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A Novel Methodology For Crowdsourcing AI Models in an Enterprise

arXiv 2103.14033 ↗First posted 22 Mar 2021cs.LG cs.AIcited by 0

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Abstract (arXiv)

The evolution of AI is advancing rapidly, creating both challenges and opportunities for industry-community collaboration. In this work, we present a novel methodology aiming to facilitate this collaboration through crowdsourcing of AI models. Concretely, we have implemented a system and a process that any organization can easily adopt to host AI competitions. The system allows them to automatically harvest and evaluate the submitted models against in-house proprietary data and also to incorporate them as reusable services in a product.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 10 references that are in the map. First posted on arXiv 22 Mar 2021.

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References · 3

  1. 2019The Deepfake Detection Challenge (DFDC) Preview Datasetcited by 209
  2. 2018Microsoft Malware Classification Challengecited by 46
  3. 2019EvalAI: Towards Better Evaluation Systems for AI Agentscited by 34

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