The spirit of the list is to pick items such that: if you disagree with an item in this list then either you are wrong or you know something I would really like to hear about.

Encryption, disk images: TrueCrypt (open source: Linux, Windows, OSX)

TrueCrypt can create portable encrypted virtual disks (files that can be mounted as a disk on any operating system).

Encryption, files: GnuPG (open source: Linux, Windows, OSX)

GnuPG is the tool to use to encrypt files for email.

Presentation: Apple Keynote (commercial: OSX)

Keynote is not quite as friendly as Microsoft PowerPoint, but it quickly produces beautiful presentations.

Reference Library: Papers (commercial: OSX)

“iTunes for PDF.” Manage thousands of PDFs and references, annotate with meta-data, place papers into multiple project folders. An interesting runner-up is BibDesk (open source: OSX).

Spreadsheet: Microsoft Excel (commercial: Windows, OSX)

Open Office and Google Docs are getting better every day, but neither come close to Microsoft Excel in functionality and versatility of user interface. If you are on a platform that supports Excel, working regularly with spreadsheets and using something other than Excel: it really means that you do not value your time.

Statistics Software: R (open source: Linux, Windows, OSX)

R is rapidly becoming the platform of choice for statisticians and is (with the addition of lattice and ggplot2) the best way to produce graphs. R has fairly nasty programming language, but has so many statistical operations available that it can not be avoided.

Technical Documentation: LaTeX (open source: Linux, Windows, OSX)

It may seem antiquated but TeX/LaTex is still far more powerful than the “WSYWYG” pretenders. The separation of presentation from specification, automatic management of references, table of contents and being able
to include PDFs from external files (which get refreshed when you re-build the document) are all lifesavers.

Version Control: git (open source: Linux, Windows, OSX)

Just about the only version control system that: doesn’t damage the data you are trying to manage by adding dot-files into all of the directories, can routinely handle large files and can work productively without a network connection. Perforce is powerful central server commercial option (with the ability to have central policies, control and review).

I look forward to learning which of my choices are considered poor and what your must-haves are.

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Introduction

Combinatorics, as it matures, becomes harder to succinctly describe. The field has progressed from the basic study of finite sets and counting techniques to being the discipline where questions involving counting, graphs, connectivity, mappings and partial orders all naturally reside. But the objects that combinatorics studies turn out not to be the correct foundation to support modern combinatorial methods. Many combinatorial methods were dismissed as mere technique until combinatorics expanded to include the natural domains of these methods: lattices, formal power series, valuation rings, matroids and many diverse algebras. One person who pushed hard for this coherence and unity was Gian-Carlo Rota.

An example of a high-school level combinatorial trick is proving the equation

by applying the binomial theorem to . This trick is transformed into a method when you recognize that you really should be working in the ring of formal power series and invent the Umbral Calculus. With the Umbral Calculus you can use the equivalence of the following two equations:

(i.e. is equivalent to ) to prove that for any two arbitrary infinite sequences the following two statements are also equivalent:

		for all	(1)
		for all	(2)

For example: we could pick and substitute it into Equation 1. With some work we see this implies .¹Then by the Umbral result we know Equation 2 must also be true so we get a new identity: . This algebraic production of a new identity is very different than the classical method of “counting two ways” (or being lucky enough to come up with a clever bijection to prove the identity).

Summary

The book “Combinatorics the Rota Way” is itself hard to succinctly describe. The first and third authors tell of writing this book using notes from the Massachusetts Institute of Technology’s course 18.315 collected over a span of more than 30 years. Gian-Carlo Rota himself was added as a posthumous author. The book itself contains more than a single course-year’s worth of material and is packed very densely.

The book’s emphasis is abstract and algebraic. The exercises are not to teach, but are instead to identify applications of combinatorics in other mathematical disciplines. The book is the product of a strong push to demonstrate many combinatorial methods in their most powerful, but not most obvious, forms. This work is clearly a labor of love and contains some remarkable material. However, due to the large breadth of the work not much time is spent on motivation or on concrete examples.

Chapter 1: Sets, Functions and Relations

The first chapter covers the definitional foundations of combinatorics: sets, lattices, partial orders, functions and relations. These are the discrete objects that the book will reason about by later building more complicated algebraic objects. This section is very dense and reads like a compressed Bourbaki treatment of discrete mathematics.

One portion of this chapter that is problematic is the section on entropy that seems to serve no purpose other than to prepare the reader for exercise 1.4.10 which demonstrates an abstraction of entropy. Also, exercises 1.2.5(j,k) are needlessly cruel in asking the reader to recreate the Robertson-Seymour graph minor theorem. There have been books where the reader is successfully guided through a major result by exercises, such as the Weak Perfect Graph Theorem in Lovász’s “Combinatorial Problems and Exercises”, but this book is not structured in that manner.

Chapter 2: Matching Theory

The second chapter is a welcome change in tone and opens with a quote from Harper and Rota describing matching theory and a clever 1979 Putnam exam problem is worked into the exercises and solutions. Central to the chapter is “marriage theorem”, which determines when matchings are possible. Also discussed is Birkhoff’s Theorem, which states that every doubly stochastic matrix is a convex combination of permutations matrices, which relates matchings to matrices. The text is lively and includes a number of well-researched asides, such as the origin of the name “The Hungarian Method.” However, there are some problems with forward reference: for example the reader is asked to work a couple of exercise (2.4.5 and 2.4.6) using the Binet-Cauchy formula, which isn’t discussed at length until chapter 6.

Chapter 3: Partially Ordered Sets and Lattices

This chapter begins with a very exciting presentation of the Möbius Function (the convolutional inverse of what is essentially the indicator function of a partial order). It is a real pleasure to see this material well presented in a general lattice setting, instead of the more common and specialized number theoretic setting. The chapter moves on to chains (ordered sequences in lattices) and anti-chains (sets of incomparable elements) in partial orders. The authors present Dilworth’s theorem which states that every partial can be covered by a number of chains no larger than the size of the largest anti-chain.² The chapter continues with Sperner Theory, which relates counting anti-chains to binomial coefficients. Chapter 3 concludes with valuation rings and Möbius Algebras: a transition to the more algebraic style found in Chapter 4.

Chapter 4: Generating Functions and the Umbral Calculus

This is a key chapter. The book introduces the Umbral Calculus, a transform space automating the manipulation of generating functions. The algebra of delta operators is introduced, which provides an abstraction of differentiation. Finally co-algebras are explored, which abstract the processes of factoring.

