Industrial Mathematics - <AUTHOR> http://www.the-adam.com/adam/math-4q6/index.html <comment><USER2> It's nice to see OR get some love on HN. I think one of the biggest problems with OR practitioners is that we have a hard time articulating what we bring to the table. My job title is "suitability analyst," but that doesn't tell the whole picture. We have slogans like "The Science of Better," but most people still don't understand what we do. OR is overshadowed by larger but not necessarily better "brands" like systems engineering and MBAs spouting words like "lean." I can't tell people that I do OR because people ask "what's that?" and don't have time for me to give them a five minute explanation. I might just point them to this page and say if you really want to know then read this. Otherwise just go ahead and think of me as an industrial engineer/computer scientist/mathematician/statistician/economist all rolled into one.

<comment><USER3> As a graduating student in this field of "industrial_engineer/computer_scientist/mathematician/statistician/economist" I found this story and the rest of the site (not the front page picture) fairly inspiring. There are no role models even with the decent amount of blogging the OR/MS community does. They are still stuffy academicians, perhaps so because they could not find role models in industry either.

<comment><USER4> Theres a guy, Marc Kuo, in Vancouver, Canada who founded/co-founded an OR- based startup: <http://www.routific.com/>

<comment><USER3> Thanks for that link. It also did remind me of one Australian company [<http://www.biarri.com/about_the_team.shtml>] that I explore from time to time. They seem to offer the most types of OR decision support for business, even with SaaS delivery.

</comment></comment></comment></comment><comment><USER5> The terms the author is searching for are "applied mathematics" and "applied mathematician." The meaning is pretty straightforward (apply mathematical tools created by others). It also requires far fewer words.

</comment><comment><USER6> Its hard for everyone to accurately describe what they do in one word, but if someone launched into a story like this when I asked him what he did, I'd laugh inside. I say that with complete empathy, because I have done the same thing, had long internal debates with myself about which stereotypes I want strangers to associate with me.

But being accurate about your job description isn't really what someone wants to know when they ask that question, is it? They're really looking for information about you, not your job. Your job title comes with a guess at a range of how much money you make, and what kind of activities you spend your time doing. Nobody really cares if your math is industrial or not. If you do a lot of math while you work, its entirely reasonable to say you're a mathematician. And since nobody knows what an industrial mathematician is, all they're going to hear is 'mathematician' anyway. :)

It doesn't help to promote poor stereotypes either, but Adam does it anyway. Its understandable and we all do it, but it sure would be better to fight the negative images than reinforce them.

"Today, they [mathematicians] produce papers for publication"

Here Adam is talking about math professors. Academics. A mathematician, on the other hand, is anyone who does math. Adam is a mathematician.

"People who design new technologies are engineers."

Not bad, but I like wikipedia's definition beter: An engineer is a professional practitioner of engineering, concerned with applying scientific knowledge, mathematics and ingenuity to develop solutions for technical problems. Adam is an engineer.

Re: analysts, he begins: "Working with pencil and paper..."

This just in, _nobody_ except for sketch artists work with pencils anymore, and even most of them are on the computer. Analysts spend their time analyzing, and Adam spent multiple paragraphs describing his brand of analysis.

A programmer is a "person who carries out the specific instructions of an engineer".

Wow. How many of you does that apply to? Generally, the programmer is the engineer, no? I can't say I've ever met a programmer that definition would apply to, I can't think of one who ever took his technical direction from an "engineer".

"The programmer is carrying out the vision of another while my software is written to support my own vision."

That seems just a little exaggerated to me, since he works for a company just like the rest of us. And lest we forget the millions of programmers releasing their wares open source, or places like the Android or Apple app stores. Those are the people truly writing software to support their own vision.

"The computer scientist seeks a holy grail of computing."

I agree with this one, and I agree with Adam that he's not one. :) But, very few people who call themselves computer scientists are actually computer scientists. Most of them are programmers. Or engineers, if you like.

Consultants are "costly parasites in American business."

That might be true, but if you are a temporary or contract hire, or the result of your time is advice to a company, then you actually are a consultant.

Ultimately, using a categorical term is necessary when describing what you do to someone else. Its up to us to determine whether those terms are neutral categories or negative stereotypes.

<comment><USER7> Abut the programmer/engineer dichotomy:

He uses the word "programmer" only for people that write code, and the word "engineer" for people that design technical solutions. Somebody can be both, a "programmer" and an "engineer", but a "programmer" is not necessarily an "engineer" if the actual technical design, strategy, and main technical questions are answered by another person (the "engineer"). This division of labour is a common model in some Big Co's (with ~50 programmers or more), not in small-medium size compaines or in the startup world.

IMHO this model is not perfect, but there is a point when the time of a high level technical person should not be wasted in trivial implementation details (whatever you call him "programmer" or "engineer")

<comment><USER8> You may find this abstraction post interesting/entertaining....

[http://earlyretirementextreme.com/scientists-vs- engineers.ht...](http://earlyretirementextreme.com/scientists-vs- engineers.html)

<comment><USER7> Thanks for sharing!

Of course this is mainly semantics, but I don't agree with the way the post uses the terms "scientist" and "engineer".

In my opinion, the difference between "scientist" and "engineer" lies in the nature of the work they do, not in the level of abstraction:

"Scientists" advance scientific knowledge.

"Engineers" design technology applying this knowledge.

I find the analogy kind of muddy, I believe that a programming language is a product of "engineering", not "science". "Engineers" had been using abstractions (black boxes) designed by other "Engineers" for quite some time now.

<comment><USER8> > Of course this is mainly semantics

Correct. If you went through the comments in that post and the linked previous post, other people also went ballistic [precisely] because of the usage of the terms rather than the abstraction he was trying to make.

So, in the end it boils down to "point of view" of looking at things, leading to the fatalistic "to each their own" response. :-)

</comment></comment></comment></comment></comment><comment><USER9> Given that his degree is in Operations Research, I wonder why he doesn't say he does Operations Research, rather than Industrial Mathematics. I often say I do OR.

<comment><USER3> He answers this question fairly concisely in the first section "What I do", the link in the first section [<http://www.the- adam.com/adam/math-4q6/hypersq.htm>], and the second last section "What I am not".

I am finishing an MS in Industrial Engineering, a synonym of Operations Research. I have also been looking for related jobs that use those skills for two years. Many relevant jobs are in big data and analytics, subjects common to Hacker News; many belong to business operations such as demand planning and supply chain management. To find jobs I use Indeed.com and this is the search query I use. I based a term project in business intelligence on the problem of finding good search terms based on course descriptions.

[[http://www.indeed.com/jobs?q=title%3A(-vp+-director+-manager...](http://www.indeed.com/jobs?q=title%3A\(-vp+-director+-manager+-Sr.+-senior+-mgr\)+\(quantitative+or+health+or+analytics+or+inventory+or+industrial+or+planning+or+quality+or+demand+or+engineering+or+mathematics+or+math+or+stats+or+statistics+or+intelligence+or+production+or+process\)+-civil+-nurse+-energy+-oil+-mental+-secretary+-dietician+-chemical+-electrical+-seniors+-community+-teacher+-aide+-professor+-physiotherapist+-tutor+-instructor+-faculty&rq=1)]

But I will digress from making this more personal. Basically from the stand point of one line job titles, there isn't one for the line of work he is in. The obvious ones are to frightening to the masses. Maybe it is just our culture today where "Math" is a four letter word.

<comment><USER9> He says he is not a lot of things, but OR person isn't one of them. In fact, what he does do sounds very much like OR to me. Do you think OR is a scary term for the masses? I find saying I do Operations Research works with many people.

It is a good time to be in the IE/OR job market. Predictive analytics is very big, even as supply chain has decreased a bit since the glory days. One firm I consult with is hiring a person like you, for example (<http://www.firstfuel.com/home/staff_scientist>).

That's quite the search query by the way.

<comment><USER3> I am not proud of its length, a by product of the poor vocabulary that summarizes my skills. Instead I have to list the words that are most likely to be associated with my skills. <http://youtu.be/qiPc1mbRCxs>

</comment></comment></comment></comment><comment><USER10> The OP has so many different business cards; there's some pathos and poignancy there.

What he is talking about has some examples that have been quite successful:

(1) Oil Refinery Operation. For input to your refinery, out back have, for each of several varieties of crude oil, some millions of gallons. For output, look at the market for the various possible products and the prices of each. Then your mission is to decide how to process the different varieties of crude oil to maximize the profit.

Early on this problem was attacked with linear programming, and some mainframes were sold. Of course, the problem is nonlinear, and there has been a chemical engineering professor at Princeton who has worked on this problem, and at least one of his students got a job in Houston.

(2) Airline Scheduling. There's a lot of money to be saved there, and the OP gives a good high level description of that problem. At times the problem has been attacked seriously by groups at least at MIT and Georgia Tech.

(3) Military. During the cold war, there was a lot of interest in various topics in applied mathematics, including operations research, in a radius of 100 miles of the Washington Monument. Indeed there was a company, Operations Research, in Silver Spring that did some 'max-min' game theory with saddle points, Sion's theorem, combinatorial optimization, etc. There were applications of optimization by the Institute for Defense Analysis for the US DoD Joint Chiefs of Staff.

