, the claim of 90% failure is ridiculous on its face. Having another MBA put together a powerpoint presentation about a company's data strategy isn't going to suddenly solve the actual issues in data science.

<comment><USER3> That was also my impression. It's kind of ironic that a Data Science/Strategist writing would be so heavily opinionated and have so little in term of data.

<comment><USER4> Maybe that's because the strategy is to produce bullshit

<comment><USER5> Ha, I like that the grammar of this distinguishes between "there is no strategy" and "the strategy is, actively, to produce bullshit" and lands on the second option, which jives with my experience :)

</comment></comment></comment></comment><comment><USER6> Data science is a horribly overloaded term.

Ask a databases person and they will tell you about ETLs and relational joins. Ask a statistician and you will hear about estimators and the bias-variance tradeoff. Ask a social scientist and they will tell you about experiments and causal inference. Ask a CS theoretician and they will mention streaming algorithms and probabilistic guarantees. Ask a machine learning person and you will probably hear a lot about prediction and stochastic gradient descent.

The approach that will breed the best practitioners is an interdisciplinary one; a great example is UBC's program: [https://masterdatascience.science.ubc.ca/program/courses](https://masterdatascience.science.ubc.ca/program/courses). And also future positions that separate the roles of data janitor, data analyst, machine learning engineer, and so on. There is a huge difference between what Facebook's Core Data Science team does and what most companies call "data science", which is sitting on a huge pile of poorly aggregated data and having little idea what to do with it.

Most importantly, data science has to be thoughtful and part of the engineering process, and can't be done after the fact with digital trace data. It's a lot easier to run experiments than it is to do statistical gymnastics with observational data.

</comment><comment><USER7> There's some irony in an article about data science using only anecdote and emotion to make it's argument. :P

PhD's are notoriously (and understandably) finicky about doing non-research work when the job is sold as research, that's why you have to be sure you really need them. That issue has been around since long before data science in SaaS companies was a thing, it's been around since before the internet was a thing.

Assuming that there really is an exodus problem, PhDs being unprepared to lead teams and do non-data-science work is one theory that seems reasonable, but it definitely isn't covering all possibilities.

Having been in a couple of companies hiring data scientists recently, I personally think the big problem is expectation for data science in general, more than who's been hired to do the job. The couple of companies I've worked with, anecdotally, seem to expect "data science" to uncover huge missing profits, expose gaping inefficiencies, and reveal new revenue streams the business people didn't see. And when there turns out to be only minor ways to streamline things, the team of data scientists need something else to do.

<comment><USER8> I don't blame the practitioners, I blame the business people who foolishly believed it was easy to shake billions out of their data if they applied enough wizardry.

for most, Big Data has been a sham, but it was very profitable for cloud vendors

</comment></comment><comment><USER9> Maybe these people want to leave because they realize they aren't adding value?

I've worked in many Fortune 500's with "data science" or "big data" teams. These are well staffed, very expensive teams that have large budgets for pricey hardware (sometimes on-prem, sometimes in the cloud)

I have never seen one of these teams produce insights or actionable intelligence valued anywhere near their cost. I mean not even close. Usually it is a tremendous money fire. (Also, before the pitchforks come out, I'm sure there are places where the data science team is a profitable department, but it's not the norm, not by any stretch)

Part of the problem is the business doesn't know what questions to ask. Part of the problem is the technology itself. Spark streaming, Hadoop, and all the other tools really aren't very good (very good being defined by helping businesses answer burning questions in a reliable and timely manner)

The most valuable data insights I've seen come from purpose built analytics tools using simple storage backends (RDBMS, elasticsearch etc) where the person running the team is a domain expert, not a "data scientist".

<comment><USER10> I'm a firm believer that data science should be pulled out of IT and put into the business. However, storage is so cheap that you should never NOT collect data if you can. It's better to dump it into a data warehouse and wait for somebody who can use it to come along than it is to never collect it.

Then, and only then, should you look at your service levels and determine if there is a need for some sort of Hadoop or Spark infrastructure.

<comment><USER11> >I'm a firm believer that data science should be pulled out of IT and put into the business.

I say this from personal experience. The major risk here is that Data Scientists will constantly get pulled in as resources to support business fires and high visibility projects that should be handled by other people.

Otherwise what happens is this: "I know you are working on that Data Science project that is scoped for 4 weeks, but can you do this Business Analyst thing the _insert exec name here_ asked for by this Friday?"

Data Scientists need to be shielded from that day to day analyst stuff, otherwise they'll never be able to do their jobs. One of the ways to do this is to put them in IT in a business facing consulting role. IT is typically (not always) is more focused on a proper solution, not day to day triage. So they can filter out projects that aren't appropriate.

<comment><USER12> This may end up repeating the mistakes of a decade or two ago: after a business leader gets two requests rejected, they are very unlikely to go back with a third request - they will simply outsource every future request. Soon the IT departments were being downsized because they couldn't get business leaders to use them instead of going outside.

</comment></comment></comment></comment><comment><USER13> The dissing of PhDs is unwarranted. Gross over-generalization. People being skeptical of ideas in a peer-review sort of way can be both good and bad. For example, the assumptions and claims of this article can do with a substantial amount of skepticism. Perhaps someone should express skepticism and view this article with the peer-review critical eye that he mentions.

I am reminded of climate-change skeptic articles that say "hey these scientists know nothing. See today it's 10 below zero. Common sense! No global warming."

<comment><USER14> Also, the idea that peer review is rife with people killing articles to save their "pet theory" is idiotic. Reviewers just want you to cite them.

<comment><USER15> Ideally, reviewers would just want your paper to be as good as it could be.

And yes, we should all appreciate not just the named author of the work, but all of the work that goes into it. This is true of all works, not just studies.

</comment></comment></comment><comment><USER16> That's very well put reasons. But another significant reason is very often a highly accurate model is not the right model that an organization wants. Hence when you are taking this modelling exercise to the next level, the whole effort of modelling fails because you have spent your time on something that is not required. Hence the accuracy-sophistication obsession of data scientists - irrespective of they are leaders or just ICs - make it tough to establish their credibility and broader organization vision.

And in many other cases, Media has created a myth of Data Scientists as Magicians, hence a lot of people expect a lot of unknowns from Data Scientists while a lot of people become Data Scientists always expecting to create unknowns and magics which is not going to yield any good better than a mere Exploratory Data Analysis based Insight from Microsoft Excel

</comment><comment><USER17> As someone (a Director) running for the exit... lack of control over: taking on new projects, staffing, infrastructure, meeting schedules, deadlines. Complete lack of ability to say "no" to our biggest client. Add in conflicting priorities from leadership, month long delays in compensation adjustment, lack of clarity around valuation status, and having to focus primarily on new and maintenance ETL work.

I got frustrated enough to where I almost quit on the spot a few weeks ago. Frustrated enough to b on the verge of tears and punches because I felt I'd wasted the past two years of my life. I worked to get myself transferred from my leadership role to, ostensibly, a more thought leadership type role which should happen in next few weeks.

However, if I don't see significant changes in January, February, and March then I'm leaving. Honestly, I'll probably leave anyway because I think I can grow my skillset, work on better problems, and set my future up better somewhere else.

What I hate about this situation is that I used to be the biggest supporter this company had. But years of this difficulty is enough.

<comment><USER18> I feel ya; this is almost exactly what I've felt this year. It's just incompetent management and leadership, and it's all too common. But it's incredibly demoralizing to be on the front lines of it. When you can't control anything, and are reduced to reacting on ever more tactical issues, it burns you out hard and fast. Indecisiveness is killer; better to pick something and do it, than waffle around forever spinning the wheels.

</comment></comment><comment><USER19> A working knowledge of some basic stats, access to some decent tooling, a good working knowledge of what the organization is trying to accomplish and the ability to persuade and lead based on findings will likely move the revenue needle much more for most companies than a pure "data science" role.

The trouble is of course we don't have a good name for that role, so it's all "data science".

<comment><USER20> Thats just smart manager with good communication skills

<comment><USER14> Most managers fail in the "knowledge of basic stats" and "access to decent tools" areas. And if they have the knowledge, most larger organizations don't have a ton of managers sitting around writing python code during the day. Their day is full of meetings.

</comment></comment></comment><comment><USER20> Data science and machine learning are different beasts. CS based Machine learning and AI seem useful in task automation. Its real value is in building IP.

DATA science is more like quant consulting.It is actually a subdiscipline in management science in my opinion.

The key role of a data scientist in non SV company is usually 6-fold. First understand the business problem thoroughly. Get the people,process and value stack nailed.

Second and this is the most imp part. Figure out how to frame the business problem. Framing isnt as linear as it looks. But it helps save a ton of time and money if you front load time in framing problem. Substep here is to frame it as an "information" or data problem.

Third articulate a strategy to gather data or information. Inhouse data available? Web scrape data, buy data, build generative models. Youd be suprised how much ML work happens in this step

Fourth shape the information to a format that can be analysed.

Fifth, study the hell out of this dataset- the PHD angle comes here. Very few people are systematically trained to study data with rigor and be humble and honest about their findings.

Lastly connect the dots between insights and business problem at hand.too often this stops with bar graphs and some scatter plots. Thats just lazy. You need to really take ownership of the problem and educate business why the solution will help and be honest about ehat it will take to get it to work. The people, process,value stack in line 1 kicks in here in recommendation and action.

A bonus point. Put some kpi to track how well your suggestions are working.

Real data science is super super hard. Its like finding a real nugget of diamond in dust.

Data science is a way thinking. Its a business culture to be honest.

</comment><comment><USER21> It was all hype. All of it. I enjoyed learning about data science, but in the end, there were no jobs I could actually apply for and realistically get. I also don't think they were providing the big wins for the company that would justify what they were getting paid. Again, all hype.

