Technology

Algorithmic biases: neural networks are also influenced by hardware

• Researchers have demonstrated that the fairness of AI models is dependent on hardware platforms used for their deployment. Some hardware configurations have been found to introduce demographic biases which are highly problematic, notably for healthcare applications.
• Model compression is proposed as a key solution for deploying neural networks on devices with limited hardware resources, such as AI capable PCs or edge computing devices.
• The adoption of co-design frameworks for hardware and software architectures will play an essential role in the drive to optimise the fairness and performance of AI models. The integration of non-volatile memory (NVM) devices and noise reduction in neuromorphic systems are also promising avenues for future development.
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An individual in a lab coat and protective glasses holds a microprocessor in their gloved hand. The setting is bright and modern, suggesting a research or technology development laboratory.
Soft Robotics Lab - ETH Zürich (lab head: Prof. Robert Katzschmann (not in the picture). From left to right: Jose Greminger (Master student), Pablo Paniagua (Master student), Jakob Schreiner (visiting PhD student), Aiste Balciunaite (PhD student), Miriam Filippi (Established researcher), and Asia Badolato (PhD student).

“Biohybrid robotics needs an ethical compass”

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Soft Robotics Lab – ETH Zürich (lab head: Prof. Robert Katzschmann (not in the picture). From left to right: Jose Greminger (Master student), Pablo Paniagua (Master student), Jakob Schreiner (visiting PhD student), Aiste Balciunaite (PhD student), Miriam Filippi (Established researcher), and Asia Badolato (PhD student).

When will we see living robots? The challenges facing biohybrid robotics

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A mathematical model to help AIs anticipate human emotions

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Lower emissions and reinforced digital sovereignty: the plan for datacentres in space

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person wearing bioelectronic fibre arrays for dual-ECG signal acquisition / credit: Wenyu Wang and Yuan Shui

Bioelectronics: disease monitoring sensors that can be printed directly onto human skin

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GettyImages - A woman is working on a computer, surrounded by two screens displaying code. The office environment is bright and modern, with stationery items visible on the desk.

Tom Chatfield: “AI could lead to a massive pollution of the world’s data and the erasure of trust.”

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