(4) Feed Mixing. A classic textbook problem in linear programming is feed mixing, and there have been rumors that at least one major animal feed producer takes this work seriously.

(5) Worker Scheduling. Airlines, hospitals, and maybe even fast food restaurants can get some significant savings via careful worker scheduling.

But such work encounters some difficulties:

(1) Data and Software. Too often the work requires some custom input data gathering and some custom software writing. Weeks or months of such work are not welcome for some one-shot question.

(2) Algorithm Power. Too often one wishes for an algorithm that shows that P = NP with a polynomial of small degree with small coefficients. Of course, the question of P = NP? remains one of the grand challenges in pure and applied mathematics. Instead of such an algorithm, too often one must look for and exploit special problem structure, write some custom, one-shot software, and struggle. The people paying the bills don't like to see the struggle, even when it is successful. More welcome is just to push a button, "Optimize" and get a best possible answer.

(3) Uncertainty. The OP is correct about the role of uncertainty: E.g., the Dean of Engineering at MIT, Tom Magnanti, gave a Goldman Lecture at Johns Hopkins on designing a large IP network, e.g., a big chunk of the Internet. Yes, it's a big problem in 'combinatorial' optimization as in, say,

George L. Nemhauser and Laurence A. Wolsey, 'Integer and Combinatorial Optimization', ISBN 0-471-35943-2, John Wiley & Sons, Inc., New York, 1999.

Yes, these problems are apparently the original motivations for the question of P versus NP.

At times companies have tried to attack this network design problem. There was work in PLano, TX associated with SMU, some early Bell Labs work, and a Cisco effort to help with multi-protocol label switching (MPLS).

Well, much of the real challenge of this network design problem is the uncertainty: That is, we know that the traffic and network capacity will be growing quickly and that we will have to continue to make major changes in the physical network. In principle if we had a probabilistic description of the growth, then we could minimize expected discounted cost over time. Alas, we don't have that probabilistic description, and if we did mostly using it would be too difficult for the algorithms and computing.

More generally for the real world I see three problems, one need, and one solution:

Three Problems.

(1) Professionalism. Such applied mathematics is a technical field in part trying to be useful in the real economy. There are other technical fields doing this, but often they have a big advantage of 'professionalism', that is, government licensing, peer review, official continuing education, code of ethics, and liability. The practice of applied mathematics has none of these and, thus, is taken much less seriously.

(2) Interface. Large US organizations, one big enough to pay for such applied mathematics for their internal use, are still organized much like Henry Ford's factory floor 100 years ago where the supervisor is supposed to know more and the subordinate is supposed just to add routine effort to the work of the supervisor.

So, there is a severely awkward interface between a subordinate working as an applied mathematician and a supervisor who does not understand the applied mathematics. And, unless the CEO and COB are such mathematicians, going up the management chain there must always be such an awkward interface.

The in-house legal staff solves this problem with some aspects of their professionalism that the applied mathematicians don't have.

Further, a norm in such a hierarchy is that the supervisor's job is just to do what has been assigned by their superior; making some innovative application of applied mathematics is not part of the job description; and pursuing such a project and failing could ruin the supervisor's career.

Also, no one had their career ruined from failing to make an innovative application of applied mathematics. And if a supervisor somehow does make such an innovative application, then every non-mathematician up the management chain to the COB can be afraid of their job.

Really, then, nearly only a secure CEO can sponsor a project in applied mathematics that is serious for the company, and only a small fraction of such CEOs will want to put such a project on their calendar.

(3) Power.

In US business, the top few people have a lot of power, want to keep it, and don't want it challenged. To them a project in applied mathematics can be a nuisance to be swatted down like a fly.

So how does computing solve the problems (1)-(3)? Awkwardly. The best situation is that the company is just a computing company -- Microsoft, Adobe, Intuit, Google, Facebook, etc. Otherwise usually the computing is so important that the non-technical people in the company struggle to work with the computing people.

The Need.

In broad terms, computing has often programmed what people did before manually. So, what was to be programmed was well understood. Now that work is slowing, and for more progress computing will have to program work that never was done manually and, thus, is much less well understood.

Then there is a challenge: Just in computing, as we move away from what was understood manually, we are left without means of knowing what the heck we are doing.

Let's take an example, finding a spacecraft trajectory to Saturn. That was never done manually. So, how was it done? Sure, with some mathematical physics, ordinary differential equations, and some numerical methods for those equations. With that work done, the corresponding software could begin. We were quite sure that the software, if written as specified by the physics and math, would work. So, it was the physics and math that let us know what we were doing.

Then, sure, in part computer science has tried to move into such applied math and, at times, the physics.

Here's the need: More progress in applying computers needs more use of math so that for good solutions to more real problems, never solved well manually, we can know what software to write and be more sure the results will be good. That is, the math does the logical connection from the real question to the real answer, and the computing then implements the data manipulations specified by the math.

The Solution.

I believe that the solution for computing and applied math has been presenting itself via some good examples. The theme is, the CEO needs to be one of the main technical guys. So, the founders of Intel, Microsoft, Google, and Facebook were the main technical guys. For applied mathematicians, consider J. Simons at Renaissance Technologies and A. Viterbi at Qualcomm.

So, for both future applications of computing and for careers of people studying technical fields without solid professional support, the path forward is for the technical person to be a company founder instead of an employee with a stack of many different business cards.

The opportunity is there, but don't expect the currently powerful non- technical guys to reach out with a welcoming hand!

Final point: For an entrepreneur with a valuable application of some powerful mathematics and with current attitudes in business, just let the mathematics be an advantage in getting a better solution for the real problem but don't mention the mathematics and, instead, let everyone else just assume that all the technical work was just routine software.

</comment><comment><USER11> It's a shame that the term consultant carries that connotation these days.</comment>


Derek Sivers on Business Models and Profitability (LessConf '09 Video) - <AUTHOR> http://b.lesseverything.com/2010/2/3/derek-sivers-speaks-at-lessconf2009

<comment><USER2> I read the book he mentions in the video last year. Its also my favourite business book of all time too. So easy to read and truly an eye-opener.

Trying to implement in my own business now.

<comment><USER3> Most of the talk is very directly from the book "The Art of Profitability" by Adrian Slywotzky.

Notes here: <http://sivers.org/book/ArtOfProfitability>

Very highly recommended reading.

<comment><USER2> Is the first example from the book "Influence: The power of persuasion" ?

<comment><USER3> Yep! Another must-read classic: <http://sivers.org/book/Influence>

<comment><USER4> Was HostBaby included in the deal for CdBaby?

<comment><USER3> Yep. Originally I wanted to sell CDBaby and keep HostBaby but there was no clean way to do it. So I sold *baby - including the right to have another business with "baby" in the name. :-)

</comment></comment></comment></comment></comment></comment><comment><USER5> I was at lessconf last year. Derek did a great job with that preso.</comment>


Ask HN: Anyone want to take over the ZenDesk C# API wrapper? - <AUTHOR>

It's been a great couple of years and I have enjoyed working on this project, but I just haven't been able to give the time this project requires. There are still a lot of active users out there so if you happen to be one of them or are just a good c# developer who would like to take this project over, then let me know.<p>https://github.com/eneifert/ZendeskApi_v2 <comment><USER2> I see that you already have 25 contributors, so you might wanna try filing an issue asking for someone to take over. A very good advice I've gotten is to grant commit access to anyone who files a PR that gets merged[0].

The best person to take over is probably in this list[1].

[0]: [http://felixge.de/2013/03/11/the-pull-request- hack.html](http://felixge.de/2013/03/11/the-pull-request-hack.html)

[1]: [https://github.com/eneifert/ZendeskApi_v2/graphs/contributor...](https://github.com/eneifert/ZendeskApi_v2/graphs/contributors)

</comment><comment><USER3> What is expected workload?

<comment><AUTHOR> Usually I spent about 4-6 hours a month on it, sometimes less. Add new features would be however much time you wanted to spend.</comment></comment>


Ask HN: Data Science portfolio projects ideas - <AUTHOR> Hello,<p>I'm looking for a couple of midium-size project ideas that are not just following tutorials. <comment><USER2> My two cents as someone who interviews tons of data scientists is that most portfolio projects are way too easy, and amount to getting generally clean data, then just calling some API from sklearn or tensorflow.

I'd like to see either more non trivial software/coding skills in getting the data and setting up a good data infrastructure or more depth on a innovative science solution.

<comment><AUTHOR> This is exactly why I'm asking. So, since you are, appearantly senior, in the field, do you have any concrete recommendations?

<comment><USER2> Sure. Let me start by saying that the data science interview/competency game isn't common knowledge. That is to say, even within our own company, where we are supposed to have standard guidelines, different organizations have different perspectives. So I'm sure other data scientists may disagree with me.

I have some trouble just giving you some full/rich idea, since there is a whole world of possibility. However, I can share some heuristics with you that you may find useful.

The first is, do you have any domain knowledge that would lend itself to a data science project? This would be one step in differentiating your idea, and allowing it to build off of existing ideas you have, as opposed to an off-the- shelf classifier project from a data science project site. This could be anything from biomedical data, to sports data, to market data etc. This will let you highlight your ability to dive deep and apply data science tools to a specific problem. Even if I'm interviewing someone who worked with medical data before, their ability to do data research building off domain knowledge is a strong signal that they will be able to do it again in a new domain.

