A complete 4-year course plan for an AI undergraduate degree - <AUTHOR> https://www.mihaileric.com/posts/complete-artificial-intelligence-undergraduate-course-plan/ <comment><USER2> No surprise that this doesn't include any consideration for the profound moral, ethical, or social implications of AI and AI solutions.

Nothing about bias in models. Nothing about communication. Nothing about privacy. Nothing about security. Nothing about resiliency. Nothing about the responsibility of the individual practitioner. Nothing about the economic or ecological impact of the work.

Every undergraduate degree should include both general, and subject specific courses on ethics, morals, social, economic and ecological impacts.

<comment><USER3> > No surprise that this doesn't include any consideration for the profound > moral, ethical, or social implications of AI and AI solutions.

Would you say the same thing for an undergrad in SE (actually asking)? I feel like the hype train for AI has moved it into a plane where it has to be some moral arbiter but it seems to me that the same demands could be placed on most fields of study including general software engineering.

> Nothing about bias in models. Nothing about communication. Nothing about > privacy. Nothing about security. Nothing about resiliency. Nothing about the > responsibility of the individual practitioner. Nothing about the economic or > ecological impact of the work.

Maybe it is just my bubble but I feel like very few AI jobs actually deal with hot button ethics (facial recognition for dubious purposes etc). It is just that these fringes get all the attention as if they represent the broad community (they don't). For instance I work in AI for satellite communications, most of the things you bring up don't really apply (any more than they do to the software engineers I work with). My former work was in AI and computer vision in marine ecosystems. Again... your moral questions don't really apply (privacy of coral reefs?). I agree it is important to be aware of these issues but most of the real jobs in AI I feel like are more scientific in nature.. not the privacy busting, bias inducing ones we hear about a lot. Again that could be my bubble to some degree I suppose though.

<comment><USER2> I absolutely do. It's why I was so quick to jump on that with this.

My personal belief is that every undergraduate degree should include these subjects. That's what separates an undergraduate degree from a bootcamp--in theory.

But I think it's especially important for engineers and scientists, because it is very often overlooked or discounted by virtue of the fact that there's so much "technical" stuff to get into.

I think schools should try to counteract that by producing more team taught material. e.g., let's not just do a regularly philosophy course, let's do a philosophy for engineering and science course that takes you through the same general philosophy, but with readings that focus on engineering and science related ideas and themes.

But we should also have courses, and woven into our courses, discussions of these larger issues. Engineers, especially, have such a profound impact on society. It's important for us to be trained to think about these things. Not what to think, but that it is necessary to do so, and perhaps some tools and reference points for being able to do so in a cogent manner.

Lastly, I think it's important for undergraduates to get some exposure to the ethical issues related to work: the relationship between the employee and employer, the intellectual property, integrity in science and methods, etc.

<comment><USER4> "It's important for us to be trained to think about these things."

This doesn't seem self evident to me.

</comment></comment></comment></comment><comment><USER5> I love initiatives like this, but IMO if you're doing a self-study "degree" aimed at practical AI knowledge, I would:

* Drop the compilers and database courses.

* Add an intro to statistics course.

* Pick one domain, since you'll need deep, proven domain expertise in one area to get hired without a real degree. So doing both NLP and CV, for instance, is probably a bad choice if this is your endgame.

* If you choose CV, add a traditional image processing course. I don't recommend to rely on whatever happens to be included in the DL for CV course. You might also want to add a good general purpose DSP course.

* Substitute exams for projects. Exams are adversarial so they don't make sense to give to yourself. You'll learn more more doing a project than you would cramming for a fake exam.

* Try to finish the whole thing in 1.5 years, not 4. Spending 4 years on a practical curriculum that doesn't yield an actual degree is a huge waste of time. Try to get the theory out the way in a year and a half so you can jump into real life projects/research. With dedication and without a rigid university schedule that forces slow progress, this is completely doable.

<comment><USER6> Compilers may not be as relevant for AI-related work, but databases are, imho. So much of real world AI work is setting up data pipelines. Knowing how transactions, indexes, and joins work is very useful.

<comment><USER5> True

</comment></comment></comment><comment><USER7> This is missing a course on software testing, particularly one that has a focus on testing software-implemented models.

I'm almost done a PhD in mechanical engineering. Some CS folks have lamented gaps in my programming-related education, _but_ I actually did take an elective course on the reliability of science which included a lot on scientific software testing. I think such a class should be required for anyone working in theory or simulations.

In engineering, concerns about the testing and accuracy of a model are typically called "verification and validation". There unfortunately doesn't seem to be a standard curriculum for the subject yet but Wikipedia can give you an idea of what this covers and how it's different from general software testing: [https://en.wikipedia.org/wiki/Verification_and_validation_of...](https://en.wikipedia.org/wiki/Verification_and_validation_of_computer_simulation_models)

AI/ML seems to have their own culture around this and I'm not sure its actually rigorous. Seems to me that they could have their own version of the reproducibility crisis.

This course should be taken after a statistics course. Parts of it rely fairly heavily on statistics.

<comment><USER8> AI is having some reproducibility issues, especially reinforcement learning:

[https://www.wired.com/story/artificial-intelligence- confront...](https://www.wired.com/story/artificial-intelligence-confronts- reproducibility-crisis/)

In other areas of machine learning, things have gotten a lot better. A decade ago people rarely released their code or trained models. I did this for an early feature learning paper in 2010, which led to it getting a lot of citations.

What I'm more worried about is the lack of science in machine learning papers. The code reproduces the result, but the reasons for the efficacy given in the paper are spurious. I like this recent paper that pokes this issue in metric learning:

[https://arxiv.org/abs/2003.08505](https://arxiv.org/abs/2003.08505)

<comment><USER7> Thanks for the links.

I would consider the science issue you mention to be related. A lot of what was covered in the "verification, validation, and uncertainty quantification" course I took was basic science. The class wasn't only about software testing. Software testing was just a major tool covered in the class for the larger goal of making reliable scientific claims. What I wrote previously wasn't clear on this, so I clarified my previous comment on this point.

</comment></comment></comment><comment><USER9> I'm not seeing an actual statistics course in there. Also GOFAI techniques seem to be only briefly mentioned in an "Introduction to AI" course, which just doesn't cut it in my view - you'd need something like an Operations Research class to really explore that stuff in more detail. Some of the more focused CS content could be cut to make room for this; OS's and DB's has been mentioned already, but maybe one could also remove the Compilers course.

<comment><USER10> Yeah, I'd probably remove compilers, and add classes on statistics, experimentation and actual data analysis.

I kinda find it hilarious that there is no mention of analysing data in this course, given that that is a core skill that all data professionals actually need. I mean, where do they think the models come from?

There's also little to nothing about ETL, which is pretty much all you do in most data sciencey jobs.

I actually think that this course is pretty revealing of the worldview of a lot of AI researchers, and may be why predictions of AI's imminent dominance across multiple fields appear to be not particularly accurate.

<comment><USER9> > "There's also little to nothing about ETL, which is pretty much all you do > in most data sciencey jobs."

Maybe one could design a custom "Databases and ETL" class for this, to make it useful for more than just data-sciencey jobs. ETL is usually covered to some extent in stats classes though, AIUI.

</comment></comment></comment><comment><USER11> I think a lot more maths is needed. "CS109 Probability for Computer Scientists" does not look like a sufficiently deep study in statistics.

Spending time studying operating systems and compilers (both things I've studied) at the cost really submersing yourself in the maths of probability seems to me to be a misallocation of a scarce resource (time).

e.g. a course in Bayesian statistics, and also in traditional statistical inference would be useful (for instance, this gives a good foundation for understanding the EM algorithm.)

