"It depends on what you mean by artificial intelligence." Douglas Hofstadter is in a grocery store in Bloomington, Indiana, picking out salad ingredients. "If somebody meant by artificial intelligence the attempt to understand the mind, or to create something human-like, they might say--maybe they wouldn't go this far--but they might say this is some of the only good work that's ever been done." Hofstadter says this with an easy deliberateness, and he says it that way because for him, it is an uncontroversial conviction that the most-exciting projects in modern artificial intelligence, the stuff the public maybe sees as stepping stones on the way to science fiction--like Watson, IBM's Jeopardy-playing supercomputer, or Siri, Apple's iPhone assistant--in fact have very little to do with intelligence. For the past 30 years, most of them spent in an old house just northwest of the Indiana University campus, he and his graduate students have been picking up the slack: trying to figure out how our thinking works, by writing computer programs that think.

In the late sixties while working at Ericsson he invented both sequence diagrams and use cases, and in later years worked on the SDL, UML and the RUP. We caught up with Dr Ivar Jacobson to hear his thoughts on where the industry is today, and where it will head in the future. Builder AU: What do you think of the state of software engineering today? Ivar Jacobson: What I see when I travel and talk to customers, participate in conferences and have discussions with experts around the world is that software development is very much still an immature discipline. We still rely on too much old work. Personally I am convinced we will change that dramatically, but it is a very slow process. I have been working on process improvement and new technologies for many years now, starting with component based development and then adding to that object orientation and now aspect orientation. I've been involved with new technology since the sixties, and I've been more optimistic than most -- it's my nature, but we are still struggling with basic stuff for many reasons.

During which season of the year would a rabbit's fur be thickest? A computer program called Aristo can tell you because it read about bears growing thicker pelts during winter in a fourth-grade study guide, and it knows rabbits are mammals, too. Aristo is being developed by researchers at the Allen Institute for Artificial Intelligence in Seattle, who want to give machines a measure of common sense about the world. The institute's CEO, Oren Etzioni, says the best way to benchmark the development of their digital offspring is to use tests designed for schoolchildren. He's trying to convince other AI researchers to adopt standardized school tests as a way to measure progress in the field.

A technique called deep learning has enabled Google and other companies to make breakthroughs in getting computers to understand the content of photos. Now researchers at Cornell University and the University of Wyoming have shown how to make images that fool such software into seeing things that aren't there. The researchers can create images that appear to a human as scrambled nonsense or simple geometric patterns, but are identified by the software as an everyday object such as a school bus. The trick images offer new insight into the differences between how real brains and the simple simulated neurons used in deep learning process images. Researchers typically train deep learning software to recognize something of interest--say, a guitar--by showing it millions of pictures of guitars, each time telling the computer "This is a guitar."

Computer scientist Jeffrey Bigham has created a speech-recognition program that combines the best talents of machines and people. Though voice recognition programs like Apple's Siri and Nuance's Dragon are quite good at hearing familiar voices and clearly dictated words, the technology still can't reliably caption events that present new speakers, accents, phrases, and background noises. People are pretty good at understanding words in such situations, but most of us aren't fast enough to transcribe the text in real time (that's why professional stenographers can charge more than $100 an hour). This rapid-fire crowd-computing experiment could be a big help for deaf and hearing-impaired people. It also could also provide new ways to enhance voice recognition applications like Siri in areas where they struggle. Scribe's algorithms direct human workers to type out fragments of what they hear in a speech.

A Singapore-based company has launched a new Android app that helps students and adults learn Mandarin on the go. Dubbed iQ-Hub, the app delivers Mandarin lessons based on a proprietary speech recognition technology that assesses your pronunciation through built-in analytics. Learners are offered immediate feedback on their speech accuracy, while parents and teachers can track a student's progress in each lesson. Besides tuition centres and new residents, the company is targeting airlines and the service industry, where frontline staff may be required to learn Mandarin to converse with the growing number of Chinese tourists in Singapore. The app comes with S$0.99 lesson packages aligned with the Singapore Ministry of Education's primary school Chinese curriculum.

The Teachable Agents Project combines research from computer science, psychology, and education to develop computer-based learning environments. These environments utilize animated pedagogical agents to facilitate science learning and the development of self-regulated learning skills. The use of animated agents allows us to extend the cognitive scaffolding provided by various computer tools and representations (e.g., searchable text, simulations, concept maps, etc.) by embedding them in productive and motivating social-constructive interactions (e.g., peer teaching, collaboration, and assessment). Current projects include Betty's Brain, a learning-by-teaching environment for science learning; CTSiM, an environment for understanding science through a computational thinking framework; SimSelf, a relatively new project that focuses on teaching students about self-regulation and metacognition in the context of science learning; and C3STEM, a community-situated, challenge-based, collaborative STEM learning environment. Our learning environments also include extensive logging of students' interactions with the system and agents.

We recently ran across Alelo (www.alelo.com), The company's very engaging, interactive 3D role playing games teach languages like Arabic and Pashto to troops being deployed to the Middle East. Using speech recognition and other technology, the titles teach foreign languages to players as they go through the game in simulated environments like Iraq. We spoke with Dr. W. Lewis Johnson, CEO of Alelo, about the firm's technology and plans. Ben Kuo: Tell us a little bit about Alelo, and what the company and product does?

To Clune, the findings suggest that neural networks develop a variety of visual cues that help them identify objects. These cues might seem familiar to humans, as in the case of the school bus, or they might not. The results with the static-y images suggest that, at least sometimes, these cues can be very granular. Perhaps in training, the network notices that a string of "green pixel, green pixel, purple pixel, green pixel" is common among images of peacocks. When the images generated by Clune and his team happen on that same string, they trigger a "peacock" identification.

A couple of years ago the directors of a women's clothing company asked me to help them develop better fashion recommendations for their clients. No one in their right mind would seek my personal advice in an area I know so little about--I am, after all, a male computer scientist--but they were not asking for my personal advice. They were asking for my machine-learning advice, and I obliged. Based purely on sales figures and client surveys, I was able to recommend to women whom I have never met fashion items I have never seen. My recommendations beat the performance of professional stylists.