1. HOW MACHINE LEARNING WILL REVOLUTIONISE THE 21 ST CENTURY Ioannis Mamalikidis, UID: 633 1 Aristotle University of Thessaloniki, Faculty of Sciences, Dept. Informatics Course Instructor: Dr. Ioannis Vlahavas

2. INTRODUCTION Requires comprehension Too many things to programme Implies re-programming on major changes, i.e. for a robot of a different form factor Robots and Machines fall short in one major and basic way: Common Sense The more natural something comes to us, the less we understand how it works Abstract Object Identification like mugs and towels which come in different shapes, colours, and textures Pre-programming tasks has proved to be a recipe for disaster for things that come most natural Machine Learning Neural Networks Artificial Intelligence The way to further our robots’ capabilities is to make them mimic our brains Ioannis Mamalikidis, UID: 6332

3. HISTORICAL DATA ON MACHINE LEARNING Ioannis Mamalikidis, UID: 6333

4. MACHINE LEARNING AND ALGORITHMS Ioannis Mamalikidis, UID: 6334

5. MACHINE LEARNING IMPORTANT DISCOVERIES [1/2] By combining computer science and neuroscience through Machine Learning robots can mimic the way our brain perceives sensory data In MIT researchers tested the object recognition capabilities of a machine compared to a human Dr. Michio Kaku lost with an accuracy of 60% compared to the 85% of the machine It’s hard because machines “see” numbers and waveforms Different colours, brightness, rotation, folding, depth, expressionDeciding what it is from an array of numbers or waveforms What is missing then? PerceptionVisionHearingSmellingTouch Machines today are mechanically capable of doing everything we need Ioannis Mamalikidis, UID: 6335

6. MACHINE LEARNING IMPORTANT DISCOVERIES [2/2] Machine Learning is going to help us live longer and with better quality of life Genome Sequencing Human User Manual Subtracting young genes from Old ones People Classification Treating Genetic Diseases Everyday objects to our rescue Cancer could as well be erased from the language Ioannis Mamalikidis, UID: 6336

7. MACHINE LEARNING IN ROBOTICS [1/3] Modular Robots Modules have minds Capability to control others Ability to comprehend where it is inside the array They adjust the way they move Walking Robots Walking is extremely complicated 20 years of research for Asimo to walk Possibilities with programmable matter Robots sent to space Dynamic Manoeuvres Difficulty acquiring accurate information Highly nonlinear system, noise, vibration, coupled dynamics Traditional methods falter in dynamic state (changing position) Machine Learning, learning the best trajectory (Fig) Ioannis Mamalikidis, UID: 6337

8. MACHINE LEARNING IN ROBOTICS [2/3] Robot Exploration Machines should move in any environment Testing in quadrupeds: Training VS DARPA Test environments (Fig. 1.) Demonstrating the path across the “training terrain” Running the apprenticeship learning algorithm Receiving “testing terrain” height map Finding the optimal policy to cross the testing terrain The future of Rovers, information and substances extraction Safe exploration Avoiding the hole (Fig. 2.) Assuming it can handle slopes up to a number (Fig. 2.) Learning the place (Fig. 3.) Jumps upwards in the beginning, then becomes bolder Ioannis Mamalikidis, UID: 6338

9. MACHINE LEARNING IN ROBOTICS [3/3] Self-Exploration: (Fig. 1) No internal model, form is a black box Sensory data create morphology hypotheses to be disproved Despite not been programmed to, having no training, and no model of itself to begin with, it learned how to move Darwin (Fig. 2.) learns how to walk like a human baby Trial and Error / Falling down and trying again It masters it eventually, like humans do Nadine (Fig. 3.) Nanyang Technological University’s receptionist Seems like a human: Real hair and soft skin Speaks: It has a voice Comprehends: It has real object recognition Ioannis Mamalikidis, UID: 6339

10. CONCLUSION New materials have often had unimaginable impact on societies Concrete and steel remodelled our cities That would be dwarfed by the technologies and materials of the future Robots in Everyday life Robots will, in essence operate like human being They will begin learning from one another We’ll get them out of their usual environment, and into our homes, hospitals and offices Even simple programmes like search engines will be changed Ioannis Mamalikidis, UID: 63310 References are available in the original paper Thank you!