The Auto Textbook Algorithm

There are many dire predictions that have all human workers being replaced by machines in the not too distant future, so this article from MIT Technology Review is likely to make educational textbook staff nervous.  That said, the underlying content from Wikipedia wasn't created by a robot - at least as far as we know...

The article explores how a group of researchers were able to create viable textbooks by building an algorithm which sources Wikipedea content.

That raises an interesting question. Given the advances in artificial intelligence in recent years, is there a way to automatically edit Wikipedia content so as to create a coherent whole that is useful as a textbook?

Enter Shahar Admati and colleagues at the Ben-Gurion University of the Negev in Israel. These guys have developed a way to automatically generate Wikibooks using machine learning. They call their machine the Wikibook-bot. “The novelty of our technique is that it is aimed at generating an entire Wikibook, without human involvement,” they say

The approach is relatively straightforward. The researchers began by identifying a set of existing Wikibooks that can act as a training data set. They started with 6,700 Wikibooks included in a data set made available by Wikipedia for this kind of academic study.

MIT Technology Review Link

Tracking the Technical Velocity of Publishing Software

One of the interesting aspects of the review I am engaged in for my annual publishing technology forecast, relates to the transition publishing industry software providers are undergoing with respect to their technology architecture.   Companies in this segment may be slow to the service oriented architecture (SOA) dance but, be that as it may, we are seeing important and significant redevelopment undertaken by the leading players.  In my report, I’ve tried to represent this as a reflection of ‘velocity’ by suggesting that those companies which are faster to adopt SOA and API driven architectures will accelerate their revenue growth and market share at the expense of other providers.

This chart represents my estimate of where some of these companies are in their development (names removed in this version).  Based on my interviews and interactions with these companies, there is a clear inflection point where companies are beginning to re-architect their platforms.  For any company, this would not be an inconsequential effort but it is especially risky for relatively small, low capitalized software development companies which characterizes this segment.  The investment effort therefore needs to be deliberate and controlled.

To reflect their development paths, I’ve estimated where I see each company’s starting point and how I expect them to move through my (self-defined) velocity funnel over the next few years.  Several segment leaders, which are advanced in their development, will move further and faster through the funnel as they convert older clients to their new solution and bring on new customers from competitors.   Those companies which are slower to invest may see customers defect and may not be able to fund further advancement through the funnel.

There will be more details on these and other market dynamics in my technology report which will be published at the end of January.