Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence - <AUTHOR> https://www.cs.cmu.edu/news/carnegie-mellon-launches-undergraduate-degree-artificial-intelligence <comment><USER4> I really do not like this move. AI and Machine Learning require graduate-level mathematical and computational skills. I don't think it's productive to pretend that we can train someone to be even remotely useful in these fields in four years of an undergraduate education. It sounds like an attempt to get around the fundamentals of csci to "skip to the interesting bits," which will produce graduates with a cursory knowledge of computers, programming, math, and data science, which is honestly worse than no knowledge at all.

I'm not fundamentally opposed, but I think this is akin to creating a "Condensed Matter and Nanophysics" undergraduate degree alongside "Physics."

Changing the name of a factory will not change the output. The only solution to creating more and better AI research is to invest in better fundamentals in computer science and mathematics, then create pipelines for specialization. Slow and low.

<comment><USER5> This is a lie that I hear a lot from AI/ML experts. To me it reeks of gatekeeping. Yes the foundations of the field and many of the breakthroughs require this knowledge, but one can be a very effective practicioner of AI/ML techniques with a few years of undergraduate level instruction. And given how many industries are kicking the tires of AI/ML, we're going to need hordes of practicioners.

<comment><USER6> I can't create a new programming language that compiles to machine code. Maybe I shouldn't be programming?

I don't see why you need to be a domain expert of the low level details to make a career out of something so useful.

<comment><USER7> I don't see why you would need a graduate degree to create a new PL that compiles to machine code. In fact, many successful PL designers lack PhDs.

Most work in CS feeds more on experience than education. A PhD is simply a way of getting deep experience (and advice) in areas that a job probably wouldn't allow for. Since ML is hot, you can get hands on experience with it these days, its not like 10 years ago when the only people looking at deep learning were pretty much researchers, PhDs, and PhD students.

</comment></comment></comment></comment><comment><USER8> If you are an undergraduate in computer science these days, it is very hard to get into advanced AI/ML classes, which are typically reserved for graduate students. Back before the ML goldrush, a strong CS undergrad interested in AI could elect to take advanced coursework beyond the introductory AI class. Nowadays, good luck getting off the waitlist! Having an official "AI major" does at least tell students, "Hey, we are making it a priority that undergraduates have access to our rich AI curriculum."

<comment><USER9> While there may be a lot of demand for AI/ML, I'm concerned to whether there are enough students with the proper foundations in math and stats to do well. New classes such as Data Science seem to just instruct students how to use algorithms and not why.

<comment><USER10> Are you talking about undergraduate courses, or non-accredited certificate courses? We've had stuff like A+ / Cisco / Java certifications for decades. They fill an important niche, but they aren't how industry leaders are trained.

<comment><USER9> Only referring to my experience as an undergrad: most students seemed to be turned away by the mathematics.

</comment></comment></comment></comment><comment><USER11> So much negativity on this discussion. I'm very surprised to see this from the HN crowd. Guess what? Computer Science, Engineering, etc... is getting more complicated and complex. So seeing a discipline (assuming this is CS) get broken down into more distinct groupings is actually a good phenomenon. Of course there's always foundational knowledge that is important to learn - <USER2> with time I feel like that information becomes de-emphasized to focus on higher-levels of understanding and knowledge.

On another note, CMU was always very good at cross-disciplinary studies. (Building Virtual Worlds comes to mind). As the article points out, this new degree bridges over to the humanities and ethics. With where we are today with AI, isn't it a good thing to train the AI developers of the future to think about the implications of their work?

<comment><USER12> I just hope that they still include software engineering etc. I've interviewed many "AI specialists" who probably know AI pretty well (I'm not qualified to make that judgement) but they can't code their way out of a paper bag. Basic data structure errors, terrible organization, etc.

<comment><USER13> Internships work wonders here. No amount of coursework can substitute for doing the real thing. IMO internship placement, not coursework, will _always_ be the best way to solve this problem.

</comment></comment></comment><comment><USER14> Carnegie Mellon was the first university to offer a PhD in Machine Learning (via the Machine Learning Department which, again, I think is relatively unique in its existence). Regardless of how you feel about the hype, they made an early bet on the field and adding an undergraduate degree seems consistent.

Source: [https://www.ml.cmu.edu/about/index.html](https://www.ml.cmu.edu/about/index.html)

<comment><USER15> What I don't yet understand is how this new AI program differs from machine learning. Is AI about broader questions about conversational interactions and interpretability, closer to the Lisp heydays of 5 decades ago, or more about applications than theory?

Edit: years to decades

<comment><USER16> From the article:

> The bachelor's degree in AI will focus more on how complex inputs — such as > vision, language and huge databases — are used to make decisions or enhance > human capabilities

My understanding is that AI is more about applying ML concepts to mimic human intelligence.

</comment></comment></comment><comment><USER17> This seems like a publicity stunt. It sounds like a CS degree where the electives are predetermined. Why couldn't they just make this a concentration when it's so intimately intertwined with CS.

The extra overhead graduates will have to deal with doesn't seem worth it.

"AI majors will receive the same solid grounding in computer science and math courses as other computer science students. In addition, they will have additional course work in AI-related subjects such as statistics and probability, computational modeling, machine learning, and symbolic computation."

They even say "other computer science students".

<comment><USER18> Well, that's basically what Computer Science degrees started out as, right? An Electrical Engineering degree with a bunch of software related electives? Even now, at UC Berkeley for example, "EE/CS" majors can choose a set of courses that end up almost exactly matching what the "CS" majors take, with not necessarily more EE. It's really just a narrowing of the electives.

There are enough AI related courses available now at many schools that it seems useful to separate "more general Computer Science" from "a focus on Artificial Intelligence", and similarly I think there's room for a separate major in "Software Engineering" as opposed to theoretical computer science.

<comment><USER19> For me this just looks equivalent to adding a new major for every sub field of electrical engineering. Signal processing, digital circuits, analog circuits ... truth is a CS major could go take the same classes and a computer engineering student could also.

<comment><USER18> I think there's just a (subjective) point where a field is different enough that it's worth distinguishing from the rest. I could see Signal Processing being a different major than Electrical Engineering, and digital circuits is basically Computer Engineering.

</comment></comment></comment></comment><comment><USER20> I think I now know how the electrical engineers felt in the '50s and '60s.

<comment><USER21> What do you mean?

<comment><USER22> I think he's referencing the beginning of "Computer Science" degrees. Computers were researched by electrical engineers and mathematicians before.

<comment><USER23> Yes. My undergraduate diploma says "Electrical Engineering - <USER3> Science". Computer science wasn't a full department yet.

<comment><USER24> Mine says "Linguistics". I took CS graduate courses, but there wasn't an undergraduate major yet.

My father-in-law had a math degree and was a math professor, and then an EE professor — the latter while he co-founded an AI lab, that hired physics major Richard Stallman and other non-CS-majors.

</comment></comment></comment></comment></comment><comment><USER25> This feels like a more useful CS degree, IMO. I don't do anything like machine learning, but for both scaling backend services and building day-to-day business logic, I've gotten a ton of value out of knowing stats, logistics, and a certain amount of pattern recognition (ah, how terms go in and out of fashion). Take this stuff instead of the other sorts of electives I was picking from - UML Modeling, for instance - and I think you'll be set up with a good broad base for understanding both code and machine learning applications, but also broader decision-making at a business level.

<comment><USER26> You had a whole class dedicated to UML Modeling? That makes me laugh, I know it gets very complicated in high level java applications, but man that feels like a waste of time.

<comment><USER25> In theory it was "system design" or somesuch.

In practice we learned nothing particularly useful what to take into account when deciding where to draw boundaries, and just focused on what was easy to represent in UML.

</comment></comment></comment><comment><USER27> Personally, I find the lack of _logic_ programming, and logic in general, a rather notable property of the outlined curriculum. In fact, "logic" is nowhere explicitly mentioned in the course titles. Neither are "formal" and "method".

For comparison, at the department of AI in Edinburgh, Prolog was very important and even actively developed to such an extent that current Prolog systems are still hugely influenced by "Edinburgh Prolog" (the original version being "Marseille Prolog"). Also, theorem proving is an important area of computer science with many connections to AI.

In Vienna (TU Wien), the related _Computational Intelligence_ curriculum also involves a lot of logic, Prolog, constraint solving and formal methods, which play an important role in many areas of AI. It is a graduate degree though and assumes familiarity with many of the topics that are mentioned in this curriculum.

<comment><USER28> >Also, theorem proving is an important area of computer science with many connections to AI.

I think this is only true if you use a different definition of AI than the one likely used here. Expert systems aren't considered to be very effective tools for useful "AI" anymore. You can't define a procedure to recognize a happy face in logic programming, at least not with any degree of efficiency.

<comment><USER29> Is recognizing happy faces the only use for AI? Who redefined AI to solely mean Machine Learning and excluded everything else that defined it before the AI winter?

<comment><USER28> No, but if you want to solve certain useful problems, ml works and expert systems don't. That's what I was getting at.

</comment></comment></comment></comment><comment><USER30> University of Toronto Engineering also is starting a Machine Intelligence option:

Engineering Science - Machine Intelligence Option

[http://engsci.utoronto.ca/explore_our_program/majors/machine...](http://engsci.utoronto.ca/explore_our_program/majors/machine- intelligence/)

What is the difference between the Machine Intelligence major in Engineering Science, and an undergraduate degree in Computer Science?

While there are some commonalities between the Machine Intelligence major and what is offered through Computer Science, engineering offers a unique perspective.

First, graduates will have a systems perspective on machine intelligence, which integrates computer hardware and software with mathematics and reasoning. This enables a focus on algorithm development and the relationship between machine intelligence with computer architecture and digital signal processing.

