My paper On the Kolmogorov-Chaitin complexity for short sequences, coauthored with my PhD thesis advisor Jean-Paul Delahaye has been published as a book chapter in:RANDOMNESS AND COMPLEXITY, FROM LEIBNIZ TO CHAITIN, edited by Cristian S. Calude (University of Auckland, New Zealand) and published by World Scientific.

An extended draft version of this paper can be found in arXiv here and the webpage we have set up for our research on what we call Experimental Algorithmic Theory can be accessed here. The results of our ongoing experiments will be frequently published on this site.The book is a collection of papers contributed by eminent authors from around the world in honor of Gregory Chaitin’s birthday. It is a unique volume including technical contributions, philosophical papers and essays.

I presented our paper at the NKS Science Conference 2007 held at the University of Vermont, Burlington, U.S. The conference blog has an entry describing my participation.

From left to right: Hector Zenil, Stephen Wolfram, Paul Davies, Ugo Pagallo, Gregory Chaitin, Cristian Calude, Karl Svozil, Gordana Dodig-Crnkovic and John Casti.

Why research on the universality of the Wolfram 2,3 Turing machine (http://www.wolframscience.com/prizes/tm23/) and the small universal Turing machine  is relevant for modern computer science:

* New techniques for proving universality are being developed (Alex Smith’s novel approach for unbounded computations from arbitrary lengths and non-periodic initial configurations).
* Completely new universal systems have been discovered (cyclic tag- systems, bi-tag systems).
* Such research provides a better understanding of universality,  its limits, its  underlying principles and its necessary and sufficient conditions.
* It is a base for actually building universal devices when only a few elements can be used, e.g. in nanotechnology or molecular computation.
* Simple/small machines may be more easily/effectively embedded in other systems.
* The old discovery/invention duality question comes to the fore: It sheds light on how simple universality is, how frequently it occurs, whether  it is engineered or not, whether  one builds universal computation or finds it in the universe.
* It could shed light on the relative feasibility of  universal Turing machines based on different tape configurations (e.g. blank characters, repetitive words, non-repetitive with computationally simple backgrounds) as actual physical systems.  At present it is not at all clear why one ought to  favor blank characters over other possible real-world backgrounds, such as “noise.”
* Questions of size and complexity  arise: It would be interesting, for instance, to find out whether there is a polynomial (or exponential) trade-off between program size and and the concept of simulating a process.
* Some questions  on algorithmic complexity arise: Will the encoding always be more complex if the machine is simpler? All theorems in algorithmic information theory depend on additive constants, which depend on the sizes of typical universal Turing machines. What is the impact of different generalizations of universality on algorithmic complexity and what is the role of  encoding in such a measure?
* Some questions arise on the relation between several variants of universality definitions: Is there an effective and efficient encoding for each non-periodic encoding preserving universality? If so, how does this impact their complexity? Is there a non-periodic encoding with blank characters for each periodic blank word encoding, and what would the impact of such  an encoding be on the size/complexity of the Turing machine in question?

The field is active and still an important area of research. Several computer science conferences include talks on small computational systems. For instance, Computability in Europe (CiE) and Machines, Computations and Universality (MCU) included such talks this year, focusing in particular on reversible cellular automata and universal Turing machines.

Here are some references from the small Turing machine community, some of them very recent:

[1] Manfred Kudlek. Small deterministic Turing machines. Theoretical Computer Science, 168(2):241-255, November 1996.
[2] Manfred Kudlek and Yurii Rogozhin. A universal Turing machine with 3 states and 9 symbols. In Werner Kuich, Grzegorz Rozenberg, and Arto Salomaa, editors, Developments in Language Theory (DLT) 2001, vol. 2295 of LNCS, pp. 311-318, Vienna, May 2002. Springer.
[3] Maurice Margenstern and Liudmila Pavlotskaya. On the optimal number of instructions for universality of Turing machines connected with a finite automaton. International Journal of Algebra and Computation, 13(2):133-202, April 2003.
[4] Claudio Baiocchi. Three small universal Turing machines. In Maurice Margenstern and Yurii Rogozhin, editors, Machines, Computations, and Universality (MCU), volume 2055 of LNCS, pp. 1-10, Chisinau Moldavia, May 2001. Springer.
[5] Turlough Neary and Damien Woods. Four small universal Turing machines. Machines, Computations, and Universality (MCU), volume 4664 of LNCS, pp. 242-254, Orleans, France, September 2007. Springer.
[6] Yurii Rogozhin. Small universal Turing machines. Theoretical Computer Science, 168(2):215-240, November 1996.
[7] Shigeru Watanabe. 5-symbol 8-state and 5-symbol 6-state universal Turing machines. Journal of the ACM, 8(4):476-483, October 1961.
[8] Shigeru Watanabe. 4-symbol 5-state universal Turing machines. Journal of Information Processing Society of Japan, 13(9):588-592, 1972.
[9] Stephen Wolfram. A New Kind of Science. Wolfram Media, 2002.