A rare (and unfortunate) typo on page-190 mis-defines a basic sequence for the delta operator as obeying instead of the correct equation: . A careful reader can spot the mistake as it is inconsistent with the the subsequent demonstrations and uses.

Chapter 5: Symmetric Functions and Baxter Algebras

This chapter treats a number of important algebraic topics. Symmetric functions are studied and identified as being the obvious class of functions that contains all of the well know generating functions already studied. Pólya’s Enumeration Theory, which is the method of counting the number of equivalence classes of distinct arrangements, is given a very interesting exposition. But the book skips the classic examples and exercises, such as counting the number of ways to construct distinct necklaces from colored beads, that would be needed for the topic to be fully approachable. Baxter Algebras, which abstract both summation and integration by parts, are introduced and via a study the sequence shift operator. By this point the book has abstract versions of both differentiation and integration, providing a combinatorial groundwork to prove theorems on “the calculus” that are more general than is possible in any one theory of differentiation or integration.

Chapter 6: Determinants, Matrices and Polynomials

This chapter is most similar to classical polynomial invariant theory, the study of symmetric functions of the roots of polynomials such as the discriminant. A major theme of this chapter is the study of the relations between properties of polynomial coefficients and the locations of roots of the polynomials. The study of matrices brings us to the remarkable Binet-Cauchy Formula for the determinant of a product of matrices. The results are deep, but it is a shame that more time isn’t spent on simple concrete applications such as using the Binet-Cauchy formula to count the number of spanning trees in a graph. This chapter reveals the parts of combinatorics that come from analysis and the study of locations of roots of polynomials (via group theory), in contrast to the parts that come from enumerating finite sets, linear algebra and abstract algebra. This is also the chapter where the exterior algebra, a favorite tool of Rota’s, is most discussed.

A typo on page 275 (a potentially confusing comma in the definition of the operation) can be recovered from because the authors have the nice habit of explicitly calling out the domain and range of functions.

Opinion

Some important questions about this book are: is Gian-Carlo Rota a coauthor, what is the purpose of the book and who is the best audience?

Gian-Carlo Rota seems appropriately labeled as a co-author, as clearly a lot of his work went into the book. The book is not suitable to be used as an introductory text book or as a reference. It is a book meant to be read. The ideal audience is capable of graduate level mathematics, is comfortable with a high degree of abstraction and algebra and is already familiar with many of the structures and techniques of combinatorics: sets, graphs, matrices, alternating sequences and generating functions. A mathematician or computer scientist wanting to learn more about the science of combinatorics will find a good read here.

The book works best as a second read of the topics covered. If you already know of a combinatorial method, like Pólya’s Enumeration Theory, this book is a good place to find the starting point for an alternate and powerful treatment of the topic. The book admits to not being self contained, and has a few forward-reference problems. However, this is forgivable when you realize the goal of this book is not to teach some easy discrete mathematics before you move on to analysis, but to extract the important combinatorial methods and themes from all of mathematics.

The content is well written, very accurate and well edited. The index is good, but not quite up to the job. The bibliography is very good and divided into three useful sections: papers by Gian-Carlo Rota and coworkers, books for further reading and a section of references.

We close with a extract from the book at hand. Many mathematicians have used the phrase “merely combinatorial proof” as a phrase of dismissal. However, when properly founded, combinatorial proofs are in fact more general than proofs that depend on additional specific details from the original problem domain. The authors take some justifiable pleasure in including points like: “Hilbert’s basis theorem is equivalent to the ‘trivial combinatorial fact’ given in Gordan’s lemma.” This is certainly a taste of combinatorics the Rota way.

Footnotes

….¹

For this use the binomial theorem to expand , differentiate with respect to and then substitute in .

… anti-chain.²

From this they derive just about the only Ramsey-theoretic style result in the book: any large partial order must have a large chain or large anti-chain.

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Q: What is the difference between a banker and a trader?
A: A banker will try and tell you a 10% loss followed by a 10% gain is breaking even.

This is a bit less arcane than some of the issues we usually discuss on the Win-Vector Blog, but it is a fun one. And it does take some effort to disabuse yourself of the banker’s fallacy.

It turns out that a lot of our instincts about something as simple as ratios is not quite right. Likely this is because the innate skills of counting leads to a deep understanding of addition and not of multiplication. Take for example the opening joke: a 10% loss followed by a 10% gain sounds like it should be exactly breaking even. But in fact it is exactly a 1% loss.

To compute the loss and gain on $100 we would say after the 10% loss we have $100*(1-0.1) = $90. A 10% gain on this remaining portion would be written as $90*(1 + 0.1) = $99 which, as predicted, is missing a dollar. An incorrect explanation would be something along the lines “well the loss was first, so it applied to a larger number than the gain.” But relative losses and gains work by multiplying and therefore is insensitive to order. It is a fact that a 10% loss followed by a 10% gain is exactly the same as a 10% gain followed by a 10% loss (which eliminates the attempted explanation). The correct explanation is the flaw was far earlier than you would think: you should not believe that the opposite of 10% loss is a 10% gain. To undo the effect of a 10% loss you need just over an 11% gain (a 11.1111111% gain).

For a more dramatic example consider the Dow Jones Industrial Average. It was at $12827 on January 7th 2008, by March 5th of 2009 it had fallen to $6594 or a 48% loss. By January 4th 2010 it had experienced a 60% gain relative to March 5th 2009- but that only got us to $10583, still a 17% loss relative to January 7th 2008. The opposite of 48% loss is in fact 192% gain (which obviously has not happened).

Bankers typically quote interest rates as if they were additive. Things like points and fees are all added. This is almost correct for small interest rates. This nearly right (but actually wrong) language is why we have a bestiary of confusing terms describing interest: simple interest, compound interest and yield. The bankers need some way to signal which numbers will actually be used for computing your mortgage payments versus which numbers will be used for advertising (and in the US they tended not to tell you many of the more important numbers until they were required to by law).

Traders, on the other hand, are very comfortable with multiplying relative losses and relative gains. The main trick of achieving such mastery is to convert multiplication into addition. The way to do this is the log() function (or the logarithm).

The log() function is simple function that has the property that log(a*b) = log(a) + log(b). For connivence lets pick our notation so that log(10) = 1. From this we can deduce that it must be the case that:

log() can not be used on zero or negative numbers (at least not if you expect a real number as a result). For other values we use our calculator.