<comment><USER22> same here. i work great in teams, masters in computer science, do really well in kaggle competitions, I understand when to use the algorithms, how they work, etc.

but in the very few ds interviews I had, I was tanked as soon I got asked questions like: whats the formula for a T test. I know what the test is, and when its not appropriate to apply it, but I don't memorize those kinds of formulas. the field is just too big to do that

<comment><USER23> I'm sorry but a standard t-test is like the most basic thing in statistics after means and variances. It's not like they want you prove the CLT or something. To me it's more like a statistics fizz-buzz.

<comment><USER24> To which, of course, the correct answer is "Unless you have good reason to believe the data is normally distributed, you should be using Mann-Whitney", then explain that :-)

<comment><USER25> Thats not really true though. The vast majority of t-tests are done using a sample average as a test statistic, and by the CLT, as the sample size goes up, the distribution of a sample average becomes approximately normal. So unless you have a really weak sample size, the t-test assumption holds even in the absence of normally distributed data.

</comment></comment></comment></comment></comment><comment><USER26> Pardon the cynicism, but all I see when I read this is MBA turd-word lobbing. It is meaningless drivel, bloviating self-promotion directed at people who don't understand anything about how their world works while thinking they are qualified to lead it because of X degree at Y institution, the admittance of whom was due to Z (powerful rich person) that is friends with his dad.

Others have noted the lack of data coming from a data strategist. That is the feature, not the flaw. Data isn't necessary in these people's worlds. They spout platitudes about data, laud it when it supports their world view, and ignore it when it doesn't. People that buy the world that this guy is selling are suckers.

</comment><comment><USER27> The author is way off base in saying software engineering is about assembly rather than discovery. That's only true of the lowest-skill non-innovating software shops, and even then, developers are constantly having to discover how to use the new tool of the month.

On an unrelated note I don't really buy into the idea of data science as a distinct thing from computer science.

<comment><USER28> > The author is way off base in saying software engineering is about assembly > rather than discovery.

Depends. The interview process that is the fad these days selects for assembly workers. Organizations using that process are doing so to find people who aren't curious about broadening their knowledge and experience, but to find people highly competent at repeatedly doing their CS curriculum over and over.

> On an unrelated note I don't really buy into the idea of data science as a > distinct thing from computer science

How is it not distinct? Data science is closer to a physical engineering discipline than an applied math one. The tools of the trade might be enhanced by application of CS, but the two are quite distinct.

<comment><USER29> > Organizations using that process are doing so to find people who aren't > curious about broadening their knowledge and experience, but to find people > highly competent at repeatedly doing their CS curriculum over and over.

And why are they doing this? Why don't they just buy an existing solution from another vendor, why build your own solution?

<comment><USER28> Because such products typically don't exist (either they aren't appropriate for the scale or the end use, or both).

There's a definite place for these workers.

</comment></comment></comment></comment><comment><USER30> As someone near graduation with a PhD in mathematics with research focusing on machine learning / image processing and beginning the job search, this didn't leave me feeling very optimistic. Is this a problem of not setting proper expectations for a role on the company's part or not fully understanding the expected duties of the position before hired on the data scientist's part?

<comment><USER31> It's a bit of both.

You are unlikely to ever achieve a position in industry that has the same freedom of investigation and time that you experienced as a graduate student, let alone the holy grail of a self-funded post-doc or the like. On the other hand, you won't achieve that as faculty either. In industry you're going to end up spending a lot of time on activities and meetings that don't relate to what you now consider "what you do" (e.g. ETL, domain interview, co-ordination etc.). Your success and happiness in this will depend a lot on whether you consider those things a waste of time taking you away from what you "really do", or an important part of how you do such activities in larger groups.

On the other hand, data science has a similar problem as software programming; failing to know how to find or produce good managers for it, companies tend to promote from the ranks of their best individual contributors. This can work well with enough support and mentorship (assuming the candidate wants to do it) but it can be a disaster without a plan and that support.

<comment><USER30> > You are unlikely to ever achieve a position in industry that has the same > freedom of investigation and time that you experienced as a graduate > student, let alone the holy grail of a self-funded post-doc or the like. On > the other hand, you won't achieve that as faculty either.

which explains my advisor's "enjoy it while you still can!" attitude whenever we talk of such things :)

<comment><USER31> They speak truth :)

</comment></comment></comment></comment><comment><USER32> Besides the demands of agile and corporate culture, is there other reasons why data science folks are leaving (if true)? For instance lack of cooperation, or not using the insights/recommendations?

<comment><USER33> Our data scientist left because instead of data science, he ended up doing more ETL and data engineering support than what he originally had signed up for.

A full-time data engineer should probably have been hired.

I wonder if this leads to an analogous discussion as [http://wiki.c2.com/?ArchitectsDontCode](http://wiki.c2.com/?ArchitectsDontCode).

<comment><USER34> Not too familiar with the data-this, data-that space. What does a data engineer do? What does a data scientist do? Does either code?

<comment><USER35> They both code. The engineer would pull the data from various sources and structure it in a way that the data scientist is happy with. (Tidy format) The DS would the code the models based on the engineer's work, which takes considerably less time.

</comment></comment></comment></comment><comment><USER36> Speak for yourself. I work as a data scientist at a large (non-tech) company. Our team of data scientists is directly responsible for massive amounts of profit that the company would not otherwise have. This article seems like a baseless generalization.

<comment><USER37> A lot of value from Data Science comes in large non-tech companies. It's not the super glamorous type of DS. It is about using data to drive optimizations, process improvements, manage supply chains, instrumenting alert mechanisms to monitor key mechanical and software components etc.

</comment></comment><comment><USER8> probably some realization that 99% of their actual job is ORDER BY, GROUP BY, SUM...not a bunch of cool math scrawled on a whiteboard

I tried warning people off of this field given that they would be doing sql query monkey work and drawing simple line charts...most definitely not an upgrade from software development like it was sold as

<comment><USER13> They're probably in the wrong company. Are you suggesting there are isn't an explosion of jobs and applications requiring advance math and machine learning or statistical inference? If so you are off the mark.

<comment><USER38> You're right of course, but still there is a point: For 1 'intellectually' interesting data science job created there's probably 10 that have more to do with data massaging and all the relatively boring logistical stuff that come with data science.

Doesn't invalidate your point, but the majority of jobs under the very broad 'data science' label just aren't super interesting after all. Guess you just have to be careful to examine exactly what a specific 'data science' position entails.

<comment><USER39> I've found this to be very true. I've got friends who were hired as data scientists, paid a great salary, and are finding themselves doing basic reporting and SQL querying all day. No statistical modeling, and certainly no building anything.

</comment></comment></comment></comment><comment><USER40> I really question this "90%" number for "failed" data science teams.

While I certainly can see overhype in the space leading to team failure (and I have indeed seen that), I'm just surprised that the 10% of teams I've been on were so successful by comparison.

But one of the nasty things I see happening in the space is that often times really great data science folks, in studying a space, come up with a way to invalidate a lot of the business models. If a major player adopted these, there is a chance of success, but it's also a major risk (as it basically unseats the rest of the business).

As such, I think there is a lot of pressure for good data scientists to end up in small teams leading what we'd call 'highly disruptive' businesses. We see this in the finance sector (where it's least likely to succeed) all the time.

</comment><comment><USER41> I've never seen a "data scientist" produce anything meaningful, at least at my company. They run some data through some Python framework and produce weird meaningless numbers that I'm supposed to be impressed by or to trust. No insight as to how that number came to be. "87.525%". Ok sweet. Could've come from /dev/urandom for all I know. At least 3 of them have left in the 2 years that I've been here.

It seems like 90% of these guys are buzzword wankers who jumped onto the "Big $$$" bandwagon. Same type of person who put "PHP Wizard" on their resume in 2005.

Good riddance.

I'm sure, of course, that quite a few of them are decent, intelligent people producing real value at real companies. But the ones I've dealt with? Nah.

<comment><USER42> You sound like a decent person. Perhaps they left because of you?

<comment><USER41> In a company that's thousands of people large, across 5 continents, I have the power to make dozens of people, most of whom I've never communicated with outside of the occasional email, leave? I basically have superpowers.

Like I said, I'm sure "data science" as a science is great, and I'm sure there's plenty of "data scientists" that I would love to sit down and talk with and learn from. I just have never met any.

</comment></comment></comment><comment><USER43> Depends on what data scientist is within an organization.

Alot of times, it means "the guy who does crap in SPSS or needs Tableau".

</comment><comment><USER44> Science progresses at the speed of a funeral.</comment>


Ask HN: Gut instinct quote for this Android Project - <AUTHOR>

Hi,
I'm looking for suggestions on how much to offer/expect for an Android Project contract. I have a New Mum website which users can submit shopping tips to (it's mostly my friends at the moment). My boyfriend made an iPhone app for the website. It is basically a read-only app for my websites API (apart from login/register). I would like to offer my users an Android app also. The project description is:
-Splash screen
-Register screen (Facebook & Email)
-Login screen (Facebook & Email)
-Map screen showing ~100 icon markers (custom icon and popup)
--Map marker icons can be filtered by category, and API searched by date and title/location
-Detail screen, after you click on a map marker. It has 1 main image, hosted on my website and some details describing the item.
-iPhone graphics would be provided, but the Android developer will have to manage all Android design (for phones and tablets etc)
This isn't a job offer (just yet!), I would just like your 'gut instinct' quote, and any supporting comments or suggestions. I hope the app would be ready in 1 or 2 weeks, is that reasonable?
If there are any questions, I'll be glad to answer where I can!
You can also contact me at MichelleMarch8 at gmail.
Merci,
Michelle
Update: while this is a Europe centric request, quotes from all over are welcome! <comment><USER2> Depending on the quality of your API, $4,000-$10,000.