I will post more later on Alex Smith’s contribution after the proof he provided to prove the universality of Wolfram’s 2,3 Turing machine.

A significant number of researchers believe that there are sentences with semantic value that could never be understood by a machine. These researchers believe that the mind has a semantic component, unlike machines. Their’s is a  Chinese Room type argument a la Searle. Consider Chomsky’s example of two books in a library with the same title, and two readers, each taking out one of the books. Do they get the same book? These researchers argue that machines would be unable to answer correctly on the basis of context since the answer would depend on a cognitive understanding of the situation. My claim is that all  meaningful components of a situation are based on a hierarchy that can be artificially represented by categories capturing the essence and functionality of  human mental operations. The answer to Chomsky’s question would be “yes” if one is  referring to the information content of the books,  “no” if one is referring to the books as physical objects.

Hacking Days at MIT and Wikimania at the Harvard Law School came to a close yesterday. Here is a brief summary:

Brion Vibber, Chief Technology Officer of Wikimedia, gave many talks. He discussed everything from why wiki projects are difficult to cache (since they are dynamical) to new features to come, like Semantic MediaWiki, a possible Xapian search engine, better Wikitags, a better parser,  possible support for  PDF documents and integration with the DjVu image format file, among other video formats like OpenID/YADIS/A-Select/better. There were some OLPC -One Child Per Laptop- computers outside which are able to synchronize themselves, being interconnected in order to play music or share any type of information through a wireless net they build by themselves.

Mark Bergsma talked about near-future  server technology of the Wikimedia projects, like 64bits servers. He provided information about the geographical sites of the Wikipedia clusters, mainly located in Florida and Amsterdam. He talked about some features of the caching architecture using squid and some new DNS technologies they are exploring, like PowerDNS and geographical balancing (e.g. BGP DNS) and object purging. He announced that they were already using the HTCP inter-cache protocol. He also announced a plan to make the switch with one core switch/router more reliable. Some of the participants proposed the use of  Planet Lab services (http://www.planet-lab.org), a collection of machines distributed over the globe running a common software package including a Linux-based OS, mechanisms for bootstrapping, distribution software and a set of node monitor tools. PlanetLab is mainly devoted to research as a testbed for overlay networks, providing groups the opportunity to experiment with planetary-scale services.

A later talk was about enhancing Wiktionary to be used as a database for external applications requiring it. Right now the Wiktionary can only be  exploited by addressing a query directly to it. A new database structure is being developed in order to give Wiktionary semantic meaning -among other things, relating each word to its translation in all other languages already in Wikitionary- which will eventually allow  many new features and the generation of a full knowledge database rather than a bunch of words ( about a million words at the moment,  in all langauges) with definitions.

An interesting talk about managing and posting onto the discussion page also took place. In a nutshell, the idea was to treat each post as a wikipage in itself. Some questions were raised about performance impact on the whole system arising from the huge amount of new wikipages, and other security and control questions emerged too but the idea seemed to be very well accepted. Finally a nice proposal to include video and audio streaming into wikiprojects was presented.

There were several talks about WikitionaryZ during  Hacking Days and Wikimania, by Eric Moeller and others.Wiktionary Z is an iniative to create the Ultimate Universal Wiktionary (pretty humble, isn’t it?) by integrating semantic knowledge into Wiktionary. The project is based on defining meaning using a short, simple phrase  that defines a word clearly and unequivocally and that could be exactly translated into all the languages of  the Wiktionary. There is also a record of the relationships of the words with each other, thus making it possible to build a machine-readable repository of semantic knowledge.