A trader uses logarithms to think additively about relative changes (also called “returns”). Breaking even is represented as 0 (our friend log(1)), relative increases are represented as positive numbers and relative decreases are represented as negative numbers. For example a 10% loss is represented additively using logarithms as log(1- 0.1) = -0.0458. Now in this logarithm notation the additive opposite of a -0.0458 is in fact (as you would hope) +0.0458. You can even double check: log(1 + 0.1111111) = 0.0458. In this notation the mathematics and the language work together- the opposite of a loss is a gain with the same magnitude (and positive sign).

Returning to our initial example: a 10% loss is represented as -0.0458 and a 10% gain is represented as log(1 + 0.1) = 0.0414, so if we add them (how we combing operations in the logarithmic notation) we get -0.0044. Notice this is not zero, and is in fact equal to log(0 – 0.01) or a net-loss of 1%.

The point is that even trivial math becomes difficult if you are forced, by language or convention, to work from false premises.

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The frenzy of anticipation and opinion about “The Cloud” is so intense and so pointless it becomes “parody proof.”
It is as Jerry Holkins and Mike Krahulik wrote (regarding a different situation):

It’s like trying to make fun of a clown. What, are you going to make fun of his tiny car? His floppy shoes? It just doesn’t work.

I would like to point out that (by computer science standards) the cloud is not new and has for some time been considered inevitable.

But what is “The Cloud?” What the cloud is depends a bit on what conversation you are being drawn into. If the conversation is about computing then the cloud is remote computers, software and services like Wikipedia, GMail, SalesForce.com, Google Docs, Amazon EC2/S3 and Google App Engine. If the conversation is about human interaction then the cloud is ecosystems like Facebook, Twitter and RSS. Each of these are facets of important longer term trends, but for individual companies and technologies the pendulum is about as fast on the down-swing as it was on the up-swing. At this time we can safely declare a number of recent important players dead: Friendster, AltaVista, WSDL, Usenet, IRC and Web2.0.

It is true that the network itself is more useful than the computer, but this idea is not new to our third millennium. The current people getting rich promoting this idea did not invent this idea, they grew up in its shadow. The early big thinkers on computers had big plans. Plans much larger than Tetris, payroll processing, COBOL and punched cards.

Take the article “As We May Think” (by Vannevar Bush, The Atlantic Monthly (1945)). In it Vannevar Bush writes:

Consider a future device for individual use, which is a sort of mechanized private file and library. It needs a name, and, to coin one at random, “memex” will do. A memex is a device in which an individual stores all his books, records, and communications, and which is mechanized so that it may be consulted with exceeding speed and flexibility. It is an enlarged intimate supplement to his memory.

At first this sounds like nothing more than “Danny Dunn and the Homework Machine” (by Jay Williams (1964), Scholastic Press)

.

But in his essay Vannevar Bush uses the phrase “it can presumably be operated from a distance” and ends his essay with a long section of how many professions would benefit from a Memex (we show here only one):

Wholly new forms of encyclopedias will appear, ready made with a mesh of associative trails running through them, ready to be dropped into the memex and there amplified. The lawyer has at his touch the associated opinions and decisions of his whole experience, and of the experience of friends and authorities.

Obviously we are reading this with a modern eye, but here we have the antecedents of hypertext and the Wikipedia.

We can trace this thread further forward to “Augmenting Human Intellect: A Conceptual Framework” (by Douglas C Engelbart (1962)) and the famous 1968 demo.

And we can further trace the ideas passing through: “Literary Machines: The report on, and of, Project Xanadu concerning word processing, electronic publishing, hypertext, thinkertoys, tomorrow’s intellectual revolution, and certain other topics including knowledge, education and freedom” (by Ted Nelson (1981), Mindful Press, Sausalito, California.)

These works were all about knowledge engineering, information storage, networking and communication. There was an extreme urgency in these works. Both Engelbart and Nelson felt we had a limited window to gain the ability to organize the world’s information before some catastrophic error or misunderstanding eliminated us all. This feeling of urgency and doom came from another exciting application of real time networked computers: SAGE. SAGE was the “Semi Automatic Ground Environment” first made operational in 1959. It involved networked computers, light pen based operator terminals and was the system that the United States had ready to fight World War III.

This was the era of near infinite budgets, block sized computer complexes, massive mainframes and IT priesthoods that ran the whole show.

The inevitable march was on. Some large fraction of the GDP would be forever dedicated to building and maintaining monument sized networked computing facilities. Your degree of relevance and power in society would be directly determined by how close you could get to these facilities. Then something happened and distracted everyone. The distraction was so immediate and so complete that by the time the inevitable march restarted (block sized Google data centers and a proposed Yahoo data center to be built attached to Niagara falls) everyone thought it was a new thing.

What happened was the 1958 demonstrations of successful integrated circuits. This and the transistor started an era of micro-miniaturization that took the world by storm. By 1971 Intel had released a single chip CPU (the 4004) as a commercial product. This chip implemented the core of a computer in a fingertip size package that contained 2300 transistors.

From here on everything was desktop calculators, pocket calculators and digital watches. And then the personal computer and the personal computer revolution hit.

IBM kicked the PC revolution into high gear when they pushed into the market in 1981. The personal computer was a supreme distraction that pulled attention away from the monolithic computers for fifteen years. And for a long while networking and shared information were both nearly forgotten. Computers were for spreadsheets, desktop publishing and other non-networked tasks.

However, out of public view the monolithic network continued to develop. The Internet was started as ARPAnet and grew connecting universities and defense contractors from 1969 through now. The messaging formats (it is inappropriate to use the more common term “technology” to describe HTTP and HTML) we call “The World Wide Web” were invented (without much fanfare) in 1989. Netscape was founded in 1994 and made the World Wide Web and Internet available to the PC. And then the Internet hit like a Tsunami. Electronic commerce and speculation funded the the initial burst. Then on-line advertising took over and we are back to building new encyclopedias, tracking everyone and once again building city block sized computers (now called data centers).

Once again we are being told our data is too important to be locked in our desk (or PC) and everything is migrating back to the mainframe (now called “the cloud”).

Will the cycle reverse? If applications are moving into the cloud now will they ever move back out?