</comment><comment><USER12> I dont understand why

> Convolutional Neural Networks for Computer Vision

is taken without traditional CV before, while NLP it says "include traditional NLP". I'd say it is a big nono to jump in to CNN directly without some basic CV, even-though CNN is outperforming most algorithm you will miss big fundamentals.

Also most first/second year courses seems too CS focused, such as OS and Databases. I would remove those two things, add Differential Equation & Discrete mathematics (and numerical methods, maybe).

At best the over focus of general CS stuff seems to create "CS with some ML experience" rather than a solid foundation of the principles behind it.

This will give you a shoddy CS knowledge, and more fragile AI/ML understanding than someone with AI/ML background.

I would call this program "Data Science" but not AI.

Edit: removed "looks good" prefix after a second take at it.

<comment><USER13> The lack of statistical content disqualifies it for "Data Science" as well

</comment></comment><comment><USER14> This is a well written article and has really good courses and topics in it.

Cynically though, I wonder how many people of those who liked it and file it under "I should get to this at some point" actually use it at all. In AI it's been a cliche now how many introductory blog posts and into YouTube videos and "how do I start" Reddit and Quora questions there are. The resources and buzz is very high for the first steps. I guess it's similar to "how do I make a game" or "hó can I learn to hack" are popular.

As I said this one is very solid and has very actionable pointers to great courses. But I find that only a small minority of people are so obsessed that they can pull this huge project on their own. It's a multi-year undertaking and even though the resources are freely available, a normal homo sapiens just doesn't work like this. For all but the wild outliers (who would find the info anyway, with no Obstacle able to stop them), the context of a university program is really necessary. It gives you time, structure and social motivation, discussing with people in the same boat, helping them out, getting help from them, in person, being forced to chew through the boring bits, not getting satisfied with your own self assessment etc.

Otherwise I think this also just gets thrown onto the pile of bookmarks that we all build, to make ourselves feel good about a future day where we somehow magically motivated and sharp to tackle and learn all those things we bookmarked.

<comment><USER15> > "n AI it's been a cliche now how many introductory blog posts and into > YouTube videos and "how do I start""

one of the frustrating things its really hard to find great advanced content, and when you reach out to HN readers, they are like 'read really advanced PHD papers'. thats not what I mean at all >.<

<comment><USER14> There are textbooks, but people (myself included sometimes) want something flashier something more palatable. But other than conference talks and papers, textbooks and lecture slides, there just isn't much out there.

It's a consequence of how the sausage is made. Textbooks take years to write so only established topics can be included in them. Researchers are under time pressure and chase performance criteria. Publishing at a good conference pushes you along your PhD path, but writing a blog post for a niche advanced target audience of maybe 100 readers is not always worth it. Especially when you have other duties beyond research like teaching courses. Industry blog posts are good, but also cannot go very deep as the audience would be lost.

Also the nature of advanced stuff is that there is less of a clear established path forward. There are tons of small specialized communities that often don't know much about each other, they are in different departments etc.

Your best bet in becoming more advanced is to use the above mentioned resources and work with people who are more advanced than you, either in academia or industry. There is no law of nature that everything must be achievable by browsing the free internet without leaving the house.

An important lesson when you get to a point in your studies is that there is no set Platonic chapter-by-chapter structure in knowledge and science. A common failure mode is to think that learning is about leveling up in some achievement tree like in duolingo, and being puzzled where the next chapter is. You have to seek it out, tackle a practical problem either from your own idea and doing a side project or by joining a group as an assistant or a company as a junior engineer/data scientist.

A lot of it is "dark knowledge", hidden inside organizations, people learning from one another. There are best practices that "everyone" just knows to do by discussing by the coffee machine, it's not in any book or paper. And papers are written in an obtuse language to not give away too much (because that will be in the next paper).

The interests of an advanced practitioner reader are markedly different from the paper writer researcher's incentives, so this can make papers hard to read and decipher what to take away from them. The goal of a paper is to frame a small incremental tweak in the context of the larger scale literature in such a way that the reviewers are sufficiently impressed to click accept. Papers are obsessed with how they fit in the academic community's pursuit. They aren't tutorials or howtos or guides. Fortunately people are now releasing more and more code. The code is often more enlightening than the aggrandized math of the paper (which often boils down to few lines of code).

</comment></comment></comment><comment><USER16> More of a meta question: but why should all undergrad degrees be 4 years? Why should an undergrad in computer science and one in AI be the same length of time?

Was it created because a school wants to charge the same amount regardless of major? Or because 4 years is an acceptable proportion of a human life to spend studying to obtain a white collar job half a century ago? Or some other reason?

(Related, why do people want the 4 year degree as a pre-requisite for most jobs? Why do some jobs -- law and medicine -- require 3 and 4 year degrees on top of it? Why is the CFA happy with 3 years of tests on your own time?)

<comment><USER17> It's probably a combination of all your questions. Simpler fee structure that takes a standardized part of young adulthood that provides a standardized amount of expertise, leading to "an undergraduate degree" denoting a certain amount of breadth and depth. It's about what a typical college student can learn in four years.

Some fields like law and medicine require more time to get practically useful, like 7ish years for law, which we can break down into units of 4 + 3, an undergraduate degree and a law doctorate (JD). Or medicine, which takes like 15 years, and is split into 4 + 4 + 3-5 + 1-4, an undergrad degree, a medical doctorate (MD), a residency, and a fellowship.

Maybe splitting it into these points helps standardize those and provide convenient points where paths split.

</comment></comment><comment><USER18> This seems optimized for AI in the hyped sense (as shorthand for applied machine learning and data science) rather than actually preparing a student to contribute to "real" AI (see work of Josh Tenenbaum or Brenden Lake). For an undergrad curriculum for the latter, I'd expect to see more on understanding intelligence in extant biological systems, eg courses in cognitive science, neuroscience, child cognitive development, and more background on animal cognition. I would also expect to see more robotics and at least some treatment of reinforcement learning.

<comment><USER19> I would also move up the second year "intro to AI" course to the first year, with an emphasis on history. You shouldn't be hearing about AI Winter for the first time after already spending a year on the subject.

</comment></comment><comment><USER20> This is a course plan for computer science. I don't see why Artificial Intelligence should have its own "degree". However, there is a trend towards these niche degrees at universities too.

<comment><USER21> We have never considered splitting medical school into subdomains at undergraduate level. Why are we trying to do this now for Computer Science?

<comment> barry-cotter Dentists, nurses, physiotherapists and physicians are all degree level medical specialties. Engineering is split. What's the argument against doing it for medicine other than tradition?

<comment><USER22> > Engineering is split. What's the argument against doing it for medicine > other than tradition?

One might argue medicine _is_ a split-off piece from natural sciences.

A counter-argument might be that while the natural sciences are almost always split, where they aren't, such as at Cambridge, medicine is still of course separate.

I think the real reason is probably just that there's more value to most medicos in a whole-body understanding than there is to most engineers in a multi-disciplinary understanding.

I'd quite like to need to routinely design electronic circuits, CAD/CAM packaging for them with certain mechanical constraints, and develop software to run on them in my work, but I don't; that'd need to be a _very_ small company working on a physical product for that not to be at least two people's jobs.

<comment><USER23> I feel that mechanical engineers should have a bit of understanding about what is going on behind the scenes when they click on things in a CAD package.

From talking to recent students and current professors, I'm not sure they are learning this as part of a degree course.

<comment><USER22> By 'behind the scenes' do you mean the physical objects that they're modelling, or how the software works?