Following that, Andre Engels talked about pywikipediabot and the challenges of writing wikipedia bots avoiding anything that used  screen scrapping, making the process of maintaning the bots quite complicated given the need to change bots everytime there is a change in the format of the articles. He also spoke about the dangers of using bots for big tasks, because errors in bot programming can lead to hundreds of thousands of damaged pages.

Other talks were about OpenID, an OpenSource authentication system very similar to Microsoft Passport in that it integrates the user’s identity in several projects (wikimedia projects, blogs, etc) into a single id. There are good plans to integrate this feature into Wikipedia soon.

WYSIWYG for Wikipedia: One of the main problems when using Wikipedia is the difficulty of editing using the Wikitags. Although technologically advanced users can easily adapt to the Wikitags system, most  people just can’t get the hang of it. Hence the need for an easy-to-use, simple editor is evident, although the lack of a proper mediaWiki parser and the complexity of the Wikitags language makes such a thing hard to implement. Anyway, Frederico Caldeira Knabben has created a very nice and useful WYSIWYG HTML editor called FCKeditor (www.FCKeditor.org), and is willing to join forces with media wiki to integrate it into wikipedia.

There was also a panel featuring Brion Vibber, Andre Engels and Erik Moeller which addressed the possibility of a  MediaWiki API. Many of the attendees were enthusiastic, and some went into a separate room and discussed the specification with Brion and Andre. They came up with a preliminary agreement that may be available soon on the web. The day ended with an enjoyable tour of the MIT’s Media Lab.

Some topics were very boring. For instance,  the Wikimedia discussion panel was mainly about internal politics and logistics. Nothing interesting for the broad audience.

From the point of view of our discussions here the most interesting topics at Wikimania related to the Semantic Web and the reliability of Wikiprojects, given  that everybody can edit the entries. Jim Giles, the author  of the Nature paper comparing Wikipedia and Britannica talked about the strong and weak points of the entries, and the reviews. According to him, Britannica made the point that most of their entries that were evaluated were in the sciences, where Wikipedia is stronger, most of the contributors being from these disciplines. The argument was that this  kind of comparison could not serve as an adequate measure of the entire corpus of knowledge covered by Britannica. Furthermore Britannica also made the point that the entries (50 in all) were badly reviewed, accounting for the fact that  Wikipedia earned a rating very close to that earned by them (3.9 errors on average per article for Wikipedia as against the 2.9 obtained by Britannica). However the author argues that the reviewers were the same for both sides, so they would on average have committed the same number of errors.

Regarding the session in which they were expecting to have a consensus on improving the Wikipedia content reliability, they didn’t reach it. According to Martin Walker, a professor of Chemistry, things gradually coalesced during discussions over the weekend. Both the Germans and the English-language people seem to have come to a similar consensus:
1. Set up stable (uneditable) versions of articles (static unvandalized
versions). The Germans expect to be testing out this idea within a month.
2. Then set up a validation system, possibly using review teams of trusted
people from wikiprojects, to check every fact (& sign off, giving the
reference source). The fact checking would be made available to any user
who wanted to take the time. This validated version would also be an
uneditable version.
3. On the English Wikipedia we thought there ought to be an outside
expert (with a PhD and a reputation) to sign off on the validated version,
so we could say: ”This page has been approved by Professor XXX from
University of YYY”.

The discussion page   set up on this issue is at:
http://en.wikipedia.org/wiki/Wikipedia_talk:Pushing_to_validation
and
http://wikimania2006.wikimedia.org/wiki/Proceedings_talk:MW2

Concerning the Semantic web, there is already a wikiproject at www.ontoworld.org which is working. The basic idea is to use tags for all pieces of information contained in the articles in order to relate them to other data.
A typical example is:
”’Africa”’ is a continent, south of [[Europe]] and southwest of [[Asia]].

where the tags for Europe and Asia signal a  relation to  countries with the same tags.