Moore’s law has a way of shrinking things (a current smart phone outperforms many early mainframes, super computers and data centers). Will individual PCs once again be more important than the network? Some of the more useful parts of the Internet (like the Wikipedia) are small enough to put on current PCs. The data centers and networks will not go away any time soon, but excitement and attention could move on to something else. Devices that you could carry everywhere and that have intermittent or expensive connections to the Internet might have an advantage in being able to cache some of the Internet. And excitement follows what is new, so a stable pervasive cloud would likely be taken for granted (like roads, power, telephone and other utilities).

Another thing that could migrate applications back out of the cloud (assuming they migrate in) is if access to the user becomes too important to delegate to the cloud. eCommerce applications take user access when they can get it, but many other applications may depend more on immediate access to the user than on grabbing fresh data from the network. For example a pacemaker is likely to run most of its application from an embedded computer- this computer might talk to the cloud when it can, but the application will be designed to stand alone as long as possible.

In the end evangelizing the coming triumph of factory scale computing and networking is pointless. It is already here and has no great need for cheerleaders.

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I have two areas of concern.

My first concern is: what is going on with the ads on Google search? Are they safe to click on? Check out this ad (from a Google search page):

Where do you think the link would lead to if you clicked on it? First guess: “www.dmb.com/duns” which is further labeled “Official Site.” This sounds like we would directly link to the venerable company “Dun and Bradstreet.” This is not the case. The text and the green site are apparently part of the ad. Hovering the mouse or capturing the link yields the following huge and hard to decipher URL:

http://www.google.com/aclk?sa=L&ai=CwmvMvAVpSsyeDpvusAO4y5D8D5aTi3qAv83oDPXK5f0CEAEguVQoA1Dw0pOr-_____8BYMn2-IbIo6AZyAEBqgQdT9AhbH2fVXmJHnIy-TNNj_HkY7JsaGV106RyaVw&num=1&sig=AGiWqtwX5zxePZHhDkpqJBojcybMzKkFSw&

q=http://track.did-it.com/n%3Flid%3D13619863%26tid%3D3fe34bfe02723%26eng_creative%3D3345771492%26eng_keyword%3Dd-u-n-s%2520number%26eng_placement
%3D%26url%3Dhttp://smallbusiness.dnb.com/webapp/wcs/stores/servlet/SmbHome%3FstoreId%3D10001%26cm_mmc%3DGoogle-_-Adword-_-online-_-d-u-n-s%2520number%26LID%3D13619863

Can you anticipate where this goes? You can see the following three URL fragments inside the URL:

• http://www.google.com/
• http://track.did-it.com/
• http://smallbusiness.dnb.com/

Reading from left to right you can be pretty sure the URL goes to a Google server that uses the rest of the URL as an argument. We can then assume that this Google server performs some bookkeeping and redirects to http://track.did-it.com/ . We can then further assume that track.did-it.com performs some more bookkeeping and redirects to http://smallbusiness.dnb.com/. Notice the first non-Google URL does not match the advertised URL. We don’t know what is encoded into each of these pieces and we are only assuming the track.did-it.com server unpacks the URL from the argument; maybe that is a red herring and it redirects us to somewhere else entirely.

Frankly I have no idea if this really happens. I do know from experience that Google did re-direct to track.did-it.com because my anti-spyware traps caught this, blocked the page load and issued a warning. This sort of thing could be a very irritating late night call from Mom- she gets a web-safety warning (anti-phishing, anti-virus, cookie request or something else) from a site she is not on, she is not loading inclusions from (images, scripts, iframes and so on) and she is not knowingly clicking on.

Is there a finite list of partners that Google allows to re-direct? Can anybody do this? Can I produce and place ads with arbitrary redirections?

My second concern is: do you even need to click to leave the Google search page?

Check out what happens with a fresh copy of Mozilla Firefox (no plugins and nothing added to the browser) when you search for “Bing” on Google:

Let’s look at that pop-up a little closer:

Why would www.bing.com get a chance to set a cookie? Doesn’t that only happen in response to a request from my copy of Firefox? Did some script on the Google search page or some obscure “web acceleration” option in Firefox pre-fetch the content of the first Google link or first Google Ad (triggering the cookie request)? Let’s not worry too much over cause (Google is the major funding source for Firefox), but look for possible effects. Does the destination site (Bing) see traffic from the Google page even if the user never clicked on the link? Something like that would inflate the already huge stature of Google as a traffic source. How much of my site’s “web traffic” comes from phantom clicks (from abandoned searches)? Finally, how safe is it? How much more than the cookie is being loaded? What if the site linked to has malware- is this a no-click infection route?

Some of these subtle features are necessary to support an ad network. But the implementation does not seem minimal. Allowing hosts to differ from ad content and performing a pre-fetch with every search both expose searchers to additional risk.

EDIT:

Found the prefetch. A Firefox tag that Google knows to set (see What is firefox prefetching?)- and sure enough if I perform Google search using Firefox we see:

<link rel="prefetch" href="http://www.bing.com/">

(and I don’t see this tag when using Safari).
So that is the mechanism- still wondering how much risk this is to users. Also wondering how much this skews traffic statistics into Firefox’s and Google’s favor (I haven’t seen the prefetch tag on Yahoo search or Bing search).

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Microsoft has tried retail outlets before. So we have some knowledge of what to expect.

In particular I am thinking of the Microsoft store that was part of the new San Francisco Metreon Mall (opened in June of 1999). At the time Microsoft had no good reason to produce such a store. They were not ready for a major consumer product push and didn’t release the original Xbox until 2001 or the Zune until 2006. This era was also a gap in their consumer operating system release cycle (Windows 98 was already out, Windows ME didn’t come out until Q2 2000 and Windows XP Q3 2001). In 1999 there still were Gateway computer retail stores and Apple Stores were still two years in the future. This Microsoft Store satisfied no discernible need, promoted no major strategy and was deservedly forgotten. From their own press release the purpose of the store was to sell “more than 90 items of apparel, desk accessories, office supplies and other items with the microsoftSF logo” ( see presspass). A fairly low marketing ambition- which predictably failed.

Fast forward to 2009. A Microsoft store could work, if Microsoft were willing to make a good one. I doubt they are willing. Likely they feel hey can easily cut themselves a lucrative slice of retail pie (now that they have major consumer products like Xbox, Zune and Windows Media Center). This will fail- these are all significant products, but together they don’t make for an interesting store or cohesive shopping experience or lifestyle pitch.