The second is can you get a semi-novel dataset? Even if it's just writing a fully-fledged python script to scrape some APIs or (maybe) web-pages, something that shows that you hunted down data, and wrangled it, as opposed to downloading data_science_project.csv.

Once you get your data, try to think of a properly engineered way to store it. A csv on your laptop isn't always bad, but familiarity with AWS/Azure APIs and storing your data on the cloud in a 'nicer' format (e.g. Parquet) (or if necessary, in a database).

In your code, can you have a lightweight API to retrieve your data? Again, I'd be looking for something that tells me you can get, store, and retrieve data in line with best practices, so if you're hired and there is messiness/challenges with data, you can manage it yourself rather than needing an engineer to do all the work for you, and your job only starting when you have a csv on your local machine.

Once you have all this, can you thoughtfully try out some different methodologies? As well as interesting exploratory data analysis? This part is harder to give concrete recommendations on, but I'd like to see something that considers the problem space, the data type, and chooses the right algorithm. Then for the algorithm you chose, I'd like you to have a medium depth understanding of how it works below the hood. The bad case is you just get some data, throw it at xgboost or a nnet, and say "well I read the API docs and sorta know how they work."

(as a side note, try not to over-complicate the problem. Always do a simple model as well as the exciting model you want to try, because exciting models usually are hard to manage in production)

Lastly, put it on your github, and really highlight it on your resume or in the interview. I often gloss over portfolio project bullet points on a resume, but I'll always check a github if it exists.

Even if the project is half-baked or not as exciting as you want, having concrete github code I can read is worth so so so much more than any coding question I could ever ask.

Finally, my recommendation is for a data scientist generalist type. I do know some data scientists who are extremely valuable, more valuable than I am, who can't do any of that stuff. Usually they just work in a jupyter notebook using data handed to them. In their case it tends to be because they are so talented/trained in, say, deep learning, that their most value to the team is having someone else do everything for them, while they tweak hyper-parameters.

<comment><AUTHOR> Thank you very much. I really like your advice. I would like to build on my domain knowledge. I'm a PhD student in cs focusing on algorithms.

</comment></comment></comment></comment><comment><USER3> My personal data science blog ([https://minimaxir.com/](https://minimaxir.com/)) was designed over the last few years specifically as a portfolio piece to get a data science job by creating advanced data visualization/analysis projects w/ code, and I was eventually successful. (it has done well on HN when it pops up too)

<comment><USER4> Just a question: why do you use the third person when describing yourself? I've seen it in resumes and some formal settings, but never on a personal homepage. Also I find it a bit odd.

</comment></comment><comment><USER5> Consider making tutorials for publications that you're interested in, but are nontrivial to read through and understand. Building a tutorial will give yourself a deeper understanding of a problem, help you communicate that understanding, and benefit the larger community.

<comment><AUTHOR> Thank you. Do you think this will be appreciated for a job interview? I think it will take lots of time and effort for that to happen.

<comment><USER5> Yes. Part of the job interview will be selling your knowledge through past work. Spending the time to tutorialize content will make it easy and stress free to talk about it to a general audience. Being able to communicate your point clearly is fairly essential IMO.

As per if they'll look at it themselves, I'm much more skeptical. The same issue is present (checking at the resume stage or at the first filter stage) with other portfolio pieces though.

</comment></comment></comment><comment><USER6> I've had fun and built interesting projects based on harvesting tweets. As some other comments suggest, data collection is an important and hard skill that most tutorial projects ignore. If you can show 0) you came up with an interesting question, 1) had the idea to get this data, 2) harvested the data successfully, 3) formatted and cleaned it, and 4) ran appropriate algorithms to look for the answer to your question, you have everything you need from a portfolio project (even if the data doesn't support your original hypothesis!).

</comment><comment><USER7> OpenStreetMap (GIS, OpenData, Humanitarian, Visualisation )

You can import - and analyse the OpenStreetMap data, and create some nice QA reports for the community.

Arxiv: [https://arxiv.org/search/?query=openstreetmap&searchtype=all...](https://arxiv.org/search/?query=openstreetmap&searchtype=all&source=header)

<comment><AUTHOR> I really find this interesting.

</comment></comment><comment> TBF-RnD Perhaps give me a hand researching text input, I'm starting to gather a rather large source of ideas to be implemented. Fun work really allows you to think outside of the box. Spans all the way from UI-design down to system calls into the os ia C. So there area lot of areas to cover. Let me know by commenting if you are interested.

<comment><AUTHOR> Please elaborate. What are you researching about text input?

<comment> TBF-RnD This is the reasoning behind the project. In short I'd say that with VR around the corner and touchscreen everywhere but no practical way of doing work as such on smarthones tablets the way we look at text input should be reconsidered. International input and accomodating for disabled people are other angles. tbf-rnd.life/blog/2019/05/21/hello-world

I'm working on compiling my findings into a book. [http://tbf-rnd.life/the- book-of-lesser-known-input-methods/](http://tbf-rnd.life/the-book-of-lesser- known-input-methods/)

Along with this I am creating a framwork that can be used to \- demonstrate \- benchmark \- provide common os support \- provide to the different models.

As such say the Dasher model can be compared more or less scientifically to say plain old keyboard method or why not chorded input

So there are plenty of interesting concepts to dig into here. From UI design in javascript to analysis on text a lot of word2vec and other fun stuff and why not 3d interfaces.

I do this as a portfolio of sorts since it demonstrates such a wide range of knowledge.

Furthermore as we are dealing with a keyboard, that is something that is _always_ in use it's really important to create a wellpolished fast method so it's not for the faint hearted.

<comment><AUTHOR> I have actually done some work with doc2vec. What is in these text data? What do you hope to extract?

</comment></comment></comment></comment><comment><USER8> I heard that a good Kaggle profile is a data science equivalent to a good GitHub profile.

I haven't tried it myself, and it looks more like smaller projects, but someone might find it interesting.

[https://www.kaggle.com/](https://www.kaggle.com/)

</comment><comment><USER9> whats your background? And what sort of job are you looking to get from it?

If you want to be an actual scientist then do something thats actually scientific: elaborate an experiment design, collect your own data, analyse it and draw conclusions from it.

For example, what's the relationship between crime in San Francisco and Starbucks locations? How's the relationship conditioned on the weather? Does the size of the parking lot adjacent to Starbucks meaningfully effect crime independent of location?

I'm a little biased but there are too many script kiddies. "Scientists" that copy/paste scripts and "analyse" by calling APIs, and don't know how anything works. Data science ala Kaggle.

<comment><AUTHOR> I'm a phd student in cs focusing on algorithms. I want to work as software engineer/data scientist.

</comment></comment><comment><USER10> You want your portfolio to communicate that you are fluent in _data_ , _resourceful_ , and think broadly on what data _is_. More generally, you want to communicate that you are valuable to the employer.

What is valuable is often rare. Some skills are common or are just the baseline.

Peculiarities in people are less commodotized, and when these peculiarities intersect with the activity domain of an organization, they become valuable. When these peculiarities are deep enough and span across a broad range and the intersection of that range and the organization's interests is quite large, they become extremely valuable.

These peculiarities are often a result of lifestyle, interests, musing, and wandering. Often acquired through the years on the person's free time and are not taugh in class.

This reads like something new-agey like the saying that goes "Instead of trying to paint a perfect picture, become perfect and just paint"

Now for more practical and less "general" speak... I'll have to bring personal anecdotes which, by definition, are about my specific experience. The pronoun "I" will be used too often for a regular post as a consequence. This serves as an example of what I mean by the above.

The first project I was involved with when I joined my current company as an Enginner was related to heart data. It was convenient that I had worked on heart data before, read a lot of medical papers on the question, worked on anomaly detection, was familiar with PhysioNet data and format but also had worked on _local_ hospital data filled with chest-hair-sweat-and-motion noise and went through the challenges it represented. I could give pointers to good resources on the question to the team, knew health professionals and faculty I was still in contact with, and personal friends who are medical doctors and surgeons I could get insights from (thinking broadly about "data" not just as in digital format and CSV, but network, friends, domain experts, insights gleaned socializing).

Another project the company did was telecom subscribers churn prediction. I was invited to a brainstorming with the team discussing data and interesting features. One of them is standard of living and financial situation. I insisted on getting USSD data from the telecom company in addition to CRM data and surveys. When I was asked what it would tell us, I asked colleagues how frequently they checked their phone balances as employees (with a source of revenue) vs. how often they did as students. They all got the point: as students, it wasn't obvious that you even had enough airtime to make a call or send a text, so you sent a USSD request (free of charge) to see how much airtime you had left (thinking about data from "human moves" perspective and not forgetting the experience of being a broke student for feature engineering). It helped the project that I had gone through some books on GSM and CDMA networks (out of curiosity) and was more fluent in the data the telco sent and their jargon. I could help the team with that, recommending reading sources curated over a long time, insights from personal acquaintances in different roles in the telecom domain (engineering, sales, marketing, etc.).

