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Concept

Artificial intelligence

Related lectures (31)

Knowledge Representation: Introduction

Covers knowledge representation in AI, logical inference, and applications in various domains.

Provably Beneficial AI: Towards Human-level Understanding

Explores provably beneficial AI, aligning AI goals with human preferences and behaviors, illustrating complexities through examples like image classification and fetching coffee.

Neural Networks: Multilayer Perceptrons

Covers Multilayer Perceptrons, artificial neurons, activation functions, matrix notation, flexibility, regularization, regression, and classification tasks.

Global Governance of AI

Explores the importance of global governance in Artificial Intelligence, emphasizing ethical practices, bias issues, and trust in AI technologies.

Landscape and Generalisation in Deep Learning

Explores the challenges and insights of deep learning, focusing on loss landscape, generalization, and feature learning.

Digitalization: Urban Systems Governance MOOC: Smart Cities, Management of Smart Urban Infrastructures

Delves into data generation, communication networks, IoT, and analytics in urban systems.

Ethics and Law of AI

Delves into different ethical theories and thought experiments in the context of AI, exploring the challenges of defining AI.

Data-Driven Insights: NLP and AI Applications

Explores building OS for heterogeneous hardware, data movement efficiency, AI advancements, and NLP challenges.

Normative News Recommender Systems

Explores challenges in developing normative news recommender systems and the ethical considerations in AI, journalism, and diversity.

Brain Intelligence: Continual Learning of Representational Models

Delves into the continual learning of representational models after deployment, highlighting the limitations of current artificial neural networks.

Bio-Inspired Learning: Neural Networks, Genetic Algorithms

Explores bio-inspired learning with neural networks and genetic algorithms, covering structure, training, and practical applications.

TILT EPFL-UNIL: Interdisciplinary Learning and Teaching

Introduces the TILT course, emphasizing reproducibility, data construction, and ethical considerations in a quantified world.

Social Media and AI for Emergency Response MOOC: A Resilient Future: Science and Technology for Disaster Risk Reduction

Explores social media analysis for emergency response and digital volunteerism tools.

Understanding Autonomy

Explores the challenges and distinctions between human and artificial autonomy, touching on ethical implications and the conditions required for true autonomy.

Introduction to Machine Learning

Covers the basics of machine learning for physicists and chemists, focusing on image classification and dataset labeling.

Ethics of AI: Update Al Act

Explores the ethical implications and risks of AI, focusing on the Update Al Act and high-risk AI systems.

EPFL Campus Overview

Covers the EPFL campus facilities, research areas, fellowship process, and program requirements.

Machine Learning at EPFL

Explores the EPFL Alice unit's role in shaping machine learning and AI in Europe, focusing on research advancements and collaboration within the AI community.

Machine Learning for Physicists/Chemists: Image Classification Log in to Mediaspace to watch this video

Covers the fundamentals of machine learning for physicists and chemists, focusing on image classification tasks using artificial intelligence.

Graph Neural Networks: Interconnected World Log in to Mediaspace to watch this video

Explores learning from interconnected data with graphs, covering modern ML research goals, pioneering methods, interdisciplinary applications, and democratization of graph ML.