In the end what we have is a big relational database underlying the system which allows queries using a SQL-type query language called SPARQL the  specification for which is at:
http://www.sparql.org/query.html

I conducted some tests using the following entry:
http://wiki.ontoworld.org/index.php?title=Germany&action=edit,
and using the Africa article I made a search of www.ontoworld.org and created a new article from a query looking for each country in Africa sorted by Population. The query was:
Editing Africa Population by Countries>

== List of African countries ==
[[Category:Country||Persons]]
[[located in::Africa]]
[[Population:=*]]
[[Area:=*]]

[[Category:Continent]]

The technology used is something called RDF. More on that at:
http://wiki.ontoworld.org/index.php/Special:ExportRDF

and there are some libraries in several languages that deal with it:
For RDF access with libraries
Get RDFLib from rdflib.net
SMW lib
RAP from www.wiwiss.fu-berlin.de/suhl/bizer/rdfapi

and the description of the MediaWiki extension project for the Semantical Web is at:
http://ontoworld.org/index.php/Semantic_MediaWiki

We also explored  some browsers being developed for the Semantic Web. They are at:
http://brownsauce.sourceforge.net/
http://simile.mit.edu

The workshop on “Using Wikipedia’s Knowledge in Your Applications”
(http://wikimania2006.wikimedia.org/wiki/Proceedings:MK1) was very interesting. There I met the speakers (Markus Krötzsch, Denny Vrandecic)with whom I exchanged information, agreeing  to keep in contact with them to discuss my concerns relating to addressing  queries to the URL and  transforming unstructured data into semantically  usable information. There was some discussion about Natural Language Processing translation to Semantic Information, directly taking clue words from the articles in Wikipedia and introducing tags and relations:

http://wikimania2006.wikimedia.org/wiki/Proceedings:DV2
http://wikimania2006.wikimedia.org/wiki/Proceedings:DV1
and
http://wikimania2006.wikimedia.org/wiki/Proceedings:MN1

I met Tim Berners-Lee who is also very interested in the Semantic Web and the idea of creating a browser exploiting these features. I also met Betsy Megas who is  working on a Semantic Web project called wiktionaryZ.org which is like the wiktionary.org but semantical. We had a long discussion about the convenience of having  a “categories” squeme in the Semantic Web. My point was that in most cases  the categories could  be built dynamicaly. They would be present in an abstract form without there being any need to  define them explicitly. A completely relational model strikes me as more interesting. People have tried to categorize everything since the existence of the encyclopedias,  but the number of possible categories can be much higher than the number of elements to categorize, simply because categories can be so arbitrary that the final number of categories can reach the number of subsets of elements, which is not useful from my point of view.

A couple of plenary sessions were held in the main auditorium of Harvard Law School. One of them featured a lecture by Lawrence Lessig, a lawyer who has been involved in cases such as the  one pitting Monopoly against Microsoft. He is the founder of the Commons Licence, better known as Left-copyright, where some rights are reserved but others are yielded to the people to allow them to be creative when using resources. He talked about the Read-Only (RO) Society, which was how he characterized  the last century,  and the new Read-Write (RW) Society which is moving toward the Commons Licence, Open Software, Open Hardware, Free and Open Encylopedias like Wikipedia, Freedom of Work/Job (freelancers and people organizing free foundations), free access to  human knowledge and communications (Web Access, Skype), Free and Open broadcasting (pod-casting), among other things.

Most of the sessions were recorded and are available at:
http://wikimania2006.wikimedia.org/wiki/Archives

And the Abstracts and Procedures are at:
http://wikimania2006.wikimedia.org/wiki/Proceedings:Index

I also found an interesting site for exploring the degree of separation between 2 different topics through Wikipedia (sometimes it works):
http://tools.wikimedia.de/sixdeg/index.jsp?from=cuneiform&to=Semantic_Web

This is a report on the Computability in Europe Conference (CiE), held at the University of Swansea, Wales in the United Kingdom in July 2006.

