We’re back again continuing to present some interesting episodes from Munich AI Summit 2018 hosted by Develandoo AI Innovation Lab. The summit, a first of its kind in the Munich area, was an AI innovation hub for many renowned speakers in the field presenting their achievements and speaking about the future of AI as well as hundreds of participants who were there to enjoy an insightful day of AI talks.
In today’s article, we’re presenting an interview with one of our prominent speakers Mohsen Kaboli who is a postdoctoral researcher and TUM-IAS fellow at the Institute for Cognitive Systems (ICS), the Technical University of Munich. He is the co-founder of TUM RoboCup soccer team and has been awarded a Ph.D. in robotics, and tactile sensing with the highest distinction (summa cum laude) from the Technical University of Munich (TUM) in 2017. He received his Master’s degree in signal processing and machine learning under the supervision of Prof. Danica Kragic from the Royal Institute of Technology (KTH), Sweden in 2011, and in April 2013 he was awarded a three-year Marie Curie scholarship to pursue a Ph.D. at the Institute for Cognitive Systems (ICS). In March 2012, he received an internship scholarship from the Swiss National Foundation for 18 months in order to continue his research as a research assistant at the Idiap lab, Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland. From September 2015 through January 2016, Kaboli spent 5 months as a visiting research scholar at the Intelligent Systems and Informatics Lab (ISI) directed by Prof. Yasuo Kuniyoshi at the University of Tokyo, Japan.
Kaboli’s talk was devoted to the Sense of Touch in Robotics, one of the most engaging topics at the summit.
Our speaker has developed a 9-month-old baby robot, the first baby robot in the world. He says the idea of the human study was to build up a research platform in order to implement or test the methodology they were developing AI. ‘’When we are talking about machine learning, many people are just thinking about data mining, just taking some data, training some algorithm, like classifying or like using some method as reinforcement learning, unsupervised learning, but actually this is not a real learning, because when we are talking about the learning, for me the learning should be the perception, because we perceive the situation, the environment, then we try to interpret, we are interacting in order to adapt or let’s say, modify the perception, then we use that one in order to learn, and we don’t learn enough, we again go back to our perception. So, perception, action, and learning. For me, this is AI,’’ explains Kaboli.
He argues that people are just concentrated on the learning part; they are not taking care of the interaction, action, and perception, which are very important for any autonomous or cognitive systems. Why a sense of touch? Kaboli says one of the main reasons to study the sense of touch is that it’s more challenging than the vision.
‘’For example, we know that there is some fancy machine learning method which is called deep learning. We’re using the cameras collecting thousands of data, and then we do the classification. But when it comes to the touch, it’s impossible because when you are touching the object, if the object is rough or for example, broken object, you know, after 1- 2 times touching or collecting data, you start bleeding because the body, our skin, are in contact with the objects. The other thing is that we have 5 million tactile sensors, but two cameras when it comes to information processing and transmitting, we have to be more intelligent. You know, we have to know how to process the data and how much data to transfer, because maybe some of the data are irrelevant. And at the moment with the robotic system, we are not able to, for example, use thousand GPU in order to process the data’’.
We had summed up some interesting points from our speaker’s talk, and if they caught your interest, you could check out the full video of the interview on our youtube channel. He further goes deep by explaining how to learn a robot not to hurt and some interesting information about his studies.
We are thankful to all our sponsors and participants and the speakers for attending our Munich-AI Summit 2018, the one and only free event at Munich related to Artificial Intelligence. We invite to our AI platform all representatives in the field of Artificial Intelligence, AI experts, and simply those who are interested in the exchange of ideas within AI innovation and big data analytics in 2019.
Develandoo has also incubated three in-house startups which are leading the markets in their areas of expertise:
- Scylla – World’s leading gun detection system
- Cibola – World’s first in-store analytics system
- Protogen – Generic Tabular Data platform
For more information, please visit – https://develandoo.com
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