Another project the company did was on reservoir characterization project for oil and gas. It happened that I had interned for the biggest oil services company in that exact position, read several books on reservoir characterization. I also had exposure to the hardware, the process, the different players and their incentives and went to actual reservoir characterization jobs (it paid to know about oil based muds, boreholes, deviation, cuttings, etc.). It helped by sharing context with the team, knowing what to look for, who to ask and what, where to get data, what domain name was that. I also had friends working in that domain in different geogrpahic locations with different companies.

Another project I was in involved sound. My training was in EE so I had more training in signal processing than the team and also had courses on acoustics. I was able to help with pure signal processing and acoustics, resources to bring someone up to speed, explanations, etc. I had interest and knowledge in the source that was producing the sound. It helped in meetings with the client because the sound source was very _peculiar_. The client was impressed because they felt I knew more than an outsider should, given regulations and the nature of the source. I was able to handle it safely and use it very accurately to their surprise and to my employer's because I had never talked about it. I also had access to people with _much more domain expertise than the client organization_ giving extremely valuable insights on real world condition and more interesting and frequent access to more diverse data sources. When we had to build custom hardware and mics, it helped that I was comfortable with a soldering iron, too.

When we did a project for a retail organization, it helped that I already was primed because I had gone through their site, read their pages source, knew they were using schema.org ontology, knew how their site was structured, already parsed their sitemap, built a scraper for that site and did all that _before joining my employer_. Plus I had the code.

Another project in banking where I had also some experience because I got interested in earlier years to how they work, wrote some code for parsing transaction data, also had friends in different banks and financial institutions explaining things (again, data of another nature and from other sources).

Another project was related to data from Programmable Logic Controllers, and it helped that I had read a bunch on the question, tinkered with Siemens PLCs, etc (it also helped when one of our new hires is a student working on a project relating on communication protocols for PLC and finding out during the interview that there's someone in the company who also was familiar, giving pointers, and adding value to his work. It helped make him work here).

Other anecdotes of visiting sites in Russian that were not translatable (images instead of text content), and being unfazed and able to sort of get around because I had tried learning Russian earlier. It wasn't much, but it saved time and just the spirit of "whatever it takes" can be contagious. This was a startup and just the boost in morale or _anything_ that removes or tames obstacles helps.

Serendipity at its finest.

And last but not least, and at the risk of being tacky: being able to communicate with people in writing, face to face, and on the phone is enormously helpful. Having a certain "lifestyle", for lack of a better word, that kept that sword sharp, helped a lot. It also helped being in sales as a college student didn't hurt.

The underlying message is: I think you can build a portfolio based on your interests and I think it helps to cultivate your interests. I think it's nice to be able to work on a Kaggle dataset with clean data in CSV format and nicely labeled images, but it helps to think about data in more ways and keep in mind that it's important to get things done and help others get them done, in any way you can. Data is much more than CSV files and annotated images. The questions to ask are:

\- How often do you think you get that kind of data (clean, ready, nicely formatted, with client being responsive and supporting you)?

\- In which ways can you bring more value to your employer by helping getting things done, often drawing on your previous experience, work, and code in a domain of interest?

\- How can you act as a lever for other team members?

\- How can you act as a bridge between stakeholders and do impedance matching to increase effectiveness of the whole _system_?

\- How do you feel about "business" helps (basic econ, ops management, marketing, accounting, etc.)? It helps transduce features/bug fixes/refactoring to business terms stakeholders understand.

\- How can you move obstacles as small as a boulder they can be?

Some things I have found useful:

\- Maintain a network of interesting and smart people in different domains (physicians and physicists, chemists, poets, painters, musicians, engineers, teachers, bankers)

\- Reading a lot about a lot.

\- Implementing stuff. Getting HTTP 429 and knowing what to do about it. Experimenting. Documenting.

\- Sharing.

\- Helping others be better at what they do, do it better and more profitably. Connecting people and wanting them to succeed.

Now, if I see that a candidate can _hustle_ , I'd be _very_ interested. I can count on one finger such a candidate, and the kid was snatched faster than I could get to him (and was snatched by an acquaintance working at a top institution with a sorry-not-sorry)

<comment><USER11> +1 . This post was really useful and detailed. Thanks.

</comment></comment><comment><USER12> If you are interested in NLP, Entity detection/Classification in news articles could be an interesting place to start.

Training Data : Wikipedia

<comment><AUTHOR> Thank you for your concrete suggestions.

</comment></comment><comment><USER13> I've got some semi-clean data that needs crunching, part of a soon to be GPL project, it's actually pretty plain but can give you stuff to blog about and post on your GitHub. My handle at gmail.</comment>


Running an LED in reverse could cool future computers - <AUTHOR> https://phys.org/news/2019-02-reverse-cool-future.html <comment><USER2> The stated theoretical limit of 1000 Watts/m^2 does not sound much when compared to the TDP of contemporary chips.

</comment><comment><USER3> Perhaps a stupid question: is this like photovoltaic cells, but in the thermal part of the spectrum?

<comment><USER4> Actually as far as I know, photovoltaic cells are actually "common" diodes. And every diode actually emits light while forward biased, it's like a inherent property of them. Electrons "leap" the electron gap in a NP junction and while "going down" emit a photon. And the reverse is true, a photon of certain wavelength inciding on a NP junction will energize an electron if the wavelength coincides with the electron gap, thus producing a voltage difference.

This is used in more interesting ways on LEDs since their construction exposes their junction to the environment. You can use their small junction capacitance while they're charged and it's variability while being exposed to photons to create "light based touch sensors". You emit the same wavelength light with contiguous LEDs and one of them is "turned off" and time it's discharging rate. Faster? Light is shining over the junction. Lower? there's no matching photons over the junction.

So, I guess yes, is like PV cells but for even wider wavelengths (AFAIK PV cells already try to harvest the most of the sun's infrared light)

</comment></comment><comment><USER5> How does this differ from a solar cell? (would make sense to capture heat/IR with one and just feed it back as electricity).

Or did they just happened to use an LED and the same thing could be done with a solar cell (feeding some power the wrong way to make it suck in a bit more)?

So it's a bit like a solar cell with a motor as a load, but you even spin it in reverse to make it suck dry the solar panel a bit more than it would be willing to give(?).

<comment><USER6> [https://youtu.be/6WGKz2sUa0w](https://youtu.be/6WGKz2sUa0w)

<comment><USER5> Yea, this is why I wondered why not use a solar cell right away.

</comment></comment></comment><comment> m-p-3 Not sure I quite understand how this works. The heat / infrared emissions it absorbs has to go somewhere right? I haven't seen any mention on that matter in the article.

<comment><USER7> (Disclaimer: I have some background in physics, but I'm not an expert.)

I think the heat is transferred from the "computer" to the LED itself. So the LED itself heats up.

To go into a bit more detail:

All physical objects emit thermal radiation (a.k.a. black-body radiation [edit, not quite correct]). The hotter the object is, the more radiation it emits and the shorter the wavelength of the radiation. For "red hot" objects, the radiation is in the visible part of the spectrum; for room-temperature objects, it's in the infrared, so you can't see it, but it's still being emitted. If you put two objects of different temperatures next to each other, they'll both emit radiation and absorb each others' emitted radiation. The hotter one will emit more radiation than the cooler one, so there will be a net transfer of energy from the hotter one to the cooler one (normally).

But in this experiment, when the researchers run the LED in reverse, this somehow suppresses the LED's normal thermal radiation emissions. The "computer" continues to emit thermal radiation, which is absorbed by the LED just like normal. But the LED doesn't emit thermal radiation back to the computer (at least, not as much as it normally would). So even though the LED is hotter than the computer, the LED acts like it's colder for thermal radiation purposes. So there's a net transfer of energy from the cooler "computer" to the hotter LED.

Of course, this isn't a complete solution; you still have to do something about the heat once you've transferred it to the LED. The article doesn't address this part of the problem. But I speculate you could just attach a heat-sink to the LED. Heat sinks work better at higher temperatures, so the computer+LED+heat-sink solution would be more effective than a computer+heat- sink alone.

<comment><USER8> > All physical objects emit thermal radiation (a.k.a. black-body radiation)

Not all materials are black body emitters. The black body spectrum is in fact an idealized emission spectrum which only few materials approach.

An LED most definitely is not a black body emitter.

You can engineer materials that absorb/emit a specific part of a spectrum and reflect/don't emit in other parts. This has uses in thermal engineering - e.g. you can shed heat by making things "white" in most of the spectrum but "black" in the infrared windows of the atmosphere. In this case they tune the behavior electrically.

<comment><USER7> True, but the distinction is irrelevant in this case.

<comment><USER8> Far from it. If all physical objects were black bodies then the LED couldn't do anything here since emission and absorption are the same process.

<comment><USER7> The article notes that the LED "acts as a very low temperature object". I interpret this to mean "the LED radiates as though its temperature is lower", rather than "the LED radiates as though its emissivity is lower". In other words, AFAICT the effect can still exist even if the LED has 100% emissivity in both absorption and emission, which would make it a black-body. So the fact that the real LED's emissivity is not 100%, is not relevant to the effect. But we're splitting hairs here.