<comment><AUTHOR> Thanks for your answer stray. The API is CRUD based, but the Android app will essentially only read the JSON data. May I ask why the large range of $4,000 to $10,000?

<comment><USER2> Because it has been my experience that programming against a difficult api takes about 2.5 times the effort as programming against an easy one.

And without the benefit of seeing the API spec, I have to provide the entire range.

<comment><AUTHOR> Thankyou for clarifying, that makes sense. Can I also ask, how your quote is weighted given the project description and time-frame that I stated? Are you using a base rate per hour and then compounding project difficulty or is it only given the project description? I'm a little unsure how such quotes are derived.

<comment><USER2> The base rate is not directly related to effort. It is instead based on value.

Sometimes this makes for easy money. Usually it does not. Almost every programming project turns out to be far more complicated than originally thought.</comment></comment></comment></comment></comment>


Ask HN: How the heck do you reach Quora with feedback - <AUTHOR>

These mothers are so closed, I can't even find anything about them or how to raise a concern, on the site. And that's what I wanted to raise a concern about.<p>Well played, Quora. I can see someone there knows Godel. <comment><AUTHOR> I just want to see start ups who frustrate and waste people's time get better. That's all.</comment>


Show HN: I made a simple email reminder app called Please Remind Me - <AUTHOR> https://pleaseremindme.xyz <comment><AUTHOR> Hi everyone!

This is my first little product and I'm super excited to show you what I built over the last 2 weeks. This is basically me scratching my own itch.

The Problem I'm generally quite bad at remembering things. And personally, just setting an iPhone reminder isn't effective at all. I tend to kill the reminder and then forget about it again seconds later. Or I tend to factory reset my phone quite often so the reminder goes with that. I really need either an email reminder on the day I need to be reminded and a way to remind other people close to me of the same thing. I can't rely on myself to remember. I really need teamwork vibes.

The Solution A simple and easy to use reminder management system that allows you to automate reminder emails to yourself and whoever else you want to be reminded. You simply create a new reminder, write what you want to be reminded about, set a date when you would like to be reminded and it will automatically send on that day. So now, if I set a reminder and include my brother's email addresses we will not forget Mothers Day next year. Simple example, but this is intended to be used with even more important things that you don't think about everyday, like being reminded before your passport expires, car license, bills that needs to be paid in time, etc.

The Future Telegram, WhatsApp and SMS reminders are coming soon.

Cheers and I'm happy to answer any questions!</comment>


Cracking LUKS/dm-crypt passphrases - <AUTHOR> https://diverto.github.io/2019/11/18/Cracking-LUKS-passphrases <comment><USER2> Maybe it goes without saying, but for this to work, your password must be bad to begin with. Or at least, the article does not point to any significant design weaknesses in LUKS; it instead documents a variety of ways to get passphrase-encrypted secrets into existing tools for bruteforcing passwords. The article suggests it is about backup or data recovery, but I think it is probably more interesting to people in the business of digital forensics.

<comment><USER3> I agree with you, but I actually used the brute force for data recovery.

I had a NAS with a 22 characters passphrase that I had up and running for years and eventually forgot the password to. When I set it up I practiced the password enough times that I was sure I would never forget it so I never stored it anywhere. After years of never rebooting the NAS parts of the passphrase eventually got blurry and when I was about to move I realized I couldn't remember it anymore. I didn't really have anything of high value stored on it, but it kind of became a pet project to try to "crack" into it again. Together with Hashcat and the extracted header I eventually managed to brute force it after a couple of weeks :)

<comment><USER4> one way to solve the problem of memorizing (long passwords) is to use something like this:

to avoid forgetting it use a string of words that make sense to your brain[1] but are unlikely to be encountered in the wild (in any texts).

Example passphrase: _" My hamster kicks soapy homework with smurf locks like a tandem at 45 o clock!"_

Then use this to generate a hash which can never be remembered in itself, and is unlikely to be brute-forced:

      $  echo -n "My hamster kicks soapy homework with smurf locks like a tandem at 45 o clock!" | sha512sum
      7364796a1ad957d7c524165aa2fec2501eaa59e6bd8380bad3252504cdb8592018e30ae2fff1b2c2295e6da7a7f47f52ef1c0e3010c054598d76fe0c6d64bac6  -

this way there is no need to remember the hash itself as long as you know how to recreate the hash (+ have the tooling present like sha512sum).

In case you want to change the hash without having to remember a new passphrase just twiddle with the input string (by changing one character only) to get a totally new hash.

If you're on a multi-tenant machine this is probably dangerous since running _`ps`_ might show other users on the system the input string when you run the command. Not an issue with single user systems. In case you want to avoid the command being recorded in your shell history file you can prefix the whole command with a blank (space).

Benefit of this is you get a pretty long hash that is impossible to brute- force and extremely hard to remember, which makes it really useful as a master-password.

<comment><USER5> You are susceptible to a length extension attack if you use sha-512 this way. You should hash twice or use sha-3

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

<comment><USER6> I think you misunderstood what they are using the hash for - neither the hash nor the plaintext should ever be revealed to a third party anyway.

That said, I don't really see the point since it's no more secure than just using the long passphrase directly.

<comment><USER4> _> don't really see the point since it's no more secure than just using the long passphrase directly. _

a 5 word passphrase isn't automatically more secure than a 5 char password if the words are predictable. interesing paper goes into this[1]. brains are generally bad in coming up with good passphrases (not enough entropy :)).

while my example is certainly very hard to predict I want to rule out an attacker predicting what makes the (nonsensical) passphrase.

[https://eprint.iacr.org/2016/246.pdf](https://eprint.iacr.org/2016/246.pdf)

Edit: there is also a video to the above paper: [https://www.youtube.com/watch?v=6-vrumB0UUw](https://www.youtube.com/watch?v=6-vrumB0UUw)

<comment><USER6> Right, but usually designs for password systems assume that the whole system is transparent to the attacker, in which case hashing it before use doesn't buy you anything. If your input phrase is low entropy then a hacker can compute sha512sum(low entropy phrase) just as easily as you can.

So to get anything out of doing this is basically just assuming that your attacker won't know (or guess) that you're doing this. Maybe it doesn't hurt, but I wouldn't trust it with a low entropy passphrase. I suppose one use for it would be getting more entropy on sites with low password length requirements, like 10-15 characters max.

Another possible problem is if your computer gets stolen and the `echo xxx | sha512sum` command is in your .bash_history file. To me this seems to add a lot of additional risk.

</comment></comment></comment></comment></comment></comment></comment><comment><USER7> I admit I didn't read the entire article, I've been reading only the text around instances of argon and PBKDF, but:

can someone ELI5 how they do 882 hashes per second if PBKDF2 is set up to take 2 seconds, for example? What's so broken about PBKDF2 that they get a > 1000x speedup?

<comment><USER8> It's trivially parrallelizable so I suspect that they're doing it on a gpu or something like that.

<comment><USER9> Which is a known "vulnerability" of PBKDF2. In any modern setup you are better served by Argon2 (or if that's not available at least scrypt). CPU time is cheap to parallelize, memory bandwidth is much harder to scale.

<comment><USER7> There must, in addition to memory, be other things that are hard to parallelize on GPU's, right? How would 64-bit integer division do on a GPU? The GPU does not have 1000x more transistors than a CPU, it can't be 1000x faster for everything, right?

The annoying thing is LUKS1 only supports PBKDF2, but LUKS2 comes with a JSON parser, and no full support everywhere yet

<comment><USER9> GPUs are essentially wide SIMD processors. If cores take different branches that can slow them down dramatically, in the worst case all cores have to execute all branches.

The other thing that slows them down is memory access. Caches are small because everything adds up quickly once you multiply it by a few thousand. They are optimized for access patterns typical in graphics, which is mostly sequential or every-x-bytes. The main memory might be GDDR5 or GDDR6, but even the 600GB/s memory bandwidth of the RTX 2080TI is quickly used up once you have 8000 threads requesting random bytes from memory.

Apart from branching and memory I don't think GPUs have many weaknesses. They can save a lot of transistors because they don't care about single-core performance. For example instead of doing sophisticated instruction reordering to hide memory latency they just switch to a different set of threads whenever they would otherwise wait for memory. There are some tasks that Intel CPUs have transistors dedicated to like AES or 64bit integers and they do loose some speed on those, but at the same time these things are easy to do in silicon so your CPU loses to ASICs. And even a GPU eventually has enough cores that the software implementation run 4000 times in parallel will beat the CPU by a wide margin again.

</comment></comment></comment></comment></comment><comment><USER10> Sure. That's why I wish I could do LUKS authentication via TPM, which can do hardware rate-limiting. Is this kind of setup possible these days?

<comment><USER11> You can use a yubikey to do it. It can work in challenge/response mode, so the yubikey is required to unlock the device. That's good for laptops.

You can also use a private gpg key and an gpg-encrypted keyfile. Yubikey can store gpg keys (with attestation if you want), and you can enable both yubikey access and gpg in initramfs. That's good for servers if you pair it with initramfs sshd.

TPM is kind of broken, as I understand it, so I didn't even bother looking into it. There's really no reason I can't carry my keys on my physical keychain, so I don't see a need for TPM. I can also put a USB stick on my keychain and use that to boot.

That way even if an attacker has physical access to the hardware, it would be require some really advanced firmware/microcode hackery to compromise the machine.

<comment><USER10> How is TPM broken? I'm curious.

<comment><USER11> Some TPM chips are vulnerable to key dumping: [https://www.schneier.com/blog/archives/2019/11/tpm- fail_atta...](https://www.schneier.com/blog/archives/2019/11/tpm- fail_attack.html)

TPM dies if your motherboard dies, so you'd need a backup key anyway.

