First day at IT conference starts with a day of presentations and papers by CITRENZ(Computing and Information Technology Research and Education New Zealand). After the warm welcome by the ITP community and staff, we got to hear our first presentation by Clarke Ching.
Clarke Ching is the author of “Rolling Rocks downhill” and “The Bottleneck Rules” and he talked about how usefull agile is and the act of “going slower” is better for the company. A great saying he said was “we can only go as the slowest department” and in most cases that is the testing/bug fixing teams.
Through out the day i went to nine talks so I will just highlight some my favorites for day one.
Morepork Vocalization
Presented by Tim Hunt, this was properly one of the most impressionable talks over the three days. His talk was about The Cacophony Project, where he built a mobile app that records wild life noises, in the hopes of capturing enough data to figure out if the birds are in danger of prey, how many there are, etc. I really liked this talked because of how they are reusing old phones to capture data and training with 100% open source content. I will definitely research more into this project and hopefully participate in helping them.
Naive approaches to AI
Riley Hunter talked about how there has been a big trend around “AI” and this has lead to a rise in people jumping onto the trend without correctly understanding the approaches and more importantly extracting the correct data from their sets. The example he used was about an AI that would pick the list the best students for the class, however the maker added gender, race and country origin data into the system which created an ethically wrong AI that shouldn’t have that information as a deciding factor.
Computer Vision on FPGA
The last notable presentation was by Firas Al-Ali. He talked about a new FPGA( Field Programmable Gate Arrays ) chip. Usually computer vision and machine learning focuses on using the process of CPU and recently GPU but with this new chip called PYNQ, which was a chip that he programmed to run machine learning predictions and the results was 500 times faster than GPU! This one was really interesting as we are still furthering the technology of how machine learning is working and I will defiantly be looking into buying one to mess around with in the future.
One day down and it was amazing!
Deja Ballard's 