<comment><USER8> The paper is talking about effective temperature for specific photon energies. Additionally black body emission refers to thermal equilibrium conditions which the LED clearly is not. And then there's the near-field coupling they're using:

 _> Recent experimental advances in near-field radiation have shown that heat- transfer rates on the nanoscale can exceed the blackbody limit by several orders of magnitude14–17, owing to contributions from evanescent and surface modes18,19. As a result, energy conversion rates can be greatly enhanced on this scale20._

So this whole system relies on not being a black body on several levels.

<comment><USER9> Even that will only work if they don't produce more heat doing that, than they pump away.

Same issue as with anti-Stokes scattering that was once held promise of "self- cooling LEDs" or using gas dynamic lasers for spaceship cooling.

There is no trick against thermodynamics after all.

</comment></comment></comment></comment></comment></comment></comment></comment><comment><USER10> This is an interesting effect.

How does the strength and efficiency of this effect compare to the cooling possible with Peltier junctions?

<comment><USER11> You can move a watt per cm^2 with a single-stage Peltier effect device, depending on the temperature difference you need. Here's a data sheet for a 9mm by 9mm device that can do 1W/cm^2 at 40C temp difference:

[https://cdn2.hubspot.net/hubfs/547732/Data_Sheets/NL1012T.pd...](https://cdn2.hubspot.net/hubfs/547732/Data_Sheets/NL1012T.pdf)

The OP claims 1000 W/m^2 theoretical max for the optical cooler. That's 0.1W/cm^2. Right now they say it's 0.6% of that theoretical max.

</comment></comment><comment><USER12> "Near-field photonic cooling through control of the chemical potential of photons" (2019) [https://www.nature.com/articles/s41586-019-0918-8](https://www.nature.com/articles/s41586-019-0918-8)

</comment><comment><USER13> This sounds like a previously known effect known as "negative luminescence": [https://en.m.wikipedia.org/wiki/Negative_luminescence](https://en.m.wikipedia.org/wiki/Negative_luminescence)

</comment><comment><USER14> Cool! It's like an infrared light vacuum!</comment>


Announcing Streamlio: enterprise-grade realtime solution - <AUTHOR> https://streaml.io/blog/announcing-streamlio/ <comment><USER2> The only thing sockpuppet voting and commenting like this does is get your site and accounts banned.

</comment><comment><USER3> Enterprise streaming solution is a very promising area. I know Steamlio has solid engineer team, looking forward to their next big step!

</comment><comment><USER4> Excellent team with a great knowledge!

</comment><comment><USER5> Great vision, great team, better future

</comment><comment><USER6> Strong team with bright ideas!

</comment><comment><USER7> Nice!!!!! Congratulations!!!

</comment><comment><USER8> really strong eng team and industrial leading streaming solutions!

</comment><comment><USER9> Well done on the launch.

</comment><comment><USER10> Sounds very exciting!

</comment><comment><USER11> Exciting news!

</comment><comment><USER12> Amazing!!!</comment>


How We All Missed Web 2.0′s "Netscape Moment" - <AUTHOR> http://techcrunch.com/2011/04/03/how-we-all-missed-web-2-0s-netscape-moment/

<comment><USER2> Wow, this is by far the best post I've ever seen on Techcrunch.</comment>


Why your iOS device may be a better cable box than the Apple TV - <AUTHOR> http://gigaom.com/2014/05/10/why-your-ios-device-may-be-a-better-cable-box-than-the-apple-tv/

<comment><USER2> Anyone else saddened by how high the "history" channel ranks? Last time I tuned in there was a show about Nazi's and Aliens and then a whodunnit about Jesus. All rather sad really, on a channel ostensibly about history.

<comment><USER3> Approximately 35-40% of the shows History runs (by show, not by air time) are fairly straight history. Another 10-15% are historical dramatizations or are arguably straight science rather than history (for example, "The Universe").

The Nazi aliens and such pay the bills that keep the serious stuff on the air (although "Pawn Stars" gets a lot of viewers, yet actually includes a lot of serious history content, so there is hope for making money without resorting to aliens or ghosts). Use your TV schedule and DVR to skip the silly money making stuff.

<comment><USER4> Tomorrow's schedule: [http://www.history.com/schedule.do](http://www.history.com/schedule.do)

* Swamp People (multiple episodes) - Cajun reality show * Down East Dickering - knockoff Pawn Stars reality show * 'Info Documentaries' \- pretty sure this is 3 hours of infomercials * Gettsyburg Civilians - a history show! At 4:30am. * UFO Files - from 7am til 5pm * Ancient Aliens - 5pm til 8pm * more UFO Files until midnight

That's the entire schedule for the day, no omissions. Reality shows, then informercials, then 17 (seventeen!) straight hours of aliens. They do spend 30 minutes on Gettysburg at 4:30am, which along with WWII is the only history the History Channel even considers touching.

</comment></comment></comment><comment><USER5> Plex app for iPhone + an Apple TV is definitely the best solution here (especially since I am outside the US and cant get any of this stuff)</comment>


Epistemic standards for "Why did it take so long to invent X?" - <AUTHOR> https://rootsofprogress.org/epistemic-standards-for-why-it-took-so-long <comment><USER2> In 1979 when I was at school in a maths class the teacher (for some reason) was talking about graphine and how it would be a game changer when invented and I said - why don't you get a bit of pencil lead and put between two bits of cellotape, rinse repeat until you got a thin layer. I was lambasted and ridiculed by the teacher.

THAT is another reason why it takes so long to invent X. People who shouldn't, quickly dismiss and idiot label anything outside the box of thinking. Still irks me, even today how I was not strong enough to stand my ground (probably been put in detention for answering back) and how I accepted that I was wrong.

<comment><USER3> > why don't you get a bit of pencil lead and put between two bits of > cellotape, rinse repeat until you got a thin layer.

I am a bit skeptical of your Account, but it is also not quite as trivial as that. The key insight wasn't just the mechanical exfoliation (scotch tape Methode). This had been used before and wasn't new by itself. The key insight was transferring it onto a SiO2 substrate. So, no worries you most likely did not miss out on your Nobel Prize ;)

<comment><USER4> Its not about that, its about dismissing practical trains of thought - outright. Ironically, the author of the article is such a person.

> To invent something is to invent a practical version of that thing.

It is not. Like with everything from the chain of command to the chain of events it takes all links in the chain to make it a chain.

You might as well argue that it is marketing that is responsible for the invention or that the consumer in their decision to purchase the newfangled contraption decides if the invention is real or not. Or no wait, the financier, he is the true visionary.

> If your "invention" is impractical, it's just a demo or prototype

Oh, that is _only this and that._ Someone who trivializes the prototype doesn't have what it takes to envision it, let alone make it. Hardly a position fromwhich to judge those who did and do.

<comment><USER5> Furthermore, if I understand the position, the patent office would not agree to the OP's definition either .. as long as the original maker of the "prototype" could describe the mechanism well enough. The inventor of the "practical" version would have to articulate what it took above and beyond the prototype and even then only be able to patent that part and not including the invention covered by the proto.

<comment><USER6> To me that sounds more like an argument against our patent system than an argument in favor of counting impractical prototypes as inventions.

<comment><USER5> The patent system is supposed to be to encourage knowledge sharing in society by granting monopoly in exchange for full disclosure of invention details. Imposing an irregular concept like "practicality" on top this is counterproductive.

Practicality is not straightforward. Was Edison's light bulb practical on its own terms or did it become practical only after the invention of electric power generation and distribution? What about economies of scale? .. and so on.

</comment></comment></comment></comment></comment></comment><comment><USER7> Some inventions are gated by scientific discovery, particularly in materials.

For example, ductile iron (which involves adding 1% magnesium to molten iron, causing carbon to precipitate on cooling as small spheroids instead of dendrites, making the iron much less brittle than ordinary cast iron) could have been invented any time after 1808, when Davy produced magnesium. But it wasn't invented until 1948. No one had done the experiment and seen that effect.

Another example, also coincidentally involving magnesium, is magnesium diboride. It was synthesized and its structure characterized in 1953, but it wasn't until 2001 that it was realized it was a superconductor with a critical temperature of 39 K.

<comment><USER8> Hopefully when we're done with this, perhaps we can extrapolate and invent the future a little faster.

If we invest a few percent more in R&D every year, for example, would that compound over decades?

If we did more Citizen Science? Individual and crowdsourced.

More X-Prize investments?

Consumer products like televisions, smartphones, smart watches, etc advance because consumers are willing to spend large amounts of money.

If robotics, or any technology, could reach a tipping point, it'll get the same investment.

<comment><USER9> Research into what... I think that is part of the problem. I was recently reading a click bait article about how some craft person knew something an archeologist didn't... The Portuguese is no one knows everything. Also look at a lot of our technological marvels ah were accidents. More resesrch won't necessarily help, if you are already going down the wrong path

<comment><USER10> But going more paths will help discover more good paths.

</comment></comment></comment></comment><comment><USER7> An example I've mentioned before on HN is the rotary pressure exchanger. It has one moving part, is 98% efficient, and the base patent was issued in 1988. Perhaps there was a lack of large application before reverse osmosis became a big thing?

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

<comment><USER11> This is pretty interesting.

> Early designs for desalination plants... have an energy consumption of over > 9 kWh per cubic meter.

