news 2023

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning hardware. With their ability to process vast amounts of data through algorithmic 'learning' rather than traditional programming, it often seems like the potential of deep neural networks like Chat-GPT is limitless.

A research team from EPFL and Wageningen University has developed a new artificial intelligence model that recognises floating plastics much more accurately in satellite images than before. This could help to systematically remove plastic litter from the oceans with ships. Our society relies heavily on plastic products and the amount of plastic waste is expected to increase in the future.

Developed by researchers, the first large-scale in-memory processor using 2D semiconductor materials could substantially cut the ICT sector's energy footprint. As information and communication technologies (ICT) process data, they convert electricity into heat. Already today, the global ICT ecosystem's CO2 footprint rivals that of aviation.

Researchers have developed a new distributed algorithm that, for the first time, solves one of the key performance and reliability problems affecting most of the currently-deployed consensus protocols. Consensus is one of the fundamental problems in distributed systems. It allows a group of machines to maintain multiple copies of data and update them consistently, even when a fraction of the machines might fail.

A new EPFL developed tool, Quotebank , has helped researchers provide the first large-scale data-driven evidence of a drastic shift towards a more negative political tone beginning at the start of Donald Trump's primary campaign in June 2015. A vast majority of Americans believe that the tone and nature of political debate in the United States has become more negative in recent years and more than half have the impression that Donald Trump is responsible.

A symphony of electrical signals and a dynamic tangle of connections between brain cells help us to make new memories. Using AI-powered models of groups of neurons, FMI researchers are working towards unlocking how the brain orchestrate this dance. Their latest study has achieved a major advance in accurately simulating the changes in the connections between neurons that sense the external environment, opening the door to a greater understanding of how countless brain cells transform sensations into perceptions and thoughts.

Evolutionary Biology Artificial intelligence (AI) can help plant scientists collect and analyze unprecedented volumes of data, which would not be possible using conventional methods. Researchers at the University of Zurich (UZH) have now used big data, machine learning and field observations in the university's experimental garden to show how plants respond to changes in the environment.

At Empa, acoustics experts have been investigating for years how noise is generated by passenger and cargo trains - and which technical and structural measures are particularly effective to prevent or at least reduce it. Their findings have now been incorporated into the SILVARSTAR project resulting in a simulation tool for rail noise that can help in practice.

A research team at the University of Basel and the SIB Swiss Institute of Bioinformatics uncovered a treasure trove of uncharacterised proteins. Embracing the recent deep learning revolution, they discovered hundreds of new protein families and even a novel predicted protein fold. The study has now been published in "Nature".

Researchers at ETH Zurich have found a new attack on AMD computer chips in which the attacker plants an "idea" in the computer without it noticing. Using that attack, it was possible to leak data from anywhere in the computer's memory. Everyone has, at one time or another, experienced how dreams can influence our moods and actions.

Scientists show that even a few simple examples are enough for a quantum machine-learning model, the -quantum neural networks-, to learn and predict the behavior of quantum systems, bringing us closer to a new era of quantum computing. Imagine a world where computers can unravel the mysteries of quantum mechanics, enabling us to study the behavior of complex materials or simulate the intricate dynamics of molecules with unprecedented accuracy.

Harnessing advanced simulation tools, a team of scientists from UNIGE, Northwestern University and University of Florida shed light on the enigmatic nature of these celestial "beasts". Black holes, some of the most captivating entities in the cosmos, possess an immense gravitational pull so strong that not even light can escape.

Drawing from Schrödinger's cat thought experiment, scientists at EPFL have built a "critical cat code" qubit that uses bosons to store and process information in a way that is more reliable and resistant to errors than previous qubit designs. Quantum computing uses the principles of quantum mechanics to encode and elaborate data, meaning that it could one day solve computational problems that are intractable with current computers.

A new AI algorithm developed at EPFL and University Hospital Geneva (HUG) will power an intelligent stethoscope - Pneumoscope - with the potential to improve the management of respiratory disease in low-resource and remote settings. As air passes through the labyrinth of small passageways in our lungs, it makes a distinctive whooshing sound.

Researchers have worked with the International Committee of the Red Cross (ICRC) to develop a first of its kind, digital system to support humanitarian aid distribution. The design uses tokens to decentralize the storage and processing of recipients information, reducing the risk of harm, and uses advanced cryptography to enable accountability.

In theory, quantum computers vastly outperform classical computers in terms of computing speed. For them to do so in practice, it is necessary to design more and novel high-speed algorithms, says ETH supercomputing specialist Torsten Hoefler. Quantum computers promise to be capable of solving some computational problems much faster than classical computers.

Compared to classical computers, quantum computers can solve complex problems in parallel and thus faster, but they are also more prone to errors. ZHAW researchers show how a hybrid approach can be used to exploit the strengths of quantum computers in a targeted manner. Quantum computers not only know the state 0 and 1, but can also represent several states between 0 and 1 by means of so-called qubits - analogous to bits of classical computers - and thus calculate many possible results simultaneously.

A research team from EPFL has developed a novel machine-learning algorithm that can reveal the hidden structure in data recorded from the brain, predicting complex information such as what mice see. Is it possible to reconstruct what someone sees based on brain signals alone? The answer is no, not yet.

A team from the University of Geneva and ID Quantique has developed single-photon detectors with unprecedented performance. These results open new perspectives for quantum cryptography. How can we combat data theft, which is a real issue for society? Quantum physics has the solution. Its theories make it possible to encode information (a qubit) in single particles of light (a photon) and to circulate them in an optical fibre in a highly secure way.

Researchers at Empa, ETH Zurich and the "Politecnico di Milano" are developing a new type of computer component that is more powerful and easier to manufacture than its predecessors. Inspired by the human brain, it is designed to process large amounts of data fast and in an energy-efficient way. In many respects, the human brain is still superior to modern computers.