<comment><USER23> I mean the kind of data structures that the software is operating on, in particular the ones that can end up in an exported file.

</comment></comment></comment></comment></comment></comment></comment><comment><USER24> There's a lot of weird choices here. The lack of math/stats is glaring, the inclusion of compilers seems to be at the cost of more relevant material for someone focusing on AI (speaking as someone who studied CS with a specific focus on PL/Compiler type things). You don't just throw project based in at the end (this should be through the entire degree), and there's two systems/OS courses included but no networking?

Generally I think having an AI degree is fine, but at the end of the day its a CS degree + a concentration no matter how you slice it. This isn't like CS splitting from math, etc.

</comment><comment><USER25> I find it pity that while "Compilers" course is always about _implementing_ compilers, "Databases" courses are 99% about _using_ database systems.

<comment><USER26> I never really though of that, but that's pretty true. I guess that using a compiler is generally a lot simpler than using a database. When using a compiler, the majority of the time you're doing something really simple compilation, or you have a build system take care of the entire thing, where as the database requires design considerations. That would be my guess at least.

But I do agree that a database implementation course would be fantastic. It's one of the most important categories of software today for sure, up there with operating systems and compilers. My Uni was going to offer a course this Fall, but COVID has led to it being delayed. Here's to hoping it's offered in the Spring.

<comment><USER20> I would argue that the "using a compiler"-class would be the programming class!

</comment></comment></comment><comment><USER27> God the CS field is really getting muddied by AI hype. Please for the love of god start with the fundamentals.

</comment><comment><USER28> 4 year degrees in AI already exist.

Here is Edinburgh: [https://www.ed.ac.uk/studying/undergraduate/2020/degrees/ind...](https://www.ed.ac.uk/studying/undergraduate/2020/degrees/index.php?action=programme&code=G700)

Here is CMU: [https://www.cs.cmu.edu/bs-in-artificial- intelligence](https://www.cs.cmu.edu/bs-in-artificial-intelligence)

I think the above degrees are more balanced than OP's proposal. More emphasis on foundations, and courses on ethics. Operating systems and compilers are useful if you go into AI engineering but are a diversion from core AI topics.

<comment><USER29> But are they free? I think that's OP's point.

<comment><USER28> I don't think that is the case. I just clicked a random course in their curriculum (Convex Optimization) and it links to a Stanford course that requires a login to access the videos.

</comment></comment></comment><comment><USER30> Yeah, that's not what my 4 year AI curriculum looked like. Mine focused more on Expert Systems. Also more logic, more software engineering, more psychology and philosophy. But much less algebra and calculus, less computer systems and parallel computing (though I took them as elective), no compilers (I don't really see the need either, though it's an interesting subject), and clearly not enough machine learning.

I also would have liked to see more robotics. Our neighbouring university had an AI curriculum that focused more on robotics.

If I could design a curriculum like this, I'd keep the focus on software engineering and logic that we had (maybe a bit less logic than we had; they were overdoing it), keep algorithms, keep some philosophy and psychology, but make them more focused on our field and include things about social impact and ethics. Definitely more linear algebra and calculus, some statistics, machine learning, and get some basics for vision processing. After the first two years, you'd get to choose between more focus on vision and robotics, or more focus on logic, statistics and expert systems. Machine learning should be included in both.

</comment><comment><USER8> I actually was on a committee to do this for a university. Ultimately, some believed it would take resources away from computer science and compete with the program, so it was a year of work without anything to show for it.

I'm still a proponent of undergraduate AI degrees, but this proposal doesn't suffice. Deployment, testing, dataset collecting, statistics, more math, better organization of electives (computer vision, robotics, NLP as applied electives), bias mitigation, ethics, and more need a role. The state and university guidelines also provide a lot of constraints. I do think that a research or applied project is essential, which is captured in this proposal.

I'd definitely remove operating systems and compilers. I took both courses at the graduate level and have been working in basic and applied AI research for 15+ years, and those courses haven't helped me with that.

</comment><comment><USER17> An AI degree that doesn't teach anything about learning about the real world from data (the stats that scientists get) seems really weird, even if that does seem to be the state of things. AI is about learning and decisionmaking, and the learning side is currently pretty heavy on the pattern recognition side, but why bake that into the education? You can't teach someone to automate learning without teaching them to learn the old fashioned way. There's a reason basic statistical inference and experimental design is such a foundation for every scientific field, but it's always missing in these AI progressions. It's sure as hell present in the jobs people going through these degrees will probably end up in.

</comment><comment><USER31> So, people are just supposed to _start_ their 4-year undergraduate degree in Linear Algebra? I know HNers are rare air, so to speak, but what about Calc 1-3 and Diff Eq?

This is like a 4 year plan once your first two years of university are under your belt.

So a combined CS / MS in AI?

<comment><USER9> Linear Algebra is quite self-contained. You'd need Calculus in there to really make sense of the probability and stats, though. Not sure about the vector calculus part and diffeq's, maybe that can be cut and the whole thing might fit in 4 years.

<comment><USER31> I just can't see how a single self-contained Linear Algebra course could in any way prepare one for the actual data science behind AI and ML. But your point is well taken otherwise.

Edit: Reviewing Bretscher (Linear Algebra with Applications, 5th), it appears you are correct; it's not until you study the applications that you need Calculus. Most Unis I'm familiar with, however, will require multivariable (Calc 3) at least as a pre-req for Linear Algebra.

</comment></comment></comment><comment><USER32> Reading the comments in this thread, I am surprised to see that many think it lacks math. I am majoring in applied math (all my professors are french-school mathematicians, in a non american university) but I deem my courses excessively theoretical. It doesn't help that the degree is 6 years long.

In the meantime I've been solving coding problems but still feel like I lack something in order to make working AI programs. Maybe someone can tell me if the non-math courses listed there are more than enough for a person like me to get into AI.

If you're curious about my background, feel free to ask.

</comment><comment><USER33> Lots of suggestions about math, ethics, SWE; I'd suggest some biology. Especially biology of sensory systems. Both for some understanding of the systems that already solve these AI problems really well, and for better understanding of human interface requirements: what do we really hear and see in these AI-generated stimuli.

</comment><comment><USER34> Why no 3 month bootcamp?

</comment><comment><USER35> This also seems to be missing any coursework outside of CS/Math.

People certainly disagree about the overall value of general education requirements, but a writing course, even a technical one, would fit nicely here. No point in doing amazing work if you can't tell people about it, after all.

</comment><comment><USER36> The proposed curriculum looks very similar to a computer science curriculum w/ an AI minor/specialization. I'm curious why a student would opt for a specialized AI curriculum rather than a broader CS one? Wouldn't the CS provide more options down the road?

</comment><comment><USER37> For comparision, here is the AI bachelor degree from JKU Linz: [https://studienhandbuch.jku.at/curr/714](https://studienhandbuch.jku.at/curr/714)

<comment><USER38> It's good that it includes an AI and Society course.

</comment></comment><comment><USER39> Professor and curriculum engineer here who has created an undergraduate degree in CS/IT. Proof: ([https://www.rtc.edu/net-arch](https://www.rtc.edu/net- arch))

First off, this is a great starting point! There is a goal for every year, the courses clearly build upon each other, and there is an end-goal. I am a big advocate for project-based learning, and I'm seeing more employers seriously consider portfolios like GitHub and blogs. No employer cares that you got a 103% on your algorithms exam, and few vaguely care about your GPA. They do care if you can hold a conversation about a topic. They do care if you applied the knowledge, like building something that uses a tree, even if you didn't explicitly write all the data structure code yourself.

