One of the most appealing aspects of the Agile movement is the breakdown of development efforts into themes, epics, and stories. I have long thought that the real problems in software development have less to do with algorithmic complexity and more to do with the difficulty of getting everyone on the same page. The theme-epic-story structure helps everyone see his place as part of a tale that has a beginning, middle, and end. We know how stories work.

All of this resonates powerfully with the work I did at Columbia in pursuit of my degree in English and comparative literature. Stories, I have come to believe, are how we make life make sense. Life is, in essence, a series of moments. The events that fill the moments have no intrinsic meaning. It is only our sense of story that gives each moment significance. This is, loosely speaking, the essence of existentialism.

Computers don’t have any sense of their existence as art of a story. To a computer running conventional software, facts have no meaning and events are not judged against values. A word-processing program spell-checks a ransom note as happily as a poem.

But what if computers comprehended the world, understood the relationships among the things whose verbal stand-ins they manipulate so fluently for us?

That’s the goal of NELL, the Never Ending Language Learning system at Carnegie Mellon University. Researchers have given NELL a rudimentary set of categories and verbal relationships, and turned it loose on the Internet. The system, which runs on supercomputers donated by Yahoo! with financial support from Google and DARPA, uses the Internet to check its hunches about relationships – what books an author has written, for instance, or whether a particular phrase refers to an item on a menu or a bill under congressional consideration. NELL’s learning isn’t supervised. The system constructs facts and relationships by assembling webs of information sources and evaluating their credibility. NELL scans and rescans millions of Internet pages and from the assembles a view of the world.

The results are impressive. NELL has composed more than 15 million beliefs about the world, structured as simple statements like playsInstrument(George_Harrison, guitar). Every day, NELL learns to read a bit more efficiently and accurately. It hones previous statements of belief and compiles new proposed beliefs. The researchers don’t see an end-point for the project. They intend to let NELL keep learning and learning indefinitely, and see what happens.

NELL doesn’t always get it right, of course. For a few days, before researchers stepped it, it believed Internet cookies were baked goods. The difference between “She bought the bread with the money” and “she bought the bread with the poppy seeds” still flummoxes Nell. For now.

If any of this sounds interesting, check out the NELL project page at Carnegie Mellon. You can download NELL’s knowledgebase if you want. You can even follow NELL on Twitter, where you’ll receive a continuing stream of the system’s new conclusions about how the world works.

Researchers say that NELL is an attempt to simulate the way human beings learn – cumulatively, gradually, with tentative assertions gradually becoming more certain. It’s true that NELL represents a new approach in that regard. But I don’t think NELL matches the human model. Human learning relies upon an extremely rich broadband stream of feedback. We learn that things fall to the ground by repeatedly dropping them and seeing it happen. NELL evaluates and weighs inputs, but it doesn’t seem to test assertions against reality. It’s unreasonable to think that NELL could perform such tests before its hardware includes robotic extensions. But until that day, I don’t think it’s fair to say that NELL’s belief-construction process mirrors human learning.

As for the differences between NELL’s beliefs, which are factual assertions that the system drops when they are disproved, and human beliefs, which members of our species cling to in the face of overwhelming contradictory evidence – well, that’s a topic for another day.

Web recommendation: This story is both important and chilling. J.D. says check it out.

J.D. Hildebrand has written hundreds of articles for dozens of publications and online communities dedicated to software development. Reading about NELL made him itch to do some AI coding.

A funny thing happened on the way to writing this blog post.

I'd intended to serve up an enthusiastic review of A.K. Dewdney's The (New) Turing Omnibus: 66 Excursions in Computer Science. I really can't help recommending the book. It's a classic collection of short essays on essential topics on computer science, including finite automata, genetic algorithms, Karnaugh maps, Cook's theorem, and more.

I loved the original edition of this book when it came out in 1989 (there were just 61 chapters, or “excursions,” in that edition). The new version includes the full text of that book along with five bonus chapters on emerging topics, including a fascinating overview of the theory underlying computer viruses.