There's also no way for you to independently audit the TPM device, so you don't know how secure it really is. Personally, I don't trust Intel to keep the TPM secure, as they've shown they can't (see the above link).

The keys are in the chip if you use them for FDE, so you're expanding your trust that someone with access to the TPM can never dump the keys. This could be a problem if your machine is stolen.

By going the yubikey route, you can move the trust to a device that's physically on your person. That way, if the machine is stolen, there's absolutely no way to recover the keys, and there never will be even if more intel vulnerabilities are found.

You could use a yubikey for the FDE keys, and only use TPM for trusting the boot device. But if you're already carrying a yubikey to decrypt your device, you might as well boot off USB too.

</comment></comment></comment></comment><comment><USER12> Good luck with people like me. As ypu know, luks per default allows over 8 megabytes of key, so, i just make a dev/urandom file that is up to the byte filling the top default keysize, which means a password of over 8 million characters, of which none or very few at best are found via the keyboard. I use at the minimum 8 million chars on all my luks devices. And I've set the key stretching to take above 15 mins to unlock, even with the right password, so good luck with John the ripper.

<comment><USER2> I have to assume this is a joke. If it isn't, well. There's not a lot of reason to use more than 32 bytes from /dev/urandom. The extra 7.97 MB of key aren't doing you any favors, nor is 15 minutes of unlock time helping — zero seconds would be fine for this use.

</comment></comment><comment><USER13> I peaked at some of the stats regarding his brute force attempt, but I couldn't figure out how much progress he was making and whether a bf was actually feasible with LUKS. Is it something to be concerned about at this stage?

<comment><USER2> LUKS1 (2004 design) uses PBKDF2 with 2 seconds worth of iterations. It's not especially susceptible to brute force. The only reasons to be concerned are (1) your password is very weak, or (2) you initialized the LUKS volume on an extremely low power or heavily oversubscribed CPU such that 2 seconds of PBKDF2 iterations is below the 2016 NIST recommendation for 10,000 iterations. (The LUKS implementation may/should have an iteration floor that would make this (2) concern invalid, but I'm unfamiliar with the codebase and unable to speak to that.)

LUKS2 uses argon2.

See, e.g., _Cryptographic Right Answers_ [1]:

> Password handling

> Percival, 2009: scrypt or PBKDF2.

> Ptacek, 2015: In order of preference, use scrypt, bcrypt, and then if > nothing else is available PBKDF2.

> Latacora, 2018: In order of preference, use scrypt, argon2, bcrypt, and then > if nothing else is available PBKDF2.

[1]: [https://latacora.micro.blog/2018/04/03/cryptographic- right-a...](https://latacora.micro.blog/2018/04/03/cryptographic-right- answers.html)</comment></comment>


Weaponized marijuana - <AUTHOR> http://www.reuters.com/article/2015/08/05/us-usa-new-york-marijuana-idUSKCN0Q92FD20150805

<comment><USER2> Has there been a recent uptick in hyperbolic reporting on drug use? Some of the stories I've seen recently seem like they are straight out of a propaganda playbook from decades ago.

</comment><comment><USER3> "Weaponized marijuana" is neither a weapon nor marijuana.

<comment><USER4> That was the most ridiculous propaganda I've heard in a while. It would be like calling alcohol "weaponized water".

</comment></comment><comment><USER5> Perhaps if they legalized the real stuff you wouldn't have fools messing with weird synthetic chemical alternatives...

<comment><USER2> In Boulder the police are playing up incidents involving LSD (w/ reporting based on anonymous, anecdotal accounts).

<comment><USER6> And to expound / clarify: 1) purported 'LSD', and 2) one incident where BPD shot and killed a CU student.

</comment></comment></comment><comment><USER7> "One man high on the drug used his hands to stop an electric saw being used by police to open a door ... leaving him covered in blood."

Um, wow. That's some drug.

<comment><USER8> I'm sure some of its exaggerated but I've heard some really messed up stuff about synthetic cannabinoids before. Since they can be many times more potent than thc they can be really easy to overdose on as well whereas marijuana overdose is virtually impossible. This is a pretty clear example of prohibition doing far more harm than good since there would be no interest in "spice" or whatever it goes by these days if the real thing was available.

I tried it once years ago after getting a free sample at a head shop and it gave me one of the worst headaches I've ever had. Never touched the stuff again.</comment></comment>


Jury Reaches Verdict in Apple vs. Samsung Trial - To Be Updated - <AUTHOR> http://www.macrumors.com/2012/08/24/jury-reaches-verdict-in-apple-vs-samsung-trial/

<comment><USER2> So far the Apple and Samsung updates are just making me angry. I can't believe that you can patent pinch and zoom and double tap to zoom.

All this story is telling me is just how much the system needs to be reformed.

<comment><USER3> I like juries.

Set aside the details of which particular patent has been claimed -- is this not a _just_ decision? Is it not _completely_ clear that Samsung copied Apple's designs to an extent bordering on fraud?

If Samsung were making knockoff purses as similar to Louis Vuitton purses as many of its phones and tablets (and stores) were to Apple's, its products would be seized and destroyed. But Samsung isn't a hole-in-the-wall designer fashion accessory vendor but a multibillion dollar operation.

<comment><USER4> A. Pinch and zoom on surfaces was invented by Microsoft Research years ago. Almost all of the "technology innovation" claimed by Apple since the Mac has been stolen/borrowed from other companies.

B. Samsung devices were rounded-rectangle designs WELL before the iPod existed, and the concept of rounded-rectangle iPad-like devices that played video existed back in Stanley Kubrick's 2001. Ei ther should invalidate a "design patent" on such a look -- "black rounded rectangle" is absolutely insane to claim Apple owns!

<comment><USER3> A. No they didn't. (Samsung didn't even claim this -- they claimed that a multitouch window resize, which is neither as useful nor as intuitive as "pinch to zoom" nor actually zooms anything was "pinch to zoom" ... go watch the video.)

B. If it were simply about "rounded rectangles" you'd be right. But it isn't and you're wrong.

The letters L and V are not protected, but overlay them and print them on a handbag and you are in deep shit. (And yes, trademarks and design patents are different things but work in much the same way and have been used against each other in lawsuits.)

<comment><USER4> >No they didn't.

OK, pinch to zoom was invented even before Microsoft used it. See: <https://en.wikipedia.org/wiki/Microsoft_PixelSense> and <https://en.wikipedia.org/wiki/Multi-touch>

A big part was the rounded rectangles. Apple claimed it and the jury supported that claim. That's reprehensible garbage, and no legal system should support it.

You're revealing yourself as an Apple fanboy; claiming that a rounded rectangle with black borders (that looks identical to previous years-old Samsung products!) is now OWNED by Apple is not sane and rational.

The LV logo is distinctive. The shape of the iPad is at least as similar to products before it as the Samsung products that came later. You can't (or SHOULDN'T be able to) take ownership of a public domain design just because you've created a popular product that uses it!

</comment></comment></comment></comment></comment><comment><USER5> I've been following the live blogging from the San Jose Mercury News kindly posted by another HN participant:

<http://news.ycombinator.com/item?id=4429940>

Direct link to the live blogging is

[http://www.siliconvalley.com/ci_21356424/live-blog- verdict-a...](http://www.siliconvalley.com/ci_21356424/live-blog-verdict- apple-samsung-patent-trial)

"Jury finds on bounce back patent that Samsung infringed Apple on all the devices in play, smartphones and tabs"

"On the "pinch and zoom" patent, jury also finds Samsung infringed Apple patents on the menu of smartphones and tablets..with just a few exceptions."

"On tap and zoom, jury finds infringement for tap and zoom feature on most of the smartphones and tablets, although no on a few, such as Nexus S 4G...split this one up by various devices, but largely in favor of Apple"

"Jury also finds for Apple on charge Samsung "knew or should have known" it was inducing its telecommunications and electronics divisions to infringe"

"Apple blitzing Samsung so far, jury now finds infringed design of iPhone contours, etc."

"Some products of Samsung being spared the gallows, but not many so far"

"Jury finds Samsung infringed Apple graphical interface on iPhone....so much for those differences Samsung argued for"

</comment><comment><USER6> A sad day for consumers everywhere, regardless of what technology they prefer. The continuing validity of patents such as "pinch to zoom on a phone" is disastrous for the industry and will just serve to make everyone's products worse.

</comment><comment><USER7> Live coverage on The Verge: <http://live.theverge.com/apple-samsung-verdict- live/>

</comment><comment><USER8> Ideal verdict: "The Judge presides that both parties should just FUCK OFF and make decent phones."

<comment><USER9> Unfortunately Posner couldn't get himself assigned to this case.

</comment></comment><comment><USER10> Oh god, the comments are sad. Not HN's comments, the link's comments.

[http://forums.macrumors.com/showthread.php?p=15520468#post15...](http://forums.macrumors.com/showthread.php?p=15520468#post15520468)

<comment><USER11> Mac forum comments often approach YouTube comments in terms of awfulness. Its a really strange phenomenon.

</comment></comment><comment><USER12> So, who's next? Gestures seems pretty common on most mobile devices, and I'm guessing this opens the door for Apple to be able to sue them all, right?

<comment><USER13> They don't need to. This sent a big warning to all the Android OEMs not to copy the iPhone.

And that is what Apple wanted. Not money.

<comment><USER6> I think we can all agree that Apple's intention was to stifle competition, not to get money. The problem is that Android already have to go out of their way to "innovate around" obvious design decisions. This makes things even harder. There is a good chance things will go the other way too, and it will make it harder for Apple to keep up with Android as they introduce new features.

I can't see this being good for anyone except Apple shareholders, and in the long run I'm not sure it will even be good for them.

<comment><USER13> No. Apple's intention was to put as much of a gap between what the iPhone looks and feels like and what Android looks and feels like.