Instead, imaging the following store.

• A Microsoft store where a competent sales staff sells major brand PCs (like a Sony, HP, Leveno and so on). But for a small mark-up they wipe out the manufacturer’s defective Windows install and spyware. They install a clean full version of Windows 7 (or Windows XP). A store where they consult with you and which version of Office really is best for you and then sell and install this.

Even I would go there (and I use Apple OSX and Linux almost exclusively). Microsoft is too big an ecosystem to ignore. We need to be able to buy mainstream (and that means Microsoft) PCs, operating systems and software packages at retail (and not just at box stores).

Let me illustrate my point using the last time I purchased a PC. After an hour of trying to deal with Leveno’s atrocious web-site (they really do not want to sell computers retail) I got up and drove to the Metreon Sony Store and purchased a Sony Vaio.

Here is what happened:

• The Sony Vaio could not handle the Vista it came installed with.
• The Sony Vaio came without restore media- making a clean re-install of the operating system impossible.
• The Sony Vaio came laden with all kinds of crapware (trial anti-virus software, Internet poker offers).
• I (later) spent around $400 on Office Professional just to find out I could not uninstall enough of the Sony demo version of Office to get rid of some sort of killing dependence on “Contact Manager” (some sort of enterprise wide service that a home PC would not have).
• I purchased two old copies of XP. I used one to reformat the Vaio and donated that to my father in law for web-surfing. We then used the other copy of XP to host Office Professional (which we really wanted and needed) inside a virtual machine on a hand-me-down Macbook. End of Microsoft Windows (outside of virtual machines) in our household. If Windows can do something good we now have no way of seeing it (since we now only run Windows inside a virtual machine, which is unfair to Windows).

A careful reader would say “this is unfair, it was Sony that was bad not Microsoft.” That is correct. But there really (right now) is no way for an individual consumer to directly deal with Microsoft. Eliminate some of the wall of stupid between me and Microsoft and I probably would use more of their products.

Here is what I (and probably most other consumers would pay big for).

• A Microsoft store that re-sells major brand PCs (Sony, HP so on) that have been opened, re-imaged with a clean OS from Microsoft (not the evil OEMs) and given out with install/restore media.
• Ability to buy a copy of Office Professional that will work on my PC. Here is my proposition. I drop off my PC and $400, next day I come back and take back only the PC and I have a copy of Office Professional that works and isn’t whining about a bunch of unresolved dependencies to servers and services I do not own. I also need to know which version of Office to get (and I know it may cost more than the cheapest one) without reading some impenetrable “enterprise white paper.”
• A store with a staff that lets me safely say “I don’t know Dad, maybe you should take it back in to the Microsoft Store.” I’ll pay. I’d buy training, support, warrantees, read marketing materials and try product demos

Again, a careful reader would point out that all of these activities are labor intensive and going to be very low margin. This too can be fixed. Once Microsoft installers are wasting Microsoft’s time and money (instead of wasting my time and money) the installers will be fixed. Installing Microsoft Office could be come as easy as selecting a new application in Ubuntu (my current gold standard in easy installs).

I would welcome and support a good Microsoft retail effort, I just don’t believe one to be very likely.

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• Special Agent Michael G. McSwain’s charges
• Mathew Goldstein’s Reuters article
• Zero Hedge blog entry

For me this triggers some strong (and sad) personal memories.

No matter what inappropriate “Robin Hood” intellectual property fantasies you have this (if true) is just wrong. I have never been a huge fan of the ACM Code of Ethics (which does cover this situation, but fails to seriously address much beyond having responsibilities to your employer) but this sort of incident reminds me why computer science needs some approximation of a shared set of ethics that we can try to refer to.

A particularly sad part of the story that attracted my attention was the reliance on “bash history” to try and establish what happened. Attempting to “prove” something using a “bash history” is something I have painful experience with. The “bash history” system is incredibly inadequate even for what it was designed for (caching recent commands). Simply having two shells open can cause non-deterministic overwriting, deletion, clobbering and time disorderings in the history file. Furthermore bash history has no dates, times, directories or any other contextual hints written into it. Finally bash history has no hashes, signatures, nonces, sequence numbers or any other device that helps establish authenticity.

Now for my story. We (by chance) caught somebody walking off with our group’s entire source tree. In the end all we had to go on was the bash history. To hostile eyes bash history is nowhere near what you would call “forensic grade evidence.” Unfortunately for us the theft was intramural, the thief was merely taking the code to another group in the same company to later mine and represent as their own work. At this point even language worked against us- every time we accidentally said something like “our code” (as in the code we produced, not the code we own) we were perceived as being anti-company. Evil prevailed (the thief was promoted) and I looked stupid for working so hard to try to interpret such low-quality evidence. But we live in an objective world- just because you can’t prove something doesn’t mean there isn’t some buried ugly truth.

So what was stolen? Not the code, that moved from one pocket of the corporation that owned it to another pocket of the same corporation. What was stolen was reputation. The thief presumably appeared to out-produce both his old colleagues and his new ones (who don’t have a few absconded person-years of development to draw from). So an apology to anyone who was asked why they could not code as fast as our escaped “genius,” it was certainly not our intent to so equip him. And a larger apology to the rest of the team, sorry we could not prove the misappropriation of your work.

Of course Shakespeare said it much better (from Othello):

Good name in man and woman, dear my lord,
Is the immediate jewel of their souls:
Who steals my purse steals trash; ’t is something, nothing;
’T was mine, ’t is his, and has been slave to thousands;
But he that filches from me my good name
Robs me of that which not enriches him
And makes me poor indeed.

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But researchers in other fields are not always so good about making copies of their papers easily available, and older classic papers (say, for example, Bradley Efron’s 1979 Annals of Statistics paper on the Jackknife) are often still worth reading, but are not always easy to find. Where to go?

This is a list of some resources that I’ve discovered over the years. The list isn’t comprehensive, by any means, but I offer them here because maybe you will find them helpful, too. The list, and my opinions, are biased towards research in the mathematical and computer sciences, but many of these resources are potentially useful for any research area, including the humanities.

JSTOR

JSTOR is a digital archive of over one thousand scholarly journals, covering topics in the humanities, social and physical sciences and mathematics. I love JSTOR. It is an incredibly useful resource, containing the full contents of every issue of every journal in their collection up to within 3-5 years of the present time (it’s a moving wall). The collection is full-text searchable. I use JSTOR to find classic papers in Math, Statistics, and Computer Science, as well as more recent papers that have been published in journals that are otherwise not available to me.

