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Announcing ODBC Data Adapter for Ruby on Rails, release 1.1
Announcing ODBC Data Adapter for Ruby on Rails, release 1.1

OpenLink Software are pleased to announce release 1.1 of the ODBC Adapter for Ruby on Rails (ActiveRecord).

This unifies data-access from a plethora of individual adapters to one common configuration in Rails; rather than having a multitude of DBMS-specific Rails Adaptors with inconsistent functionality and behaviour, you can now focus on a single data adapter with consistent behaviour across ODBC-accessible databases on all Ruby-supported platforms. This release adds support for DB2, MySQL, Sybase and SQL Server. The supported DBMSes now include: Oracle, Informix, Ingres, OpenLink Virtuoso, SQL Server, Sybase, MySQL and DB2.

The adapter can be downloaded from rubyforge:
http://rubyforge.org/projects/odbc-rails/

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10/23/2006 13:03 GMT-0500
Why Web 2.0 clones are not innovative
Why Web 2.0 clones are not innovative

Why Web 2.0 clones are not innovative:

Richard MacManus at ZDNet writes his view on Web 2.0 clone applications. He observed that every country has its set of Web 2.0 clones — bookmarking sites that looks del.icio.us, photo sharing sites that like Flickr, social networking sites like MySpace, community news sites like digg, etc. He criticizes those Web 2.0 clones being non-innovative.

It’s true that most of the clone apps don’t come with innovative ideas, but it would be unwise to think that they totally have no values. Contrary to Richard’s point of view, I think clone apps are essential ingredients in helping the IT business in developing countries to become innovative.

Innovative ideas don’t usually born in the thin air. They requires extensive testings and experiments. The mature IT business in the US has extensive knowledge and experience in developing innovative ideas. People here have a general idea about what works and what doesn’t. In many developing countries, however, the settings are completely different.

Take China for an example. Its IT market is still in an infant stage comparing to that of the US. Chinese businesses that recently entered the market are still in the stage trying to figure out how to make profits and establish a sustainable business model. The need to be innovative now, perhaps, is not on the todo lists of the business executives.

Furthermore, the past generation of Chinese engineers and developers were not exactly trained to be innovative and think outside-the-box. They were trained with impressive memorization skills and obey orders from superiors. It’s unfair to expect this generation of Chinese IT workers to live and breath with innovations as their US counterparts do.

Given this type of harsh environment in many developing countries, it’s quite natural to act as copycats and repeat business ideas that have good track records. In fact, it’s a good business if being a copycat can bring profits.

We don’t criticize Yahoo! Maps being a copycat of Google Maps. We don’t criticize Google Notebook being a copycat of del.icio.us. Why should we criticize foreign Web 2.0 clones when their intention is to learn how to enter a global IT market and to become prosperous? Maybe in the cloning process, copycats will discover innovative ideas by accident.

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10/23/2006 12:02 GMT-0500
What Problem Does Natural Language Search Solve?
What Problem Does Natural Language Search Solve?

What Problem Does Natural Language Search Solve?:
Matt Marshall recently posted a story about a new search engine looking to raise a lot of money at a very high valuation, which has created quite a bit of buzz as people argue over whether or not the company has a chance, or deserves such a high valuation. Matt followed up with more details on the company, though he still expresses some reasonable skepticism. Like many people, my first reaction on hearing about it was that I can't remember a year that's gone by without someone claiming to have come out with a revolution in natural language search. However, when it comes to search engine news, no one can go through the history and explain why something is a bad idea quite like Danny Sullivan can. He lists out all the attempts at natural language search, and shows how each one failed (in some cases, miserably). He also points out that the problem with natural language search is that it requires everyone to change their behavior. As with any startup, when you're looking at their chances, the big question to ask is pretty simple: what problem does it solve? Plenty of people have figured out how to search with keywords. In fact, many of us find it more natural and faster than trying to construct a natural language query. So, while all the natural language search engines that come along insist that searches suck because they can't understand the the searcher, it's not clear that's the real problem. When people want to use a search engine, they want to find what they want. That means being able to search quickly. Dumping two or three keywords into a box is always going to be a lot faster than figuring out the natural language equivalent. So, perhaps someone can enlighten us. What is the problem natural language search solves?

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(via Techdirt)

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10/23/2006 12:02 GMT-0500
         
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