Secondly, graduates will benefit from an approach that encourages problem framing and design thinking. Design thinking is a method for the practical and creative resolution of problems, which encourages divergent thinking to ideate many solutions, and convergent thinking to realize the best one. Students will be able to frame and solve problems in the MI field, and apply MI tools to problems in many application areas. These include finance, education, advanced manufacturing, healthcare and transportation. This field is in a phase of rapid development, and engineers are well equipped to contribute as a shaping force.

<comment><USER31> I got my BSc at U of T, in Artificial Intelligence (and Cognitive Science)... in 2006. So ahead of the curve! This was right before the big deep learning explosion, at the very end of the last AI winter. Our lecturers spent a whole lot of time lamenting at the endless disappointments of AI research. I walked away deeply skeptical, and can't help but see the current ML hype as a glass half empty.

<comment><USER32> I'm currently about to enter my freshman year of College, and have been looking at majoring in Cognitive Science. What were your thoughts on it/it's applicability to the rest of your life?

<comment><USER31> I think it very much depends on where you're doing it. There are many approaches to cog sci, so your experience will likely be different depending on your profs, their schools of thought, and the kind of research being done at your institution. U of T at the time was dominated by people doing work in embodied cognition (e.g. Evan Thompson), neo-continentalism / phenomenology, philosophy of mind, and a few dynamical systems people. I very much enjoyed it, but I later learned that this was a rather unorthodox take on cognitive science, not at all representative of how things are done elsewhere. I'd stay away from programs too rooted in more traditional experimental cognitive psychology, or developmental psychology. To me this seems incredibly dry, but I guess it depends on your own personal proclivities.

</comment></comment></comment></comment><comment><USER33> My undergraduate degree (from The University of Edinburgh) is Artificial Intelligence. I remember when I was visiting different universities in the UK back in 2000, Edinburgh was the only one I saw which offered AI as a "real" degree. Everywhere else it was a specialization which was tacked on in the final year of a computer science degree.

That seemed really odd to me then. Seems even odder now.

<comment><USER34> I'm curious to hear about your experience. In my mind, artificial intelligence can't be separated from computer science. In fact, I feel like you need a full Comp Sci degree before you can effectively apply your skills to real world AI challenges.

<comment><USER35> I am currently studying this degree at the same university. A few AI concepts (NLP and Formal Language Processing) are introduced in the 2nd year. Other than that, all courses are CS/Maths. Keep in mind that at Scottish Universities, students apply directly to their degree and besides one or two courses per year (some like Medicine or Law often have no electives), students take only courses within their degree. This way, with most AI courses in 3rd and 4th year, students tend to have a strong enough grounding in CS principles and Maths for this material. That's not to say that the degree is perfect, or providing "real/production" AI, but it is certainly well done.

You can see the courses here - [http://www.drps.ed.ac.uk/18-19/dpt/utaintl.htm](http://www.drps.ed.ac.uk/18-19/dpt/utaintl.htm)

<comment><USER33> Oh cool, what year are you in?

If it's 3rd or 4th I was one of the judges at your systems design practical.

</comment></comment></comment></comment><comment><USER28> This looks good (which shouldn't be surprising coming from CMU). I'm kind of impressed by how similar this was to my undergrad curriculum (focusing on AI/ML and CS theory). Looks like a fun program.

Also wow, Great Theoretical Ideas in Computer Science[1] is a hell of a course. Induction, DFAs, matchings, TMs, complexity, NP, approximation and randomization, Transducers, crypto, and quantum algos. That's a lot of material, even if most of it appears to be only introductory level.

[1]: [https://www.cs.cmu.edu/~15251/schedule.html](https://www.cs.cmu.edu/~15251/schedule.html)

<comment><USER36> yeah, it's rather notorious at CMU for being particularly challenging and fast-paced, especially for a freshman course. sometimes called "two-fifty- fun"!

<comment><USER37> I'm getting a panic attack just reminiscing about it.

213 and 251, the twin terrors.

</comment></comment></comment><comment><USER38> Do you call this Artificial Intelligence?

I dont call this AI, I call this automation.

I know AI is a buzzword, but unless something is trying to think, its not AI to me.

What they are talking about seems to be automation through lots of code.

But hey, I havent been keeping up with this field, not sure what people are calling this.

<comment><USER39> > additional course work in AI-related subjects such as statistics and > probability, computational modeling, machine learning, and symbolic > computation

How is this automation and not AI?

<comment><USER40> To me "AI" means it learns _by itself_. Including the decision what to learn, and how. Having done quite a bit of statistics courses over the last few years (albeit with a focus on medicine/biology) and some of free the basic machine learning courses, AFAICS that is not the case, what and how something is learned is all decided and done by the human(s) in front of the computer, no? So, I don't see much "intelligence" \- in the machine. Lots of it in those humans, of course.

<comment><USER41> > To me "AI" means it learns by itself

Your definition doesn't match the real definition. Technically, a hard coded rule-based decision algorithm is a form of very basic AI. You seem to be confusing ML and AI- ML is a subset of AI that focuses on _training_ a complex model.

<comment><USER40> No I'm not confused, as I said, I took the courses. I know what _is_. I'm just saying that I don't see this as "AI" at all and why. I don't really care that someone decided to define what is possible now as "AI" for whatever reason because I don't agree and don't see that as reasonable. It's not like those "definitions" are laws either, ask around, even among professionals, and you get as many different definitions as you want. Therefore I prefer to use a "common sense expectation/interpretation" approach, and "common sense" here to me means coming from above (where we want to go), not from below (what we have thus far achieved).

</comment></comment></comment></comment></comment><comment><USER42> "AI majors will receive the same solid grounding in computer science and math courses as other computer science students. In addition, they will have additional course work in AI-related subjects such as statistics and probability, computational modeling, machine learning, and symbolic computation."

<comment><USER43> And it will still look less beneficial than a standard comp Sci degree unfortunately. The only good part is that the school is pretty prestigious, so not as bad. Hopefully we don't have another AI winter.

</comment></comment><comment><USER44> For those who don't want to click through all the links, here is the syllabus:

[https://www.cs.cmu.edu/bs-in-artificial- intelligence/curricu...](https://www.cs.cmu.edu/bs-in-artificial- intelligence/curriculum)

It seems reasonable to me. They are required to take 7 humanities courses. I certainly hope they are required to take a lot of other classes where they are required to read, reason, and write.

</comment><comment><USER45> I think if this is more the fundamentals for AI rather than "this is all you will ever need to know", in other words NOT vocational, then this makes a lot of sense. When I started counting off the prerequisites to know what you are doing in ML, I could see it filling up a few years of coursework. Calculus up to multivariate calculus (gradient descent), a semester or two of statistics (gotta understand precision / recall, expectation, moments, marginalization), some programming (how are you going to implement your solution?), the fundamentals of regression (overfitting, cross-validation, regularization), don't forget linear algebra. Then there's some prerequisites for unsupervised learning like expectation maximization. SVMs? You'll be needing some constrained optimization and some applied math to make/understand a reasonable solver. This seems like the greater part of an undergrad degree.

</comment><comment><USER46> A long long time ago, I got a Bachelors degree in Logic and Computation, with a specialization in Computational Linguistics from the Humanities and Social Sciences Department at Carnegie Mellon. Seemed to be the closest thing to an "AI" degree on offer at the time, from my undergrad perspective.

<comment><USER47> As of recently, CMU had a Human-Computer Interaction track, which I know a lot of HSS students took.

<comment><USER36> There's an entire second major (and minor) in HCI, now :-)

</comment></comment></comment><comment><USER48> Seems like the university put a decent amount of thought into the program. I wonder whose brainchild this was, and pushed for it to be its own degree?

Regardless, even if a student no longer decides to pursue AI research or employment after graduation, they still have a marketable skillset for a variety of jobs.

<comment><USER18> So others can also see the thought they put into the program, here's the actual curriculum:

[https://www.cs.cmu.edu/bs-in-artificial- intelligence/curricu...](https://www.cs.cmu.edu/bs-in-artificial- intelligence/curriculum)

<comment><USER49> Thanks. I was wondering about that. Do you know, by chance, what books or notes they might use?

<comment><USER18> I'm starting with gathering the book requirements for some of the electives which might be of interest to me...

For 85-712 COGNITIVE MODELING:

How Can the Human Mind Occur in the Physical Universe? 2009 Author: Anderson, John

ANSI Common Lisp 1996 Author: Graham, Paul

For 85-211 COGNITIVE PSYCH:

Cognitive Psychology and Its Implications 7TH 10 Author: Anderson, John

For 85-814 COGNITIVE NEUROSCIENCE:

No books listed.

For 85-421 LANGUAGE AND THOUGHT:

Language in Mind: An Introduction to Psycholinguistics 2014 Author: Sedivy, Julie

I'll update this with more books shortly.

For 15-386 Neural Computation:

From course website: [http://www.cnbc.cmu.edu/~tai/nc17.html](http://www.cnbc.cmu.edu/~tai/nc17.html) Trappenberg T.P. (TTP) Fundamentals of computational neuroscience, 2nd edition, Oxford University Press 2009 (required/recommended). Hertz J, Krogh A, Palmer RG (HKP) Introduction to the theory of neural computation., Addison Wesley 1991 (reference).

For 15-150: Principles of Functional Computation:

From course website [http://www.cs.cmu.edu/~15150/](http://www.cs.cmu.edu/~15150/) There is no required textbook for the course. All material we expect you to be familiar with will be covered in sufficient detail in the lectures and lecture notes. There is an optional (and free!) text which some students find useful, called Programming In Standard ML (PSML). This book is based on the lecture notes for the predecessor to this course, 15-212.

For CS 15-122: Principles of Imperative Computation:

[http://www.cs.cmu.edu/~15122/syllabus.shtml](http://www.cs.cmu.edu/~15122/syllabus.shtml) No textbook, but uses C, Emacs, Linux.

For 15-381: Introduction to AI Representation and Problem Solving:

Artificial Intelligence: A Modern Approach, Third Edition (Typical at most schools for teaching Intro to AI/ML.)

