sharadsinha

Artificial Intelligence (AI) for All Workshop

In Artificial Intelligence, Education, Science & Technology Promotion and Public Policy, Welcome to Engineering on September 3, 2019 at 10:16 PM

My colleague, Clint and I organized an AI for All workshop on August 31, 2019. The workshop was attended by forty high school students and their teachers from school in and around Ponda, Goa. It was a day well spent in an academic activity where we interacted with these students and introduced very basic concepts of AI to them. Our hope is to get them excited about AI and that they develop an inquisitiveness to learn more about it. The workshop was supported by a grant from ACM Special Interest Group on AI (SIGAI) under its AI Activities Fund.

We also released an “Artificial Intelligence (AI) Storybook” which is available for free download: ACM-SIGAI-IIT Goa-Storybook.

The student participants were given printed copies of the storybook as a token of appreciation for showing interest in the subject of artificial intelligence.

AI for All Workshop

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Auctioning Algorithms : for those who design algorithms!

In Education, Research and Development on April 20, 2017 at 4:56 PM

The Algorithm Auction was the world’s first auction of algorithms in 2015. This auction was meant, like most other auctions, to celebrate something. In this case, it was the algorithms (in the form of code) that can be considered artsy. Organized by Cooper Hewitt, Smithsonian Design Museum and Artsy, the auction brought together vintage items like hand written and signed code of the original Hello World C program by Brian Kernighan, a very compact Perl code (6 lines and named qrpff) that could decrypt content on a DRM protected video disc etc. The qrpff code fetched 2500 US$.

I had only heard about auctions of cellular spectrum, houses, historical artifacts and vintage collection items. The auction of algorithms was the idea of a company by the name Ruse Laboratories which it seems has ceased to exist. I could not find any good reference or website. Nevertheless, I think that this was a wonderful idea. Looking for art in science and technology is very interesting. I had organized a thematic issue around this subject in the Nov-Dec. 2016 issue of IEEE Potentials.  This auction goes to prove that a curious mind can come up with really novel ideas and open up doors for others. My friends who design algorithms have something more to cheer about!

Translational Research: What I learned doing (seemingly) mundane task of video annotation

In Design Methodologies, Education, Embedded Systems, Engineering Principles, Research and Development on November 27, 2016 at 3:04 PM

In the recent past I have been doing some work related to automatic video annotation. Videos that you and I take can be annotated with data about the contents of the video. The contents of the video can mean: objects, their types, their shape, background scene (moving or static), number of objects, static and in-motion objects, color of objects etc. One would like to keep a track of objects as the video progresses. Tracking helps in knowing when an object appeared in the scene and when it disappeared. All of the prior work on automatic video annotation is not really completely automatic [1], [2] etc.. They are semi-automatic at best and manual input and control is still required when annotating using these methods.

While doing this work, I developed a better understanding of some of the so called “automatic object tracking for surveillance” solutions out there in the market.  None of these solutions can ensure a complete hands-off scenario for humans. Humans still need to be involved and there are reasons for that.  At the same time, it is also possible to do everything in cloud (including human interaction) and claim it as “hands off for a user”. In this case, it is simply that the client is paying someone else to provide the service. It is not a stand-alone autopilot kind of system installed in a user’s premises. Real automatic video annotation is extremely hard, especially when the scene can change without any guarantees. If we add “video analytics” i.e. ability to analyse the video automatically to detect a certain set of activities, it again becomes very difficult to propose a general solution. So, assumptions are again made and these can be based on user requirements or can be domain specific (say tennis video analytics at Wimbledon). Here is a system which may be of interest to you: IBM’s Digital Video Surveillance Service and a few others described in the paper titled “Automated visual surveillance in realistic scenarios“.

Most of the research work makes certain assumptions either about the scenes or about the methods they use. These assumptions simply fail in real world scenarios. These methods may work under a “restricted real world view” made using a set of assumptions, but when assumptions fail, these methods become limited in applicability.

I believe this is a critical issue that many researchers who want to translate their work into usable products have to understand. This is where both strong theoretical and practical foundations in a discipline are needed: theory gives the methods and the tools, engineering tells you what can/cannot be done and the two can interact back and forth.