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Concept

Existential risk from artificial general intelligence

Related publications (20)

Probabilistic and Deterministic Wellposedness for Low Regularity Dispersive Equations

Katie Sabrina Catherine Rosie Marsden

In this thesis we will present two results on global existence for nonlinear dispersive equations with data at or below the scaling regularity. In chapter 1 we take a probabilistic perspective to study the energy-critical nonlinear Schrödinger equation in ...

EPFL2024

Waterborne Virus Transport and Risk Assessment in Lake Geneva Under Climate Change

Tamar Kohn, Chaojie Li

Climate changes influence lake hydrodynamics and radiation levels and thus may affect the fate and transport of waterborne pathogens in lakes. This study examines the impact of climate change on the fate, transport, and associated risks of four waterborne ...

2024

Next-Generation Closed-Loop Neural Interfaces: Circuit and AI-driven innovations

Mahsa Shoaran

Next-Generation Closed-Loop Neural Interfaces: Circuit and AI-driven innovations ...

IEEE Solid-State Circuits Magazine ( Volume: 15, Issue: 4, Fall 2023)2023

The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations

Tanja Christina Käser Jacober, Vinitra Swamy, Jibril Albachir Frej

Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems, often defined as determining which features are most important to a model's prediction. As models get larger, more ubiquitous ...

2023

Language Model Decoding as Likelihood–Utility Alignment

Boi Faltings, Robert West, Maxime Jean Julien Peyrard, Debjit Paul, Valentin Hartmann, Martin Josifoski, Frano Rajic, Jiheng Wei

A critical component of a successful language generation pipeline is the decoding algorithm. However, the general principles that should guide the choice of a decoding algorithm re- main unclear. Previous works only compare decoding algorithms in narrow sc ...

Assoc Computational Linguistics-Acl2023

A Multimodal Dataset for Automatic Edge-AI Cough Detection

David Atienza Alonso, Tomas Teijeiro Campo, Lara Orlandic, Jérôme Paul Rémy Thevenot

Counting the number of times a patient coughs per day is an essential biomarker in determining treatment efficacy for novel antitussive therapies and personalizing patient care. Automatic cough counting tools must provide accurate information, while runnin ...

New York2023

Probabilistic methods for neural combinatorial optimization

Nikolaos Karalias

The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

EPFL2023

Robust Training and Verification of Deep Neural Networks

Fabian Ricardo Latorre Gomez

According to the proposed Artificial Intelligence Act by the European Comission (expected to pass at the end of 2023), the class of High-Risk AI Systems (Title III) comprises several important applications of Deep Learning like autonomous driving vehicles ...

EPFL2023

Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain

Georg Michael Joachim Starke

The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain- ...

2023

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Marco Antonio Rios

By supporting the access of multiple memory words at the same time, Bit-line Computing (BC) architectures allow the parallel execution of bit-wise operations in-memory. At the array periphery, arithmetic operations are then derived with little additional o ...

2023

Large-scale detection of marine debris in coastal areas with Sentinel-2

Devis Tuia, Marc Conrad Russwurm, Sushen Jilla Venkatesa

Detecting and quantifying marine pollution and macroplastics is an increasingly pressing ecological issue that directly impacts ecology and human health. Here, remote sensing can provide reliable estimates of plastic pollution by regularly monitoring and d ...

Cell Press2023

Re-focusing explainability in medicine

Georg Michael Joachim Starke

Using artificial intelligence to improve patient care is a cutting-edge methodology, but its implementation in clinical routine has been limited due to significant concerns about understanding its behavior. One major barrier is the explainability dilemma a ...

2022

Advancing the Adaptability of Compliant Robot Controllers for Exploration, Interaction, and Manipulation

Farshad Khadivar

As technology continues to evolve, robots are becoming an intrinsic part of our lives. While robots surpass human capabilities in precision and speed, they are far from matching humans' ability to adapt to unexpected changes. Humans can quickly and complia ...

EPFL2022

Using “proof of personhood” to tackle social media risks

Bryan Alexander Ford, Aengus Killian Collins

The ease of creating fake virtual identities plays an important role in shaping the way information — and misinformation — circulates online. Social media platforms are increasingly prominent in shaping public debates, and the tension between online anonym ...

International Risk Governance Center (IRGC)2021

Current Solutions and Future Trends for Robotic Prosthetic Hands

Silvestro Micera, Solaiman Shokur, Vincent Alexandre Mendez

The desire for functional replacement of a missing hand is an ancient one. Historically, humans have replaced a missing limb with a prosthesis for cosmetic, vocational, or personal autonomy reasons. The hand is a powerful tool, and its loss causes severe p ...

ANNUAL REVIEWS2021

Learning and leveraging shared domain semantics to counteract visual domain shifts

Róger Bermúdez Chacón

One of the main limitations of artificial intelligence today is its inability to adapt to unforeseen circumstances. Machine Learning (ML), due to its data-driven nature, is particularly susceptible to this. ML relies on observations in order to learn impli ...

EPFL2020

Butterfly Attack: Adversarial Manipulation of Temporal Properties of Cyber-Physical Systems

Mathias Josef Payer, Amir Aminifar

Increasing internet connectivity poses an existential threat for cyber-physical systems. Securing these safety-critical systems becomes an important challenge. Cyber-physical systems often comprise several control applications that are implemented on share ...

IEEE2019

PROPER: global protein interaction network alignment through percolation matching

Matthias Grossglauser, Seyed Hamed Hassani, Ehsan Kazemi, Hasan Pezeshgi Modarres

Background The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological know ...

2016

Experimental and theoretical analysis of capillary-driven self-alignment dynamics for R2R manufacturing of system-in-foil devices

Massimo Mastrangeli

This paper reports a study on the dynamics of foil-based functional component self-alignment on big plastic substrates. We investigate the dependence of alignment time and final precision of stacking of foil dies on a number of system parameters, such as p ...

2012

Reform and risk management in the urban water sector : the role of regulation

Traditionally, urban water services were characterised by local monopolies, where the incumbent was publicly-owned. This was explained by safety, health, economic, and technological reasons related to the sector's specificities. However, in spite of this, ...

EPFL2007