I attended a mini-course on Quantum Computing given by Julia Kempe, a lecture on the Church-Turing thesis by Martin Davis– who defended it against proposed models of hypercomputation– and a  lecture on Proof Theory. Another very interesting lecture was on Godel and Turing’s remarks on the Human Mind (the dichotomy argument from Godel and the mechanistic vision from Turing). Among other noteworthy lectures were Samuel Buss’ on Complexity of Proofs, John Dawson’s on Godel in Computability, Wilfried Sieg’s on the Concept of Mechanical Procedure in Godel and Turing, as well as many presentations on hypercomputability and computing over the reals. I met people whom I had only known through email exchanges, like Felix Da Costa from the Technological Institute of Lisbon, Robert Meyer professor emeritus at the National University of Australia, and Julia Kempe from France who is a renowned researcher in the quantum computing field and with whom I shared some doubts I had concerning where the restrictions in Quantum Computing lay which constrained its power to the set of recursive functions. I also met people from SUNY who are doing interesting research on Turing-computation, studying isomorphisms between Oracle machines and the relation with the Tenenbaum theorem upon the uniqueness of the recursive model of PA (Peano Arithmetic). Many lectures were given on computing over infinite time and space and computing at the limit of the general relativity theory. The conference was intended to take the pulse of the field of hypercomputation in Europe and worldwide.

NECSI/ICCS Conference Report, Quincy, Greater Boston, USA, July 2006.

First lesson: For every complex problem there is a simple, neat, wrong solution.

I attended talks given by Ed Fredkin on Finite Nature, Lazlo Barabasi on Complex Networks, Christoph Teuscher on Biology and Computation and John Nash on his research upon Game Theory.
* Ed Fredkin presented a table salt 3-D cellular automata model that fulfils all physical constraints on symmetry and energy conservation. The model is surprisely Turing-universal. As a reminder, the Zuse-Fredkin Thesis is a Church-type thesis which claims additionally that the universe being a Cellular Automaton can be understood in terms of the evolution of  Cellular Automata. An interesting paper entitled “Church-Turing Thesis is Almost Equivalent to Zuse-Fredkin Thesis” by Plamen Petrov is available here>
http://digitalphysics.org/~ppetrov/
And much more information on the interesting ideas of Ed Fredkin is available in
http://www.math.usf.edu/~eclark/ANKOS_zuse_fredkin_thesis.html and on  Ed Fredkin homepage at MIT, which  includes some remarks on why this thesis is not in agreement with  Stephen Wolfram’s, since Wolfram does not intend to imply that the universe is a classical cellular automaton but rather conceives of   a discrete universe based on systems performing simple rules and producing all the complex behavior we find in nature. Such systems are comparable to Turing machines, tag systems, axioms or any other equivalent system.
* In his lecture, Lazlo Barabasi claimed that behind all complex systems there are complex networks, in particular Free-Scale Networks (with a few nodes very well connected with others, and many nodes weakly connected). These nets are efficient and robust (even minus random nodes they remains connected)except under attack (provided the best connected nodes are targeted).
* Christoph Teuscher gave a lecture on computation inspired by biology. However, as he himself admitted, it was not his area of expertise.
* John Nash presented his research on Game Theory using Mathematica as an engine.
* I met Hava Siegelmann and one of her fellows, Yariv, who is working on Artificial Intelligence. Siegelmann worked some years ago (while completing  her PhD dissertation) upon a model of computation called Analog Recurrent Neural Network or just ARNN which, under certain circumstances,  is able to compute more functions than the set of recursive functions , which are those computed by the Turing machines. She is now working on topics related to Molecular Biology. I asked her about the forceful  critiques delivered by traditional logicians like Martin Davis, who wrote a paper entitled “The Myth of HyperComputation.”    The target of most of these critiques is a certain circular argument—to compute more than Turing machines it is necessary to use non-Turing computable weights previously coded into the neural network. It has been known for a long time that the set of all real numbers is able to encode any arbitrary language, even if it is non-Turing computable. What is remarkable from my point of view is her result relating to complexity classes, since weights with lower complexity are able to compute a higher class when  used in those networks. Aditionally she argued that even with a stochastic function her networks are able to solve non-computable functions. Recently I discussed the fact with Stephen Wolfram and we agreed that she is assuming strong randomness. I would say however that Siegelmann’s work is much more beatiful from a complexity point of view than from a “hypercomputational” viewpoint. In her book published under the title “Neural Networks and Analog Computation: Beyond the Turing Limit ” she proves that: a) there exists an universal neural network with only 9 neurons, and b) that  p(r) suffices to compute a non-computable function, where r is an arbitrary complete real number but p(r) represents the first p digits of the expansion of r–which means that linear precision suffices to achieve “super-Turing” capabilities, assuming that the neural network can have access to any possible real number before the computation. In other words this seems to be true only if all possible real numbers are allowed a priori (just as in the Turing machines an unbounded tape is neccesary to carry out all recursive languages, and neural networks with rational numbers as weights do not compute the same set of functions as neural networks with whole numbers as weights, the first having been  proven by Klenee to compute the same set as Turing machines and the second  to compute the same set of languages as finite automata, those called regular languages).
I exchanged ideas with some other interesting people, like an engineer from the Space and Airbone Systems Department of Raytheon. And I met John Nash Jr. during the gala dinner  at which he was presented with an award  for his contributions to  Complexity Theory, mainly honoring his work relating to Game Theory.