> Many early SWRO plants built in the 1970s and early 1980s had an energy > consumption of over 6.0 kWh per cubic meter of potable water.

But it doesn't go on to list the comparable performance of the newer post-1988 patent designs (except to say 98% efficient). Do you have any idea what in terms of kWh/m^3 that converts to?

<comment><USER12> [http://www.scientificamerican.com/article/israel-proves- the-...](http://www.scientificamerican.com/article/israel-proves-the- desalination-era-is-here/) says Sorek produces drinking water at US$0.58/kℓ by reverse osmosis at 7.1 MPa. 7.1 MPa is by definition 7.1 MJ/m³, so 98% efficient at the mechanical level would be 7.2 MJ/m³. (As someone else pointed out, though, 98% is the efficiency of the pressure exchanger, not the whole electro/mechanical/hydraulic system.) 6 kWh is 22 MJ, and 9 kWh is 32 MJ. US$0.58 is the cost of about 52 MJ, but that includes things like the cost of building the plant and defouling it.

</comment></comment></comment><comment><USER13> All inventions have prerequisites that people don't think about. The steam engine is the first invention people think about if they were time travel, scribble something on a bit of paper and become rich. You'll need several boring things that need to happen for you to make a working steam engine.

You'll need the materials. A lot of strong, cheap steel. Preheated blast furnaces weren't invented until the early 1800's. Thomas Savery had the idea for the steam engine almost a hundred years before the Watt, but Savery's engines kept blowing up because the lack of strong steel.

You'll also need to overcome trade barriers too. You'll also need cheap coal (ironically requiring steam engines to become cost effective) and high quality iron ore (ideally from Sweden). Through out most of history, empires hated trading as it could create vulnerabilities.

There's also the market prerequisites, no one wants your expensive steam engine if a donkey pulling a wheel is cheaper and more reliable.

<comment><USER14> Thinking about this and going down the wikipedia rabbit hole of inventions scares me. I've heard the Dark Ages happened in part because society collectively forgot how to re-create the advanced technology from ancients, so once things inevitably broke, people just became that less efficient. Another area which strikes me as complex as metalworking is textiles. What if we forgot how to use the machines for harvesting cotton, spinning it into threads and then weaving it into clothes? I wouldn't be able to help at all in such a catastrophe, despite holding advanced degrees. I'm afraid I wouldn't even know how to fashion a spindle, or operate one. Hopefully the internet has enough information that this doesn't happen again?

<comment><USER15> Well, the scholars at the time thought so anyway. They were very keen on classical knowledge.

More realistically, the "dark ages" were a time of political dislocation and fragmentation of trading networks, so Europe just got a lot poorer. Rome had knit together a vast trading network, but without Roman armies you couldn't trade long distances anymore.

You forget how to build Roman roads when you don't have a government around to build roads, and even if you did, you don't have the money or manpower anyway.

Medieval Europe invented a heavy plow, which the Romans never came up with, so it was not all disintegration.

[https://sciencenordic.com/agriculture-agriculture-- fisheries...](https://sciencenordic.com/agriculture-agriculture--fisheries- anthropology/how-the-heavy-plough-changed-the-world/1381548)

<comment><USER16> Watermills were also on an evolutionary path (so to speak) in the early Middle Ages. From the dedicated wiki page [1]:

> Largely unaffected from the turbulent political events following the demise > of the Western Roman Empire, the importance of watermilling continued to > grow under the new Germanic lords. (...) By Carolingian times, references to > watermills in the Frankish Realm had become "innumerable".

[1] [https://en.wikipedia.org/wiki/List_of_early_medieval_watermi...](https://en.wikipedia.org/wiki/List_of_early_medieval_watermills#Historical_overview)

</comment></comment></comment></comment><comment><USER17> It's also amazing to me how quantitative, evolutionary advances to some technologies that might seem futile or superficial enable some qualitative technology leaps.

For example, miniaturization of computers seemed pretty futile to me in the 90s. Indeed, why would I care if that big box becomes slightly smaller?

That miniaturization is basically what enabled the whole smartphone industry. The large-scale availability of small and powerful chips in turn enabled the drone / quadcopter to become feasible (a quadcopter is too unstable to fly on its own, and there's no real way to stabilize it mechanically like we do on RC helicopters; it has to be stabilized electronically).

I think the best inventions come from recognizing the kind of qualitative leaps you can do from evolutionary advances to existing technologies.

<comment><USER18> Or rechargable batteries. Even lithium ion batteries weren't better than state of the art NiMH batteries when they first came out in the 1990s. Evolutionary improvement let us develop quadcopters, e-bikes, e-scooters, electric cars, smartphones, e-cigarettes, tablets, and countless other devices that simply weren't that practical 3 decades ago. And this process continues.

</comment></comment><comment><USER19> My favourite example of an "idea behind its time" is the torque amplifier, which enabled mechanical analog computers on invention in the early 1900s. It is made of nothing more complicated than a source of rotary power, a couple drums/pulleys, and string/rope:

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

<comment><USER20> I don't understand why this is called an "amplifier" rather than simply "a clutch". The torque input is always the same; there is no "amplification" of the torque. The tensioned rope or spring simply applies more or less of the torque to the output, by varying the friction on the drum.

<comment><USER19> The output gets more torque, just like a capstan allows a person to amplify tension on a rope. Maybe this will explain better than the wikipedia page: [https://www.youtube.com/watch?v=ailf7bz9H0o](https://www.youtube.com/watch?v=ailf7bz9H0o)

edit: spelling, grammar...

<comment><USER20> The reason I wondered, is that in years past I had serviced machines that used a "wrap spring clutch"[1] which I knew used the same principle. These are mentioned in passing in the Wpedia article on clutches[2] where it says they obey the "Capstan equation". That article[3] opens,

> The capstan equation or belt friction equation, also known as Eytelwein's > formula, relates the hold-force to the load-force if a flexible line is > wound around a cylinder (a bollard, a winch or a capstan)

So there's the generic idea, which can be viewed as a clutch or a bollard. The bollard is an "amplifier" in the same sense that a transistor is, where a small controlling voltage regulates a larger current flow. However the wrap spring clutch is on/off, not proportional, so is effectively a torque SWITCH.

[1] [https://www.warnerelectric.com/products/clutch- products/wrap...](https://www.warnerelectric.com/products/clutch- products/wrap-spring-clutches)

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

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

<comment><USER19> I think a better transistor analogy than a FET is a BJT, where both the amplified quantity and control signal are electrical current.

The key difference between a clutch and torque amplifier is that, with a clutch, the output shaft power all comes from the input shaft. The torque amplifier's output shaft power mostly comes from the output drum, not the input shaft. The drums are constantly spinning, powered by some external source. [https://www.youtube.com/watch?v=oNNkNc7mFJ4](https://www.youtube.com/watch?v=oNNkNc7mFJ4)

</comment></comment></comment></comment></comment><comment><USER21> It's crazy to think that the modern bicycle was invented the same year as the modern car, both in 1885. Although apparently the ball bearing was a limiting factor for the creation of each.

<comment><USER22> The vast majority of advancements come directly from materials science. New materials are so strongly correlated to advancements, that I think there should be national labs that run government scale experiments to search for new substances.

<comment><USER23> > The vast majority of advancements come directly from materials science.

This is one of the most thought-provoking comments I've ever seen on HN!

Can you expand on that for a couple of paragraphs?

<comment><USER24> I don't think these are the "best" examples as they are probably not completely accurate, but there is probably a reason why the Stone Age, Bronze Age, Iron Age, and Steel Ages exist as a concept.

Also I think it makes sense since materials science is more applied chemistry/physics/engineering, so naturally materials science is huge because it represents 3 fields of knowledge interacting.

<comment><USER25> im not sure "steel age" is a common term, but I agree with the idea. the (second) industrial revolution was spurred by availability of steel

anyway, you can take it further. the information age we are in is arguably characterized by silicon

</comment></comment></comment></comment></comment><comment><USER26> I was reading a popular OER Astronomy textbook yesterday. Long sigh. "Why did it take so long to..."? Regrettably not. "How very long will it eventually take to...", write an intro Astronomy textbook, that doesn't bungle the color of the Sun? I still don't know of a single one. With true-color in a leading image, and in illustrations. With no misconceptions about yellow stars, or scattering to yellow, or blackbody color, or color perception. With explicit mention of stellar classification color's non-perceptual white-point of blue Vega. With correctness from clarity, not from ambiguity and omissions. Such a text could have been written any time in the last few decades. People have been suggesting it. So how many more decades will we wait? It's a mistake to confuse systemic communication, coordination, and incentive dysfunction, with "people don't care" (as the interventions needed are different)... but they do superficially look so similar.

Similarly, atoms are taught very poorly, even by the incoherent standard of chemistry education content. I'm currently trying to decide whether to create a little exemplar of better, to speed up too-long conversations about transformative content improvement. "Atoms are little balls"; interactive _accurate_ simulations; real pictures. Consider those pictures. There are _lots_ of wonderful images and videos of atoms... on peoples' drives. Not in papers, for space. Not on lab websites, for why bother, when few visit. Rarely on youtube. A few show up in talks, also space constrained, also rarely on youtube. So to achieve a minimal standard of "when introducing a thing, _show the bleeping thing_ ", would require a lot of mucking about, asking after images, educating about copyright... sigh. At least accurate electron simulation is getting easier with time, with open-source python replacing expensive commercial replacing good-luck-with-that fortran. And yet, for how long will student understanding and careers suffer from rubbish content? One more year? 5? 10? 25? More?