For 10-401: Introduction to Machine Learning

Machine Learning, Tom Mitchell. (optional) Pattern Recognition and Machine Learning, Christopher Bishop. (optional) Machine Learning: A Probabilistic Perspective, Kevin P. Murphy, available online, (optional)

</comment></comment></comment></comment><comment><USER50> That... is a cool degree name.

Still waiting for CMU to launch an Undergraduate Degree in Digital Currency, though.

<comment><USER51> lol. Undergraduate Degree in what-so-ever-buzzwords.

</comment></comment><comment> a-dub I think you can make this degree out of the standard electives offered in any good CS program, although the courses at CMU are more likely to be _great_ rather than just good.

To me it was just "the cool CS electives that you get to do if you get all the math, stats and signal processing down pat."

Sad news is that the fields that make up these interesting classes are things that people do PhDs in, so unless you get a PhD you're unlikely to get anyone to pay you to do them when you're done and will get stuck making the help button for the Google Cloud for Education Administrators Console anyway...

<comment><USER10> The help button for the Google Cloud for Education Administrators Console is made by PhDs.

</comment></comment><comment><USER52> I think its interesting that Deep Learning is just one course in a cluster of electives. To read recent press you might think that's all current AI is.

</comment><comment><USER53> Related: China has just published the first AI textbook for high-school students.

[http://www.scmp.com/tech/china-tech/article/2144396/china- lo...](http://www.scmp.com/tech/china-tech/article/2144396/china-looks-school- kids-win-global-ai-race)

</comment><comment><USER54> My degree was in Computer Science & Artificial Intelligence way back in 1998 at the University of Birmingham (UK) - interesting to see not that many places offered it until recently.

Good to see that other undergrads are going to have access to AI/ML courses rather than them being solely for post grads.

</comment><comment><USER55> In Fall 2007, USF (CA) CS program allowed me to take a Grad AI course as an undergrad. However, my coursework was graded differently ss an undergrad. I had a blast taking it, learned alot but I can say the requirements to get in depth with the material require a graduate program.

</comment><comment><USER56> I feel like i would rather be going into a DS interview as a CS grad with ML/AI experience than as an AI grad.

Maybe i'm wrong here, but our biggest painpoint hiring for our datascience team is lack of dev skills. Simple stuff like deploying a model to heroku & or writing tests

</comment><comment><USER57> Interestingly, I majored in Artificial Intelligence for my undergraduate degree, which has been a thing in the Netherlands for thirty years now. Vastly different scope, probably, but still interesting - I believe there are si universities here offering the program.

</comment><comment><USER58> What's most interesting about this list are the wide range of courses offered for undergrads in the topic (that is, assuming they are regularly offered) -- a very impressive list. Other schools will be hard-pressed to offer something so diverse and interesting.

</comment><comment><USER59> What did they call it before? As the article mentions, CMU has been doing AI for a long time.

<comment><USER60> We never had a differentiated "AI" _undergraduate_ major before. A student who wanted to concentrate on AI/ML would have used their electives to synthesize something they liked. The CS curriculum is:

[https://csd.cs.cmu.edu/academic/undergraduate/bachelors- curr...](https://csd.cs.cmu.edu/academic/undergraduate/bachelors-curriculum- admitted-2017)

So that student would pick AI-ish classes using their applications elective and two CS electives.

In contrast, the AI curriculum:

[https://www.cs.cmu.edu/bs-in-artificial- intelligence/curricu...](https://www.cs.cmu.edu/bs-in-artificial- intelligence/curriculum)

Removes several of the required courses from the CS curriculum (such as the upper-division systems requirement - OS/networking/distributed systems and the logic & languages requirement), adds another required math course (modern regression), and then uses the space from those freed-up courses to add a bit more depth in the AI core. It also shifts the set of available electives towards a more stats/ML/AI-centric group.

It's not a _huge_ change from our CS curriculum, but it's one that lets AI/ML- interested undergrads create something that's more stats-heavy and deeper in AI than they would have been able to with the CS version. Keep in mind this is all still within the school of computer science.

This doesn't change things at the masters and Ph.D. level.

<comment><USER61> As a CMU BS-CS graduate myself, the most obvious and startling shift is no OS or networking requirement. That alone makes it "not the Computer Science undergrad track" as far as I'm concerned.

(Not to mention the notable lack of the utterly gigantic forest of higher- level discrete math concepts and programming language theory. Were I in a place to re-do an undergraduate career, this would have been very appealing to me relative to what CMU offered).

</comment></comment></comment><comment><USER26> I love the ethics requirements. My current uni doesn't have this and I'm so glad I took it at the college I attended as an underclassmen. The different ethical theories apply so well to a lot of work being done in computer science.

<comment><USER8> My traditional CS curriculum had ethics as the capstone. Do most CS programs not do this?

<comment><USER61> I do not think they do.

</comment></comment></comment><comment><USER62> In general, I'd say why even have a separate degree, but it makes sense for CMU with their rich AI history with the Robotics Institute. They probably have a lot of opportunities that could fill an entire major.

</comment><comment><USER63> Looking at the course list ([https://www.cs.cmu.edu/bs-in-artificial- intelligence/curricu...](https://www.cs.cmu.edu/bs-in-artificial- intelligence/curriculum)), I'd struggle to believe that students are going to come out of this strong enough to be effective in AI. I never went to CMU, so I don't know how rigorous the "Modern Regression" course is for actually getting people sufficiently well-grounded in statistics to be able to overcome p-hacking and similar fallacies in analysis. I also would much like to see some sort of capstone project showing that the student can actually pull the AI together to make something complete, rather than having a merely theoretically background.

<comment><USER64> How is that different from any other Undergraduate program. At the end of the day undergraduate degrees are like the bare essentials of education - there is a life long journey of learning in any technical field.

<comment><USER63> The short of it is that AI isn't an undergraduate-level specialization. Having a demonstrated capstone project, a full system that someone could point to when in an interview, would go a long way to ameliorating concerns. Masters degrees generally have a thesis that qualifies, and it wouldn't be hard to make a senior project be a requirement for an undergraduate degree (my CS department had such a requirement).

</comment></comment></comment><comment><USER65> That's why I chose to major in applied math. Impossible to invalidate, though if society somehow manages to do so, I won't be mad sheerly because of how impressed I'll be.

</comment><comment><USER66> Has been standard in Europe for quite some years now to see an undergraduate degree in AI ... weird seeing the US lag in this.

</comment><comment><USER67> Reputable academic institutions should not get caught up in passing trends, if they want to stay reputable.

<comment><USER68> If it's a passing trend then CMU already hired too many tenure-track assistant profs. It looks like they will be used at least for some teaching.

</comment></comment><comment><USER69> It seems similar to when universities started spinning out stats degrees as separate from math

</comment><comment><USER70> Which university is going to be the first to start offering blockchain degrees?

</comment><comment><USER71> >include a strong emphasis on ethics and social responsibility

<comment><USER72> This should be for all CS majors, not just those in AI

</comment></comment><comment><USER73> I lead an AI research lab, and I feel that a large part of the work is just coding. So I hope graduates of this program will be excellent coders. I won't be hiring AI graduates that don't know how to write code.

</comment><comment><USER74> That is so awesome. I think it is very valid to do so.

</comment><comment><USER75> > _providing students with in-depth knowledge of how to transform large > amounts of data into actionable decisions._

That is a depressing definition of artificial intelligence.

</comment><comment><USER76> so... what will we call a graduate holding such a degree?

<comment><USER72> A CS degree with an AI concentration closer to that of a masters student than an undergrad. While I think the importance of this degree is small, there are jobs that will prefer that.

</comment></comment><comment><USER77> IMHO, a "modest proposal" for the the CMU CS AI degree, CMU CS, and much of STEM field academics: Have much of the department and program borrow from _clinical medicine_. So, have the department be in part a _clinic_ for solving problems from outside academics via STEM material, information technology, CS, AI, etc.

E.g., yes, continue to have seminars with graduate students and professors with, call it, solutions looking for problems but also have people from outside academics with problems looking for solutions.

In the halls, should find, yes, students and professors but also eager, determined people from outside academics with problems looking for solutions. So, in part the halls should look like the ER of a major research-teaching hospital, like a cardiac center, stroke center, trauma center, birthing center, oncology ward, etc. working on important real problems from outside academics.

So, some problems will yield to data collection, _filtering_ , exploratory data analysis (J. Tukey), graphing, descriptive statistics, cross tabulation, some simple hypotheses tests, etc.

Some problems will yield to optimization -- differentiate, set to zero and solve; linear programming, multi-objective linear programming, network linear programming, integer programming, quadratic programming, non-linear programming, convex programming, etc. There can be approximations, Lagrangian relaxation, achieving necessary conditions for optimality, exploitation of particular problem special structure, heuristics.

There can be classic statistics, especially multi-variate statistics, regression, principal components and factor analysis, discriminate analysis, experimental design and analysis of variance, catagorical data analysis, time series analysis.

And there can be more advanced tools in deterministic and stochastic optimal control, more in probabilistic and stochastic model building, etc.

There can be work in natural language understanding, computer vision, and robotics.

Some of the work for routine solutions can be done by students as part of apprenticeship, meeting and working with people from outside academics, etc.

Then for the better stuff, some of the more serious problems from outside academics can be the start of research for students or faculty. Partly the justification for the research would be the importance of the real problem.

There is an old recipe for rabbit stew that starts out, "First catch a rabbit.". Well, a recipe for applied STEM field work could start out, "First find an application ..." or at least a good problem. Then, sure, look up, stir up lots of good theorems and proofs and algorithms and code but focused on the motivating real problem.

And then the research already has one good application. At that point, curiously, importantly, the chances of another application are relatively high, that is, higher than a first application for work with so far zero applications.

