RIT 2017 Internship Experience

The last regular day of work. Today i finally think i perfected my presentation, at least i should have. All i have left to do is practice my verbal speaking, and have the suave confidence of a 1940's salesman. Final day bring it on.

Today we had our presentation practice and i can say without a doubt i was the least prepared for the 10 minute limit. After nearly bombing the pre-presentation i learned much watching the others and then took the rest of the day to implement what i had learned to my presentation. After cutting back on the content and implementing hidden notes into the presentation to have a backup for vocal information, i presented again later that day improving much more than before but still 3 minutes over the 10 minute limit. I know exactly what i should do and will implement it, and send it to Joe tomorrow before the day is through. I do have to focus on my verbal presentation skills more, i find that once i hit a block of explaining the information the quality of the rest of the presentation is reduced.

Today was a solid day. The majority of the day was finalizing my Presentation for tomorrow. And the rest of the day was getting the reinforcement code to launch via command line, and editing the code in visual studio. The internship is ending soon and all loose ties are being tied up. I'm beginning to think about all the things i must do in the coming months to prepare for my application to RIT this coming fall. I've much to do and after the internship ends, i will have no time to hesitate in my preparations to ensure i am not only accepted, but am received with priority or at least regard.

The mass allotment of time was allocated towards further work on my final presentation. I also worked on an updated abstract which better represents what will be talked about on the day of presentation. The rest of the day was dedicated towards the reinforcement code toy problems.

Joe, i suggest using this new abstract and the title as it is more representative of the final presentation. Modelling Human Hand-eye Coordination Using Machine Learning Titus Mickley Perform laboratory Advisors: Kamran Binaee, Rakshit Kothari, Gabriel J. Diaz We use our   visual system  to collect information of an environment, and perform an  action such as catching an object.  Currently machines do not have the same capabilities as humans when it comes to analyzing an environment and performing inside the environment  efficiently .  By recording participants head, hand, and eye position/orientation in a controlled virtual environment as the subjects repeatedly attempt to catch a  virtual  ball  with a real  paddle. A simulation of the virtual environment was created to convey the subjects data visually. A basic Reinforcement Learning algorithm is then created, allowing an agent to learn autonomously in a 3D ecosystem. The results of the study could assist in integrating

Today has been a immensely productive day. I have been working on my Presentation and after getting it to a semi-presentable state i showed everyone at the weekly meeting to get as much critique as i can. I got a lot of positive critique and overall most of the senior staff were impressed with what i had currently shown and where i said i would take the presentation. I will continue to work on my presentation until every aspect is deemed perfect by my standards and the standards of those around me.