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Blog
Lighton intègre “Visual RAG” dans sa plateforme : première mondiale pour l’analyse d’images et de documents à grande échelle
LightOn annonce l’intégration de “Visual RAG” dans sa plateforme. Cette avancée marque une première mondiale en permettant aux utilisateurs d’exploiter et d’interagir avec des documents mêlant textes, images, graphiques et diagrammes, grâce à une IA capable d’analyser simultanément ces différentes sources d’information.
LightOn releases PAGnol, the largest French Language Model
Paris-based startup LightOn, maker of photonic co-processors for large-scale AI, unveils today PAGnol, a 1.5 billion parameter language model.
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Summary of LightOn AI meetup #13
Efficient Neural Networks Training through Locality Sensitive Hashing
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Deep Reservoir Computing and Beyond: Fast and Lightweight Neural Networks
The 8th LightOn AI Meetup rocked! This time, we had Claudio Gallicchio, Assistant Professor at University of Pisa, talking about Deep Reservoir Computing and Beyond.
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LightOn’s AI Research Workshop — FoRM #4: The Future of Random Matrices. Thursday, December 19th.
On Thursday, December 19th, we held our 4th research workshop on the Future of Random Projections (FoRM#4).
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LightOn at #NeurIPS2019
Laurent Daudet, (LightOn CTO and Co-founder), Iacopo Poli (Lead ML at LightOn) and Florent Krzakala (consultant at LightOn and Co-founder), are currently at #NeurIPS2019 in Vancouver. One poster will feature some work performed with LightOn’s processing Unit and will be presented by Laurent or Iacopo.
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LightOn’s Third Research Workshop
At LightOn, we usually define ourselves as a hardware company that does Machine Learning or a Machine Learning company that does hardware. it depends on who we are talking to. Sometimes we may even mention that we are using light as a means of performing computations of interest to high dimensional Machine Learning.
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Shedding Light on the “Grand Débat”
This article is LightOn’s AI Research (LAIR) first contribution focused on applying LightOn’s Optical Processing Unit (OPU) hardware to generic large-scale Machine Learning tasks. Today we tackle the recently released public dataset of a nation-wide public debate and our first trial in using LightOn’s OPU for a Natural Language Processing task.
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