Two possibilities occur to me:

1) Personal digital assistant (e,g, Apple's Siri). As the technology improves, this will turn your cell phone into a very smart and capable info-servant. Within 5 years, Siri (and its ilk) *will* change the way we interact not only with computers, but the outside world. (Of course this assumes the availability of speech recognition and generation as well.)

2) Automated government regulation. Many gov't regulations require businesses to summarize and report their activity on a regular basis (e.g. monthly/quarterly) so regulators can confirm that gov't's many laws are obeyed. In a few years this likely will change. Government will monitor business transactions automatically in real time, looking for patterns that have been found to predict / reveal misbehavior (illegal as well as just non-conforming). This could greatly lighten governmental oversight and make it almost impossible to game the system, since the patterns of misbehavior would be formed through machine learning, not procedural statute. Since regulator patterrns would not be publically visible, they'd be very hard to circumvent. This could reinvent the role of government and regulatory oversight.

Hello Bashar,

I think the killer application of ML could be the one that can learn replicating the human nervous system. Such an application can be both used as a tool for understanding human nervous system, as well as it can be used to program human-like robots.

We are currently working on this kind of research and you can find our initial findings in our latest paper. Here is the link for its preprint version:

http://efe.ege.edu.tr/~ogurcan/publications/gurcan_et_al_saso_2012_preprint.pdf

Önder.

Two possibilities occur to me:

1) Personal digital assistant (e,g, Apple's Siri). As the technology improves, this will turn your cell phone into a very smart and capable info-servant. Within 5 years, Siri (and its ilk) *will* change the way we interact not only with computers, but the outside world. (Of course this assumes the availability of speech recognition and generation as well.)

2) Automated government regulation. Many gov't regulations require businesses to summarize and report their activity on a regular basis (e.g. monthly/quarterly) so regulators can confirm that gov't's many laws are obeyed. In a few years this likely will change. Government will monitor business transactions automatically in real time, looking for patterns that have been found to predict / reveal misbehavior (illegal as well as just non-conforming). This could greatly lighten governmental oversight and make it almost impossible to game the system, since the patterns of misbehavior would be formed through machine learning, not procedural statute. Since regulator patterrns would not be publically visible, they'd be very hard to circumvent. This could reinvent the role of government and regulatory oversight.

Hi Önder Gürcan , Wai-keung Fung and Randolph Crawford.

Thank you for responding to my question and sharing your views.

Good answers indeed!

Bashar

Different perspectives lead to different killer applications of ML.

The first perspective is that losing the trust in ML approaches. From this perspective, the killer application is characterized by missing dimensions and information that cause undesirable characteristics for the data such as very heavy overlap. understanding speeches over internet automatically using a computer is an example of these applications since there are overlap between the pronunciations from different countries.

The second perspective is producing a robust tool that replace ML itself. This could be a smart system that able to design a representation model for new applications and generating a learning algorithm with an optimal adaptive behavior to the characteristics of the data.