This curriculum is designed for the elite, think a student that would do well at Stanford. This is probably an obvious comment, as the majority of courses come from Stanford, but it's important to note that the breakneck speed of this curriculum targets the top 1-5% percentile of students. If our hypothetical freshman is a high school graduate they need to have done well on the BC Calculus, AP Statistics, and AP Computer Science exams at minimum. It also assumes that the student has enough computer experience to pick up advanced skills rapidly. You could argue that "Introduction to Computer Systems" and "Programming Fundamentals" are entry level, but reading carefully they are closer to the 2nd or 3rd CS course a student would take in a normal sequence. Week 2 in the programming fundamentals talks about Stacks and Queues, and Week 1 in Intro to Computer Systems introduces Unix, the CLI, and GitHub all in one week. These are very advanced topics for students that come in with 0 knowledge. You will need either rigorous admissions requirements, or prepare for a high first-year drop out rate.

We tried a 4th year very similar to what was described in the article. Students could pick a final project done in partnership with industry, or report on their internship/career if they were already in one. Students responded with "What do I need to do to get full credit?", "Can you give me step-by-step instructions that I can follow?", and "What will be on the exam?" (there are no exams in the program after year 2). After 3 years of being explicitly told what they must do to succeed, students have correctly learned that going above and beyond in a class rarely yields extrinsic benefit within the scope of a class. To put it another way, students are trained to work efficiently in a classroom environment, "Exactly as hard as I need to get the exact grade I want, and not 1% more." It's not necessarily a bad mindset, but we need to train students out of habits that are bad if applied outside of the classroom. In the case of my program, we chose to set a bar in the 4th year but didn't tell students how high to jump. This translates to removing a lot of clarity in assignment rubrics, and providing direction but not answers. A lot of students flailed, but none failed (yet!). Graduates report a smoother transition into industry. We also introduced GitHub in their third year as a portfolio tool, few students have enough knowledge to understand and use it before then. At the end of every quarter students build a final project in groups, and apply all of the skills that go into a good repository (collaborators, pull requests, readmes, CI, etc.). While not all employers are looking at the actual projects, all students who have graduated thus far have said they used the knowledge of talking about a project in interviews. On the internship/project classes/research front, unless you are using your reputation to open those doors for students (as I had to), a student's best chance of arbitrary contribution is through GitHub Issues and PRs. Your college's reputation is also a major factor here; In the case of my specific college, Amazon Web Services won't work with us because of a teaching agreement that went sour before I was hired.

Some critiques from others I'd like to comment on, in lieu of the author: "Why isn't there core class X?" \- Most students can't handle more than 2 core classes per quarter. That means 24 core classes over a 4 year period. Choose wisely. I think the author chose well, but no plan survives it's first encounter. My curriculum certainly didn't, and 3 years in we've thrown out almost all of the curriculum we initially wrote.

"No ethics, soft skills?" \- This is a core class curriculum. Electives and additional classes for "rounding out" a student occur during at a later phase of curriculum design, usually when it's time to meet accreditation standards. From there you will not like the second part of this answer. In my 3 year study on building an IT bachelor's ([https://www.nsf.gov/awardsearch/showAward?AWD_ID=1601140](https://www.nsf.gov/awardsearch/showAward?AWD_ID=1601140)), we found ethics training to work AGAINST a student's hiring prospects (cue pitchforks). Our Business and Industry Leadership Team (representatives from technology companies) rated "teaching ethics" at an average of 2.1/5 (A 2 means slight disagree that this should be taught). They marked "ethical knowledge application" at 1.4/5 (A 1 means strongly disagree that this is important). The BILT team commented that they were unlikely to listen to a recent graduate's ethical concerns on a project, they would regard a graduate raising the concerns as a 'nuisance', and that they would fire the graduate if their ethical concerns significantly impacted their job performance (cue more pitchforks). Finally, consider the fresh graduate's perspective. The typical first-job-out-of-college mindset is "I have a ton of debt. I'll take the first job with the largest salary." I see this advice regularly on HN.

</comment><comment><USER40> I think CMU's 15-213 is better than Stanford's CS107.

</comment><comment><USER41> I'd like to see a similar one for computer science

<comment><USER31> If you are serious, pick an institution and view any of their ABET accredited programs. Look for Computer Science or Computer Engineering and then go to the University to view the curriculum: [https://www.abet.org/](https://www.abet.org/)

<comment><USER35> I would not rely on ABET for this.

Stanford, CMU, Yale, Cornell, Columbia, and Princeton aren't ABET accredited. Devry Tech is, but I still think you should give Stanford and CMU a second look.

</comment></comment></comment><comment><USER42> Machine learning is not AI, but a part of it.</comment>


The first smart trench coat - <AUTHOR> http://www.motiif.us/

<comment><USER2> Interesting. I'd like more technical details to be more up front - right now it seems like more of a high-end "this coat looks awesome and has awesome abstract technology built in to make you feel awesome" thing.

From what I can gather: it's a decent looking coat with a Karma wifi hotspot and battery backup in the pocket.

How much will wifi cost per month? Does it operate under the standard Karma deal where you get 100MB free when other people use it?

Is the coat washable? Do I have to go through a complicated process to get the electronics out before I wash it?

Is there an advantage to having this built into a coat vs. carrying a Karma hotspot in my pocket or laptop bag? Does the coat solar charge the battery?</comment>


Fundable is back up? - <AUTHOR> http://www.fundable.com/

<comment><USER2> Oh, yeah, that little episode really inspires confidence in a financial service.

Seriously, take it down until you sort out your issues, guys.

<comment><USER3> FAQ - Q - What happens if the co-founders have a major spat over ownership rights and coding bugs?

A - We'll announce it to the world, have a fight behind closed doors, and re- open several days later as if nothing had happened. Hopefully, most of your pledges won't even notice and it will be business as usual.

<comment><USER4> My apologies if I'm stating the obvious, but this funny Q&A is not actually present in <http://www.fundable.com/static/faq/> . It might have been a lighthearted way to acknowledge the troubles and say they're back at it.

It appears they are simply in full denial.

</comment></comment></comment><comment><USER5> They're dead. They might as well rename the site to 'unfundable', anybody that puts their money in the hands of a bunch of trustees that present themselves as hysterical infighting hissies has only themselves to blame.

Pay out, shut down. Those are the two things left in the history of 'fundable'.

</comment><comment><USER6> Lot's of comments here are saying fundable is dead, but I don't think so. The web is big. Lots of bad things have happened to plenty of sites and they remain up and viable. I think we over-estimate the memory of the average internet user.

There are probably lots of fundable users now who don't know what just happened and there are countless more in the future who will never know.

This incident is really nothing major. Ford Motors built and released cars they _knew_ were going to blow up and kill people and look at them today. People still buy Fords.

Do you really think some little founder spat that changed the home page for a couple days is going to destroy fundable? No way.

</comment><comment><USER7> It should be interesting to see how they recover from this. I would have expected some sort of rebranding effort and to have them 301 fundable.com to the new site.

Even without the ridiculous public drama of last week, they could have used an overhaul of their image.

</comment><comment><USER8> Haha... Who is going to trust them after all this

<comment><USER9> Unfortunately most people coming across there website would be none the wiser.

<comment><USER8> I am sure it'll always come up in the search results...

</comment></comment></comment><comment><USER10> Louis must have got his domain back.

<comment><USER5> Registrant:

John Pratt

       ATTN: FUNDABLE.COM

       c/o Network Solutions

       P.O. Box 447

       Herndon, VA.  20172-0447

<comment><USER10> you think John let the site go back up?