So, maybe CMU can develop some relatively broad expertise in, say, scheduling, logistics, supply chain optimization, facility location, monitoring, automation, etc.

When especially good results have been obtained for some business, sure, the Chair of CS, the Dean of the School of Engineering, the President of CMU, and various CMU Trustees might call the business CEO and mention that CMU has a fund .... That is, solicit donations!

When the program is established with good credibility, audit the financial benefits obtained and suggest that 10% back to CMU will get a seat a the Dean's Round Table, etc.

Research-teaching medical schools deal with real problems and also make progress in research.

Academic departments of engineering, etc. should do much the same.

<comment><USER13> Whenever it makes sense to ground research in practice, CMU professors generally do so by working with industry and govt collaborators. Many CMU CS professors also do some paid consulting on the side.

However, top tier PhD programs are not and never will be highly discounted consulting shops. At places like CMU grad students have perhaps more academic freedom than even their advisors. And good thing.

The day CMUs of the world become "Accenture with cheap student labor" is the day basic research dies.

<comment><USER10> What is evil about non-basic research?

<comment><USER13> Nothing. Why are you asking this here?

</comment></comment></comment></comment><comment><USER78> Will students do better than random on exams?

</comment><comment><USER79> Is CMU trying to compete with Udacity? I personally couldn't take a degree in AI seriously.

<comment><USER48> How many jobs could you get with a Udacity certification versus an actual bachelor's degree? On that note, how many people took the AI classes at Udacity _after_ getting an undergraduate degree at a 4-year institution?

<comment><USER80> I took the Udacity Deep Learning Nanodegree after a masters in CS. It was really fun, and I would highly recommend it.</comment></comment></comment>


Lytro Announces New Light-Field Camera Photo Features - <AUTHOR> http://allthingsd.com/20121115/with-new-features-lytro-aims-to-show-its-futuristic-camera-is-no-one-trick-pony/ <comment><USER2> So it's a TWO-trick pony. I was going to order one. Severely underwhelmed after seeing the first images. The flash player requirement to view the multifocal pictures makes them next to useless (can't share on social networks, can't view on iPad, etc.).

The focus shift feature is nice, but after seeing 50, it seems nothing more than a gimmick, and one that gets darn boring darn fast. This latest feature is cute as well, perhaps more useful even, but again not earth-shattering.

It's just a matter of time before a Samsung simulates the same thing via 'focus bracketing' and storing lots of smaller pictures (they'd probably still be bigger than the Lytro "resolution"), apply a little "focus stacking" algorithm like Photoshop to determine "focal plane" hotspots, and load the focal plane based on the selected hotspot. This little video shows a "fake lytro" image created by taking 10 DSLR pix: <http://www.youtube.com/watch?v=KozKofC01_Q>

This latest feature could possibly be "simulated" (equalled?) by slight physical movement (circular/conical?) of the sensor in the focal plane.

The light field technology is rather ancient by Internet standards, e.g. see this lovely video on the Stanford Light camera, from 2006 (!) which also explains both features rather well: [http://www.youtube.com/watch?NR=1&v=9H7yx31yslM](http://www.youtube.com/watch?NR=1&v=9H7yx31yslM)

Finally, if you're still interested in experimenting with this, check out a $10 solution: <http://web.media.mit.edu/~raskar//Mask/>

So, where does this leave Lytro?

<comment><USER3> To my knowledge, accurately building and calibrating a stereoscopic camera is a significant pain. Saying you could just wave your phone around and extrapolate a 3D scene is easily 10+ years out, because people make terrible tripods, and the requirements for planarity, etc. to do stereoscopic well are pretty strict. That said, there are 3D phones with parallax screens and stereo cameras; they're big and bulky and not that great.

The cool thing I saw about Lytro isn't their flash based player. Its the idea of giving you another degree of freedom after a picture is taken. Like colour correction, you can do focus correction, DOF correction, etc. I would still export one flat image as a result, but gaining that flexibility without carrying around a monopod to take 10 bracketed images is awesome to me.

<comment><USER4> I'd love to have that freedom... combined with everything else that I've come to expect from a DSLR. Lytro's cameras are nice novelty gadgets but it's not clear to me if they're trying to move in the direction of working with a sensor/DSLR maker to enable this. I think that's what they should focus on...

<comment><USER3> I gave this some thought below, but unfortunately fitting a new, more expensive sensor is probably not going to happen soon. The current 1.8 megapixel is a cheap commodity sensor, and it's still probably costing them buckets to have them fabbed with their custom microlenses. Something like a Kodak 8MP sensor would probably be 20x as expensive, and talking them into making you a custom SKU would be much harder.

Edit: after a bit of digging, it looks like they make the micro lens array themselves and buy the sensors without one. This obviously makes acquisition easier, but as the pixel pitch decreases ( by an order of magnitude, to compete with a modern SLR ) the complexities of building and attaching that array increase significantly.

</comment></comment></comment></comment><comment><USER5> As someone who works with robotics, I can imagine the applications of a real- time, video version of this. Stereovision would become much simpler and more reliable.

</comment><comment><USER6> The interesting thing about Lytro is not so much it's current offering, but the potential the technology unlocks.

<comment><USER7> I would be more excited about a Lytro that would record a second or so of full high speed video (1000fps would be ideal, but it'd probably still be useful with much less), so that you could adjust both the focus and the exposure after the fact. Eliminating the need to take a bunch of photos in a row to get a "good one" would be a legit improvement.

That and fitting it into a phone. :)

<comment><USER3> I would be interested in knowing if their tech could ever be phone-sized. It looks like focusing the light correctly on the sensor is more difficult than with a conventional camera ( their promo video looks to show about 8 lens elements). The entire design is basically a big lens with the sensor and screen on the back, that's why they adopted such a strange form factor. That said, there is significant variability in size with traditional camera lenses, so maybe once the market matures someone will figure out a way to produce cheap plastic light-field lenses.

As far as the high-fps goes, they use a standard sensor with custom microlenses. Procuring a new sensor, either for higher resolution or faster frame rates, is probably more expensive and less likely than continued software updates, and maybe even changes to the enclosure and lenses. I suspect sensor acquisition is a significant part of these cameras high price.

</comment></comment></comment><comment><USER8> people don't have to invent bullshit explanations of how they think this stuff works - the thesis is here <http://www.lytro.com/renng-thesis.pdf>

it is more than a stack of images.

<comment><USER2> If you were referring to my post. I wasn't explaining how this works (I know how it works). I was outlining how I think the current effects/benefits to the consumer can be mimicked.

The current _output_ format, which is a stack of JPEGs with a depth map, would cover 80% of the result with 20% of the effort/technology. Capturing this stack of JPEGs (e.g. as high speed video frames) is not beyond the realm of our current camera technology.</comment></comment>


Physics, Topology, Logic and Computation: A Rosetta Stone - <AUTHOR> http://arxiv.org/abs/0903.0340 <comment><USER2> One of the authors, John Baez, has been blogging since before the concept existed. If you're interested in these kinds of topics his _This Week's Finds in Mathematical Physics_ is an amazing resource -- even more amazing that it's usually accessible to those of us who aren't professional physicists.

<http://math.ucr.edu/home/baez/TWF.html>

<comment><USER3> Yes, This Weeks Finds is brilliant, though not so weekly these days.

Also, on the subject of links between topology and logic - Louis Kauffman has a lot of interesting writings:

<http://www2.math.uic.edu/~kauffman/>

</comment></comment><comment><USER4> Oh great, now my brain hurts. Does anyone know of any papers mapping cryptography to category theory? It seems that there could be some interesting results of such a thing, even if it is just reasoning about security protocols in terms of string diagrams.

</comment><comment><USER5> One of the authors, Baez, wrote "Gauge Fields, Knots, and Gravity" a lovely, cheap, and fairly accessible intro to applications of topology in mathematical physics. Worth a glance if you find yourself wondering about all this</comment>


New species combining wolf, coyote, and dog emerges in eastern North America - <AUTHOR> http://www.economist.com/news/science-and-technology/21677188-it-rare-new-animal-species-emerge-front-scientists-eyes?cid1=cust/ednew/n/bl/n/20151029n/owned/n/n/nwl/n/n/NA/n <comment><USER3> One outcome of this interbreeding is that these animals have lost their fear of people, but they retain their predatory instincts, making them quite dangerous.

There are coyotes in the northern part of Nova Scotia that have attacked lone hikers. A woman was killed, in fact a few years ago, and there have been numerous scary encounters in which the animal creeps closer and closer to a wary human, much like a predator approaching its prey.

The coyotes in this part of Canada are said to have interbred with dogs; it's not clear that these are the wolf-coyote-dog hybrids described in the article, but anyway these animals harassing hikers have been hanging out in the forested national park, as wolves would do.

Park rangers have tried to control the population, with varying results. Simply shooting a few of the coyotes actually can backfire; it seems to stimulate larger litters to replenish the population.

We might have to return to the pioneer approach of shooting them on sight, and hope this instills a healthy fear of humans as they once had. It's good having them around, because they control the rodent population which is a vector for disease bearing ticks and other problems. We just don't want them stalking our children in the local park.

<comment><USER4> Coyotes have only killed two people in North America in all of recorded history (and if you check recorded history for wolf attacks it goes back at least to the 1800s). [https://en.wikipedia.org/wiki/Coyote_attacks_on_humans](https://en.wikipedia.org/wiki/Coyote_attacks_on_humans)

A 3 year old child in 1981 and a 19 year old woman in 2009. Both victims were alone at the time of their attacks. Coyotes killing humans is an exceedingly rare occurrence.

<comment><USER5> You cannot make sense of an emerging phenomenon by looking at century old records of superficially similar phenomena.

The 3 year old case sounds like an outlier, regular coyotes getting at an unprotected child.

The case of the 19 year old may be the canary on the coal mine. A fully grown adult should have scared off the coyotes, but that's not how it happened. We should be asking what was different in this case and why the expectations were not met.