Where do the spots on animals come from?
Turing’s answer to this question as well as much more on Turing and modern Fibonacci phyllotaxis is  presented and analysed by Jonathan Swintons in his Deodans’ blog
http://www.swintons.net/deodands/archives/000091.html

The Web as a graph, adaptive crawlers, and mining the Web from unstructured data?

http://www.almaden.ibm.com/webfountain/resources/TheWebasaGraph.pdf

To be discussed soon…

How To Criticize Computer Scientists or Avoiding Ineffective Deprecation And Making Insults More Pointed, from http://www.cs.purdue.edu/homes/dec/essay.criticize.html

In recent exchanges, members of the faculty have tried in vain to attack other Computer Scientists and disparage their work. Quite frankly, I find the results embarrassing — instead of cutting the opponent down, many of the remarks have been laughably innocuous. Something must be done about it because any outsider who hears such blather will think less of our department: no group can hold the respect of others unless its members can deal a devastating verbal blow at will.This short essay is an effort to help faculty make their remarks more pointed, and help avoid wimpy vindictives. It explains how to insult CS research, shows where to find the Achilles’ heel in any project, and illustrates how one can attack a researcher.The Two Basic Types Of Research: Most lousy insults arise from a simple misimpression that all researchers agree on the overall aims of CS research. They do not. In particular, CS has inherited two, quite opposite approaches from roots in mathematics and engineering. Researchers who follow the mathematical paradigm are called theorists, and include anyone working in an area that has the terms “analysis”, “evaluation”, “algorithms”, or “theory” in the title. Researchers who follow the engineering paradigm are called experimentalists, and include most people working in areas that have the terms “experimental”, “systems”, “compiler”, “network”, or “database” in the title. Complex Theory And Simple Systems: Knowing the tradition from which a researcher comes provides the basis for a well-aimed insult.Theorists Favor Sophistication. Like mathematicians, theorists in Computer Science take the greatest pride in knowing and using the most sophisticated mathematics to solve problems. For example, theorists will light up when telling you that they have discovered how an obscure theorem from geometry can be used in the analysis of a computer algorithm. Theorists focus on mathematical analysis and the asymptotic behavior of computation; they take pride in the beauty of equations and don’t worry about constants. Although they usually imply that their results are relevant to real computers, they secretly dream about impressing mathematicians.Experimentalists Favor Simplicity. Like engineers, systems researchers take pride in being able to invent the simplest system that offers a given level of functionality. For example, systems researchers will light up when telling you that they have constructed a system that is twice as fast, half as small, and more powerful than its predecessor. Experimentalists focus on the performance of real computer systems; they take pride in the beauty of their code and worry about constants. Although they usually imply that their results can extend beyond real computers, they secretly dream of filing patents that apply to extant hardware.The Insult: Knowing that CS can be divided into two basic groups helps immensely when criticizing someone. There are two basic rules: identify the type of the researcher and issue an insult for that type. Avoid saying anything that inadvertently compliments them. If performed well, an insult will not only stun the researcher (who will be shocked to learn that not everyone agrees with his or her basic value system), but will also intimidate others in the audience.Identifying A Type: Identifying the type of a researcher is usually easy and does not require a strong technical background or real thinking. It can be done using keyword matching according to the following lists. Detecting Theory: You can tell someone is a theorist because they slip one or more of the following keywords and phrases into lectures and technical conversations: “theorem”, “lemma”, “proof”, “axiom”, “polynomial time”, “logarithmic”, “semantics”, “numerical”, “complexity”, “nondeterministic” or “nondeterminism”, and “for large enough N”. They write lots of equations, brag about knocking off the “extra log factor”, and often end their lecture with an uppercase “O” followed by a mathematical expression enclosed in parentheses. You can also recognize a theorist because they take forever to prove something that may seem quite obvious. (I once sat through an hour lecture where someone proved that after a computer executed an assignment statement that put the integer 1 into variable x, the value in