Whether that stifles competition is a separate issue.

<comment><USER14> You know Apple's intentions pretty well! Are you a C-level executive there? Or are you just speculating the exact same as he is?

</comment></comment></comment></comment></comment><comment><USER15> Considering that Apple is a beloved American company and Samsung a relatively obscure Korean company, isn't anyone else skeptical that a jury strictly composed of US citizens can be truly impartial in this case?

</comment><comment><USER3> If Apple is smart they'll donate their winnings (or pledge to donate them) to a universally laudable cause, like MSF. They don't need the money, this was never about the money, and this will underline the point.

<comment><USER16> I'm not sure I agree. Apple was pushed into acting as an outsourced R&D and marketing consultancy for their business partner, Samsung. They're entitled to a fee for their services, especially given the success Samsung has enjoyed as a result.

</comment></comment><comment><USER17> thank goodness patent exhaustion was upheld.

<comment><USER13> Absolutely. This is wonderful news for those that care about standards.

</comment></comment><comment><USER18> Looks like Apple have crushed Samsung.

<comment><USER19> Should be a nice boost for Apple's stock price Monday.

<comment><USER20> Really?

I don't think any one seriously expects Samsung to not be able to sell phones because of this so there won't be a bump due to analysts expect apple to steal Samsung customers.

And AAPL US Equity has about 1 Billion shares outstanding so the reward, if it gets paid and it probably won't, will come out to a one time boost of $1 per share.

So if a $1 rise int he stock price is considered a nice boost then I guess AAPL's stock should have a nice boost on Monday.

<comment><USER19> AAPL is up $12 this morning.

</comment></comment></comment></comment><comment><USER21> I think this is one of the most disappointing verdicts since the OJ trial.

</comment><comment><USER22> I get the feeling whoever comes up with the best graphic / table of the verdict will get a lot of play. The live streams are really hard to follow on what is what.

</comment><comment><USER23> 1 billion, 51 million 855 thousand dollars... Wow

<comment><USER24> Meh. So they have one lean quarter.

RIM had to pay $650,000,000 to a patent troll with no products, for violating a patent that no one had seen before. By comparison, considering the massive size of the companies involved and the brazen copying and infringement, the Samsung verdict would seem light.

</comment></comment><comment> at-fates-hands I'm actually surprised of such a lopsided victory. I've been following this pretty close and felt like Apple has really overstepped their bounds.

Of course it won't matter. Samsung will keep this going for a while on appeal until they win and then Apple will appeal. I don't see a clear victory for either company for a long, long, time.

<comment><USER25> As usual the only ones that will really win from this insanity in the long term are the lawyers.

And even the lawyers will not win as much as they think, because they will have set back technological progress decades behind.

</comment></comment><comment><USER26> Looks like Apple won this one

<comment><USER27> The appeal is guaranteed to be requested from Samsung, and will likely be granted due to the behavior of the judge.

This one is going to go well into extra innings. The question is whether there will be a timely injunction of Apple's likely attempt to cut off Samsing's sales of infringing products in the US.

<comment><USER28> Judge Koh could learn from Posner. Tell them both to "figure it out" and cross license. If that doesn't work, "Get out of my courtroom" would. If I was Samsung CEO. I would cease shipping components to Apple tomorrow, then file a anti-competitive practices lawsuit against Apple.

</comment></comment></comment><comment><USER29> Wow, crazy result. I feel [to be updated with an edit later]!</comment>


Google Doesn't Believe Wi-Fi Data Collection Didn't Break U.S. Law - <AUTHOR> http://online.wsj.com/article/SB10001424052748703509404575301012138471350.html?mod=rss_Technology

<comment><USER2> Your double-negative headline asserts the opposite of what the article says.</comment>


Goodbye Wholesale Brands - <AUTHOR> http://jamiequint.com/goodbye-wholesale-brands <comment><USER2> One hidden assumption is the high growth of internet retail implies a high growth of fashion clothing growth. Not sure why that applies. Sounds good, just not backed up by numbers.

Its hard to think of a commodity with more of a conspicuous consumption purpose than expensive fashion clothes, other than perhaps cars. The act of shopping for them, being seen shopping for them, the whole trying them on and looking a mirror, seems to reach or exceed the enjoyment of eventually wearing them in public.

I would imagine sizing is a complicated issue impacting possible 10% annual growth rates and all that. Tee shirt sizes are simple so online tee shirt sellers do well. I have bought my last four pairs of shoes on line because they're identical mfgr, model, size, width. I'm thinking high fashion clothing sizing might be somewhat more complicated. "do these stripes make my butt look fat" is hard to answer if you don't try the clothing on. As if thats ever an easy question to answer.

Finally you can increase annual sales of $300 fashion brand jeans by 10% per year for quite a few years, but eventually you bounce off declining median adjusted incomes, permanent decrease in economic activity, long term demographic decline stuff like that. It is very much like growing the 50+ foot sailing yacht market by 10% per year, you can do that for awhile, but eventually you run out of people capable of paying $300 for a pair of jeans, err, buying 50+ foot sailing yachts... The fashion market may not be big enough to make the subset of internet sales large enough to be viable. Perhaps walmart has more to fear from amazon than the major fashion brands... there's a lot more people buying $25 walmart jeans wanting to save $5 at amazon than people buying $300 jeans hoping to save $200.

(edited to add that if you agree with the assumptions of the article, its a well written and well analyzed article with no obvious mistakes. I just happen to disagree with several core assumptions which has quite an effect on my opinion of the conclusion.)

<comment><AUTHOR> Apparel has actually been the driving force in e-commerce over the last few years: [http://www.emarketer.com/newsroom/index.php/apparel- drives-r...](http://www.emarketer.com/newsroom/index.php/apparel-drives- retail-ecommerce-sales-growth/)

<comment><USER2> That's a good, general, factual article you've linked to.

Superficially I saw mostly general sector wide results in the article. However I have bought a lot more tee shirts and cafepress-type products and cheap identical non-designer shoes than $200 scottevest products.

My impression of the article is it was focusing solely on high end whereas I'm arguing the bigger action is probably at the low end.

<comment><AUTHOR> You are correct, I was mostly talking about wholesale designer brands which are mid-to-high end (priced at the cost of someone like J. Crew or Gap or above).

It's actually interesting though, at the mid-to-low end similar disruption is happening in a different way. There are 'designer' brands that exist at these price points, but they are being disrupted by the department stores that previously purchased them shifting to private label production (brands the stores produce themselves and label with their own brand), and shifting fast. In 1970, 25% of department store retail was private-label brands, in 2005, 50%, in 2010, 60%. [1]

[1]: The New Rules of Retail - [http://www.amazon.com/gp/product/B004AP9TQM](http://www.amazon.com/gp/product/B004AP9TQM)

</comment></comment></comment></comment><comment><USER3> I run e-commerce for a fairly large apparel manufacturer and wholesaler on the low end and have worked for other manufacturers. All manufacturers are looking to cut out the middleman, or at least replace it with a cheaper middleman like Amazon.

<comment><USER4> Don't you think higher end brands have an aversion to selling on Amazon? Having tried to sell a brand product on Amazon I have found that the Amazon customer is very price sensitive.

</comment></comment><comment><USER5> (Forgive me for the length of this post, I didn't have time to make it shorter.)

TL;DR: The author's thesis is that wholesale apparel designer brands can recoup margins by selling direct online. The way this will be accomplished is by the brand itself holding inventory.

Here's 100 years of experience condensed into four words, so if you're considering disruptive ideas in the apparel industry (like this one) please consider that:

INVENTORY IS THE ENEMY.

I am part owner of a 100-year old vertical apparel outfit in midtown Manhattan, and was there on hand every day for 12 years. We make custom men's suits and sell direct to the consumer, but that's only been the main revenue stream for a little more than a decade.

My great-grandfather started the business as a wholesale manufacturer in Brooklyn circa 1913, and my grandfather grew it into a national wholesale men's clothing line, supplying many of the nation's stores with their private- branded tailored clothing lines.

My father took the big move of selling direct to the customer in the late 70s, from the factory and warehouse on 5th ave in Manhattan. By the early 80s, especially as the result of clever marketing and other market factors, the retail business exploded. The consumers LOVED that the clothing was made in NYC, that they could see it being made, and that it was less expensive because middleman margins had been cut out.

So, my father bought a huge former department store on Broadway in the mid-80s, with a three-floor factory above, and was pumping out suits in record quantities (for our business). Also, our suits were wholesaled to Japan, Germany, etc, under our name.

Then the market shifted. Suddenly my father was stuck holding quantities he couldn't move. (The same thing had happened to my grandfather numerous times.) Overseas manufacturing hit full swing, and even with the cut margins, it was getting impossible to compete. We nearly went bankrupt by the time the "casual trend" hit during the tech boom of the late nineties.

In 1999, I came in to help shift the factory back to purely custom-made tailored clothing. NO INVENTORY. MADE TO ORDER ONLY. It was a huge retooling process, and since I was in my early 20s and there are no baby boomers who learned custom tailoring, I had to fill in the generation gap by learning the craft completely, and computerizing the whole pattern-making process. (Doing this custom is a near-impossible task that few do, and I eventually wrote my own software for it.)

We _had_ to stop _stocking inventory_ or we never would have made it to 100 (this year) if we had hung on to the idea that a small brand can hold its own inventory.

Here's an old Jewish garmento joke from the 70s, it's caustic but we say it often: "Inventory killed more Jews than Hitler."

There are very few brands out there that can handle vertical operations like this, and fewer people to manage it. Trust me, we've been hiring candidates for ages.

Brands will incur all that additional personnel overhead and the _incredible risk of stocking inventory_ , and need the huge marketing budget to sell purely online with no retail locations to build awareness (or at least be reliant on their existing, pissed off accounts for that). The author recognizes this, but glosses over it, and that's why I told this long story.