<comment><USER4> I don't see how you can call 1 case an emerging phenomenon. More over that there haven't been any other cases since.

I don't think we should be afraid, as the OP mentioned, of coyotes stalking our children in the parks because of one isolated incident.

<comment><USER5> > I don't see how you can call 1 case an emerging phenomenon. More over that > there haven't been any other cases since.

It is really easy, you start with one model of reality, then a piece of evidence comes that does not seem to fit the model.

The first step is to formulate hypothesis that explain that gap between the theory and the practice. Normally, the next step would involve gathering evidence that disproofs each hypothesis, and whichever you cannot disproof, it is the real explanation (which either will confirm your model or provide raw material to refine). Since I have no strong incentive to investigate this particular cases, I will just let be.

However, what I pointed out in my first comment is this: If you brush under the carpet every piece of evidence that do not seem to fit your model, you will end up with a broken model and a very bumpy carpet.

<comment><USER6> > you start with one model of reality, then a piece of evidence comes that > does not seem to fit the model

This is not emergence of a new phenomenon, this is an outlier[0]. There are always outliers. Claiming that a new phenomenon is emerging necessarily implies multiple data points to distinguish it from isolated statistical anomalies, which will otherwise be regarded as simple outliers caused by factors isolated to that incident.

There's an important difference between "brushing under the carpet evidence that does not seem to fit your model" and simply regarding such evidence, tentatively and in the short term, as an expected statistical anomaly until there is sufficient data to recognize a trend. There is no trend here, and until there is, it is completely reasonable to treat isolated incidents as outliers.

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

</comment></comment></comment></comment></comment></comment><comment><USER7> In eastern Los Angeles, coyotes are _everywhere_ , to the point where in some areas you run into them constantly day or night. They're stealthy - silent and very calculating. You can tell many of them are part domestic dog and they don't seem phased by proximity to people and appear to understand the workings of the city to some extent. I have seen the mentioned looking both ways when crossing roads, and also use of sidewalks.

Coyotes are very good at not calling attention to themselves when needed. In fact I lived next to a den of them in LA for years and never heard a peep, despite seeing them staking me out from my neighbor's roof in broad daylight, testing the perimeters of my house more than a few times.

The thing is they're smarter than we give them credit, adapting to the man made environment and expand territory very quickly. We talk about controlling their population but they can parry - adeptly skilled at out-maneuvering people. Hold eye contact and you realize even though they look like a little dog, they're not your friend - they're studying you.

The speed at which they're expanding territory and where they're headed on the East coast now, is interesting. Growing up in southeastern Pennsylvania we never saw coyotes really, but in the last few years I'm hearing lots of stories about them from family. And now even here in NYC they're making an appearance as well.

The coyote / dog mix in LA seemed to not only have adapted to urban areas but use it to their advantage. Now add wolf to the mix and drop them in the environs of bountiful woodland and endless suburban sprawl of the eastern seaboard, what happens?

If an apex predator were to adapt into becoming an anthropocene survivor species, a prerequisite would be having intelligence enough to outwit humans. A species partly forged in human company, with increased intelligence, that uses our own environment as an advantage, and can hunt and eat us. Oh and reach full maturity in about a year. They may seem cute now, but give them a few generations and they might not be so cute any more.

<comment><USER8> If they are really as stealthy as you say, the last thing they will do is be aggressive toward humans.

From an evolutionary perspective, I can't imagine a worse strategy than hunting and eating humans.

<comment><USER9> > From an evolutionary perspective, I can't imagine a worse strategy than > hunting and eating humans.

Being an aphrodisiac according to traditional Chinese medicine probably tops that.

</comment></comment></comment><comment><USER10> Check out _Nature: Meet the Coy-wolf_ if you have Netflix (presumably in the US only)

Also, available here: [http://video.pbs.org/video/2365159966/](http://video.pbs.org/video/2365159966/) (not sure if region restricted, sorry)

This page has a bunch of other resources: [http://www.pbs.org/wnet/nature/coywolf-meet-the- coywolf/8605...](http://www.pbs.org/wnet/nature/coywolf-meet-the- coywolf/8605/)

<comment><USER11> Region restricted to me in UK. However there's this "news" report on the PBS doc being made, [https://www.youtube.com/watch?v=Sd18fLEf_Cw](https://www.youtube.com/watch?v=Sd18fLEf_Cw) which includes excerpts.

</comment></comment><comment><USER12> In a parallel development, a hybrid pigeon, hawk, and roadrunner—the "pigeawkrunner"—has emerged in the same environments as the coywolf. Reports that the coywolf's attempts to catch the pigeawkrunner frequently backfire, resulting in deadly if amusing rock-falls, are as yet unsubstantiated.

<comment><USER13> I saw that story, I think it was on the same site that had the piece on the Midwest entrepreneur who recently closed a successful round A for his oversized magnet company.

<comment><USER14> That's the company that the WSJ described as "profits that seemed to hang in the air, before falling off a cliff"?

Associated Coyote Magnetic Enterprises - was that the name? What was their stock symbol?

<comment><USER15> They have really diversified in recent years, making lateral moves from blacksmithing tools to large-diameter springs, and then into rocketry. They truly are a company that makes everything.

</comment></comment></comment></comment><comment><USER16> used to go out with two of my brothers in the fields near our house in northern Vermont. The grass was chest height on a full grown man with some shorter spots where clover or ragweed or shorter grasses had taken root.

We would hear the coyotes howling over the ridge and go to the middle of the field and call them. When they crested the ridge to investigate we would crouch down really low on all fours with our eyes down. They would creep up on us with two or three going off to our flanks. When they got close enough we would stand up, wave our arms and hoot and holler, scaring them off. It was probably foolish for many reasons but we were in our late teens or early twenties and thought that a three on three mano-e-pata match was no contest in our favor.

We didn't do this often but it happend more than once.

</comment><comment><USER17> So this is why we have been noticing exponentially more "coyotes" roaming around the suburbs of the GTA recently?

My girlfriend was walking our dog last week and saw 3 of them within an hour. The next morning she saw 2.

The other day I was walking the dog and some kid stopped me to warn me about a "wolf" that was growling at him around the corner.

This is all within steps of our small "downtown" and I just kept thinking how strange it was to see so many of them in such a short period of time. I have lived here all my life and I don't think that I have ever seen a single "coyote" in the flesh.

Looks like it's time to start carrying some pepper spray on my usual dog walks? The thought of watching some wild animal devour my dog (or me) is terrifying.

<comment><USER18> Pepper spray? Are guns outlawed in Canada? Why not just shoot it on sight?

<comment><USER17> Guns are basically outlawed in Canada, yes.

You are allowed to own a handgun, but it has to be locked up 100% of the time unless you're at a gun range or out hunting with a government license.

You can own "long guns" too but that's a different and much longer story.

Still though, you're definitely not allowed to carry it around with you walking your dog and shoot any coyotes you see fit. In suburbia at least.

</comment></comment></comment><comment><USER19> Never heard of these being called "coywolf", but it's been known for a while that eastern coyotes are partly mixed with wolves. Good for them, too. Western coyotes are kind of wimpy. Now if we could breed the coyote with various bears, North America might start to rival Africa for impressive and fearsome predators.

<comment><USER20> "Western coyotes are kind of wimpy."

Not around here. In Portland, Oregon, in the west hills <2 miles from downtown and the Willamette River, we are witnessing a marked increase in coyote sightings, and scary interactions with humans.

In the last few weeks we've seen coyotes 2 to 3 times a week during daylight, curiously almost always around 3 PM. Until recently it was rare to see coyotes at all. They are fond of rifling through the contents of garbage cans. We now use extra layers of "security" to prevent coyotes getting into the trash.

They are bold, fearless and evidently numerous. A couple of days ago a coyote was wandering up our driveway when my wife was nearby pulling weeds. Of course, she got out of the way. Based on its direction I was concerned it might go into the garage, dislodging it from there could be a big problem.

Fortunately that day the coyote headed elsewhere. However people have become alarmed to the extent a neighborhood meeting is scheduled next week to consider options. There's serious concern about safety of small kids in the area, and really I can understand that source of worry.

<comment><USER19> Is it legal to shoot them there? (The coyotes, not the small kids...)

</comment></comment></comment><comment><USER21> Somewhere on the Internet, a furry just gained yet another fursona.

> LIKE some people who might rather not admit it, wolves faced with a scarcity > of potential sexual partners are not beneath lowering their standards.

Oddly appropriate.

EDIT: Nevermind, looks like they have at least 3 years on this joke: [https://www.furaffinity.net/view/9465519/](https://www.furaffinity.net/view/9465519/)

<comment><USER22> Let's just say that Furry Twitter is having _lots_ of fun with this news story.

<comment><USER21> Heh. My only contacts in Furry Twitter happens to be Infosec Furry Twitter. :P

</comment></comment></comment><comment><USER23> _The wolf, dingo, dog, coyote, and golden jackal diverged relatively recently, around three to four million years ago, and all have 78 chromosomes arranged in 39 pairs.[6] This allows them to hybridize freely (barring size or behavioral constraints) and produce fertile offspring._

<comment><USER24> Four million years is recent? We split from chimpanzees three to six million years ago.

<comment><USER25> Yes, it is recent.

We are evolutionary newcomers.

<comment><USER26> I don't think chimps can breed with humans however.

<comment><USER23> [https://en.m.wikipedia.org/wiki/Humanzee](https://en.m.wikipedia.org/wiki/Humanzee)

</comment></comment></comment></comment></comment><comment><USER27> I live (and grew up in) in Central New York (as in: middle of Upstate New York). We've had "coydogs" as long as I remember. I sort of assumed it was a myth, in fact I remember being told it was a myth and that they were just plain coyotes.

Then again, the kids also claimed that they were faster, smarter, and would hunt humans...so there was definitely some mythology going on.