<comment><USER5> What I think isn't really relevant, that's just speculation and I hate to speculate.

Maybe they kissed and made up, maybe they want to sell the site to some sucker that might think it has value after all this, I haven't a clue.

Mail him and ask ?

</comment></comment></comment></comment><comment><USER11> viral marketing at its finest.

1) Create a trauma 2) get two posts on HN 3) ??? 4) Profit

</comment><comment><USER12> I imagine that legal (and police) pressure was brought to bear, given the quoted content of some of the emails sent to customers.</comment>


Spotify remove 'hate conduct' policy following backlash - <AUTHOR> https://www.bbc.co.uk/news/newsbeat-44341720 <comment><USER2> As the "public square" becomes increasingly dominated by internet platforms, we will have to rethink what the preservation of free speech requires.

People who support internet censorship stand on the legal ground that internet companies are private companies and as such can do what they want.

But, at least in America, the sanctity of free speech in the abstract "public square" of life takes precedence over the agency of business to do what it wants.

A business cannot (barring libel and similar edge cases) obstruct people from sharing their views in the public square, and similarly they should not be allowed to restrict the speech - or - content shared by individuals - or - creators online, provided that speech or content is legal, because the internet behemoths - are - the public square.</comment>


Besides Musk, Bezos and Gates, who are other smart entrepreneurs? - <AUTHOR> https://capitalandgrowth.org/questions/2323/besides-elon-musk-jeff-bezos-and-bill-gates-who-ar.html <comment><USER2> George Hotz of comma.ai is a rising star in the self-driving car industry.</comment>


Report: Uber CEO's Group Trip to Escort Bar Made Female Employee 'Feel Horrible' - <AUTHOR> http://gizmodo.com/report-uber-ceos-group-trip-to-escort-bar-made-female-1793639349 <comment><USER2> Sorry as much as I hate Uber in principle and culture, this is a complete non story.

<comment><USER3> One doesn't want to see one's superiors participating in ritual dehumanization, regardless of the rest of the context.</comment></comment>


Review of Nestle water permit neglected for decades - <AUTHOR> http://www.desertsun.com/story/news/environment/2015/07/23/review-nestle-water-permit-neglected-decades/30562241/ <comment><USER2> >But the agency's records clearly show that efforts to review the permit were initiated between 1999 and 2003. Then those efforts suddenly stopped, and nothing in the records indicates exactly why.

>Gene Zimmerman, the forest supervisor who was in charge at the time, retired in 2005. He now does paid consulting work for Nestle.

>Zimmerman has said he doesn't see any conflict in working for Nestle in his retirement.

I wonder if he sees any conflict working for Nestle before retirement.

<comment><USER3> People often express opinions like yours when talking about any subject that has to do with the government. Where does this inherent distrust come from?

Is it really so weird that a company would hire someone with intimate knowledge of a system in order to help navigate that system? This type of hiring occurs all the time, it literally has a name in the tech community - "acquihire". Do you find acquihires just as distasteful and filled with conflicts of interest?

Why do you doubt Zimmerman due to his current relation to Nestle but not Loe and Earney due to their current relation to the conservation movement? Surely, Zimmerman's position as forest supervisor actually makes him more credible than a biologist and a permit administrator?

<comment><USER4> contrary to what abduhl wrote in his statement asking where the distrust comes from, I find myself thinking the exact opposite:

where does our inherent trust to government come from? When I work with you I have to prove that I'm trustworthy. That happens either through working together or by you looking at my track record on github, mailing lists or whatever else.

Yet, when it comes to government officials no such thing applies. We trust them based on the fact that they supposedly work for government and therefore are supposedly trustworthy. But their track record generally shows the exact opposite.

And yet when I come home in a perfectly safe, good area of London, if I want something from my neighbour, I have to wait for her to open her 10 locks and open a tiny bit of the door to hear her ask what I want from her.

The only reason I see that speaks for them is the appeal to authority. We trust them, because we trust that an authority that has more power than we do is more trustworthy than us and by extension anyone appointed by them is as well.

<comment><USER5> _Yet, when it comes to government officials no such thing applies._

No. Government positions are subject to various oversights. Much of the role of democratic forms of government _are_ precisely that oversight. Though yes, it's quite often very imperfect.

Elections, FOIA requests, investigative journalism, lawsuits, review by other branches (e.g., state of county/municipal, federal of state/local), accounting/accountability offices (GAO for the US federal government), etc.

<comment><USER6> People realize that oversight is a public aspect of most government activity, but they also see that the rules of oversight are created by government and that those who make the rules tend to occupy privileged positions and receive large donations from powerful parties who have an interest in influencing those rules. So while the ideal government is self-governing, there's a perceived lack of that quality.

<comment><USER5> As I noted, the oversight isn't limited to government.

And _removing_ government doesn't _improve_ oversight.

<comment><USER7> It also doesn't imply it works or cant be gamed.

</comment></comment></comment></comment></comment></comment></comment><comment><USER8> As the article mentions, the USFS is underfunded and understaffed. As a result, (and as is also the case with USFWS and NMFS), permit related matters are often "triaged" with items having a low percieved environmental impact (or politically risky, or risk an expensive lawsuit) put off so that limited resources can be spent on more pressing matters.

That doesn't mean corruption and regulatory capture aren't issues, but they aren't a complete (or even major) part of the problem.

I guess also it doesn't bother me too much if drinking water is being extracted from a national forest as these forests are required by statute to be managed for multiple uses including resource extraction. Relatively speaking, siphoning off water for drinking seems like it is likely to be a relatively low impact activity, even when it's a bigevilcorporation like Nestle who is doing the extraction.

<comment><USER9> As gets mentioned basically every time this comes up, Nestle's total water consumption in California last year was approximately equal to the amount of water used by two golf courses. California has around 1200, with over 100 in desert regions.

Of course, as the California Golf Course Superintendents Association is quick to point out, parks and golf courses combined use up only 1% of potable water in California. They like to point the fingers at almond growers, which consume about a gallon per nut. Almond growers note that an ounce of lentils takes 71 gallons, and an ounce of beef 106 gallons. Farmers in general blame housing. And so on.

Vanity fair did a somewhat amusing chart about the blame game: [http://www.vanityfair.com/culture/2015/04/california- drought...](http://www.vanityfair.com/culture/2015/04/california-drought- shaming-diagrammed)

(Note: Take all the numbers with a grain of salt; they're self-serving press releases, if not outright lies. Even so, it's pretty clear Nestle's not to blame for California's water problems; whether their usage is the 0.008% of total California water use the company claims or, hell, ten times that, it's not a big deal.)

<comment><USER10> Taking these numbers with a grain of salt is only going to exacerbate the situation.

<comment><USER9> Wondered if anyone would make that joke. ;)

</comment></comment></comment></comment><comment><USER11> In BC Canada Nestle is also causing a stink over water use but it's not why you think.

NAFTA says that once bulk sales of water begin it that's it Pandora's Box can't be shut.

People in BC and Canada are worried if Nestle is charge even a small amount that will be seen as a bulk sale of water and then that's it game over the US will demand we sell water to the dry western states.

Sure it isn't exporting it but it is the sale of water to a corporation and it is the water not the service to deliver the water, but that all may be step one to exporting it.

<comment><USER12> that only happens because they also have the few politics that care about environment in the pay roll. i mean, they donate to campaign...

nobody cares or win elections with water rights. so it's very cheap to lobby that area. nobody cares!

this excuse about the mass sale is nonsense. several countries have limits on number of wells someone/company can have and limits on water extraction. it's freaking simple.

