“Learning How to Learn”: Techniques to Help You Learn with Dr Barbra Oakley (CLASSIC)

Learning How to Learn

Humans have fundamental ability and cognitive resources to learn new concepts and acquire new skills and knowledge, although this may not seem natural to most of us at first. The key is to understand how the brain works so we can harness its potential by developing and adopting learning techniques that are effective and more rewarding. In this episode of Bridging the Gaps, I speak with Dr Barbara Oakley about “Learning how to learn”. Dr. Oakley encourages learners to recognize that everyone learns differently. Recognizing the benefits and drawbacks of various learning approaches depending on a learner’s natural brain functioning, she argues, is the first step in learning how to handle new information.

Dr Barbara Oakley is a professor of Engineering at Oakland University in Rochester, Michigan. She is an inaugural “Innovation Instructor” at Coursera, an online course provider, where she co-taught one of the world’s most popular massive open online course “Learning How to Learn”. Her work focuses on the complex relationship between neuroscience and social behavior. She has written many books including “Learning How to Learn: How to Succeed in School Without Spending All Your Time Studying; A Guide for Kids and Teens”. Her book “Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential” is also relevant to this discussion.

We start the conversation by discussing Dr Oakley’s education and professional journey, which led to her developing interest in “Learning how to learn”. We then discussed our present understanding that how learning occurs in the brain and how the brain acquires new knowledge. Dr Oakley explains why it is important to understand the working and functioning of the brain for developing and adopting effective learning techniques. Mindshift on Bridging the Gaps She then explains a number of effective techniques for effective learning such as when to focus and when to take a break, she discusses significance of practice and being persistent. Dr Oakley then discusses in detail the effectiveness of Pomodoro technique. We then discuss the future of MOOC (Massive Open Online Courses) and universities in the age of online teaching and learning. We also touch upon the possible impact of over-reliance on and excessive use of technology for online learning.

Complement this discusion with Growth Mindset: A Must Have Tool for Success with Professor Carol Dweck and then listen to
And then listen to Education: What works and what does not, with Professor John Hattie. Also listen to Multiple Intelligences, Future Minds and Educating The App Generation: A discussion with Dr Howard Gardner.

By |January 3rd, 2022|Knowledge, Neuroscience, Podcasts, Research|

“The Self-Assembling Brain” and the Quest for Artificial General Intelligence with Professor Peter Robin Hiesinger

How does a network of individual neural cells become a brain? How does a neural network learn, hold information and exhibit intelligence? While neurobiologists study how nature achieves this feat, computer scientists interested in artificial intelligence attempt to achieve it through technology. Are there ideas that researchers in the field of artificial intelligence borrow from their counterparts in the field of neuroscience? Can a better understanding of the development and working of the biological brain lead to the development of improved AI? In his book “The Self-Assembling Brain: How Neural Networks Grow Smarter” professor Peter Robin Hiesinger explores stories of both fields exploring the historical and modern approaches. In this episode of Bridging the Gaps, I speak with professor Peter Robin Hiesinger about the relationship between what we know about the development and working of biological brains and the approaches used to design artificial intelligence systems.

We start our conversation by reviewing the fascinating research that led to the development of neural theory. Professor Hiesigner suggests in the book that to understand what makes a neural network intelligent we must find the answer to the question: is this connectivity or is this learning that makes a neural network intelligent; we look into this argument. We then discuss “the information problem” that how we get information in the brain that makes it intelligent. We also look at the nature vs nurture debate and discuss examples of butterflies that take multigenerational trip, and scout bees that inform the bees in the hive the location and distance of the food. We also discuss the development of the biological brain by GNOME over time. We then shift the focus of discussion to artificial intelligence and explore ideas that the researchers in the field artificial intelligence can borrow from the research in the field of neuroscience. We discuss processes and approaches in the field of computing science such as Cellular Automata, Algorithmic Information Theory and Game of Life and explore their similarities with how GENOME creates the brain over time. This has been an immensely informative discussion.

Complement this discussion by listening to The Spike: Journey of Electric Signals in Brain from Perception to Action with Professor Mark Humphries and then listen to On Task: How Our Brain Gets Things Done” with Professor David Badre.

Quantum Computers: Building and Harnessing the Power of Quantum Machines with Professor Andrea Morello

Quantum computers store data and perform computations by utilizing properties of quantum physics. Quantum computations are performed by these machines by utilizing quantum state features such as superposition and entanglement. Traditional computers store data in binary “bits,” which can be either 0s or 1s. A quantum bit, or qubit, is the fundamental memory unit in a quantum computer. Quantum states such as the spin of an electron or the direction of a photon, are used to create qubits. This could be very useful for specific problems where quantum computers could considerably outperform even the most powerful supercomputers. In this episode of Bridging the Gaps I speak with professor Andrea Morello and we discuss fascinating science & engineering of conceptualizing and building quantum computers. Professor Andrea Morello helps us to unpack and tackle questions such as what a quantum computer is and how we build a quantum computer.

Andrea Morello is the professor of Quantum Engineering in the School of Electrical Engineering and Telecommunications at the University of New South Wales Sydney, Australia.

I begin our conversation by asking professor Morello what a quantum computer is, and how it differs from classical and conventional computers. The no-cloning theorem’s implications in the field of quantum computers are next discussed. The no-cloning theorem states that it is impossible to create an independent and identical copy of an unknown quantum state. Professor Morello’s team uses single-spin in silicon to construct quantum computers, and we go over their approach in depth. The true value of quantum computers can only be realised if we develop creative algorithms that make effective use of quantum computers’ exponentially huge information space and processing capability. We discuss this in detail. We also touch upon the concept of quantum chaos and discuss research in this area. This has been a fascinating discussion.

Complement this with “2062: The World That AI Made” with Professor Toby Walsh and then listen to “Artificial Intelligence: Fascinating Opportunities and Emerging Challenges with Professor Bart Selman.