The real disruption of the apparel industry is technologically enabled mass customization. This has been talked about for ages but the operational skill to pull it off at scale is not there. I was granted a patent on using bodyscanners to make custom clothing years ago, in anticipation of this disruption, and I'm still waiting for it to happen, but it seems faaaar off.

The author says that a brand holding its own inventory is the "new" industry model. It is actually one of the oldest and most dysfunctional, and fraught with risk.

<comment><AUTHOR> Hey! Thanks for the long and detailed reply. (On a side note I enjoyed the Pascal reference: [http://en.wikipedia.org/wiki/Lettres_provinciales#Other](http://en.wikipedia.org/wiki/Lettres_provinciales#Other) :) I definitely agree with your main point, inventory is the enemy. I'm not trying to claim that this is an entirely new idea, however, it is a fact that brands are moving online and doing so quickly in a way that has not happened en masse before. I cover in the article that many brands will probably mis- manage this transition and go out of business.

My own TL;DR of the article would be something more like this:

Brands are moving online rapidly, this will mean they have to hold inventory. This is a new risk they have not taken before and some may fail because of it. They will take this risk because there is margin benefit as well as threats from direct-to-consumer online retailers taking their business. Going forward, direct-to-consumer with higher value to the consumer will be the 'new normal'.

<comment><USER5> I understand what you mean. And your bottom line that online retailing is growing and will cause a shift in the apparel industry, as it has in most others, is certainly valid. I'm just not sure the shift you're describing is likely.

I think this strategy is untenable for almost all of the designer brands in the market you're addressing, because the assumption of all the risk is not a good business model in any industry.

Let's look at VC for a moment. Having been involved in it, there is an obsession with risk analysis and reduction, and with good reason. A model that says "Let's take 100% of the risk and capture the margins!" probably can't support a whole market shift, and would probably be difficult to fund. And funding of some kind would be necessary for most brands to be able to stock goods.

You're very knowledgeable about the back-end of the apparel business, it was cool to see a story like this on the front page of HN.

<comment><USER4> First off congratulations on having a business that has lasted 100 years! That is a rare accomplishment these days.

I think you both have an interesting perspective on the future of apparel and e-commerce. The one thing that I think deserves mentioning is that it has been getting easier and cheaper to own the means of production so you can convert raw materials into finished goods with out holding lots of inventory. You also need the manufacturing capabilities if you want to do mass customization.

My limited experience with this has come over the past 3.5 years building DODOcase.com. We ended up building all of our own manufacturing and hold less than 2 weeks of inventory, while over 30% of our online sales are one off custom built products.

My hope is that the future is brands built online that actually make their own stuff. I agree with Jamie that the brands of tomorrow will have to be more hands on but just holding inventory and shipping D2C is not enough, I think they will have to own and master the manufacture of their own products.

<comment><USER4> Also as a side note I just started reading (yesterday) "LL Bean: The Making of an American Icon" by Leon Gorman grandson of LL Bean and former president of the company. It is a fascinating read on the ups and downs of a 100 year 4th generation family run business. It sounds like something you might find relevant to your business.

<comment><USER5> I will check this out, thanks.

</comment></comment></comment></comment></comment></comment><comment><USER6> This is pretty spot on.[1] A company like YOOX is doing "E-commerce as a service" for fashion brands stuck in this position: [http://www.yooxgroup.com/en/company_profile/the_group.asp](http://www.yooxgroup.com/en/company_profile/the_group.asp) (warning - autoplaying video!)

[1]Source - I work directly with a wholesaler who matches almost every description in the article.

</comment><comment><USER7> How about have a crowdfunding system to bridge designers and consumers directly? Well, I'd say it could be like Kickstarter in fashion. Granted, there will be many aspects to make adaptions, but the core is almost the same.

<comment><USER8> Brands like Stock Mfg. Co. are already doing this: [https://www.stockmfg.co](https://www.stockmfg.co)

</comment></comment><comment><USER9> This is a really important insight. The chunk of GDP that is dedicated to ferrying money from consumers to producers in the 'fashion' space is going to be hugely disrupted. The level will be no less disruptive than music or literature.

We can predict then that aggregators and re-sellers of fashionable clothes will go out of business, and discovery marketplaces like Kickstarter, Ebay, Etc, will create the channels between consumers and their products.

I would guess that small run clothing factories will be a growth industry, more so if they are highly automated.

</comment><comment><USER10> Given all the presumptions you've made in your article, it seems like many of these brands would be well-served to let Amazon handle the fulfillment. The brand would still control pricing, marketing, and manufacturing, but warehousing/shipping/returns could be handled by Amazon. This removes risk to both the brand and consumer, as well as spreads the high fixed costs of warehousing over a large pool of businesses.

<comment><USER11> > as well as spreads the high fixed costs of warehousing over a large pool of > businesses.

(Note, I'm speaking from some experience here, but it's total amateur-hour experience. I wrote a system for tracking and selling books via half.com and later amazon.com, back when half.com was a thing. At one point I had well over ten thousand books in my inventory to 'test' the program. hah. It actually wasn't so bad; there just isn't any money in it. I might go back to it if I retire; it was fun to have all those books around. I've also worked around several junk dealers, who used the 'have employees who know where shit is' method, and my SO has written an inventory system for our personal stuff, which works, except that barcoding and describing all our stuff is a... daunting amount of work.)

eh, shipping in a timely manner, yeah, if you don't have enough work for a full-time person, you probably wanna outsource. It's a pain in the ass to make a trip to the post office for what amounts to five bucks in profit.

But the cost of warehousing? I think is actually pretty low. Even here in silicon valley you can still get santa clara warehouse space for around a buck a squarefoot/month, in thousand-dollar increments.

Even here, you can get folks capable of operating a simple label printer and mailing stuff out for something like $12-$15/hr, if you have more than 20 hours a week. Especially if you only have a few SKUs, I think it's pretty simple.

now, if you have a thousand SKUs, either you need people who know your inventory really well, and you will be in serious pain when anyone quits... /or/ you need a very good computer system for handling what is where... and setting that up and maintaining all your SKUs is skilled labor. On top of that, the computer system is only as good as the employees scanning the items and locations (or putting the items in the right location; but I personally think the approach of barcoded bins and barcoded items is right; the user barcodes the item, then barcodes the bin, then puts the item in the bin. )

But /that/ is a whole lot more work than it looks like. So yeah; For a few SKUs? a couple grand a month, even in a very high cost of living area and without using your garage, and you can move a lot of product. For many SKUs? yeah. that's where your trouble starts.

I really think that once you have enough work to keep a kid busy mostly-full time, your costs are probably going to be lower doing it yourself.

On the other hand, you do have a good point about the consumer trust of amazon; For me, buying something through amazon (something sold by amazon, not something sold /through/ amazon; that's completely different.) is very easy; very little friction, and I know it will get here the next day. I'll pay a few bucks extra to get a thing from amazon vs. somewhere I've never bought from. (My /feeling/ \- and I don't have anything to back this up, is that amazon is picking up on this, and their prices are slowly floating up vs. everyone else.)

</comment></comment><comment><USER12> You have to assume people care about fashion. I don't but I guess since my wife works at Tommy Bahama and I get cheap nice stuff I shouldn't make any statements. But generally I dressed like slob before then. Its just now I dress like a slob in fancy slob clothes. :)

</comment><comment><USER13> So 370$ is more than double than 231$? Thanks for the nice graph!</comment>


Ask HN: Do VCs or Angels invest in blogs? - <AUTHOR>

I've started a blog (http://thestartupcafe.com) and I really want to focus my time fully into building it up into a quality destination and community for entrepreneurs and startup enthusiasts. However, between my full-time gig and other projects, I'm finding it difficult to put 100% into it. As I'm sure this is a problem many people have, I've started to wonder if angels and VCs invest into blogs like they invest into apps and such. I'd like to raise some seed money to allow me to invest my time fully into this. What would you suggest I do? Is this possible or should I keep this as a side-project/hobby? <comment><USER3> Even if they did invest money, would you want to take it? The minimum it's probably worth raising is say, $50K, when you figure that the legal fees alone might run $3-5K. To make the investor a good return on that, you probably need to create a business worth $250K minimum (for a 5X return.) A single-writer blog just isn't going to be worth that much, especially when you consider that you have to subtract your own comp from the profits before calculating the value of the franchise.

If you're going to build a small lifestyle business that has relatively moderate growth trajectory, you need to do it without raising money that expects a big growth rate. If all you need is say 15-20K, just borrow it on a personal basis from a microlending club like LendingClub.

If you're not willing to take that kind of risk? Don't expect anyone else to, either.

<comment><AUTHOR> Solid, grounded advice. Thanks! You're right especially on you're last point, I gotta be willing to take the risk if I expect someone else to.

</comment></comment><comment><USER4> Yes.

The Huffington Post, Business Insider, GigaOM, The Bleacher Report and many more have.

You have almost 0 chance of raising money until you have a serious sized audience though, unless you have a rockstar background like being Editor in Chief at Engadget. There really is no excuse not to be able to organically grow a blog.

With blogging do you not find that you have to have the determination and dedication to wanting to get your words out there (and thus you find time to write one blog post a day) or maybe you shouldn't be doing a blog - <USER2> reach out to the startup foundry or the next web as a contributor?

<comment><AUTHOR> I've definitely got the drive and determination to push this blog to the forefront. I've been kicking my own butt to make sure that there's always a new post M-F. I've also been asking for advice/feedback and looking at analytics to see what's working and what's not.

As for Paul at The Foundry, we're chatting on the phone tomorrow. I hope he'd consider contributing :)

</comment></comment><comment><USER5> I believe OM Malik (gigaom.com) took funding, but I'm not able to find the source right now.