</comment></comment><comment><USER13> Any article about corporate consumption of public water in California feels a little silly without reference to San Francisco's $30k/year right to Hetch Hetchy. Yosemite Valley's neighboring valley, on a national park that every American pays for, is flooded and destroyed and San Francisco doesn't even pay enough to even cover the human maintenance of the land, let alone the benefit they get from the water.

</comment><comment><USER14> Here in BC Canada, nestle has been tapping our natural water resources for free. They have been tapping a well in hope bc

Our government in turn setup a deal where nestle pays $2.25 CAD per million litres of water they extract starting in 2016.

They took 265 million litres last year, what a farce, they will only by charged about 600$ a year at the new price... Better than nothing but still... I pay out of my ass for water.

Nestle in turn sells bottled water for about $1 to $3 per litre...

Recent article on the matter: [http://www.cbc.ca/m/news/canada/british- columbia/nestlé-b-c-...](http://www.cbc.ca/m/news/canada/british- columbia/nestlé-b-c-water-deal-too-cheap-says-ndp-1.2964709)

<comment><USER15> _I pay out of my ass for water_

You pay for _treated_ water. If you dig a hole in the ground you'll get untreated water for free.

<comment><USER16> There is a subtle difference between hole in the ground in any place and a [http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRS...](http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=165.110&SearchTerm=spring%20water%20nomenclature)

</comment></comment></comment><comment><USER17> I have hiked up in these mountains and seen some of the springs Arrowhead uses to get its water from. The ones I have seen are small pipes running from small springs, taking a small amount of the spring water. The San Bernardino mountains are next to LA. I am not an expert, but I don't think a large amount of water is used by anyone from these mountains. The US Forest Service probably just thinks it is an insignificant amount of the total water supply to pay tons of money to experts to come up with the required bureaucratic report. It really wasn't until the media starting referring to Arrowhead Mountain water company as "Nestle" that it started getting any coverage.

<comment><USER18> I'm curious how much water they actually take down the mountain (especially since I believe they have another well down the hill in San Bernardino... or "San Bernadino" as the article says half a dozen times). Even if it isn't much, it is _seems_ silly since the communities up there have to import water from elsewhere, and a big part of the cost of doing that is pumping the water up to an elevation of ~1 mile.

That said, you're probably right that they're sending down a negligible amount of water, especially compared to what the water agencies up there pump locally or even compared to the declining water levels of the lakes in Arrowhead and Big Bear

</comment></comment><comment><USER19> I think if funding is an issue, they should simply shut Nestle's operations down.. their permit is expired, period... if they want a new permit, part of that deal would they should have to fund said impact study. It's really not a difficult problem with a difficult solution here.

It's pretty obviously a combination of apathy and corruption.

<comment><USER20> Especially considering Nestlé's resources. It's not like you are taking away a permit from a local community cooperative or something like that.

</comment></comment><comment><USER21> ''The answer to 99 out of 100 questions is money.''

<comment><USER22> I think you have your numbers backwards.

</comment></comment><comment><USER23> A couple of things all the 'experts' in how the government works here seem to have overlooked-

1) 'Quid pro quo' is a lot harder than it seems- it requires Zimmerman to commit a crime, then trust that Nestle will take care of him after. This is pretty rare.

2) Zimmerman does have value to Nestle, though, in the form of knowledge of USFS processes, like the renewal process. If he weren't hired by Nestle I'm sure he would be hired by another company for this knowledge.

3) If any corruption did occur, it was probably in the form of one of Nestle's senators tapping the shoulder of the director of the USFS, leading to direct or indirect pressure to not review the permits. This could be very subtle (i.e. budget is cut, word comes down from on high that something else is highest priority, and if it ain't broke don't fix it).

</comment><comment><USER24> Here's an idea: You cannot take material gain that would have been illegal in your employ for 2x your time of employ, or four years, whichever is longer.

> Gene Zimmerman, the forest supervisor who was in charge at the time, retired > in 2005. He now does paid consulting work for Nestle.

</comment><comment><USER25> I'd like to use this precedent to drive with an expired driving license. It's discriminatory to allow some parties to continue engaging in licensed activity while penalizing others for "the same conduct."

</comment><comment><USER26> Government agencies have a tendancy to be incentivized to pick on small guys who are easier/simpler to harass. The beurocrat gets the same amount of credit for closing a small case as closing a lrage complicated case. For example this article cites the forest service reviewing water permits for a couple of small cabins and requiring them to install tanks at a substantial cost instead of going after Nestle who is pumping 10's of millions of gallons a year.

</comment><comment><USER27> It's amazing to watch one of the most sprawled-out car cultures I've ever experienced bogeyman water bottling and almond production for their CO2-powered drought. Absolutely amazing.

</comment><comment><USER28> Government failed us yet again. Remind me, why am I being forced to pay 30-35% of my paycheck to these idiots taking payouts and working like fat slugs off my dollar? This is why the climate is so screwed up. Government isn't responsive. You have to make industry pay true cost for use of finite resources. Similar to taxing the finite capacity of the atmosphere to absorb greenhouse gases. Externalities should be priced in economics. Duh? You build a model to computer GDP but you don't take off future survival. Then what is growth but short winded elations. Anthropocene needs to wise up before sixth extinction sets us free, brutally.

<comment><USER5> Funny, and here I sit thinking that it's a case of business corrupting government, for its own ends.

<comment><USER29> To be fair, this should be a prime example of a case where free market types AND those that believe in strong public protection of resources can agree that it stinks. There can be no libertarian defense of this behavior. It is a corrupted government process keeping a company from paying the true market price for the resources it is using. All actors in this case are warping the process for the enrichment of the company and lining the pockets of a few key players.

Also, pulling water out of a desert watershed, trucking it up to Canada, to ship it back down to the US to sell in little plastic bottles is the height of corporate capitalist insanity.

<comment><USER5> That's why I align myself with neither side strongly. There are balances of power and checks required. On the market, on business and monied interests, on government (and various branches, agencies, etc.).

Almost like an engineering problem where you want to ensure no one process overwhelms all others.

</comment></comment></comment></comment><comment><USER30> Heh. Once the TPP comes into effect, Nestle will be able to sue the USFS for "loss of future projected revenue" if they ever actually enforce the contract end date.

</comment><comment><USER31> > A pipe running from the top of the San Bernardino mountains carries mountain > spring water to Nestle North America's tanks below where its then > transported to Ontario for bottling.

wait, let me get this straight: a pipe runs from the top of the San Bernardio mountains carying moutain spring water to tanks below where it's transported for bottling?!?!?!

( _joke /sarcasm_) That line is pasted like 5 or 6 times as the tagline for most the images in the article. Talk about repetitive!

</comment><comment><USER32> I commenced my boycott of Nestle products the very same day their head honcho asserted that water is not a human right. There are many other good reason not to purchase Nestle's wares it's just that that single statement drove home my understanding that Nestle employers and stockholders are notorious criminals.

My boycott is difficult not just because I enjoy many Nestle products but because it is not always easy to determine what products Nestle actually makes. I have learned to read product labels very very carefully.

Many fine foods and beverages that were once prepared by other, independent businesses that are now Nestle subsidiaries. Even if Nestle does not own the manufacture it distributes their products.

Just for grins, read the ingredients from a few Nestle foods soldin the United States, fly to Geneva then read the ingredients of their Swiss products. One of the greatest scams in all of human history resulted in American children drinking nonfat milk.

Here in Vancouver I drink "Swiss Chocolate Milk", made in the United States b Alpenrose with whole milk.

