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DATE: 06 January 2020, 16:00 to
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Lecture 1 Public Lecture: 6 January 2020, PM
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Lecture 2: Tuesday 7th January 2020, PM
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Lecture 3: Wednesday 8th January 2020, PM
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Artificial intelligence: success, limits, myths and threats Lecture 1
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ICTS
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ICTS Campus in Bangalore
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What is the Goal of the ICTS?
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Enabled by 3 interactive missions:
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During the past decade ICTS has achieved some measure of success in all its three missions!
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Programs:
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Sample Programs...
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Programs in Machine Learning
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ICTS-Infosys Foundation Lecture series:
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Research
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ICTS People: Faculty
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Students and Postdocs
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ICTS as a platform for new initiatives:
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Science Outreach
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Public Lectures
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Kaapi with Kuriosity
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Abdus Salam Memorial Lectures
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Einstein Lectures
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Vishveshwara Lectures
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D.D. Kosambi Lectures
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Mathematics of Planet Earth MPE 2013, Bengaluru
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Bangalore Area Science Habba
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Mathematics Circles
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ICTS Organization
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ICTS Resources
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Thank You!
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Artificial Intelligence: Success, Limits, Myths and Threats
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Chapter One - Myths and Reality
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The new era of AI
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ImageNet Database and Challenge
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Convoy of self-driving trucks completes first European cross-border trip
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The new era of AI
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2 - Language understanding
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AlphaGo
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July 2019 : Pluribus
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Chapter Two - Machine learning
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Machine Learning
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Test phase=present new picture, that the machine has not yet seen
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Chapter Three - The Machines: Artificial neural networks
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Everyone recognizes
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Artificial neural networks
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Frank Rosenblatt's perception
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What is new since Rosenblatt's perceptron?
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Neural network reading digits
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Performance on handwritten digits
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Deep neural networks
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Bigger networks, more parameters. Larger database!
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New computing paradigm. Collective representation of information, going to larger scales. Robust.
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Chapter Four - Why deep networks are not yet? a panacea
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Three main problems:
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1- Huge amount of labelled data is necessary for learning in deep networks
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Oh, look at ko bamoule! Do you see ko bamoule?
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Chapter Five - About scientific Intelligence
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Quote from Chris Anderson -The end of Theory: The data deluge makes the scientific method obsolete
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Thought experiment :
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We are still very very far from General Artificial Intelligence
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Conclusion - So, what is going to happen?
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Predicting the future
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Predicting the future ?
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A major concern for the present:
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In 2018:
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Take-home message
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The End
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Q&A
Description:
Explore the successes, limitations, myths, and potential threats of artificial intelligence in this comprehensive lecture by Marc Mézard, Director of Ecole normale supérieure - PSL University. Delve into the recent breakthroughs in machine learning and deep networks, examining their applications in image interpretation, speech recognition, and game-playing. Gain insights into how deep networks are programmed to learn from data, understand their current limitations, and critically evaluate whether their achievements truly constitute "intelligence." Reflect on the foundations of scientific intelligence and consider the potential societal impacts of AI, including job displacement and autonomous decision-making systems. Engage with thought-provoking discussions on the future of AI, its role in scientific inquiry, and the ethical concerns surrounding its widespread adoption.

Artificial Intelligence: Success, Limits, Myths and Threats - Lecture 1

International Centre for Theoretical Sciences
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#Computer Science #Artificial Intelligence #Machine Learning #Deep Learning #Computer Vision #Neural Networks #Science #Scientific Method #Autonomous Vehicles #Self-Driving Cars #AlphaGo #ImageNet
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DATE: 06 January 2020, 16:00 to