I'm not sure if any of the other major ones did too -- TechCrunch, Engadget, The Next Web, Venture Beat, etc.

</comment><comment><USER6> IMO an angel might, but not a VC. VCs look for 10x return on their investment of _at least_ 500k-1mm, and a blog needing that kind of investment or providing that kind of return is highly unlikely.

</comment><comment><AUTHOR> If there are any old HN thread on this, I'd love to read them too.</comment>


The way to Lisp - <AUTHOR> http://www.tuxdeluxe.org/node/153

<comment><USER2> One thing that confused me: Why can't the author bring himself to write the word "Python"? He spells it alternately "PYTH0N" and "Py_thon". Is this some sort of anti-SEO? Or a reaction to seeing "LISP" in print too many times? Or some sort of inside joke?

Edit: Hmm... The article appears to be somewhat dated, if not a little exaggerated... With no new posts in the last two months, it seems Lemonodor.com is no longer the "Slashdot of the Lisp world".</comment>


Ask HN: What are the resources you would suggest for Machine learning? - <AUTHOR> I would like to know resources which you have used (online, I get 100s of things and I feel paralysed by choices) and found useful?
I would like to know some beginners friendly things (beginner level in this field, not in the programming domain), which focuses on concepts and  their applications in a balanced way.
And also, do you recommend to use some special programming language for this? I use Java on daily basis and/but open to learn some new languages (pyhton may be?, though I was told, Java as almost equal ML related libraries, if not more).
Thanks in advance. <comment><USER2> Andrew Ng's Coursera course on Machine Learning:

[https://www.coursera.org/learn/machine- learning](https://www.coursera.org/learn/machine-learning)

There's also this course on Neural Networks by Geoffrey Hinton:

[https://www.coursera.org/course/neuralnets](https://www.coursera.org/course/neuralnets)

If you do the Andrew Ng course, you'll have to learn/know Octave (or Matlab). Otherwise, Python is very heavily used in ML these days and you could do a lot worse than learning Python. R and Octave are both very useful as well. And, as you note, there is a lot of machine learning software available in the JVM world as well. Scala in particular seems to be gaining some ground in this world.

</comment><comment><USER3> Pedro Domingos ML course on Coursera is also very good. Regarding neural nets, there's no better intro than online book by Michael Nielsen: [http://neuralnetworksanddeeplearning.com/](http://neuralnetworksanddeeplearning.com/)

The best way to learn is to avoid any libraries, and try to code the fundamental algorithms (SVM, KNN, MLP, etc) from scratch. The language is not important, so I'd stick with Java if that's what you know best.</comment>


Ask HN: Javascript parser in Java/Scala? - <AUTHOR>

Does anyone know if there is a good Javascript parser in Java or Scala? <comment><USER2> You might be able to copy the parser out of the Google Closure Compiler. <http://code.google.com/closure/compiler/> you can be sure it works, and is stable. I think though it uses Rhino under the hood, so you could look at that too. <http://www.mozilla.org/rhino/>

<comment><AUTHOR> Thanks! That looks promising.

<comment><USER3> Rhino is _really_ fast. Years ago I wrote a javascript scripting interface to one of my applications and I was surprised that for our use cases it was running ~ 95% of the speed of raw java!</comment></comment></comment>


Why Why Functional Programming Matters Matters - <AUTHOR> http://weblog.raganwald.com/2007/03/why-why-functional-programming-matters.html <comment><USER2> _Thus, it is possible to make a language "better" by removing features that are considered harmful, if by doing so it makes programs in the language better programs._

Pareto and Cost/Benefit! A Type System is just a set of features in the compiler and other programming tools. Does our field have good data on the cost-benefit of features in type systems? Granted, this is quite complicated. Additional type data can enable features, like more kinds of and more reliable automated refactorings, but it can also incur costs, like slowing down the writing of new code and the programming tools.

Due to the Pareto principle, I suspect that most of the benefit of both dynamic language environments and type systems come from a minority of the features in each. I also suspect that many of the costs vary with context and time-frame. "Programming in the Large" problems may never, ever apply to certain projects. Long term maintenance issues may not apply to other projects.

"Experiments" in programming language design generally seem to be at a ridiculously large granularity with ridiculously poor experimental design. (Let's write a new language!) Is it any wonder then, that our "field" is really "half a field?"

</comment><comment><USER3> So every "language" basically becomes a "hub" language, with lots of sub- componenent syntaxes, dedicated to a specific task. Functional programming would be the future of all "Hub" programming, if it were not for the performance costs. The "language" a project is written in, boils down to the percentages one or several of the tools of the swiss-army-knife Hub language are used- or even subverting (as in replacing) another language. You could create a sort of functional-programming-tool in assembler - if your project is performance thirsty. So i guess the next step is to allow architects to limit certain language features to prevent architectural decay. Templated Packages that adapt the language percentage of reused Components to the projects needs?

</comment><comment><USER4> I think this is a good blog post, but we might want to modify the subject line to let people know that this is from 2007.</comment>


Ask HN: I'm 18 in Sydney. Part time work at unicorn, or go to uni/college? - <AUTHOR> I'm an 18 year old self taught developer in Sydney. After graduating from high school, I applied and got a contractor job at a local office of a super-unicorn. I love the company and culture, have got nothing but stellar feedback, however the local engineering work is drying up to a part-time workload. There's just a limit to what's left to do in a local operations/support office.
The options I'm considering are the following:
- Do part time for this unicorn.
- Find a full time job in Sydney.
- Go to uni (college) for something else I'm interested in.
I love the unicorn, but I'd like something more stable and a bit of higher-impact work. I've discussed this slightly internally but haven't pushed as things are still in a bit of flux.
Unfortunately, the tech scene in Sydney is quite limited and due to lacking a degree, I'm ineligible for US E2 visas. At this stage I'd prefer to join a larger company and learn from bright people; instead of working at a bland consulting company for example.
I'm interested in more things than software engineering and is open to studying other fields, although my current experience & FOSS contributions are all coding-related.
Where do I see myself in 5-10 years? Who knows? Maybe making a startup, because when I made one I loved every moment of it.
What do you think I should do? <comment> brian-armstrong Going to uni is a good chance to interact with some very smart people in an environment where people are largely motivated to learn. It will give you a chance to learn quite a lot of fundamentals at a quick pace, and if you spend your time well, you'll get quite a lot out of it. It won't turn you into a good dev, but it will give you lots of pieces that you'll start to connect later in your career.

You can also pick up lots of good stuff from working, but you need to be very careful about what habits and practices you keep. You're going to be in an environment where people are motivated to just get things done. Some people will focus on improving, others will not. You will have your own project deadlines to meet. You might get mentored by smart people, but it's not guaranteed, and politics can play a large role here. Nobody is obligated to make you great.

Working will inevitably be the thing that crystallizes your developer abilities, and I don't think anyone gets good without it, but going to a university helps you learn things that people will often just take for granted in the workplace (unless they don't know them- those unknown unknowns can be tricky)

<comment><AUTHOR> Thanks for your insight! I definitely agree the environment of uni can be great and don't doubt it will be valuable for me, but I do wonder if the opportunity cost of uni is worth it for me personally.

I suppose I like self-learning more and have been coding, either as a hobby, freelancing, or on my own startup, for 5 years. My experience at this unicorn and elsewhere has made me question just how much I'll get out of a Comp Sci degree. I'm someone who spent most of high school classes coding, and my spare time hacking with embedded devices or mitigating DDoS attacks.

Even disregarding that the value of bachelors of comp sci may be substantially less for me personally, I don't know if software engineering is something I want to build a career in anyway.

Doing Comp Sci commits me to this track to some extent. 4 years of full time work, very frugally saved and invested in an index fund, can become very considerable amount. I can afford to save the vast majority of income for the next few years -- so why not optimise for it?

P.S: Are you Brain Armstrong of Coinbase? Love what you're doing!

<comment><USER2> _the opportunity cost of uni is worth it for me personally._

That's a good question but it's hard to evaluate the opportunity costs of either.

 _My experience at this unicorn and elsewhere has made me question just how much I 'll get out of a Comp Sci degree._

CS programs typically and primarily teach things other than 'coding'.

 _Doing Comp Sci commits me to this track to some extent._

It doesn't. You can always drop out. This isn't to say that if you find the idea entirely unappealing, you ought to do it anyway because of some silly reason. But if you want to genuinely weigh the options, it's better to not misrepresent them to yourself. Let's say you've decided you'd rather keep on working. Terrific, keep doing it. Or maybe that degree in music theory sounds like it might be interesting. Go ahead and try it.

<comment><AUTHOR> > CS programs typically and primarily teach things other than 'coding'.

Yeah, but practically what I'm doing most of the time is architecturing, coding, or debugging, and know/'don't mind learning' a decent amount of 'everything else' to be productive.

I had no trouble learning A* or Minimax or Quicksort when I needed it, I learned _enough_ about neuron networks to build something 'good enough' in two days, I knew enough about networking to mitigate a layer 7 DDoS, etc.

I think I have enough surface breadth to know, most of the time, which tool or algorithm I'll need -- and can then learn that. I don't know too much about genetic algorithms for example, but I think I'll know when it's suitable for the job.

I do not doubt that CS will be valuable to me. I just question "how valuable", because 4 years is a long time.

> It doesn't. You can always drop out.

Good point. I thought that I'd be making a huge commitment, but I won't be in reality. Starting a degree will allow me to better evaluate its value to me too.

Thank you!

<comment><USER2> _I had no trouble learning Astar or Minimax or Quicksort when I needed it, I learned enough about neuron networks to build something 'good enough' in two days, I knew enough about networking to mitigate a layer 7 DDoS, etc._

Of course. But pop into a bookstore or library and leaf through SICP or TAoCP or the white book or Patterson and Hennessy, etc. There's a reason these and many other topics are subjects of years-long study. It might turn out to not be your thing but you seem somewhat dismissive of it all and it might be to your detriment, whether or not you give a whit about pursuing this academically (I'm not a CS grad myself, incidentally).