For a parent to feed their children nonfat milk is child abuse.

<comment><USER33> Alpenrose Swiss Chocolate Mile is re-run milk, which is to say unsold expired milk that's repasturized and sweetened.

<comment><USER34> This couldn't be further from the truth. The production manager at Alpenrose dairy was contacted about the ingredients in Alpenrose Swiss Chocolate milk and the main ingredients are: Fresh wholesome Milk, Cream, Sugar and Cocoa.

</comment></comment></comment><comment><USER35> Forget it Jake, it's Chinatown [1]

[1]: [https://en.m.wikipedia.org/wiki/Cadillac_Desert](https://en.m.wikipedia.org/wiki/Cadillac_Desert)</comment>


First time entrepreneurs have 18% chance of success; 2nd time entrepreneurs: 30% - <AUTHOR> http://hbswk.hbs.edu/item/6045.html <comment><USER2> Misleading title. From the very first sentence:

"All else equal, a venture-capital-backed entrepreneur who starts a company that goes public has a 30 percent chance of succeeding in his or her next venture. First-time entrepreneurs, on the other hand, have only an 18 percent chance of succeeding, and entrepreneurs who previously failed have a 20 percent chance of succeeding"

<comment><USER3> "a venture-capital-backed entrepreneur who starts a company that goes public"

There's, like, four total people in the world who match that description in web-based companies over the past few years.

</comment></comment><comment><USER4> They use a strange metric for success, in that the company has to go public. I'd say a good acquisition is clearly also a "success". Assuming that far fewer companies go public than are acquired (and make the founders wealthy), their numbers are quite a bit low.

At any rate, those numbers are already HUGELY higher than I had thought.

<comment><USER5> I think issuing dividends on a consistent basis (applies to public & private companies) & total profitability is a better measure of success than going public or getting acquired. The latter two rely too much on someone else.

</comment></comment><comment><USER6> Entrepreneurs who sit on their asses and never take a shot have a 0% chance of success. Ignore the stats. Take your shot.

</comment><comment><USER7> Lies, damn lies, and Harvard Business School statistics.

<comment><USER8> Its science!

</comment></comment><comment><USER9> I submitted this a day ago:

<http://news.ycombinator.com/item?id=384801>

</comment><comment><USER10> There was a paper by the National Bureau of Economic Research from back in 2006 that had a similar study and findings. I dug through it and brought out the relevant parts (relevant to me at least) here:

[http://www.sanjayparekh.com/skill-versus-luck-in- entrepreneu...](http://www.sanjayparekh.com/skill-versus-luck-in- entrepreneurship-and-venture-capital/)

</comment><comment><USER11> Web startups, 60% of the time they work every time!

<comment><USER12> I was going to go with 99% of the time they never generate enough revenue to cover their costs, but each to their own I suppose.

</comment></comment><comment><USER13> Which means if you dedicate yourself to starting two businesses you have a 57% chance of succeeding at least once.

<comment><USER14> Ok, I have no idea how you came up with 57%. Even if you add 18%+30% (which is not mathematically valid) you'd only get 48%. How in the world did you get 57%?!

The real probability based on the article (according to my calculations) is 34.4%, which is actually much better than I would have guessed.

Here is how I came up with that.

The article states a first time entrepreneur succeeds at an 18% rate. And someone succeeds at a 20% rate given they failed the first time.

P(First Time Success) = .18

P(First Time Failure) = .82

P(Success | First Time Failure) = .20

P(Second Time Success) = P(Success | First Time Failure) x P(First Time Failure) + P(First Time Success)

0.344 = .18 + (.82 * .20)

In words: 18 percent of entrepreneurs will succeed on their first try. 82 percent will fail. Of that 82 percent that failed, if they try again, they will succeed 20 percent of the time. To get a number from the original population of first time attempts you have to multiply the 82 percent who failed by the 20 percent who succeeded on the second try which results in 16.4%. That 16.4% is the percentage of the original population who tried on the first try but did not succeed until the second try. The end result being 34.4% of the original population will be successful on their first _or_ second try.

Hopefully that makes sense.

* edit to format the formulas a little better</comment></comment>


GPT-3: Response to Philosophers - <AUTHOR> https://drive.google.com/file/d/1B-OymgKE1dRkBcJ7fVhTs9hNqx1IuUyW/view <comment><AUTHOR> The PDF is taken from this tweet thread: [https://twitter.com/raphamilliere/status/1289129723310886912](https://twitter.com/raphamilliere/status/1289129723310886912)</comment>


Ask HN: Who's using Facebook login on their site? (Is it necessary now?) - <AUTHOR>

Hi HN,
I'm thinking of adding Facebook logins to my site; however, they apparently require me to link it up to my personal FB account (or at least, want my credit card/mobile number).
Has anyone added FB logins to their site and tracked how many people use it? I'm trying to decide if this is something I need to do. <comment><USER2> I added it a while back to my startup's site (<http://collegejobconnect.com>) and used my college email address that was already on file to get my api key.

Depending on what language your site is coded in, it's not terribly difficult to integrate and gives another way for potential customers, users, etc. to access any "registered users only" sections ... you can also pull a lot of data out of the open graph api if need be. Documentation is not great, but there enough tutorials out there should you get stuck (or just ping me).

</comment><comment><USER3> What do you mean? In order to get a facebook api key, you have to have created an app as a facebook user.

<comment><AUTHOR> To create an app as a facebook user, you need to give them either a college email address, a mobile number, or a credit card. Otherwise facebook connect, and enabling people to login to your site through facebook, is not possible.</comment></comment>


Is NordVPN a Honeypot? - <AUTHOR> http://vpnscam.com/is-nordvpn-a-honeypot/ <comment><USER2> A corporate VPN makes sense.

Using an untrusted VPN to do something like tunnel an HTTPS connection to get around geo-blocking makes sense.

Using a paid VPN to protect ones privacy, has never made any sense to me. The vast majority of those companies I've seen are sketchy as can be. A VPN is just about perfectly situated to track users - possibly better than even the ISP since the VPN provider doesn't have to contend with a NAT device obscuring the number of actual users. Combine that opportunity, with the fact that many VPN providers have minimal name recognition - in case of bad press, spend $10 on a new domain name - and are competing on price with what appear must be small margins. What would really surprise me would be a report that proved that the vast majority of paid VPN providers aren't up to some funny business. Yet, someone VPNs have a reputation of being a mechanism to protect privacy.

<comment><USER3> >Combine that opportunity, with the fact that many VPN providers have minimal name recognition - in case of bad press, spend $10 on a new domain name

meanwhile, if comcast/spectrum is injecting ads or monetizing your browsing history, you have no recourse. what are you going to do, switch ISPs?

<comment><USER4> The problem here is a lack of critical mass. IME, most people don't care about any of this. I recently tried to explain to my classmates why "free" apps are typically not free; they basically got mad @ me for doing so. And this, is generally _factored into a business model_ by anyone slightly scrupulous.

So, and I've not done this myself (yet), the options are: lower your standards to those of the unwashed masses; or 2) become the service provider yourself (hopefully w/ a group of like-minded individuals).

Of course, #2 will be somewhat difficult because there's a lot behind-the- scenes non-technical stuff that goes into 1) forming and sustaining a company; and 2) bringing a thriving product to market.

That said, you could try to fork #2, and instead of bringing your solution to the broad market, roll fight-club style and hope that obscurity guarantees its security/functionality. This, truthfully, is probably the best and most feasible option for the avg. person/people. (Sadly)

</comment></comment></comment><comment><USER5> I think his evidence for being a honeypot is speculative at best. The more likely explanation is that it's simply a mediocre VPN service bolstered by fake reviews and marketing money. Snake oil is so much cheaper to produce than something actually nefarious.

