Modulus provides an open framework for developers to create modular, inter- operable modules. These modules are designed to be modular (surprise?), reusable and inter-operable locally and remotely via peer to peer communication protocols. Modules are lightweight and general enough to wrap over any machine learning tool. Developers can also organize modules into a module file system, representing their own module hub. Developers can also expose their modules as public endpoints through their local peer, and can restrict access based on their accounts signature. Modulus is by design open source and does not rely on any tokenomics, allowing developers to monetize their public endpoints through any tokenized asset including their own.
Salvatore Vivona (University of Toronto)
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2019 : Poster Session #2 »
Yunzhu Li · Peter Meltzer · Jianing Sun · Guillaume SALHA · Marin Vlastelica Pogančić · Chia-Cheng Liu · Fabrizio Frasca · Marc-Alexandre Côté · Vikas Verma · Abdulkadir CELIKKANAT · Pierluca D'Oro · Priyesh Vijayan · Maria Schuld · Petar Veličković · Kshitij Tayal · Yulong Pei · Hao Xu · Lei Chen · Pengyu Cheng · Ines Chami · Dongkwan Kim · Guilherme Gomes · Lukasz Maziarka · Jessica Hoffmann · Ron Levie · Antonia Gogoglou · Shunwang Gong · Federico Monti · Wenlin Wang · Yan Leng · Salvatore Vivona · Daniel Flam-Shepherd · Chester Holtz · Li Zhang · MAHMOUD KHADEMI · I-Chung Hsieh · Aleksandar Stanić · Ziqiao Meng · Yuhang Jiao