</comment></comment></comment></comment></comment><comment><USER3> Going to look for a job without a degree is like jumping out of a plane without a parachute - you could survive, but your chances are greatly improved by the parachute.

You're 18. Get the school done, work part time if you can. By 22 you will have a lot of doors open, whereas the 'unicorn' will just grind you up and replace you with another willing (undegreed) 18 year old in a few years.

<comment><USER2> >Going to look for a job without a degree is like jumping out of a plane without a parachute

That sounds completely untrue, especially for someone who's already _had_ a job without a degree. It shouldn't discourage anyone from pursuing academic work if they want to but the analogy is terrible.

<comment><USER3> Fine - a degree is like a condom: it is better to have it and not need it, than need it and not have it.

Trust me - you'll thank me at the first round of layoffs.

<comment><USER2> _Trust me - you 'll thank me at the first round of layoffs._

I'm afraid I don't. I've been through layoffs and I've had to do some layoffs. Degree has never been a significant factor in either.

<comment><USER3> Lets clarify: what field & sized companies?

Because you can't even get a foot in the door without a degree most places; now I'm curious.

<comment><AUTHOR> I suspect more conservative (e.g. financial, government) firms may only shortlist those with a degree (especially if hiring is done by non-engineers), but I don't think 'most places' is true. I applied to six places and received two offers, one from where I'm at now and the other from a startup.

My Googler friend told me that as long as I can get an interview, simply having a degree or not is 'irrelevant'.

Maybe it's not a question of degree, but if you've done anything that sets you above?

</comment></comment></comment></comment></comment></comment><comment><USER2> You're 18. You've got plenty of time to do whatever the crap you want and change your mind about it if you don't like it. Don't let silly terminology like 'unicorn' and absurd unanswerable questions like 'Where do you see yourself in 5 to 10 years' distract you from trying things

</comment><comment><USER4> Well, going to uni would minimally give you the paperwork to get in the door places. You can do it without the paper, but more and more places require it. Now, it might cost some money, and depending on the setup there, you might have to work nevertheless. Uni sometimes let you make contacts and learn things you didn't consider. This route might be your safest/easiest option, mostly because it gives you a definite edge on those other self-taughts (plus you might be able to test out of some classes based on experience/knowledge). This would defnitely be a bood way to expand your field of knowledge, since it is completely possible to learn something other than what you now know.

However, if you can make the other work, and simply get a job, that might be a better option, depending on the impact school would have on your life and finances. Might be harder to find a job and harder to expand your field.

My actual suggestion, if you think your life will allow, is to work part-time in the field while going to uni. You aren't sure where you want to be in 5-10 years, which is completely fine: This simply opens up as much as possible for you... in theory, anyway.

</comment><comment><USER5> I'm Australian and I would really recommend you go to uni and get the piece of paper. You are still young and as more and more time passes, it becomes harder to be able to go back and study full-time.

I've personally found that working in the US is such a fulfilling experience (particularly in SF/SV) and having a degree will make the visa process much easier.

You can still work part-time or freelance and uni will be a great way to meet like-minded people (AKA potential cofounders) if you're interested in founding something in the future.

<comment><AUTHOR> Thanks, super interested in an Aussie's (your) perspective!

Being about to get an E2 visa is definitely great.

Can I ask for your depth of knowledge before you went to uni? What degree did you do, and how deep was the scope? I'm just asking because I've been programming for 5 years, on various levels and I'm wondering about how much 'new stuff' I'll learn.

<comment><USER5> Do you mean the E3 visa?

As for me, I started building websites in year 11 for friends/family - I was self-taught HTML, CSS and Wordpress. I had no "real" programming experience, which is where we might differ from each other.

I did an accelerated diploma in Design and then went back and did my bachelors in Comp Sci at USyd. The programming components were definitely new to me (Java, C etc), but you may have experience with them already.

I think it's safe to assume that CS is really not about teaching you how to program - many people graduate and do not know how to code. What you do gain is a deep theoretical knowledge that is really important and useful (algorithms, data structures etc). There are many threads on HN where the differences between self-taught & CS students are compared, you should definitely check them out.

Ultimately, I think it really depends on what you want to be developing. If you want to work at FB/Apple/Google/MS or anywhere outside of Australia, get the degree. If you want to found your own startup, I could see an argument of why the degree might be less useful. That said, I think very few people would regret studying CS or software engineering, it's always going to pay off.

</comment></comment></comment><comment><USER6> Go to university & get a degree. A degree opens a lot of doors in the future, even if you think it shouldn't matter. That's both simple things like "Getting your CV past a clueless first-screen HR person", and complex things like "Applying for a visa to live/work abroad".

Also, if you're working as a developer already then the first year of university is likely to be straightforward for you. Depending on the hours, you could probably keep the part-time job and study (but out of the two, you should prioritise the study).

Finally, I'd recommend you use your free time in university well. Volunteer for charitable organisations; help out with your student union; take up a sport; keep learning things not on the curriculum. All of these are fulfilling in and of themselves, but will also benefit your future too.

</comment><comment><USER7> Go to the university, try to become top of your class and learn everything the University has to offer (parties and girls included).

You have time for the rest. Nothing stops you from working part time or as a contractor while studying.</comment>


Livestream of DeepMind vs. Lee Sedol Match - <AUTHOR> https://gaming.youtube.com/watch?v=vFr3K2DORc8 <comment><USER2> Holy cow, this is totally epic.

And, this the first time i've been truly excited by a sporting event. Wow, so that's what that feels like!</comment>


Posterous no longer includes site names in Facebook streams - <AUTHOR> http://www.adrianscott.org/posterouss-branding-grab-a-week-after-the-aff

<comment><USER2> Absolutely can't stand the inexcusably large mouseover area around the yellow "Posterous" links at the top of these blogs. That's the truly obnoxious thing here

<comment><USER3> Other themes have less obtrusive versions with transparent logos. Most people end up leaving the basic theme because that's what simplicity is about -- reducing the number of choices. People who care a lot can change it. Most people don't care.

<comment><USER4> I think it's more an issue of most people don't care enough to send you a message about it. It's still extremely annoying and frustrating, because often times it simply won't go away, and so I have to move my cursor back and forth a bunch of times until it decides to disappear.

<comment><USER3> You're right -- I misunderstood your initial comment. I'm going to think about this some more. Really appreciate the feedback.

<comment><USER2> I also find the wording a bit strong, too: "Shouldn't you?" My snarky response is "Only if I wanted all my content to have an obnoxious yellow thing at the top that cheapens my personal brand." Politely put, I find it offputting and presumptuous. "So can you" is a similar message that's much less aggressive.

</comment></comment></comment></comment></comment><comment><USER5> Wait. How was that a "scandal"?

</comment><comment><USER6> Honestly I wish the title of the blog post was a link. From feedback I have received, it is very difficult to know where to click to read the entire post.

<comment><USER3> We would love to be able to put the full blog post title in there. The Facebook Stream API limits what we can put in that space.

I think this is a good candidate for an advanced setting. For other autopost sites we allow customization here. We'll discuss with the team.

</comment></comment><comment><USER7> I'm a Posterous user and I really like the service but it has been interesting to watch the moves they have made lately since Tumblr has been getting a lot of positive press.

I wonder if these changes have been influenced by investor pressure to increase their brand awareness and to start to press the revenue button in order to compete with Tumblr.

<comment><USER3> This was literally a bug fix due to user complaint about blog name truncation. There is no conspiracy here.

<comment><USER8> It's not really a branding grab. The reason is pretty simple. We were contacted by Facebook because our stream stories were in violation of their terms of service, which forbid "Calls to action" in the body of the stream story. For instance, take a look at the old style stories we used to publish:

<http://skitch.com/vincentchu/dne9u/facebook-vincent-chu>

In this example, the "Read more on postmodern babbler" text was in violation and we were asked to remove it. So we did. But I still wanted people to have a "Read more" call to action somewhere, so I put it in the "Action links" area. Unfortunately that field is only 25 characters long. We've found that most people's blog titles will _not_ fit into 25 characters. In fact, we've seen blogs where truncating the action link after 25 characters leads to some unfortunate text. For instance:

"Read more on Vince's Analytics Site" would become "Read more on Vince's Anal"

So in the interest of not creating bad looking text, we changed the text

<comment><USER4> As icey said in a comment on the blog post, you could probably fix that with "Read more on Vince's A..."

<comment><USER9> That doesn't really solve the problem: "Bob's Assault on Stupidity" becomes "Read more on Bob's Ass..."

Arbitrary truncation of English text is guaranteed to result in amusing edge cases. Besides, how often does a blog title fit into 25 - len("Read more on ") - len("...") = 9 characters? I couldn't even find a posterous that wouldn't truncate under that rule. Truncation is ugly- it should be a worst-case exception, not something applied to every single post.

<comment><USER10> I think kyro's point is: if you're going to truncate a word, truncate following the initial letter, then you can't possibly form an undesired word.

</comment></comment></comment></comment></comment></comment><comment><AUTHOR> FYI, the title of this link was changed by HN. The new title does not reflect the point that not only were the site names removed, but that the Posterous brand was used in place of them -- even though the link can go to a domain name other than posterous, for blogs using domain name mapping.

</comment><comment><USER11> Such a great opportunity for a founder's blog to step up and say, hey we're a maturing business, here's this new setting, here's how to opt-out if you don't like it.

Gives them 95% of the value and 0% of the internets coming down on them.

<comment><USER12> If you add a setting every time someone throws a hissy fit, you're going to have a lot of settings.</comment></comment>