x was 1.)Detecting Systems: An experimentalist will slip one or more of the following keywords and phrases into lectures and technical conversations: “architecture,” “memory,” “cpu” (sometimes abbreviated“CISC” or “RISC”), “I/O” or “bus”, “network”, “interface”, “virtual”, “compile” or “compiler”, “OS” or “system”, “distributed”, “program” or “code”, and “binary”. They talk about building programs and running the resulting system on real computer systems. They refer to companies and products, and use acronyms liberally. Their lectures often end with a graph or chart of measured system performance. You can also recognize an experimentalist because they describe in excruciating detail how they set up an experiment to measure a certain value even if the measurement produced exactly the expected results. (I once sat through an hour lecture where someone carefully explained how they used three computer systems to measure network traffic, when their whole point was simply to show that the network was not the cause of the problem they were investigating.)Forming An Insult:The key to a good insult lies in attacking whatever the researcher holds most dear and avoiding whatever the researcher does not care about. Thus, an insult lobbed at a theorist should focus on lack of sophisticated mathematics such as the following:Despite all the equations, it seems to me that your work didn’t require any real mathematical sophistication. Did I miss something? (This is an especially good ploy if you observe others struggling to understand the talk because they will not want to admit to that after you imply it was easy.)Isn’t this just a straightforward extension of an old result by Hartmanis? (Not even Hartmanis remembers all the theorems Hartmanis proved, but everyone else will assume you remember something they have forgotten.)Am I missing something here? Can you identify any deep mathematical content in this work? (Once again, audience members who found the talk difficult to understand will be unwilling to admit it.)In contrast, an insult lobbed at an experimentalist should imply that the techniques were used in previous systems or that the work isn’t practical such as:Wasn’t all this done years ago at Xerox PARC? (No one remembers what was really done at PARC, but everyone else will assume you remember something they don’t.)Have you tested this on the chip Intel got running last week in their lab? (No one knows what chip Intel got running last week, but everyone will assume you do.)Am I missing something? Isn’t it obvious that there’s a bottleneck in the system that prevents scaling to arbitrary size? (This is safe because there’s a bottleneck in every system that prevents arbitrary scaling.)How To Avoid Having An Insult Backfire On You: A misplaced insult can backfire, turning into an embarrassment for the attacker and a victory for the intended attackee. To avoid such occurrences, remember the following:Never attempt to attack theoretical work as not considering constants, as unrelated to real computer systems, or as requiring too much sophisticated mathematics. (The intended victim is likely to smile and thank you for the flattery.)Never attempt to attack a system as too small, too simple, or as lacking sophisticated mathematics (Again, the intended victim is likely to smile and thank you for the flattery.)Never attempt to attack systems work simply by saying that it’s so simple and obvious that you could have done it. (For years, people said that about UNIX and the TCP/IP protocols.) In fact, this is merely an extension of a ploy used by children on a playground: “Oh yeah? I could have done that if I wanted to.” Don’t try using it or someone will tell you to grow up. Attacking Crossover Work: Although rare, a few researchers include both theoretical and experimental work in the same project. Insulting such combinations can be tricky because a researcher can escape unscathed by pointing to one part of their work or the other as the answer. You can try to attack both parts simultaneously:I note that the systems aspect of this project seems quite complex. Do you think the cause of the convoluted implementation can be attributed to the more-or-less “simplistic” mathematical analysis you used?However, a clever insult can avoid talking about the work by suggesting sinister reasons for the paradigm shift:I notice that you did something unusual by combining both theory and experiment. Did you decide to try a second approach because you had insufficient results from the first?You seem to have a little theory and a little experimental work combined into one project. Isn’t it true that if you had a sufficiently strong contribution in one or the other you would have lectured about them separately?A Final Plea: I certainly hope faculty will take this essay to heart and sharpen their insult skills. In the future please make all your thrusts count.