</comment><comment><USER28> There is a great PBS Nature episode on the Coywolf. There is footage of these animals leaving in close proximity to humans near major cities.

Link:[http://www.pbs.org/wnet/nature/coywolf-meet-the- coywolf/8605...](http://www.pbs.org/wnet/nature/coywolf-meet-the- coywolf/8605/)

</comment><comment><USER29> What a beautiful creature!

<comment><USER30> Indeed, had a look at a few clips and pictures and look and indeed traits remind me of a Fox more than it's genetic-background heritage.

ADD: [https://en.wikipedia.org/wiki/Canidae](https://en.wikipedia.org/wiki/Canidae) most interesting compliment to this article

</comment></comment><comment><USER31> I find these stories intriguing. Several have come together over the last decade or so, this one, the bear hunt in Florida because of too many bears, the Burmese Pythons in the Everglades eating everything, mountain lions living in many parts of the Bay Area near people, the rat explosion in NYC.

All wildlife finding a niche in the urban and suburban world we've created and retaking territory originally ceded during an aggressive hunting and trapping phase of our existence.

Once we become the hunted what then? We have not yet seen these animals predating on the homeless but I expect it's only a matter of time.

<comment><USER32> The Burmese Pythons in the Everglades don't fit your pattern. The Everglades is neither urban nor suburban, the pythons live in areas that were never really settled by people, and of course the pythons are not native so are not 'retaking'.

And it's hard to say anything about NYC's rat problem as there are no good estimates of the rat population. The generally held belief has been one rat per person, but a statistician recently argued that there are only two million. Quoting further from [http://www.nytimes.com/2014/11/06/nyregion/8-million-rats- in...](http://www.nytimes.com/2014/11/06/nyregion/8-million-rats-in-new-york- data-suggest-that-legend-is-flawed.html?_r=0) :

> The health department says its efforts have paid off. "We have seen an > overall decrease in the number of active rat signs throughout New York > City," Levi Fishman, the deputy press secretary for the department, said in > an email.

> How much of a decrease? Mr. Fishman said that "there are no scientific > methods for being able to accurately count the number of rats in New York or > any large city." Similarly, Kevin Ortiz, a spokesman for the Metropolitan > Transportation Authority, which is well steeped in the battle against > rodents, said it had never quantified the rat population living in the > subway system.

Instead, I suggest a possible bias to your information sources: everyone has cameras, and takes pictures of everything, so the number of rat-related videos has gone up.

You bring up 'the homeless'. As a reminder, many of those people living and killing animals in the 'aggressive hunting and trapping phase of our existence' did not do so from homes, so I don't think that's the relevant characteristic.

<comment><USER31> Your point about the rats is well taken. It does make for good click bait and over exposure serves multiple interests beyond simply informing the public.

I worry about the homeless as a vulnerable population who is disproportionately threatened by wildlife in an urban setting. Whether it is from plague carrying fleas on rats running around an encampment or a group of coywolves or a mountain lion deciding that this particular human sleeping under a bush in a park might be prey.

<comment><USER32> Sure. My comment is different. "Homeless" humans managed pretty well against lions, tigers, and bears. I think it's the defenseless you're concerned about. A house is one sort of defense. So is a car. So is a homeless encampment. So are guns and dogs. Few homeless are defenseless in the way you mean. While some people with homes are still defenseless against the threats you are worried about.

If you are concerned about plague, I think you should look more at domestic cats than homeless humans. Cats kill and eat infected rodents and pass the disease to humans. There have been 16 in the US because of that transmission mechanism. For that matter, there have bee 64 cases as a result of someone butchering or skinning an animal.

And while traditionally linked with poor sanitation leading to rat infestation, "plague in New Mexico has increasingly occurred in more affluent areas, a result of continued suburban and exurban development in enzootic plague foci." It's rich people who are helping to spread the plague these days, not the poor!

[http://wwwnc.cdc.gov/eid/article/21/1/14-0564_article](http://wwwnc.cdc.gov/eid/article/21/1/14-0564_article) goes into more detail, and points to "performing common outdoor peridomestic work (e.g., cutting brush or chopping wood)" and "a result of contact with infected fleas that were brought into the home by indoor/outdoor pets" as the two largest vectors.

This isn't to say you shouldn't worry, only that more information might bring more focus into what you should worry about, and homelessness leading to plague should not be one of them.

(P.S. I'm an inveterate researcher. I tracked down these details in part because I enjoy it. I can totally understand how this style is outside the usual cocktail style discussion, which is all this topic really deserves, and don't expect or demand a comparable response.)

<comment><USER31> (P.S. I think its _awesome_ , I love a person who explores the questions more deeply.)

I think you make an excellent point vis-a-vis homeless vs defenseless. My exposure to plague warnings has primarily been in the county and state parks around the Bay Area. The primary vector being fleas per [https://www.cdph.ca.gov/programs/vbds/Documents/PreventingVB...](https://www.cdph.ca.gov/programs/vbds/Documents/PreventingVBDinNationalParksinCA.pdf)

We have also got a number of lion sightings/encounters although I could not find the 2014 or current data ([http://www.dfg.ca.gov/wildlife/lion/trends.html](http://www.dfg.ca.gov/wildlife/lion/trends.html))

And of course the linked article talking about Coywolves and relating to their lack of fear of humans.

My thesis is that human/wildlife encounters will increase as the populations of these various species increase in response to greater success in living in urban and suburban areas. And my conjecture is that as a result of increased encounters there will be more incidents where the defenseless are harmed. Have not yet thought of a good way to test that hypothesis yet.

And that has also lead to exposure to racoons and bears both of whom are willing to cross paths with humans in order to scavenge food or food scraps.

</comment></comment></comment></comment></comment><comment><USER33> Technically not a new _species_ , rather a new _subspecies_.

<comment><USER34> This puzzled me as well. Do we not have a word for this? Is _subspecies_ really the word? In linguistics mutually intelligible but distinct `languages' are called dialects. Similarly is there a term for mutually interbreedable but distinct `species'?

<comment><USER35> > Similarly is there a term for mutually interbreedable but distinct > `species'?

It's species or subspecies. Animal classification has always been a little bit fuzzy and has some legacy cruft laying around. Like wolves, coyotes, and dogs are distinct animals with different behaviors but are definitely capable of interbreeding.

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

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

For domestic animals, we have the noun breed, as in breed of dog.

</comment></comment></comment><comment><USER36> Fascinating. I have had a number of urban close encounters with coyotes in the west US, and the prospect of a similar animal but with less fear of human is certainly concerning.

</comment><comment><USER37> Hybridization is super interesting from an evolutionary perspective. Two populations can evolve down very different paths. Evolving all sorts of new genes and adaptions. Then hybridization mixes it all up. And over time, the best combination of genes from both species will be selected for. Creating something more fit than either of the original species.

<comment><USER38> Not so fast with the evolutionary fantasies. If they can breed and produce fertile offspring, are they really different species? Maybe we've got the definitions wrong somewhere.

<comment><USER39> > If they can breed and produce fertile offspring, are they really different > species?

Species are defined more-or-less arbitrarily. It's essentially impossible to come up with a meaningful definition of "species" because of the nature of biology.

Imagine a gigantic tree, beginning with the first organism billions of years ago, with every living thing that ever existed as a node. Now, for the sake of the thought experiment, imagine that none of the lines ever died out.

There's no way to really consistently draw a line between one node and another and say "these are two different species." We pretty arbitrarily decide "well, these two sets are sufficiently different so let's call them two difference species." Like sibling commenters noted, sometimes hugely different species can interbreed and produce fertile offspring. Sometimes extremely similar (and related!) species can't breed. Or sometimes they can but never will except under laboratory conditions.

<comment><USER38> We make this classification, so we can adjust the rules until our model fits reality at an acceptable level. So let's define species as groups of individual of a similar genotype. We were not able to define and measure genetic distances in the past, but now with the ability to read whole genomes, we can do just that.

> sometimes hugely different species can interbreed and produce fertile > offspring

Then they are obviously not hugely different. Were we just comparing phenotypes when we decided to classify them as different species? Let's improve on that.

<comment><USER39> > So let's define species as groups of individual of a similar genotype. We > were not able to define and measure genetic distances in the past, but now > with the ability to read whole genomes, we can do just that.

How similar?

Consider the following: imagine that you assembled a gathering of all your ancestors in the male line for say, the past two million years. Let's say, for illustrative purposes, that the gap between each generation is twenty years. So you'd have 5 people to represent a century - you, your father, your grandfather, your great-grandfather, and your great-great grandfather. That makes 50 people per millennium, 500 people per ten thousand years, 5,000 people per hundred thousand years, and 50,000 people per million years. So two million years of ancestry gets you 100,000 people, the size of a small city, or about enough people to fit in the Rose Bowl stadium.

So really, not that many people in the grand scheme of things. Now line all those people up in order going all the way back to the first guy, who we'll just call Adam. The difference between Adam N and Adam N+1 is very small. There's no point at which you can say "Adam N is this species and Adam N+1 is that other species." But there's a hell of difference between you and Adam.

The same logic applies to life in general, the tree is just a lot bigger and messier and we're talking about distant cousins rather than ancestors, and some lines are extinct.

But going back to your proposed definition - similar genotype - we can have all kinds of bizarre situations. Say we require the genotype to be 99% similar. By this definition, we conclude that Adam M and N are the same species. We also come to the conclusion that Adam N and Adam O are the same species. But wait! Adam M and O are only 98% similar! What do we do - <USER2> multiple species labels to the same individuals?

 _Species_ has proven a necessary and useful abstraction, but it nevertheless doesn't hold up well under scrutiny. That's fine, as long as we recognize its limitations.

> Then they are obviously not hugely different. Were we just comparing > phenotypes when we decided to classify them as different species? Let's > improve on that.

Genotypes certainly provide useful information, but they can also muddy the waters.