Access to JSTOR is available to members of participating institutions, mostly universities, but also many public libraries. I have access to JSTOR free with my San Francisco Public Library card, via the SFPL website. (I believe that any resident of California is eligible for a SFPL library card with proof of California residency; good news if you are in California and your local library doesn’t subscribe).

As a side note, San Francisco Public Library subscribes to several quite useful digital research services, including FirstSearch, the OED, Encyclopedia Brittanica, and Morningstar. Some of these other services also provide access to selected full-text articles. SFPL also participates in ILL (Interlibrary Loan) and Link+, a similar cross-library loan service. All good reasons to support your local library!

ArXiv

ArXiv is a pre-print server hosted by Cornell, serving pre-prints of papers in Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance and Statistics. Many important researchers use ArXiv to get around the fact that major journal publishers insist on holding the copyright to articles published in their journals. “Pre-prints” haven’t yet been published, and hence the authors are free to distribute them freely. Fields Medalist Terence Tao regularly distributes his about-to-be published work through ArXiv.

On the other hand, ArXiv has very open submission policies, so you should be more careful of the papers you find here than you would be with a refereed or curated source, such as JSTOR or PubMed Central (which we will discuss later). ArXiv has, unfortunately, more than its fair share of what Augustus de Morgan used to politely call “paradoxers“. The “Journal Reference” field of the article summaries will generally give you an indication of whether or not the paper is legitimate, in the sense of having been peer-reviewed; but note, for instance, this paper on a polynomial-time algorithm for Traveling Salesman (the Traveling Salesman problem is provably NP-complete, so a result of this magnitude would win the Clay Millennium Prize, if true).

Another side note: I’ve linked to the Amazon page on de Morgan’s Budget of Paradoxes because that was the first synopsis I found. The copyright on the book has expired, so if you are actually interested in reading it (it’s fairly funny, in places), you can find the full version on Google Books or Project Gutenberg.

CiteSeerX

CiteSeer was the original search engine and archive for online technical papers; it got me through graduate school, and my first post-PhD position at SRI. I don’t believe that the original CiteSeer system is still active, but its successor, CiteSeerX, is being developed and hosted at Penn State. It concentrates on computer science literature, as did the original. CiteSeerX builds its corpus by webcrawling, so again, the papers it finds are not necessarily refereed. Like its predecessor, CiteSeerX search results include the paper’s abstract, a BibTex citation, a list of the paper’s references, a pointer to the paper’s original location, and (usually) an archived version of the paper, in case the original link has gone dead. Good stuff.

AccessMyLibrary

AccessMyLibrary is a service that pools the periodical resources of several libraries across the United States. Any article in a periodical held by a participating library is available for free download to anyone who holds a library card in any other participating library. I find this service less useful than JSTOR: the holdings are generally newspapers and popular magazines, although there are some journals represented, as well as law and business reviews. The download format strips all of the original formatting from articles, which makes them rather ugly and a bit harder to read. I think you lose the figures, too. Still, it’s free if you have a library card, and it’s a good place to search for an article if you can’t find it anywhere else.

Questia

Questia is a for-pay service that claims to have “the world’s largest online collection of books and journal articles in the humanities and social sciences, plus magazine and newspaper articles”. Their collection is full-text searchable and, as they say, “you can read every title cover to cover”. Good luck doing so, though — articles and book chapters are not downloadable. Instead, you have to read them through Questia’s online interface, which is pretty clunky. On the plus side, they allow you to build your own “bookshelves” to collect books and articles that are relevant to you by topic or project. You can bookmark key sections, and highlight key passages. I used Questia when I was involved in research projects with psychology and organizational science aspects. I could get hold of articles or textbooks that I wanted to look at faster than through Interlibrary Loan, and more conveniently than going down to Stanford. The subscription fee at the time was cheaper than a membership to the APA or buying the articles piecemeal from Elsevier, or whoever.

Currently, Questia’s subscription fee is $19.95/month for full library access; you can also subscribe to specific collections (such as Psychology, Literature, or Philosophy) for $9.95 per collection per month.

Mendeley

Another way to find useful literature is to connect with other people out there who share your interests. Mendeley is a tool that allows you to organize your collection of research papers, share it with colleagues, and to peruse the collections of other researchers with similar interests. I haven’t used it myself; but a friend of ours who is an active and influential AI researcher recommends it. It’s certainly worth a mention.

PubMed Central

PubMed Central is a free digital archive of biomedical and life sciences journal literature, sponsored and managed by the NIH. We don’t do life science research here at Win-Vector, but I’m mentioning PubMed because of this awesome policy by the NIH:

NSF and DoD should institute similar policies, too.

Google Books, Google Scholar

Yes, they’re out there. Personally, I find them less useful than JSTOR or a subscription to (say) IEEE Explore. Google Scholar generally returns the abstracts of articles at sites that don’t provide open access to the full-text article, such as the website of the journal that published the article, or the website of a restricted research archive, like the ACM. This is useful, in that it tells you that the article exists, but it’s rather frustrating, too. I don’t find Google Scholar to be significantly more helpful than doing a general Google search on the same keywords. On the other hand, some people swear by Google Scholar, so obviously your mileage may vary.

Google Books has a very annoying habit of returning hits on your search terms, then not giving you read access to the page in question. Useless. If you happen to be doing research in an area where older books in the public domain are still of interest (for instance, my amateur interest in folklore and mythology), then Google Books can be quite helpful; of course, this situation is generally not true in technical research.

Offline: Your Local University Library

Here in the Bay Area, we are fortunate because the Stanford Library System has generous visitor access policies. The visitors’ policy statement is here; briefly, non-Stanford visitors are allowed 7 courtesy visits per year, with no borrowing privileges. For more visits, you can purchase an access card. I used the Stanford Libraries when my company was down in Mountain View, and I’m grateful for their openness. I don’t think many universities are as generous as Stanford is, but if you are near a university campus, it doesn’t hurt to check. For instance, the University of San Francisco will sell access cards to their library, with or without borrowing privileges, to non-affiliated visitors (it ain’t cheap), and allows practicing California attorneys access to their Law Library. San Francisco State has a Friends of the Library program, whereby non-affiliated visitors have access and borrowing privileges to the CSUSF library collection for $45/year.

