Challenges and Opportunities of Edge AI for Next-Generation Implantable BMIs

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Chip -scale optical frequency combs enable the generation of highly -coherent pulsed light at gigahertz-level repetition rates, with potential technological impact ranging from telecommunications to sensing and spectroscopy. In combination with techniques ...

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

Electro-optical photonic integrated circuits (PICs) based on lithium niobate (LiNbO3) have demonstrated the vast capabilities of materials with a high Pockels coefficient1,2. They enable linear and high-speed modulators operating at complementary metal–oxi ...

Integrated quantum photonics leverages the on-chip generation of nonclassical states of light to realize key functionalities of quantum devices. Typically, the generation of such nonclassical states relies on whispering gallery mode resonators, such as int ...

Redox homeostasis is a key factor in maintaining cellular function and health. The main determinant of the intracellular redox potential is ubiquitous glutathione (GSH) together with its oxidized dimer (GSSG). Importantly, both redox equilibrium and GSH ho ...

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

Artificial intelligence (AI) is increasingly used in an ever larger number of industries. Alongside this development, however, abundant works argue that AI-driven systems are lacking in terms of safety, ethics and transparency. As a direct consequence, the ...

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

Electrical stimulation of the nervous system has emerged as a promising assistive technology in case of many injuries and illnesses across various parts of the nervous system. In particular, the invasive neuromodulation of the peripheral nervous system see ...

This thesis presents an extensive exploration of neuroelectronic interfaces, focusing on microfabrication, in silico modeling, and their applications in designing and fabricating devices for neural interfacing. The research encompasses both peripheral nerv ...

Neuroprostheses have been used clinically for decades, to help restore or preserve brain functions, when pharmaceutical treatments are inefficient. Although great progress in the field has been made over the years to interface with the nervous system, surf ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Digital twins are virtual models of physical objects or systems that enable real-time monitoring and analysis. In the ﬁeld of stone masonry buildings, digital twins can be used to assess damage, predict maintenance needs, and opti- mize building performanc ...

Implantable neural interfaces with the central and peripheral nervous systems are currently used to restore sensory, motor, and cognitive functions in disabled people with very promising results. They have also been used to modulate autonomic activities to ...

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...

Challenges and Opportunities of Edge AI for Next-Generation Implantable BMIs

Chattez avec Graph Search

Dissipative Kerr soliton generation at 2μm in a silicon nitride microresonator

Graph generative deep learning models with an application to circuit topologies

Lithium tantalate photonic integrated circuits for volume manufacturing

Generation of entangled photon pairs from a silicon bichromatic photonic crystal cavity

HaloTag-Based Tools for Live-Cell Imaging and Elucidation of Organellar Redox Biology

Driving and suppressing the human language network using large language models

Voices from the Frontline: Revealing the AI Practitioners' viewpoint on the European AI Act

Machine Learning for Modeling Stock Returns

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Modeling, fabrication and validation of 3D neural interfaces for peripheral nerves and brain organoids

Unraveling behavior and cortical signals to guide the development of soft neuroprostheses for auditory restoration and spreading depolarization

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

EdgeAI-Aware Design of In-Memory Computing Architectures

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Digital Twins of Stone Masonry Buildings for Damage Assessment

Organ Neuroprosthetics: Connecting Transplanted and Artificial Organs with the Nervous System

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation