Igor Carron
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View article: Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences Open
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions and user experiences, especially in the context of 6G syst…
View article: Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment
Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment Open
Modern deep learning relies nearly exclusively on dedicated electronic hardware accelerators. Photonic approaches, with low consumption and high operation speed, are increasingly considered for inference but, to date, remain mostly limited…
View article: Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment
Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment Open
Artificial Neural Networks (ANN) are habitually trained via the back-propagation (BP) algorithm. This approach has been extremely successful: Current models like GPT-3 have O(10 11 ) parameters, are trained on O(10 11 ) words and produce a…
View article: High-fidelity and large-scale reconfigurable photonic processor for NISQ applications
High-fidelity and large-scale reconfigurable photonic processor for NISQ applications Open
Reconfigurable linear optical networks are a key component for the development of optical quantum information processing platforms in the NISQ era and beyond. We report the implementation of such a device based on an innovative design that…
View article: LightOn Optical Processing Unit : Scaling-up AI and HPC with a Non von Neumann co-processor
LightOn Optical Processing Unit : Scaling-up AI and HPC with a Non von Neumann co-processor Open
We introduce LightOn's Optical Processing Unit (OPU), the first photonic AI accelerator chip available on the market for at-scale Non von Neumann computations, reaching 1500 TeraOPS. It relies on a combination of free-space optics with off…
View article: Photonic co-processors in HPC: Using LightOn OPUs for Randomized Numerical Linear Algebra
Photonic co-processors in HPC: Using LightOn OPUs for Randomized Numerical Linear Algebra Open
Randomized Numerical Linear Algebra (RandNLA) is a powerful class of methods, widely used in High Performance Computing (HPC). RandNLA provides approximate solutions to linear algebra functions applied to large signals, at reduced computat…
View article: Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment Open
The scaling hypothesis motivates the expansion of models past trillions of parameters as a path towards better performance. Recent significant developments, such as GPT-3, have been driven by this conjecture. However, as models scale-up, t…
View article: Artificial intelligence: From electronics to optics
Artificial intelligence: From electronics to optics Open
Machine Learning and big data are currently revolutionizing our way of life, in particular with the recent emergence of deep learning. Powered by CPU and GPU, they are currently hardware limited and extremely energy intensive. Photonics, e…
View article: Light-in-the-loop: using a photonics co-processor for scalable training of neural networks
Light-in-the-loop: using a photonics co-processor for scalable training of neural networks Open
As neural networks grow larger and more complex and data-hungry, training costs are skyrocketing. Especially when lifelong learning is necessary, such as in recommender systems or self-driving cars, this might soon become unsustainable. In…
View article: Random projections through multiple optical scattering: Approximating Kernels at the speed of light
Random projections through multiple optical scattering: Approximating Kernels at the speed of light Open
Random projections have proven extremely useful in many signal processing and machine learning applications. However, they often require either to store a very large random matrix, or to use a different, structured matrix to reduce the com…
View article: Development of a Neutron Spectroscopic System Utilizing Compressed Sensing Measurements
Development of a Neutron Spectroscopic System Utilizing Compressed Sensing Measurements Open
A new approach to neutron detection capable of gathering spectroscopic information has been demonstrated. The approach relies on an asymmetrical arrangement of materials, geometry, and an ability to change the orientation of the detector w…