Assume that we take the definition of "any two organisms that can interbreed and produce fertile offspring are the same species" as our preferred definition. (This has its own problems: for example, did you know mules sometimes _are_ fertile, just not usually? Did you know it's _conceivable_ that humans and chimpanzees can interbreed?) It is _entirely possible_ for A and B to be distantly related genetically, yet able to interbreed, while A and C are closely related and unable to interbreed. "Can interbreed" is not necessarily a proxy for genetic distance.

</comment></comment></comment></comment></comment><comment><USER40> Coywolf isn't a very good name—I think Wolfote rolls off the tongue much better.

<comment><USER41> Or perhaps the "dire woof".

</comment></comment><comment><USER42> It's becoming more of a problem in northwestern Connecticut for sure.

</comment><comment><USER43> aww... I've have reached my article limit.

<comment><USER44> Just click on hn's _web_ link and then read the article through google.

<comment><USER45> Thanks for pointing that out. I never knew one could do that.

</comment></comment></comment><comment><USER46> And part human! (Come on it's almost Halloween)</comment>


The Great Ethnic Food Lie - <AUTHOR> https://www.washingtonpost.com/news/wonk/wp/2016/04/22/the-great-ethnic-food-lie/ <comment><USER2> > Most cheap Indian food is made by Bangladeshis and Pakistanis, and most > Indian food here is cheap. Of course, people don't realize that. But it's > true. More than 70 percent of the Indian restaurants in New York City, for > instance, are not run by Indians. They are run by Bangladeshi and Pakistani > restaurateurs.

Isn't that ironic - to claim inferiority of the food preparation due to the nationality of the persons preparing it, when you are complaining that americans treat food the same way.

Lets take a history book, shall we ... and a map while we are at it. Those territories were split fairly recently. I am willing to bet that Pakistani people could prepare decently Rajastani dishes, or the Bangladeshi from west Bengal.

And of course the concept of Indian food is ridiculous by itself. As every other country that has varied climate zones, terrain and people - my wild guess is that India probably has at least 10-20 distinct cuisines based on what is available here, what grows well and the religion and customs of the people that inhabit the territory.

</comment><comment><USER3> > But behind our public enthusiasm for Indian, Thai, Vietnamese, Ethiopian, > Korean, and the many other foreign cuisines that can be enjoyed in cities > like New York, there is also private, and yet pronounced, form of bias, a > subtle hypocrisy that suggests we think these foods are inferior.

Dumbest statement I have ever read.

<comment><USER4> It's the big new stupid thing social justice warriors are hyping up lately, an asinine claim that by enjoying food from other countries we are calling it inferior.</comment></comment>


Old Man River City – A Community Dwelling Machine - <AUTHOR> https://solutions.synearth.net/a-community-dwelling-machine/ <comment><USER2> Part of the power of cities is that they balance density and modularity. You don't need an enormous capital outlay to build a city all at once. It can grow and shrinks organically at an individual building, street, and transit line level based on the needs of the population and industry, and can update itself piecemeal as new materials and construction techniques come into play. Building an integrated "community dwelling machine" seems to disregard all of that, and the practical reality if it would even have been possible to fund the thing in the 1980's would have been an incredible, outdated, derelict hulk in East St. Louis by 2019.

<comment><USER3> I don't the modularity is necessarily lost with a mega structure like this- interior remodeling of office, residential, and space happens all the time. As for the updating- East St. Louis had extremely out dated housing stuck in the 1980s when this was proposed and it hasn't gotten better AFAIK.

I think the real problem (outside the aforementioned capital outlay) lies in the issues with the interface with the rest of the world/community. The Arcology is just to self contained and reality isn't. It's often hard enough to find locations within a current large office building or complex, it would be even harder inside this concept. That's really going to limit the retail and service industry inside a mega structure like this. The circle shape is also a problem- circles don't pack well, so there is a natural stand off are between the Arcology and the rest of the community. Integrating the internal and external transport networks and infrastructure would be darn near impossible.

</comment></comment><comment> crooked-v The endless miles of windowless and half-populated internal corridors seem like they'd be both be awful to live with and serve as a substantial enablement of crime.

<comment><USER4> From this part of the description I get the feeling that it wouldn't be a solid block of interior levels but would likely have some sort of atrium space that is spanned by bridges

>Inside-that is, below the moon crater's three-and-a-half-mile-eircumferenced, surface-terraced mountain mass-are all the communal services not requiring daylight: for instance, all the multilevel circumferential trolleyways, interlevel ramps, roadways, and parking lots, with numerous radial crosswalks and local elevators. There are radial crosswalk bridges at every four terrace levels. These provide bridges-never more than two decks up or down-for walking homeward, outwardly from the interior community bowl, to one's individual, terraced, tree-hidden dwelling area.

So it would probably look more like any of the countless building atriums currently in existence, see [https://www.google.com/search?q=building+atrium](https://www.google.com/search?q=building+atrium)

he also describes the crater structure as being an A-frame so I think that lends credence my supposition.

You could certainly have filled in sections where needed to provide office or retail space. It would actually be quite practical to partition the interior space at regular intervals with a wall consisting of offices facing in to the atrium space behind which you could place retail and a main thoroughfare spanning from the inner to outer parts of the A.

</comment></comment><comment><USER3> My immediate thought was that Apple Park (the spaceship) looks like a miniaturized commercial space only decedent of this idea. Even the scale is roughly constant- Apple Park houses 12000 employees in roughly 1/10th the size of the Old Man River City, which was to hold 125,000.

<comment><USER5> There is another, similar building in the United Kingdom.

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

<comment><USER3> After reading that, I realized the US pentagon building is also a roughly similar concept, and is almost exactly the same diameter as Apple Park.

</comment></comment></comment><comment><USER6> Arcologies always seemed like a neat idea to me, but I've never seen an in- depth look at their proposed infrastructure.

What would power and communication distribution look like? HVAC? I assumed chill water with several distributed plants. This place is going to need lots of loading docks or it's own trainyard for food and other consumables. Domestic and waste water would probably both need to be handled on site.

I've never seen those aspects of an Arcology design explored.

<comment><USER4> I think the key to working this out would be extending current practices employed for large buildings with an eye to interconnection. Maybe the best strategy would be to modularize the arcology so that it would be composed of many interconnected structures that are each more or less self sufficient. You could apply this to the Old Man River City by designing it as individual slices of a toroidal pie and then replicating this design until you have the full shape.

</comment></comment><comment><USER7> At one point, Google was proposing building a dome over their part of Mountain View. What happened with that?

</comment><comment><USER8> My take: This project's success would have depended on the ease and affordability of maintaining it.

</comment><comment><USER9> "Thus landscape-partitioned from one another, the individual homes beneath the umbrella dome do not need their own separate weather roofs."

Is this saying that the houses themselves wouldn't have roofs? That would seem like a pretty significant privacy and security issue.

<comment><USER10> At first I thought it must have meant that the dome would make weatherproofing individual roofs unneccesary (e.g. no need for a waterproof membrane if the dome diverts all rain), but from the line "The experience will be that of living outdoors in the garden, without any chance of rain and out of sight and sound of other humans" I think you must be correct.

Putting aside the facts that A) some of us like the rain and the dome would prevent that, not to mention forcing total reliance on artificial irrigation if you want to have a garden, and B) it relies on the assumption that the dome will never be cracked or compromised in any way, I must agree with you on the privacy and security issues.

The design seems built around the idea that good spaces make good people, and good people make good neighbors. This could not be further from the truth. I live in a "nice" area and most people are selfish assholes, with absolutely no consideration for their neighbors or (seemingly) any awareness that their actions effect other people.

I have had to call the police multiple times for noise disturbances, have caught my neighbors leaning over the fence and spraying my plants with pesticides (I have a bunch of native plants and ground covers (well groomed, not runnning wild) instead of a traditional manicured lawn, which I believe they find offensive and were trying to kill - plus I have pets which chew on the plants and don't want them getting poisoned), constantly have people throwing rubbish over the fence into our yard, have had stuff stolen from the yard (fence materials, paving stones, etc. that we were in the middle of building with) etc.

If this city plan came to fruition I have no doubt it would degenerate into a anarchistic hellscape within a month. My house walls and roof protect me from the weather, but more importantly they protect me from the society in which I live.

<comment><USER4> Your initial assumption was correct. The sentence you quote is probably describing what is now known as an indoor-outdoor area that combines elements of a garden with a living space. Most of the house would be enclosed:

> The floors of the individual homes on the outward terraced slopes penetrate > inwardly of the "mountainside" to provide an 85-percent-enclosed family > apartment set back into the "mountain's" surface

I do agree that the idea of only separating the exterior parts of the houses with landscaping is a bad idea. Continuing the walls out to the edge would make more sense, good fences make good neighbours and all that. The biggest difficulty would be the visibility of your exterior space from above since lower levels project out further than higher ones. No nude sunbathing unless you aren't shy.

Honestly the dome overhanging the whole structure is the most ridiculous part of this plan. It doesn't make any practical sense. I could see an argument for doming the inner area like a sports arena though. It would be far more practical and useful to extend a glazed roof over the outdoor area to provide protection from weather and equip it with a retractable shade that can block the hot sun and prying eyes. Combined with walls on either side and you have a nice sun room that is more private and secure while still being much more luxurious than a simple balcony.

<comment><USER9> Now that you point out that all of the houses are mostly "underground" the dome seems especially odd since climate control would likely be relatively easy.

</comment></comment></comment></comment><comment><USER11> Good advice for sea steading.

City's are easy if modular.

Buildings like this are only good for dystopian science fiction.</comment>


The world is entering a third stage of a rolling debt crisis - <AUTHOR> http://www.economist.com/news/briefing/21678215-world-entering-third-stage-rolling-debt-crisis-time-centred-emerging <comment><USER2> I've heard it said (and I don't know how true it is) that during the Reagan (I think) administrations, they "convinced more than half of the people that they were in the top 50%", meaning that people began to think of themselves as more well-off than they actually were, and started spending more than saving.

