Artificial intelligence at ETH Zurich
Artificial intelligence is having a growing impact on our daily lives and is also revolutionising research. ETH Zurich recognises its responsibility in this area and is striving to promote innovation and trust in this fast-evolving technology.
The applications and methods of artificial intelligence (AI) are becoming increasingly visible and present in the everyday life of science, business and society. AI and machine learning not only affect private users and industrial processes, but are also changing the way in which researchers and computers share their work (see box below).
In principle, AI can help to expand methods in every field of research, and both AI and machine learning are now firmly established in teaching, research and knowledge transfer at ETH Zurich.
Innovation through connecting research areas
ETH Zurich’s strength in AI lies in:
- Excellent basic research into the theory and methods of AI in mathematics, statistics, computer science, IT and data science, with a focus on learning-based methods.
- Excellent cutting-edge research that applies AI, and the quality of infrastructure. AI applications can be found in research fields as diverse as natural sciences, engineering, robotics, health, manufacturing, climate, environment, energy, mobility, architecture, construction, design, society, law and security policy.
A combination of excellence in the general aspects of AI and cutting-edge research in the individual disciplines offers huge potential for innovative AI methods that are reliable, explicable and trustworthy.
The ETH AI Center – a central hub for AI
Building on its existing strengths, ETH Zurich opened the ETH AI Center in October 2020. The new ETH AI Center will lead the way towards trustworthy, accessible, and inclusive AI systems for the benefit of society.
It unites researchers of AI foundations, applications, and implications across all departments at ETH. Starting with the involvement of 29 professorships, its own premises and new Fellowship programmes, the centre will reinforce ETH’s strong position in research into this key technology.
The ETH AI Center will join forces with the best AI research institutes in Europe and beyond to accelerate progress, support start-ups and collaboration in industry, and promote the next generation of AI researchers, managers and entrepreneurs. The ETH AI Center is part of the European AI network external pageELLIS and a platform for dialogue between science, business, politics and society.
Contact
ETH AI Center
Universitätstrasse 6
CAB E 73.1
8092
Zurich
Schweiz
Rising student numbers in AI
The student numbers at ETH reflect the increased importance of AI: in 2012/13, just a few hundred students attended a course in machine learning – this figure has now risen to almost 4,000. “Introduction to Machine Learning” is the most popular lecture. Every ETH department has students who attend courses in AI.
Since 2017, ETH has been responding to this demand with an additional Master’s programme in data science and a diploma of advanced studies in data science.
Wide range of ETH spin-offs in the AI field
ETH spin-offs from the ICT (information and communication technology) sector generally account for a high proportion of newly established ETH spin-offs, and this share has recently increased further still.
In the last three to five years, the number of new start-ups and ETH spin-offs with an AI focus has also increased. The founders include students, graduates and professors.
ETH spin-offs that use AI methods are active in a wide range of areas, as illustrated by the following selection: real estate (UrbanDataLab), pharma (aiNET, deepCDR), cybersecurity (Exeon Analytics, Xorlab, Futurae), model development (Modulos, LatticeFlow), sewer inspections (Hades Technologies), autonomous robots and drones (Sevensense, Voliro, SeerVision).
An overview of further ETH spin-offs in AI and other areas is available from ETH transfer. The ETH AI Center contributes to strengthening AI start-ups and entrepreneurship.
Artificial intelligence and machine learning
Artificial intelligence (AI) refers to technology that enables computers to help humans with tasks that require intelligence to solve.
One important area of artificial intelligence is “machine learning”, which has its roots in statistical and data-driven processes. In machine learning, a computer uses training data to learn independently how to identify patterns and regularities in datasets.
Such processes can generate valuable results, particularly in the case of very large, complex or heterogeneous data sets. AI methods complement the researchers’ creativity and often deliver surprising suggestions that researchers have not considered.