<comment><USER4> While you are correct that the "evidence" is speculative, I've long thought that the seemingly coordinated push to get avg. people to use VPNs was suspicious. Additionally, when I articles and comments rationalizing why one company is better than another, I see a lot of holes in what's said. For example, people don't seem to understand that registering (basing) a company in one place _doesn 't preclude it from operating elsewhere_.

Another thing, most people, including me, don't know who the owners and operators of these companies are. I see lots of comments about wanting to avoid gov't surveillance and the like, but w/o knowing the deets on the owners and operators, people could be just making the surveillance easier; same is to be said for those trying to avoid giving the data to their ISP (maybe the ISP owns all or a stake in one's VPN).

So, I think that RR's advice in one of his/her articles about avoiding all of them is probably fair, although considered impractical for the average person @ this point.

<comment><USER2> Genuinely curious - how is it hard to avoid a VPN? Can't you just not use one?

<comment><USER4> Well, to clarify, I'm referring to RR's advice not to use any of the consumer- level services. And since, as far as I know, they are all fee-based 'tools', I don't see why one can't not use them.

As always, I'm happy to have someone correct any flaws in either of my posts here.

</comment></comment></comment></comment><comment><USER3> >Here is a honeypot VPN would do. Does NordVPN Meet Every Checkpoint?

>Need a BIG Company to Back it Up

I'm not sure why that's a requisite for a honeypot. Why contract a company to do it rather than doing it in-house? It's one more loose end to take care of and one more source for leaks.

> "Fake" Product Consumers Want

> Invest Into Product to make Good Honeypot

it's consistent with the fact it's a honeypot, but it's also equally consistent with the fact that it's a business that wants to grow by any means necessary. besides, I'm seeing plenty of nordvpn advertisements on mainstream youtube channels, and according to this article, CNN. if nordvpn is a honeypot, who is their audience? you're probably going to end up with 90% squeaky clean people (in terms of online activity), and 10% weed buyers.

>Use "Security" Features to Gather Data

this is nonsensical as well. why go about this in a detectable way (kill switch failing all the time), when you can passively monitor the connection (very easy to make it 100% undetectable), then follow up using parallel construction?

</comment><comment><USER6> They get a fairly crappy review, including being awarded the "Shady" badge, at "That One Privacy Site", which I have trusted for years.

[https://thatoneprivacysite.net/2016/09/03/nordvpn- review/](https://thatoneprivacysite.net/2016/09/03/nordvpn-review/)

</comment><comment><USER7> I wish there were some independent organizations, with the trust and respect that organizations like the EFF and ACLU have earned, that would regularly audit services like VPNs, Duck Duck Go, FastMail, and ProtonMail to make sure that they're really respecting privacy.

<comment><USER6> For VPN and email, I really like "that one privacy site": [https://thatoneprivacysite.net/](https://thatoneprivacysite.net/)

<comment><USER8> No PIA review/mention, though. They are a big provider.

I used to be on NordVPN but after two years they went south. Very happy with PIA today (I just need to appear in another country, so no fancy or serious (personal safety) needs)

<comment><USER6> No PIA review, but they do appear on the comparison chart. [https://thatoneprivacysite.net/vpn-comparison- chart/](https://thatoneprivacysite.net/vpn-comparison-chart/)

<comment><USER8> Thanks, I missed that big list.

There was also a guy who compiled a very comprehensive list of VPNs (with plenty of interesting information) but I cannot locate it right now (I remember it was in a Google Spreadsheets document)

<comment><USER6> That's the same guy!

<comment><USER8> Ah, cool then, thanks! I liked his work a lot and his data helped me to choose my first VPN (which, incidentally, was NordVPN)

</comment></comment></comment></comment></comment></comment></comment><comment><USER9> This Jobs' quote makes sense, but I don't think it is applicable in the sense that the article used it for, as it's nowhere near monopoly:

"When you have a monopoly on the market, it's not the product people that make the company make more money. It's the sales and marketing people that get promoted, and they end up running the company. The product people get driven out of the decisions, and the company forgets what it means to make great products. The people running these companies have no conception of a good product between a bad product. They have no feeling in their hearts for wanting to help the customers."

</comment><comment><USER10> I've seen the same advertising uptick in the Dashlane Password Manager. But looking at google trends may just be me [https://trends.google.com/trends/explore?date=today%205-y&q=...](https://trends.google.com/trends/explore?date=today%205-y&q=Dashlane,Nordvpn)

</comment><comment><USER11> I'm actually going to work on the NordVPN project in a month or so.

As far as I know and from what I've seen I can tell you that its a legit company with legit products and is only aiming to do good. It was started by two friends, without any investors and to this day it still is absolutely independent and run by the same two guys

</comment><comment><USER12> What a content free pile of speculation.</comment>


What Would Be on Your List of Teach Yourself Software Engineering? - <AUTHOR> I really enjoy Teach Yourself Computer Science[1]
 and I would like to know what would be on your list (books and topics) for Software Engineering.<p>1. https://teachyourselfcs.com/ <comment><USER2> One of the most important skills to develop is the practice of breaking up chunks of work into smaller pieces (and completing them) so that progress can be made on what initially appears to be an insurmountable and abstract problem.

<comment><USER3> nice

</comment></comment><comment><USER4> In my experience most of computer science is about being clever.

ubiquitous artificial general intelligence is for me the obvious contemporary north star.

the problem is that an approach to AGI has yet to be discovered so any content regarding implementing AGI from current literature should be allowed into the conscience with caution.

the solution is to recognize that however implemented the AGI mind will mirror our human mind insomuch as it will be created by other human minds

Therefor a productive question is: how does my mind work? and investigate this question sincerely using your inner voice to map the properties of a thought

then you can endeavor to confidently implement an AGI knowing that whatever content you encounter was developed from an environment similar to the one your inner voice finds itself in.

The key insight to acquire is that the quality of your system will be tied to the quality of inner voice dialogue you have with your self not the quality of books/papers published by others

</comment><comment><USER5> Eloquent JS is a decent starting point. W3 schools is even better.

But nothing will ever beat opening up notepad++ and making a one file html/css/js website of your own and having to research how to implement every idea in your head!

</comment><comment><USER6> Oh i thought this was an actual question and not spam.

Brand new account, one post....

<comment><AUTHOR> THis is an actual question and not spam. I am not sure how can this be considered spam. I am not affiliated with the website above, I thought it was quite famous; I believe I discovered it on HN.

</comment></comment><comment><USER7> Buy a Raspberry Pi, build a bootable SD card, then teach yourself some system management basics (shell, init, filesystem, etc.)</comment>


What is the easiest lifehack? The word "No" - <AUTHOR> https://medium.com/@davedri/say-no-cdb948a74382#.dqsqatuhx <comment><USER2> "After a time," said old Mathers disregarding me, "I mercifully perceived the errors of my ways and the unhappy destination I would reach unless I mended them. I retired from the world in order to try to comprehend it and to find out why it becomes more unsavoury as the years accumulate on a man's body. What do you think I discovered at the end of my meditations?"

I felt pleased again. He was now questioning me.

"What?"

"That No is a better word than Yes," he replied.

― Flann O'Brien, The Third Policeman</comment>


2048 in Augmented Reality - <AUTHOR> http://quentin.bonnard.eu/2048/

<comment><USER2> It gave me two sevens. They combined to make a nine.

<comment><USER3> That's Numberwang!</comment></comment>