I have no idea if that's accurate, but it's an interesting thought. For the economy overall, it's probably best if everyone buries themselves as far into debt as they can, because it increases spending tremendously. Max out credit cards, buy as much "stuff" as possible (cars, real estate, college degrees, whatever).

The problem is that when the first real bump in the road comes along, suddenly most people are leveraged to the hilt and can't absorb the hit. And it feels like as long as I've been conscious (and maybe longer, who knows), we've been in this cycle of "easy money, spend spend spend" followed by "crap, bubble". Sure there's money to be made on the upside, but there's even more to lose on the way down.

<comment><USER3> If you drink too much at night, you'll get a hangover in the morning. The same is true of spending and debt.

<comment><USER4> That's _usually_ true for personal debut. For governments, it's a dangerous misconception.

The only problem with personal debt is when it becomes systemic. The fallacy of composition is that what's good for individual is not necessarily good if we all do it at the same time. Normally lowing your price to be more competitive is a useful strategy, but not when it becomes a race to 0. We saw this in the great depression with farmers publicly throwing out their product.

As for governments, the austerity meme is class politics in disguise, and tends to lead to nasty social blowback. Governments can change monetary policy and other law, giving them a lot more options.

<comment><USER5> You know, government debit can grow until it's not sustainable anymore. And seems to be doing exactly that world around for the last couple of decades.

I know this disagree with mainstream economics, and almost all niche economics theories. But it's happening again and again, so fuck the theories.

<comment><USER6> Which of these debt peaks was unsustainable, and why?

[http://www.mybudget360.com/wp-content/uploads/2010/12/us- pub...](http://www.mybudget360.com/wp-content/uploads/2010/12/us-public-debt- vs-gdp.png)

<comment><USER4> [https://en.wikipedia.org/wiki/Sh%C5%8Dwa_financial_crisis](https://en.wikipedia.org/wiki/Sh%C5%8Dwa_financial_crisis)

Japan (at the time, primarily a few zaibatsu) had serious financial problems when their export bubble popped in the 1920s. Unfortunately, they bought into myth that austerity lowers debts _really badly_ , and decided it was a good idea to cut out 30% (!) of their GDP in two years. When that only made the situation worse, they doubled down and tried to cut another ~10%.

The zaibatsu and 37 banks went under in the inevitable bank-run, and quite a few financial leaders were assassinated when the military realized their budget was about the only thing left that could be cut.

Compared to that mess, the US has done a relatively good job of inflating away it's debts. Our gridlock blocked most of the austerity "fixes", so while we still have a mess of an economy, at least it isn't slashing a third of our GDP.

</comment></comment></comment></comment></comment></comment><comment><USER7> The one parent comment here addresses consumer credit/debt in the US.

The article is about unsustainable debt building up in emerging markets due to attractive interest rates on risky bonds in an environment where safe, conventional returns of 5-9% are extremely hard to come by:

 _A dollar-denominated government bond issued in 2012 by Zambia, a copper-rich country with an average GDP per person of $1,700 a year, offered just 5.4% interest; even so, it was 24 times oversubscribed as rich-world investors clamoured to buy. The following year a state-backed tuna-fishing venture in Mozambique, a country even poorer than Zambia, was able to raise $850m at an interest rate of 8.5%._

Now data from the IMF is showing that corporations and governments were probably not investing these loans into profitable activities:

 _Growing debt in emerging markets is not of itself something to worry about. It may be that savings are getting into local capital markets more effectively or that there are more, better investment opportunities. Sadly, those happy possibilities do not seem to account for what is now going on. While corporate leverage in emerging markets has been going up, corporate profitability there has fallen, says the IMF. There is plenty of evidence to suggest that rapid debt build-ups are the hallmarks of periods of indiscriminate lending that eventually end in tears._

So this article has little to do with the average American consumer. It's about banks looking for higher rates of returns in riskier markets and doing dumb things with their money. If they have not sufficiently calculated and priced out these risks, which is what happened in 2007 (purposefully), then a lot of this debt might start defaulting, which could lead to another financial contraction as banks find themselves yet again with risky, misvalued assets on their balance sheets, eating up an unsustainable portion of their portfolios and limiting their ability to lend.

The difference is that screwing up corporate lending might not be as damaging as fudging consumer lending, such as mispriced and unsecured mortgages. The author draws this conclusion from the findings of one OECD paper, so take that with a grain of salt.

Does anyone want to discuss the actual contents of the article, rather than what they think the title implies?

<comment><USER8> Data from the IMF must be taken with a grain of salt given that their agenda is to provide loans with impossible terms and then repossess national resources when a country defaults.

"America has put [the debt crisis] behind it" isn't quite true either. A large part of the cash withdrawn from ZIRP and quantitative easing has gone straight into record-setting stock buybacks over the last three years, propping up the market and increasing income inequality without creating any real value or skilled jobs.

<comment><USER9> Yeah so actually the IMF puts out some great economic research that is pretty highly regarded across the econ community, further, your pet theory for what happened is really only accepted in maybe some media outlets, but not really the academic community. "A large part of the cash withdrawn from Zero Interest Rate Policy"? Like what? That doesn't even make sense. Are you talking about how low interest rates and a dearth of profitable investment projects causes CFO's to see that the best immediate use for their cash is to return money to shareholders and shore up their balance sheets, after this huge balance sheet recession we had?

The generally accepted theory is that there has been a worldwide demographic slowdown combined with a large number of countries accumulating huge current account surpluses, leading to "the world being awash in savings." This oversupply of capital causes the natural rate of interest to drop, and that is the rate that the Fed needs to follow (it really doesn't so much decide on a proper rate as much as it estimates it mathematically), as it will cause stagnating growth or deflation if too high compared to the natural rate (!!!!!), but will cause inflation if it's actually "too low." So there's no evidence ZIRP has been "too low," in fact all the evidence points to the fact that interest rates actually haven't been low enough.

</comment></comment></comment><comment><USER10> I wish that articles like this were not confined to the international finance ghettos of The Economist and The Financial Times, but that were also discoverable in local daily American and European newspapers. Because when we talk about the professional investors chasing yield and ending up with bad outcomes, we are also talking about the pension funds and American school teachers, bus drivers, municipal workers, etc.

</comment><comment><USER11> Why aren't first world governments issuing bonds with good interest rates anymore?

<comment><USER7> Federal Reserve sets short term interest rates throughout most of the market through the Federal Funds Rate (FFR). It dropped the FFR to ~0% after the financial crisis, but instituted a brand new policy: 0.25% interest on reserves held at the bank in order to get banks to be less risky and loan against more safe assets that they keep with the treasury.

Conventional economic thinking is that low interest rates spur economic activity, as individuals and institutions that would have once parked the money in safe government bonds and earned a return on the interest would instead be forced to lend out into the real economy to find a decent rate of return.

The problem is that the money supply is too large due to QE and there is not enough demand for viable, long-term projects such as infrastructure, R&D, education.

Plus the government continues to run into the debt ceiling. If it were to raise interest rates on its bonds, it would be paying out more on its already enormous debt.

</comment></comment><comment><USER12> Taking this to a much smaller scale...does anyone have any predictions for how ripples from this will impact the housing markets (particularly in the Bay Area that has lots of money from China pouring in still)?

<comment><USER13> Is it actually possible to easily invest in housing markets? I looked at some local REITs but none of their stock prices/returns reflect rent increases at all, and their share prices have just been down lately.

Actually buying land is still fairly hard to get into!

</comment></comment><comment><USER9> Wow, nobody mentioned the natural rate of interest yet?</comment>


Kindle Führer: "Mein Kampf" Tops Amazon Charts - <AUTHOR> http://www.vocativ.com/01-2014/kindle-fuhrer-hitlers-e-book-gold-mein/

<comment><USER2> Laughing at the vaguely inappropriate inline adverts: Blah blah Hiter blah. NOW READ THIS: APPLE KNOCKOFFS YOU WON'T SEE AT CES

</comment><comment><USER3> And this is on HN because [...]?

<comment><USER4> No idea, but if these lists were topped by "50 shades of gray", I totally get why "Mein Kampf" tops them now. They are not very _expensive_ , whatever the _coin_.

That said, for 99 cents I'd buy a hardcopy of the book. I'd be interested in what Hitler had to say, also. Scratches the back, to give a glimpse at Fuhrer's manifesto :-) that doesn't make me a Nazi overnight.</comment></comment>


Chrome deb/ubuntu x86 - <AUTHOR> http://www.google.com/chrome/intl/en/eula_dev.html?dl=unstable_i386_deb

<comment><USER2> Can definitely tell its a unstable build. I cannot open up any dialogs for example and when I do a search if I type to fast in address bar and hit enter the last couple characters are lost. runs just as fast as it does in my windows system (or so it seems) I have been very put off with the state of the browsers in Linux, I hope Chrome can give firefox or epiphany some real competition.

<comment><USER3> Firefox 3.0.10 is horribly slow on my system, it crashes pretty frequently on startup. I've been using the Ubuntu Chromium daily builds off of Launchpad for the past for days (<https://launchpad.net/~chromium-daily/+archive/ppa>), and it's really been a refreshing experience - the web is responsive again! It obviously isn't ready for release yet, but if you build that into your expectations, it's actually quite pleasurable to use.

</comment></comment><comment><USER4> is there a 64bit version, too?

<comment><USER2> [http://www.google.com/chrome/intl/en/eula_dev.html?dl=unstab...](http://www.google.com/chrome/intl/en/eula_dev.html?dl=unstable_amd64_deb)

<comment><USER5> It's not a native 64bit binary as it uses ia32-libs.

<comment><USER6> Some interesting info: [http://neugierig.org/software/chromium/notes/2009/05/javascr...](http://neugierig.org/software/chromium/notes/2009/05/javascript- heap.html)</comment></comment></comment></comment>