Extra Blog #1: Mobia Modeler: easing the creation process of mobile applications for non-technical users

Comments:

TBD

Reference Information:

Title: Mobia Modeler: easing the creation process of mobile applications for non-technical users

Authors:  Florence Balagtas-Fernandez, Max Tafelmayer and Heinrich Hussmann ofUniversity of Munich, Munich, Germany

Presentation Venue: IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces

Summary:

The researchers of this paper are working on a method by which people without programming skills are able to design and develop applications for mobile devices. The motivation for this is to enable those without any programming skills to be able to build their own apps without having to learn how to program.

The researchers are initially focusing on mobile applications that are related to the health and medical domain spaces. However, they intend to extend their work in the future to other domains unrelated.

Discussion:

This reminds me of a similar push by middleware tool makers that are developing simple visual development tools within the video game development industry. There are a few different potential solutions created to date. There are two that have been developed with people who are more technical in mind. One was the Torque Engine and the other was Unity3D. Both required some knowledge of scripting or programming to make the end results fully effective.

There is currently another tool that is available for users of Apple products. GameSalad, a company that has their development team in Austin, has created a tool to be able to create iPhone and iPad content without having to know Objective C or proper programming techniques. Game can be created by complete neophytes. Still, this doesn't mean that the content produced is going to necessarily be great, but it makes it more accessible to the average person.

Book Reading #52: Living with Complexity

Chapters 3 and 4

Summary:

TBD

Discussion:

TBD

Paper Reading #25: Estimating user's engagement from eye-gaze behaviors in human-agent conversations

Comments:

TBD

Reference Information:

Title: Estimating user's engagement from eye-gaze behaviors in human-agent conversations

Authors:  Yukiko I. Nakano of Seikei University, Tokyo, Japan and Ryo Ishii of NTT, Kanagawa, Japan

Presentation Venue: IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces

Summary:

The goal of the research contained in this paper is to using a software to determine the level of engagement in a conversation being invested by the human participant. The motivation for this study is to create an agent that can creatively control the interactions between itself and the human. The software the researchers propose is intended to be able to learn the human individual's personal gaze profile and tailor its responses accordingly if it detects the human's attention wandering.

Discussion:

This is interesting in that it looks like the authors are trying to create an agent that would have a good chance at passing the Total Turing test. This potential advance could give the agent a more "human" quality that might induce an actual human subject to wonder if the one they are communicating with is a person or a computer. If they could incorporate this appropriately with a full engine to simulate it, there would be a good chance they could fool many people into assuming it was a person on the other end of the communication.

I'm not sure what else it would take, but this could be ultimately incorporated into androids or robots to an extent that we would have intelligent agents housed in bodies that could be instructed to do dangerous or menial work. The one danger is that should these agents achieve consciousness to the extent that they question the validity of their own existence we may find they would choose to take matters into their own hands in such a way that it would prove detrimental to our species. Care should be taken when implementing this so it is mutually beneficial for creator and created.

Book Reading #51: Living with Complexity

Chapters 1 and 2

Summary:

TBD

Discussion:

TBD

Full Blog: Why We Make Mistakes

Comments:

TBD

Reference Information:

Title: Why We Make Mistakes

Author:

Presentation Venue:

Summary:

TBD

Discussion:

TBD

Paper Reading #24: Usage patterns and latent semantic analyses for task goal inference of multimodal user interactions

Comments:

TBD

Reference Information:

Title: Usage patterns and latent semantic analyses for task goal inference of multimodal user interactions

Authors:  Pui-Yu Hui, Wai-Kit Lo, and Helen Meng of The Chinese University of Hong Kong, Hong Kong

Presentation Venue: IUI '10 Proceedings of the 15th international conference on Intelligent user interfaces

Summary:

This paper is about creating a system that has the capability to interpret vocalized speech and written words. The system that is being proposed would be able to ascertain the semantic meanings with the communication and analyze it in such a way that it would demonstrate a form of machine learning.

The system combines the analysis of three subsystems to achieve this result. The system implements latent semantic modeling (LSM). Spoken locative references (SLR) consumes input from parsed Chinese vocalization. With further processing, it is eventually sent to the singular value decomposition (SVD) module. So far, the researchers are reporting a 99% accuracy result using their technique.

Discussion:

I think this could have a profound impact on semantic recognition systems in the future. The Chinese language is comprised of many complex symbols and has been described as one of the most difficult languages to learn. A system with a machine learning capability that would be able to interpret semantic meaning based on user input could go a long way to providing more accurate translations and understanding of input from the language.

This same technique could be applied to other languages. The result of all of this would be the ability to create machines that could take written and spoken input from any language and create an accurate translation of concept and meaning between multiple disparate individuals regardless of cultural heritage or ethnic background.

Book Reading #50: Why We Make Mistakes

Chapters 12 and 13

Summary:

TBD

Discussion:

TBD