As with individuals, society has a great deal of "yeah, I really should do that; been meaning to; but I just haven't gotten around to it yet".

<comment><USER27> > _As with individuals, society has a great deal of "yeah, I really should do > that; been meaning to; but I just haven't gotten around to it yet"._

Most of it caused by "who's going to pay for it? I can't afford to do it on my own". And, sadly, the need to make money at every step of the way is what causes a lot of these problems. You wouldn't have to educate anyone about copyrights when dealing with pictures of atoms if there weren't a couple layers of rent-seekers in between you and the photographer.

> _a minimal standard of "when introducing a thing, show the bleeping thing"_

One thing I'm surprised I haven't seen anyone do yet is a kind of "continuity of zoom" image from everyday scale to nanoscale. Imagine a video (or better yet, a frame with a slider you can drag back and forth yourself) depicting an object - say, a metal sheet, or a fly's wing, or something - that starts in 1:1 scale, and then the zoom level gradually increases, going through overlapped perspectives of camera, optical microscope, ... [whatever they use in the middle] ... up to a scanning microscope, so you can watch as the image is being zoomed all the way to the atomic level. With no jump cuts in between. Would do wonders for people's sense of scale and understanding of what the world is made of.

<comment><USER28> See Powers of Ten from 1968. Although I imagine there are more recent examples.

<comment><USER27> Haven't seen that. All the recent examples I saw were vector drawings (Flash animations, then HTML5 ones, and their renditions on YouTube).

Still, I assume that that 1968 video was mostly fiction and artist's imagination between ~ 10^-5 and 10^9. With current-era tech, we should be able to go down to 10^-8 with a real shot of a real object.

<comment><USER28> It's by Ray and Charles Eames and is considered to be pretty groundbreaking. But, yes, we know a lot more and have more imagery regarding the small scales in particular than we did 50 years ago.

</comment></comment></comment></comment></comment><comment><USER29> If you liked this article I would recommend "How To Invent Everything" by Ryan North. The book is effectively a time travelers guide to reinventing technology.

<comment><USER30> This book actually does try to answer questions like "what's necessary to invent the bicycle?"

According to the book, bikes depend on 2 major branches:

Bikes -> Spinning wheels -> Natural fibers -> Farming

and

Bikes -> Steel -> Kilns/Smelters/Forges (this has quite a lot of decendents) -> Mining -> Farming

Very interesting book.

</comment></comment><comment><USER31> >Wheeled Luggage

I think that one is pretty obvious. You need to be a traveler going somewhere you need to bring luggage to... but it has to be somewhere you can't just have someone help you or use a dolly (e.g. taxi or hotel) but also needs to have smooth surface for the wheels (roads/sidewalks/flooring...), and it has to be a traveler who can't just afford to hire a servant/car/cart/horse to transport those goods.

Prior to train stations, is there any reasonable place a traveler could want to go that would even cause the necessary demand for wheeled luggage?

<comment><USER32> Probably not but wheeled luggage was invented almost two centuries after the railway!

<comment><USER33> The railroad provided wheels. Every station had a large cart. Unload your trunk from the carriage to cart, then push the cart up to the train, then load onto the train where it was stacked. Nobody had to personally handle their luggage much, and they also typically carried a larger volume of stuff. As such built in wheels wouldn't have been desired for rail road travel as there already was wheels available when you needed them.

</comment></comment></comment><comment><USER34> I wonder if there have been any truly physically-gating dependencies? Meaning, physical and natural phenomenon where certain advances were impossible before they happened? For instance, certain technology that absolutely could not have existed before, say, a certain comet flew past because before then there was no evidence to believe X. Is there any reason to believe that we couldn't have been at this technological level 1,000 or 10,000 years ago?

<comment><USER24> Things getting cool enough after the big bang seems to be the obvious one.

But on a more serious note, maybe modern encryption? The physical gate being the literal ability to get rocks to count fast enough to finish decrypting something before the heath death of the universe

<comment><USER35> I'd actually put modern crypto in the opposite bucket: there's virtually no physical constraints at all. You could do RSA by hand if you had to, and if nobody _else_ has computers, you can pick a key size small enough for doing it manually to be practical.

<comment><USER24> Oh I agree. I guess I was approaching this from the angle of the use of long keys where it would be literally impossible to decrypt unless computers exist.

We could also get into the sub argument of math being a property of the universe. Does encryption exist if we don't discover it? Trying to imagine a universe where our concept of math is impossible to the universe just not working that way

</comment></comment></comment></comment><comment><USER36> Please take the time to enjoy this. I'll leave it to others who know the work of James Burke to explain [https://youtu.be/7G8YHWbi-9U](https://youtu.be/7G8YHWbi-9U)

<comment><USER37> Oh damn you to hell!

I cannot see a james Burke show/presentationwithout being sucked in and watching the whole thing. It's just not possible. Even if I'm just walking by I get sucked in.

Why can't today's presenters/media types be as good as him?

</comment></comment><comment><USER38> Perhaps economics/accounting ideas would be able to be invented sooner, as they have less reliance on physical materials/supply chains etc.

Here's my 3 favorite candidates:

\- insurance based on statistics

\- double entry book-keeping

\- credit cards

How early could they have been invented? (How early were they invented in primitive forms?)

<comment><USER39> That's a really interesting observation. My knowledge on the history of finance is woefully inadequate, but stocks seem to be another concept that was popularized very late.

</comment></comment><comment><USER40> the author sets out on a very difficult exercise, made more so if he does not include the other inventive civilizations. documenting china's inventions, for instance, required more than a lifetime of work by Needham; volumes continued to come out even decades after his death around 1990; some dozens of densely worded volumes comprise his masterwork and it is still thought to be far from complete. some of what the British patent office was approving in the 1800s were already in their modern form in china at the time of Christ. such examples are many, and I expect similarly so for India, the Arabs, the Persians, the Mayans, the Incas, etc.

</comment><comment><USER41> Why is it taking so long to invent the semantic web? It could have a large economic impact, but solutions don't catch on. We have a specific way to say "I am a teapot", but not a generic way to unambiguously make simple statements like that. At least not a way that has gained traction.

What's the missing tech? Maybe there isn't one, and we're just an Eli Whitney coder away from making it happen.

<comment><USER42> The semantic web is a solution in search of a problem; most websites don't have semantics beyond "the page looks like this", and couldn't be trusted to describe them accurately if they did. Enabling a machine to understand a website in the same way that a human can would be valuable, but is probably an AI-complete problem; in the meantime the best path towards it is probably platforms for easy mostly-automated web scraping or testing (In fact the most useful stepping stone towards a semantic web I've seen is probably adblock, with its simple slider/checkbox interface for telling it "this piece is an ad" in the cases where it failed to figure that out).

Maybe "why are Selenium tests so flaky? Can we do better?" would be a good starting point if you want to work on this problem. The inability of most (all?) companies to write _good_ browser-based test suites is effectively those companies' inability to recover the semantics _of their own site_.

<comment><USER43> I never made the link between semantic web and the pain that are browser tests, but now that you say it, it makes sense (especially if you use semantic attributes to identify the page elements for your tests).

</comment></comment></comment><comment><USER44> My favourite idea is the internet. The romans could have done it with flags / torches and towers. Don't tell me it wouldn't pay for itself. Sending data over long distances at that type of speed would have paid for itself multiple times over, even if it were one tiny fraction of the bandwidth we have today.

<comment><USER45> There's something like this in the movie Lord of the Rings: The Return of the King

[https://www.youtube.com/watch?v=i6LGJ7evrAg](https://www.youtube.com/watch?v=i6LGJ7evrAg)

I wonder if this method of communication was EVER used by any civilization.

<comment><USER46> It's been described throughout history, so quite certainly.

<comment><USER45> Ohhhh, that's true!

[https://en.wikipedia.org/wiki/Beacon#For_defensive_communica...](https://en.wikipedia.org/wiki/Beacon#For_defensive_communications_\(historical\))

</comment></comment></comment></comment><comment><USER47> The ENIAC credit seems to be further complicated by the tube based code- breakers that came out 3-4 years before on a top-secret basis, only in the last few decades documented publicly: [https://daytoncodebreakers.org/brief/one_sheet/](https://daytoncodebreakers.org/brief/one_sheet/) and [https://daytoncodebreakers.org/more/sitemap/](https://daytoncodebreakers.org/more/sitemap/)

</comment><comment><USER48> I misinterpreted "X" as meaning "X windows"

Good article, but I still wish it was about X windows...definitely a buzzkill.

</comment><comment><USER49> The article was on to something, that something only becomes viable when its stronger or faster then a human. Because human labor has always been cheap. I'm sure engines and other things existed before, but they where only available for kings, or smart people with free time (money). What have been the single most important factor for our recent technology explosion is that human labor has become more expensive because of opportunity cost. People will not join the army if they can get better paid doing something else. So it's also solves wars and crisis. But it can only be achieved politically. If you where a king, there wouldn't really be any incentive to make other peoples life better, as you then would have to pay more for services, and the people might overthrow you if they think they can fare well on their own.