And there you have it. Research away!

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As more of our life becomes digital (work, finances, passwords, pictures, contacts,dairies,videos and email) we must be more diligent in backing up our data. If your hard drive fails at work you might lose some spreadsheets (and you might not lose anything if your IT department is on their toes) if you computer fails at home you lose your wedding album. Your hard disk will fail and try to take all of your data (life) with it- it is a matter of when not a matter of if. You want this to be an inconvenience, not a disaster. Become expert at backing up and take the time to help others.

First some definitions. Everything stored on your computer is called “data” and it is most commonly stored on a single “hard drive.” The act of making an extra copy of your data is traditionally called “backing up.” The act of trying to get access to your extra copy of your data is traditionally called “restoring.” The whole point of backing up is to be able to restore. If you can’t get your data back it really doesn’t matter what steps you took. Backing up with no ability to restore is just cargo cult behavior.

If you have a professional service available they will likely do a better job than you can (this is one reason that larger businesses have professional IT staffs). However, at home you are likely on your own.

This is an opinion piece and I am advocating backing up everything (whole drives) locally. If you do not back up everything you will need to choose what to back up and what to skip- and you will make mistakes and lose things. If you do not have a local back up, you might not be able to restore (back up service goes out of business, internet connections are still too slow to be practical). At the very least you should have a local back up; a remote back up is a good second step. Remote back up services are a good idea for important data and there are some high quality ones, but a few have gone out of business (Xdrive) so do not want one to be your only chance of salvation.

Let us first address a technical issue- what sort of set-up are you backing up? The three most common situations are: Windows, OSX and other Unix (Linux/BSD, yes I know OSX is a Unix). Each of these have different appropriate tools:

• Windows:

  For Windows Home type operating systems you are unlikely to have access to Microsoft’s back up tools (which is a real shame, the tools are more useful at home than at a business). So you need to install something.

  I have not researched the Windows world extensively, so I can not give advice. I can, however relate my experiences and current policies.

  I now avoid EMC Retrospect (often comes free with USB drives) at all costs. My experience has been that EMC Retrospect is hard to use to restore your data (the whole point of backing up). For me it often refused to run (due to licensing issues) and it was very sensitive to the exact version of the Microsoft.Net framework that was installed on my Windows system. Two separate times an update in the Microsoft.Net system rendered EMC Retrospect unusable (and broke nothing else).

  I have happily purchased Acronis True Image three times now (twice for myself and once for a friend). Their website is a bit confusing (you must be careful to get the retail product, not the many thousands of dollar enterprise product). The software seems to be very good. It can back up, restore and can even read data from an “image” (which means you can get to your data with out even restoring).

• OSX:

  An embarrassment of riches:

  The free options include following Jamie Zawinski’s wonderful advice (which I am shamelessly stealing from here) , using the free copy of SuperDuper! (which is very good and a complete back up solution even in the free version) or Time Machine (the back up utility included in the current Mac operating system: Leopard).

  One huge advantage of modern Macs is if you have formatted your drive correctly you can boot off a USB drive. So if you use the above instructions you can plug your back in and use it to run (delaying your need to open up your machine or attempt a restore until later). This is also important in rehearing your restore procedures.

  Finally, if you have the cash there is the somewhat over-priced (but wonderful) Time Capsule. You can live without Time Capsule, but it is part of my “dream set up” (described below).

• Unix:

  Follow any sort of advice on how to script back ups (such as Jamie Zawinski’s) and you should be protected. Rsync is a great tool.

More important than the back up tools is having a precise back up goal and a matching back up plan. I use my own goal and plan as an example and you can use it as a basis for safer or more risky plans (depending on your resources and needs).

My goal is to: (with very high probability) not lose more than a week of my life. The plan to achieve this is a full local back up every week and the willingness to buy some new equipment if I have to do a restore. A failure could delay my work for a day or so, but not put me out of business. For my business it does not make sense to ensure “no down time”- this is an unreasonably expensive thing to try to achieve (and the inappropriateness of this goal is one reason many people have no back ups at all). My worst case “restore” plan is to drive to a store and buy the cheapest temporary computer. A more likely case is I just need to use one of my extra drives to do my restore (very cheap). I would then restore the back up onto a fresh drive (or the temporary computer) and work from there until I could repair or replace my major system.

My back up plan has several “eyes open” weaknesses. I only back up every week, so I could lose a week’s of data if my disk dies right before a back up. Also, to restore my data could take a day and $500 (trip to store to buy a temporary computer and hours to restore drive contents). Knowing these weaknesses are the point of the back up plan: I am trading hoping that my drive doesn’t blow up and take all of my data away for hoping my drive doesn’t blow up and cost me a day of work and few hundred dollars. That is I am trading the Sword of Damocles for worrying about something like stubbing my toe. Drive failures while inevitable are not frequent. if I put a quarter in a jar every day I don’t have a drive failure I would more than likely have the $500 needed to perform an emergency restore saved up long before I have a drive failure. By not purchasing excess extra equipment (computers) before the failure I save money by maybe not having to purchase it all or at least purchasing cheaper and better equipment at the time of failure (instead of now).

Now to describe my implementation of my plan. First I purchased the following
things:

• Time Capsule (optional):

  

• Thermaltake External Hard Drive SATA Dock ($40 : Newegg):

  

• Two 1TB drives ($90/each Newegg, these
  are the cheaper “internal” drives that go into desktop computers or into the Themaltake dock. If you don’t like the ugly you could skip the Themaltake dock and buy USB drives instead.):

  

So for a little over $220 I am in business. Every week I could take one of the drives out of its envelope, stick it in the Thermaltake dock and use one of the tools described above to create a complete back up. What I actually do is even better. Any time I want I ask my computer to use Time Machine to back up to the Time Capsule (typically takes about 20 minutes) and then once a week I stick a drive in the Themaltake dock and let the Time Capsule copy itself onto the drive (so both me and my computer are completely uninvolved in the 8 hours this step can take). For offsite back ups (to defend against things like fire) I can take one of the drives to a safe place off site (locker, safe deposit box). I recommend physical protection (locks, fire safes) to protect your drives (not encryption, there is a good chance you will get something wrong with encryption and not be able to restore).

