e-Market e-Madness, e-Nough.
There are, they say, hard and soft sciences, not to be confused with difficult vs. easy, but more related to claims of objective, measurable, repeatable precision (we stout hardies) versus subjective, hand-waving, proofs-by-assertion (you big softies). The spectrum of fuzziness typically ranges from pure mathematics and physics at the diamond-tipped top, then descends via chemistry and biology (almost converging to synonyms), ending with a series of “life” and “social” sciences. The latter at least co-opt the intentions and vocabulary of the scientific method and rightly escape the “beyond-the-soggy-pale” category of pseudo-science (astrology, UFOlogy, pyramidiotology, hidden-Bible cryptology ... ad astra, ad nauseam). Honest “theology” wriggles through the colander by rejecting the “scientific” model.
Of course, science, life and society being what they are (send me a $1,000 check for this month's definitions), the hard/soft debate is doomed to waffle on. The paradox is that comparing the hardnesses of any two disciplines requires a valid metric—and that metric will depend on the hardness of the hardest involved domain. You can hear the magic predicate meta creeping into the equation. It reminds us that the very foundations of the purest of pure mathematics (formal set theory) were softened (nay, Osterized and Cuisinarted) by Gödel's meta-mathematical shocks in 1931.
It's still difficult to accept that the hardest queen of the sciences proved so brittle after millennia of complacency. Harder still to note that everyday mathematics and all the dependent sciences rumbled on, regardless. However, there was a clear dent in the traditional hierarchy.
We may avoid an arithmetical operator>> with a sort of “diamond-scratches-glass” ordering, but that moves us to unprovable, contentious, domain-dependent, metaphorical comparisons (e.g., in Political Science, we readily declare that Lincoln was a better president than Clinton).
There are other parameters available for comparing sciences. Some, such as “usefulness”, are possibly more determinable and worthy of discussion. Thus, cosmology (already disputed in the hard/soft science ratings since we can't, as yet or ever, repeat the “big bang” experiment, do a tachyon glide into the local wormhole, or contact our nearest parallel universe) seems to offer useless theories and predictions: whether the cosmos expands forever or collapses after 10 billion years is, to most readers of Angela's Ashes, hardly even worth mentioning.
What of our provably most useful sciences: economics and computer science? Demi-soft economics has been dubbed the “dismal” science, while semi-hard computer science must surely be the most boring (most of its formal results, dated 1935, are proofs that “this is impossible—don't bother!”) Yet hand-in-hand, both sciences have triggered the most undismal, unboring IPO stock-market episodes since the South Sea bubble. What is anything really worth? Forget the Marxian cosource-sweat-value-added axioms. If dazed bidders offer $1 million for a single Yahoo Japan share, then that is, by definition, its current “worth”. Next question? Red Hat may or may not fairly distribute its IPO gains, but they missed out 500% by not calling themselves e-Red e-Hat e-Linux. And just wait until I launch e-skb-gnu-e-free-hardware.com.

Today’s modular x86 servers are compute-centric, designed as a least common denominator to support a wide range of IT workloads. Those generic, virtualized IT workloads have much different resource optimization requirements than hyperscale and cloud applications. They have resulted in a “one size fits all” enterprise IT architecture that is not optimized for a specific set of IT workloads, and especially not emerging hyperscale workloads, such as web applications, big data, and object storage. In this report, you will learn how shifting the focus from traditional compute-centric IT architectures to an innovative disaggregated fabric-based architecture can optimize and scale your data center.
Sponsored by AMD
Built-in forensics, incident response, and security with Red Hat Enterprise Linux 6
Every security policy provides guidance and requirements for ensuring adequate protection of information and data, as well as high-level technical and administrative security requirements for a system in a given environment. Traditionally, providing security for a system focuses on the confidentiality of the information on it. However, protecting the data integrity and system and data availability is just as important. For example, when processing United States intelligence information, there are three attributes that require protection: confidentiality, integrity, and availability.
Learn more about catching the bad guy in this free white paper.
Sponsored by DLT Solutions
| Making Linux and Android Get Along (It's Not as Hard as It Sounds) | May 16, 2013 |
| Drupal Is a Framework: Why Everyone Needs to Understand This | May 15, 2013 |
| Home, My Backup Data Center | May 13, 2013 |
| Non-Linux FOSS: Seashore | May 10, 2013 |
| Trying to Tame the Tablet | May 08, 2013 |
| Dart: a New Web Programming Experience | May 07, 2013 |
- RSS Feeds
- New Products
- Making Linux and Android Get Along (It's Not as Hard as It Sounds)
- Drupal Is a Framework: Why Everyone Needs to Understand This
- Home, My Backup Data Center
- A Topic for Discussion - Open Source Feature-Richness?
- Dart: a New Web Programming Experience
- Developer Poll
- What's the tweeting protocol?
- May 2013 Issue of Linux Journal: Raspberry Pi
Enter to Win an Adafruit Prototyping Pi Plate Kit for Raspberry Pi

It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Prototyping Pi Plate Kit for Raspberry Pi.
Congratulations to our winners so far:
- 5-8-13, Pi Starter Pack: Jack Davis
- 5-15-13, Pi Model B 512MB RAM: Patrick Dunn
- Next winner announced on 5-21-13!
Free Webinar: Linux Backup and Recovery
Most companies incorporate backup procedures for critical data, which can be restored quickly if a loss occurs. However, fewer companies are prepared for catastrophic system failures, in which they lose all data, the entire operating system, applications, settings, patches and more, reducing their system(s) to “bare metal.” After all, before data can be restored to a system, there must be a system to restore it to.
In this one hour webinar, learn how to enhance your existing backup strategies for better disaster recovery preparedness using Storix System Backup Administrator (SBAdmin), a highly flexible bare-metal recovery solution for UNIX and Linux systems.




44 min 59 sec ago
1 hour 19 min ago
1 hour 42 min ago
6 hours 30 min ago
7 hours 17 min ago
8 hours 51 min ago
10 hours 28 min ago
12 hours 25 min ago
12 hours 43 min ago
13 hours 13 min ago