</comment><comment><USER50> I think the point about an "obvious" demand for a product is important, but what is obvious changes over time. After the industrial revolution it was obvious that certain improvements could make a lot of money in industry, but that was not obvious eg to the inventors of the Roman steam engine.

</comment><comment><USER51> In case you were curious why it took till 3500 BC to invent the wheel:

[https://www.livescience.com/18808-invention- wheel.html](https://www.livescience.com/18808-invention-wheel.html)

<comment><USER52> The 'why didn't the Incas, who were brilliant engineers eminently capable of mastering the axle, invent the wheel' is a fun question too. But one easily answered by looking at how little of their territory is flat enough for a wheel to be useful.

<comment><USER53> Plenty of people use cars, buses and railways in Peru today. The wheel is definitely useful in that territory, it just wasn't advantageous enough to over existing tech, so it needed to wait until complementary technologies had been invented in other cultures.

<comment><USER52> Made a lot more sense to start cutting and maintaining gently graded roads through the Andes for civilisations who started millennia earlier with the premise that horses/oxen were available and good at pulling stuff and once you got through the mountains everything would be nice and flat. Iron helped a lot too, of course.

The wheel still isn't particularly useful in reaching a number of Inca sites even given dynamite and the internal combustion engine. It wasn't that Incas were averse to the concept of roads so much as they didn't see why roads shouldn't have stairs.

Llamas are good at climbing steps and terrible at pulling carts...

</comment></comment></comment></comment><comment><USER54> My favorite example is the Edison phonograph. I see no reason why someone like Newton could not have invented this. We could have have recordings of Mozart and Beethoven playing the piano.

</comment><comment><USER55> Colossus predates ENIAC [https://en.m.wikipedia.org/wiki/Colossus_computer](https://en.m.wikipedia.org/wiki/Colossus_computer)

</comment><comment><USER56> Sometimes thinking of an idea is the hardest step after all.

How many of us have just sat there how many times, with all the tools we could need at our disposal, but not sure of what to do with them?

</comment><comment><USER57> What software do you think could help speed up discoveries/inventions? Ideally, something which doesn't require immense computing (like materials simulator).

<comment><USER4> Ill pester you with a riddle I came up with the other day. I'm calling it the apples and oranges problem. If we could answer it it would increase progress a thousand fold:

The question is: How do you compare unrelated features?

To put silly: What is more important, a led on your coffee machine or gears on your bicycle and by what margin?

How much is CPU speed worth vs memory vs screen resolution vs battery life?

We could make a chart for each for what it costs, we could make a chart for the technical advantage or disadvantage, we could make a chart for consumer demand. I'm probably forgetting 10 things here....

Now imagine each of those to be dynamic(!)

If the CPU does zero cycles per second it will render the entire computer useless. If it is 0.8 Ghz and the goal is [say] web browsing it is almost as worthless as the 0 Ghz. In a few years 1.5 wont be enough either. The infinitely large memory costs an infinitely large amount of money.

If we could resolve this puzzle we could make giant leaps forwards.

Until we do grandma will have to pick her phone on gut feeling and the market will just have to anticipate that.

<comment><USER58> There's no puzzle or riddle. You compare unrelated features by looking at customers' revealed preferences in terms of how much they are willing to pay. Economists do this type of analysis all the time.

</comment></comment></comment><comment><USER59> why did the suitcase with wheels take until 1970s

</comment><comment><USER60> The bicycle is a pretty poor example of this. The word "car" is derived from the word "carriage". People already had horse or ox drawn "cars" centuries before the bicycle was invented. There simply was no need for an inferior method of transportation.

<comment><USER61> I think you're comparing bicycles to an idealized version of horses. Real horses get tired quickly, get hurt easily, and are quite expensive. Assuming decent roads, a bicycle would often be more convenient, and almost always cheaper.

From Wikipedia: "A stagecoach traveled at an average speed of about 5 miles per hour".

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

<comment><USER52> > Assuming decent roads, a bicycle would often be more convenient, and almost > always cheaper.

I think you're assuming an idealised version of roads. In all seriousness, good roads were usually cobblestones and bad roads rutted tracks until bicycle pioneers started lobbying for roads to be paved smoothly enough to make their then-expensive hobby more practical for transportation than horses and horse drawn vehicles. Asphalt and Portland cement roads were new technologies in the nineteenth century too.</comment></comment></comment>


SpaceX Livestream – First Private Passenger on Lunar BFR Mission - <AUTHOR> https://www.youtube.com/watch?v=zu7WJD8vpAQ&feature=youtu.be <comment><USER2> Yusaku Maezawa in 2023. Inviting 6-8 artists to travel with him. Hope this happens.

dearmoon.org live after the broadcast.

<comment><USER2> dearmoon.earth</comment></comment>


Why our startup is selling services - <AUTHOR> http://blog.davejafari.com/why-were-selling-services

<comment><USER2> I wish you would have expanded a bit more. Consulting does indeed bring in some chashflow when its most needed (I do it, too (email on profile)). But what are your reasons for consulting, aside from money?

Also, consulting brings a host of other problems. Managing time is a tough one. Unless one is a circus juggler, switching between projects is almost impossible. Plus people tend to push back their MVP to keep a client happy.

Anyhow, just write a bit more.

<comment><AUTHOR> It sounds like your curious on how to manage both a client and an internal project. I'll be happy to share our experiences doing so later. The simple explanation is to have a good understanding of your development velocity, treat each project the same in resource allocation, and set expectations for both your team and your client.

In our case, we have more time-flexibility in our current client project as it was done on a fixed-price bid. We're also at different stages of each project: one is firmly in implementation and the other is in leaving initial research and starting into business model iterations via customer development.

<comment><USER2> I've been doing consulting for a while. Not only on software, but on other industries.

I'm curious about your whole experience. It seems that you are a bunch of smart people cooking up an awesome startup. That's why I want to read more.

You mention doing a fixed-price bid project. Could you expand on that?

<comment><AUTHOR> I don't really adhere to the fixed vs variable pricing schemes too strongly, they are just trade-offs. In fixed-price, we're taking much of the implementation risk onto ourselves. In exchange, we ask for a stringent requirements phase and a little flexibility on delivery dates from our client.

Our sprints are basically at 2/3rds utilization and we've reserved the right to take a couple off-weeks between sprints over the course of a 4 month project. This gives us some strategic leverage in picking up attractive small projects so we don't have to completely close up. It also gives us the opportunity to do full sprints on our own product if our MVP tests, developed during the 2/3rd sprints, look good.

That being said, flexibility does not mean half-assed. We're doing our best work whether it be for our clients or our customers.

</comment></comment></comment></comment><comment><USER3> I like this article, but an important word that's missing from it is "demand". Consulting allows you to keep an eye on what the market wants.

On the flip side, building a product allows you, potentially, to deliver something that people don't even realize, yet, that they want.

Putting the two together: If you can abstract concepts from their material demands while delivering their material demands, you get paid to produce something that they want now and to learn what they might want that they don't even realize.

<comment><USER4> Exactly. The approach that my current employer used (that worked really well) was to start with consulting, find out what customers valued the most, and turn that into a product. This way they were profitable from day 1 and had absolute proof that the product would be successful before writing a line of code-pretty damn smart if you ask me.

</comment></comment><comment><USER5> i think it's great in theory, and it can work.

It just takes a lot more self control. It's too easy for the consulting side to take over, and it requires an iron will to prioritize that doesn't pay over work that does.</comment>


Ask HN: how many points do I need to be able to censor others people's headlines? - <AUTHOR>

My recent submission had a headline 'BBC fired respected scientist for denying man-made climate change'. It was censored by unknown editor to 'BBC ignored botanist for denying man-made climate change'.
The headline was not the best. It should have read 'banned' instead of 'fired', however anyone who has fired his lawyer would not be splitting hairs over the choice of words. The  essence of the matter was clear to anyone.
What amazes me is why people attack the choice of words or the messenger (a tabloid in this case) when they should be arguing with the article itself?
So how many points should I get on HN before I can go around amending other people headlines to suit my religious beliefs? <comment><USER2> It does not have to do with points. HN moderators can change titles.

They only change titles when they are inaccurate or misleading. That was clearly the least of the problems with the story considering it has been deaded.

<comment><AUTHOR> why?

<comment><USER2> Not sure which point you are asking that to, but I'll guess...

The reason inaccurate and misleading titles are some times changed are because people do not want inaccurate or misleading titles.

<comment><AUTHOR> No, I was not referring to the title. It was not be the best, but it was not misleading. Readers followed the link on the title, read the article and voted it up to the front page anyway.

Why to kill a front page thread with a lively discussion?

<comment><USER2> Users with sufficient karma flag problematic stories. It was the users that called it down.

<comment><AUTHOR> I'm not going to bore you to death with my questions so please you do not have to answer.

However, I am puzzled what was problematic with that story apart from that it challenged certain consensus scientific views (which was the reason for submitting it on Hackers News).</comment></comment></comment></comment></comment></comment>