Using Time Machine gives me the benefit of having multiple back ups so I can look at earlier versions of files and the speed of only needing to perform incremental back ups (only what has changed needs to be copied). Another way to get the advantage of having extra versions of all of your files is to put most of your files under management of a “source control system” like Bazaar. Systems like this (free, runs on Windows, OSX and Unix) let you keep all versions of all of your files (answers things like “what did I have in the file before I deleted it last week?”) and are incredibly useful (you will wonder how you lived without them).

Finally I end with some “defensive thinking” required to succeed with back ups. I have not said why I purchased two extra drives. This is so I can rotate which extra drive I back up onto. Drives most often fail when being used- so it is very plausible that my main machine could die while backing up. If the main machine dies while backing up then not only is its data lost but the back up is also useless (as the main machine was interrupted while trying to write it out). This is not quite ironic because while it is contrary to what you would want it is not unexpected. To be safe from a failure during the back up procedure you must have a second drive that is not being used. Only after the first back up is known to have succeeded can you then back up onto the other drive.

You must rehearse and think through all of your back up steps. If you are lucky you will find flaws in your plan during rehearsals instead of when you go to restore. For example tape back up procedures are notorious for writing out years incremental back ups that don’t work during a restore attempt. Use a system that allows safe rehearsals (such as trying to boot from a bootable back up or inspect a file from an Acronis image or Time Machine archive). Plans that only allow restores are not safely rehearsable (if the rehearsal fails you damage something on your primary machine). Also: if you are really trying to restore you are not likely to be in a good mood, iron out potential kinks with rehearsals not during a panic.

No plan is perfect- we can not cheaply eliminate all risk. In this case what we can do is eliminate exposure to likely scenarios. Data loss can still happen, but it is not inevitable.

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The manual subtly sold an incredible point of view: the engineer’s view. The manual appears trivial at the surface but is in fact a very good rhetoric pushing a fascinating point of view: you can infer things quickly. This led me to think about a number of technical viewpoints (engineers point of view, scientists point of view and lastly mathematicians point of view). They are all lumped together as “quantitative” but they are radically different.

Listen to this (from the beginning of the HP15C calculator manual):

Notice the emphasis on the physical activity of calculation. The emphasis is not on equations, mathematics or physics. The calculation is deliberately described as key strokes. No attempt is made to justify any of the steps or numbers used. The point being made is: if you are agile and ready (have the correct fore-knowledge) you can calculate. If you can calculate you can know things. Robert Heinlein made this point about slide-rules in his science fiction story: “Have Spacesuit- Will Travel.” And likely a similar joy can be felt while accounting on an abacus.

This is the engineer’s view: the world continuously gives up many small and simple clues as to what is going on around you. These are like “tells” in poker. You can reason from them and build incredible things using them. The smallness and simplicity of the techniques are pure comfort.

In Michael Lewis’s “Liars Poker” the author mentions a moment when he knows that everything he is being told about the market is a lie. He knows this because he attempts to converts one statement about the market into another using his calculator. When he attempts the conversion (figuring out something he was not supposed to know from clues coming from something he was told) it does not add up. Importantly he describes working this out on his calculator- not using a sophisticated computer model or a spreadsheet. He is comfortable in his heterodox position because he calculated it by hand in small and simple steps.

This joy in comparing one conclusion to another (using a calculator) differs from the idealized scientist’s view in that there is no derivation or application of deeper laws. The engineer’s view is: if you can remember it or guess at it then you don’t need to derive it.

Some of the great scientists (Enrico Fermi) and mathematicians (Stanislaw Ulam) became masters of the engineering view and could dazzle with it.

One of Fermi’s famous stunts was measuring the yield of a nuclear bomb test by observing how far scraps of paper were moved. Fermi may have worked from first principles, but he could also have used a simple pre-prepared trick. If he had observed how far scraps of paper had moved in an earlier conventional bomb test (which he now knew the yield of) and then applied a simple engineering trick called “dimensional analysis” that let him reason the amount of work observed (how far the slips of paper were moved) depended linearly on the bomb yield and decreased as the cube of how far away he was from the explosion. So all he did was compute the ratio of of how far the slips moved in each test and then divide this three times in succession by the ratio of how far way he was from the center of each test. Merely being able to divide told Fermi something (the new bomb yield) before he was officially allowed to know it. Notice how he did not need to use any facts about the bombs being tested, the speed of sound, atmospheric pressure, density or temperature.

Such reasoning may seem crude- but it is far more informative and far more exciting than the published work of many lesser scientists. The bulk of most merely poor scientific work (as opposed to outright wrong work) is of the form: “here are some pointless measurements I got by applying an expensive new instrument in exactly the situations the manufacturer designed it for.” Or “here are some manipulations that seem original since I don’t feel I have to cite any non-physicists.”

I side with the mathematicians (not the engineers or even scientists) and I think it is safe to say that mathematicians (who have their own particular view) are more sympathetic to the engineer’s view than to the scientist’s view.

One joke that has been told about me is that I am not happy at a presentation unless there is an equation on the board. This is typical of mathematicians. The excitement comes from the opportunity to “kick the times.” Once you remove enough details an equation is a simple statement of the form “A=B” (to borrow the title of a wonderful book by Marko Petkovsek, Herbert Wilf and Doron Zeilberger). An equation is a welcome moment of concreteness in contrast to the many painful abstractions that are necessary for much of mathematics. The dirty secret is that mathematicians perk up when an equation is on the board not because they like equations- but they are hoping to plug in values for “A” and “B” such that the equation is shown to be false. My branch of mathematics (theoretical computer science) is more a competitive than a cooperative field. One measure of audience interest in my field was if somebody to grab the magic marker out of your hand to try and write down a counter-example to what you were trying to demonstrate. Gian-Carlo Rota tells a similar tale where someone in a mathematical audience grabs the chalk and tries to complete the presentation.

One reason I side with the mathematicians and not the engineers is: if pressed too far the engineer’s view goes wrong. The way it goes wrong is found in the thick classic comprehensive engineering handbooks. These books attempt to store and systematize all of a given field’s engineering knowledge. Once you attempt to become comprehensive and are devoting all of your intellect to memorizing and applying the standard approximations and estimates you are lost.

I also do not side with the scientists because mathematicians have no sympathy for trying to “buy your way out of solving a hard problem” by running an expensive experiment. Mathematicians do work with data (even messy data) but we call this “application” not “proof.”

To me the best view is: if you can derive anything then you do not need to remember anything.

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