The (New) Turing Omnibus is intended to be a crossover book. While the writing style and approach make it accessible to those with no background in computer science (assuming they have sufficient motivation to wrestle with the mathematics, concepts, and notation), I think the book is really more useful as a sort of review or refresher for professionals. I've never written any code in the computer vision realm, but after reading Dewdney's essay on the topic I feel I have a basic understanding of the field. It's this kind of mind expansion that I expect, and receive, from Dewdney, who served for years as the author of the Computer Recreations and Mathematical Recreations columns in Scientific American.

As you can see, I think The (New) Turing Omnibus is a swell book. And under ordinary circumstances I would have no hesitation about recommending that you pick up a copy for yourself and for any nascent computer scientists in your life.

Here's my problem. In addition to the lucent writing, academic rigor, relevant topic selection, and overall terrific work in his computer-science essays, Dewdney contributes articles to an organization that has branded the terrorist attacks of September 11, 2001 a conspiracy. I spent a couple hours at the organization's Web site – I won't mention it by name here because I don't want to encourage traffic to the site – and found that it includes material I find not only wacky, but hateful.

I now face an ethical dilemma. How do I recommend that you purchase a copy of this truly good book when each sale benefits an author who holds and promotes ideas I can't accept?

I might have kept silent, choosing another book or idea as the topic for this post. But that would have deprived my readers of the knowledge of this truly admirable book, which I believe you will find both interesting and useful.

Or I could go ahead with my recommendation, despite the fact that my words indirectly benefit an author whose beliefs are contrary to my own – and, in my opinion, to both common sense and moral decency.

As you can see, I loosed this Gordian knot by choosing a third path. I've recommended the book and shared my ethical misgivings with you. Because ethical people can choose different courses of action in this circumstance, I have passed my dilemma along to you.

You're welcome.

What's your opinion? Is a good book a good book, regardless of the source? Or do ethical principles require us to evaluate the beneficiaries of our actions, and to refrain from contributing to the well-being of those whose actions harm the world? Drop me a line in the comment section below.

I look forward to hearing from you. And oh, yeah – for those of you who find my name vaguely familiar – it's great to be back. I look forward to chatting with you frequently here at SD Times.

Web recommendation: I hope to pass along the link to an interesting or useful Web site at the end of each of these posts. In this installment I recommend Coding Horror: Programming and Human Factors (http://www.codinghorror.com/blog/). Jeff Atwood's blog isn't updated as often as I'd like, but it's full of on-target observations, in-depth contemplations, and random good stuff. J.D. says check it out.

J.D. Hildebrand has written hundreds of articles for dozens of publications and online communities dedicated to software development. He recently relocated to a small town outside Belgrade – stop by if your travels take you through Serbia.

You read that right. Someone finally took the time to sit down and reverse engineer the 6502 for a public talk at a security conference. That's the processor at the heart of the Atari 2600, among other famous devices. In the spirit of getting this year off to a "never too late to be cool" start, Behold Michael Steil's talk from the 27c3 conference in Europe: Reverse Engineering the MOS 6502 CPU.

For more information on the 6502, check out this visual representation of the processor, and read this interesting post from Russ Cox.

The Association for Computing Machinery this morning announced its first 2008 Turing Award recipient. Barbara Liskov was the first American woman to earn a Ph.D. in computer science. She also has quite a number of obligations at M.I.T. She is a Ford Professor in Engineering, Department of Electrical Engineering and Computer Science, Computer Science and Artificial Intelligence Laboratory, and Programming Methodology Group. That's a mouthful of departments in which she works. But it appears that her career and knowledge base are fundamentally applicable to just about everything in software. Quoting the ACM site:

Liskov revolutionized the programming field with groundbreaking research that underpins virtually every modern computer application for both consumers and businesses. Her achievements in programming language design have made software more reliable and easier to maintain. They are now the basis of every important programming language since 1975, including Ada, C++, Java and C#. 

Liskov heads the Programming Methodology Group in the Computer Science and Artificial Intelligence Laboratory at MIT, where she has conducted research and has been a professor since 1972

Congratulations to Liskov on receiving computing's highest honor.